journal in image processing

IEEE REVIEWS IN BIOMEDICAL ENGINEERING, VOL. 1, 2008 157

The Impact of Neurotechnology on RehabilitationTheodore W. Berger, Senior Member, IEEE, Greg Gerhardt, Mark A. Liker, and Walid Soussou

Clinical Application Review

Abstract—This paper present results of a multi-disciplinaryproject that is developing a microchip-based neural prosthesisfor the hippocampus, a region of the brain responsible for theformation of long-term memories. Damage to the hippocampusis frequently associated with epilepsy, stroke, and dementia(Alzheimer’s disease) and is considered to underlie the memorydeficits related to these neurological conditions. The essentialgoals of the multi-laboratory effort include: 1) experimentalstudy of neuron and neural network function—how does thehippocampus encode information? 2) formulation of biologicallyrealistic models of neural system dynamics—can that encodingprocess be described mathematically to realize a predictive modelof how the hippocampus responds to any event? 3) microchipimplementation of neural system models—can the mathematicalmodel be realized as a set of electronic circuits to achieve parallelprocessing, rapid computational speed, and miniaturization? and4) creation of hybrid neuron-silicon interfaces—can structuraland functional connections between electronic devices and neuraltissue be achieved for long-term, bi-directional communicationwith the brain? By integrating solutions to these component prob-lems, we are realizing a microchip-based model of hippocampalnonlinear dynamics that can perform the same function as partof the hippocampus. Through bi-directional communication withother neural tissue that normally provides the inputs and outputsto/from a damaged hippocampal area, the biomimetic model couldserve as a neural prosthesis. A proof-of-concept will be presentedin which the CA3 region of the hippocampal slice is surgicallyremoved and is replaced by a microchip model of CA3 nonlineardynamics—the "hybrid" hippocampal circuit displays normalphysiological properties. How the work in brain slices is beingextended to behaving animals also will be described.

Index Terms—Brain-computer interfaces (BCIs), brain-ma-chine interfaces (BMIs), cognitive/memory prostheses, deep brainstimulation (DBS), motor system prostheses, multi-site electrodearrays, neural prosthesis, neurotechnology, neurotrophic factors,nonlinear systems analysis, Parkinson’s disease, rehabilitation,site-specific drug delivery, .

I. INTRODUCTION

A. Growth in Biomedical Engineering

B IOMEDICAL engineering has seen remarkable growthduring the last 15–20 years—growth that promises to con-

tinue well into the future. There are several factors fueling this

Manuscript received October 23, 2008; revised October 23, 2008. Currentversion published December 24, 2008.

T. W. Berger is with the Department of Biomedical Engineering, Center forNeural Engineering, Viterbi School of Engineering, University of Southern Cal-ifornia, Los Angeles, CA 90089 USA.

G. Gerhardt is with the Departments of Anatomy and Neurobiology, MorrisK. Udall Parkinson’s Disease Research Center of Excellence, Center for Micro-electrode Technology, University of Kentucky College of Medicine, Lexington,KY 40536 USA.

M. A. Liker is with the Department of Neurological Surgery, Keck School ofMedicine, University of Southern California, Los Angeles, CA 90089 USA.

W. Soussou is with QUASAR, Inc., San Diego, CA 92121 USA.Digital Object Identifier 10.1109/RBME.2008.2008687

heightened level of activity, including the huge expansion inthe field of medicine, which along with an increased level oftechnology in all phases of medical treatment, has provided asustained “pull” to the growth in biomedical engineering. Ex-panded medical treatment in the arena of the nervous systemhas been in direct response to what are now substantial popula-tions of patients with damage to, and dysfunction of, the brain,spinal cord, and the peripheral nervous system. The numbers ofpatients and the cost of care just in the USA alone are daunting.For example, the number of stroke patients numbers approx-imately six million, with a cost-of-care over $50 billion/year.The number of epilepsy patients numbers two–three million,with a cost-of-care approaching $15 billion/year. Brain traumafrom blunt head injury has led to a patient total of almost twomillion costing over $50 billion/year. What promises to be thelargest patient population in the future are those suffering fromdementia and Alzheimer’s disease, which today numbers nearlyfive million patients, with care costing over $100 billion/year.Other age-related brain disorders, such as Parkinson’s disease,are rising rapidly due to the increase in longevity resulting frombetter health care. These numbers in the future will be aug-mented by rapidly rising population of Type II diabetics, withthe complications arising from peripheral neuropathy.

If one considers just sources of funding as measures of com-mitment to biomedical engineering, federal levels of govern-ment have responded with major investments in the National In-stitutes of Health (NIH), i.e., doubling of the NIH budget in the1990s, and the creation of the National Institute for BiomedicalImaging and Bioengineering (NIBIB) in the year 2000, a newInstitute dedicated to biomedical engineering—research at theinterface between engineering and biology. Although biomed-ical engineering has expanded in all areas of medicine and bi-ology, the escalation has been particularly intense with respectto the neurosciences, and the treatment of neurological and neu-ropsychiatric disorders. While the NIH was expanding its mis-sion precisely in areas supportive of biomedical engineering,this expansion was taking place in the context of an explosivegrowth in the neurosciences, and NIH’s undeniable support forthe neurosciences, e.g., “the Decade of the Brain.” Thus, manyof the broader investments in medical and biological scienceshelped both to grow and to align biomedical engineering andneuroscience.

The National Institutes of Mental Health (NIMH) hasinvested strongly in quantitative neuroscience and neuralmodeling, with its development of the Program in TheoreticalNeuroscience. The National Institute for Neurological Diseasesand Stroke (NINDS) has maintained a 20-year investmentin their “Neural Prosthesis” Program, with a stronger, more

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158 IEEE REVIEWS IN BIOMEDICAL ENGINEERING, VOL. 1, 2008

widely based effort now in effect and planned for the future.The National Science Foundation (NSF) also has seen sus-tained budget increases, again with federal investment beingparticularly strong for sub-fields at the interface between en-gineering and the neurosciences. The NSF has created severalof its premier Engineering Research Centers in research areasthat overlap strongly with core areas of biomedical and neuralengineering, e.g., the Biomimetic MicroElectronic SystemsCenter at the University of Southern California. The Depart-ment of Defense (DoD), including the Defense AdvancedResearch Projects Agency (DARPA), the Office of Naval Re-search (ONR), and the Telemedicine and Advanced TechnologyResearch Center (TATRC), among others, also has supportednew ventures that require integrated efforts by neuroscientistsand engineers, for example, to identify biological principals ofsystem design that then have been used successfully to developneural prostheses, brain–computer interfaces, and large-scalehardware implementations of neural systems that can interfacedirectly with the brain. Biological principals of brain functionalso have been used to guide the design of next-generationcomputer architectures required to support more “cognitive”software for higher-level decision making required for bio-in-spired robotics. Finally, the last half of the 20th century haswitnessed a sustained increase in philanthropic activity directedspecifically at biomedical and neural engineering (e.g., TheWhitaker Foundation), increasing both the quantity and qualityof research activity, and expanding education and trainingactivity in biomedical engineering.

B. New Generation of “Neurotechnologies”

One of the major consequences of these investments inbiomedical engineering has been the development and appli-cation of a new generation of “neurotechnologies”: equipmentand procedures designed to reverse the consequences of damageor disease of the nervous system, and even to substitute formissing neural tissue. Replacement of damaged neural tissuerequires a substantial depth of understanding of the globalneural function involved, and of how the tissue in questioninteracts with the larger neural system to which it contributes.Likewise, engineered solutions to the problems of neural repairand/or replacement imply a substantial capability to modelbiological functions, and to translate those models into effec-tive medical or experimental procedures. Some of these new“neurotechnologies” are still in the research pipeline, given the20+ year timeline typical for development and FDA approvalof new medical procedures. Some new technologies, however,have already emerged and are being applied to humans fortreatment of nervous system disorders. Others have progressedsufficiently far with animal models that it is reasonable toproject their likely effects on the human population. The needfor such technologies is increasingly acute, particularly asthe present population ages, e.g., age-related disorders suchas Parkinson’s Disease, memory disorders due to dementia,stroke-related loss of neural structure and function, traumaticbrain injury, as noted above, increase the number of patientswith nervous system disorders and thus requiring application ofnew nervous system treatments technologies. In total, the tech-nologies and methodologies reviewed here arguably represent

Fig. 1. Illustration of the DBS electrode implanted in a subcortical targetand connected to the subclavicular implantable pulse generator. Courtesy ofMedtronic Inc.

the first generation of technologies emerging from our modernunderstanding of the nervous system.

We have focused here on five major technologies: deepbrain stimulation (DBS), intra-brain injection of pharmacolog-ical agents, micro-electrode technologies, brain-implantableneural prostheses, and noninvasive brain–computer interfaces(BCIs). Obviously many other neurotechnologies have notbeen included (e.g., neural prostheses for bladder control,cochlear implants, etc.,). We chose the neurotechnologies wedid because we believe that use of these in particular is about toincrease markedly in the coming years. In addition, some of thetechnologies to be discussed have not been previously used clin-ically or are just now reaching clinical trials, e.g., implantableneural prostheses, and thus represent novel approaches thatmay radically change our view of what is possible in the futurearena of clinical treatment. Our goal in this chapter is to reviewseveral classes of these emerging neurotechnologies, and toexamine their current state of development, and their likelyimpact in terms of opening new directions for rehabilitation ofthe damaged CNS.

II. DEEP BRAIN STIMULATION: INTEGRATION OF FUNCTIONAL

NEUROSURGERY AND ENGINEERING

Deep brain stimulation (DBS) is a technology that providesfor the application of a programmable current to structures ofthe brain which are critical to the pathology of a neurologicaldisorder (Fig. 1). It is a culmination of a variety of clinical and

BERGER et al.: THE IMPACT OF NEUROTECHNOLOGY ON REHABILITATION 159

technical advances. Prior to the development of DBS, neuro-surgeons treated Parkinson’s disease (PD) and other movementdisorders by creating well-circumscribed lesions, either chemi-cally or radiothermally, in targeted structures of the brain. Theeffectiveness of electrically stimulating subcortical regions toabate tremor was discovered serendipitously decades before theFDA approval of DBS implants [1]. Despite the lack of clarityof its mechanism, DBS proved to be a safe, reversible alterna-tive treatment to lesioning procedures [2]. With the developmentof cardiac pacemaker technology and advances in stereotacticsurgery, the concept of applying continuous electrical stimula-tion to the brain as a form of medical therapy was able to betranslated into an implantable medical device. Over the courseof the past decade, nearly 40 000 Parkinson’s disease (PD) pa-tients worldwide have benefited from DBS, as well as manypatients with essential tremor (ET) and dystonia. New indica-tions may be on the horizon for diseases without effective orlow-risk treatments such as Tourette’s syndrome, treatment-re-sistant depression, obsessive-compulsive disorder, addictive be-havior, and obesity.

A. Development and Use of Deep Brain Stimulation forMovement Disorders

Lesions were the primary therapy for movement disorders,especially Parkinsonian tremor, until L-dopa was introduced inthe late 1960s. As opposed to surgical ablation of neural path-ways, L-dopa pharmacologically modulates basal ganglia cir-cuitry to alleviate parkinsonian symptoms, which had obviousadvantages in terms of patient morbidity. After the introduc-tion of L-dopa, the use of surgery for treating Parkinsonism de-creased dramatically. However, L-dopa is not without its ownset of shortcomings. It does not stop or slow the progressionof the disease, and its benefits wane over time. As Parkinson’sdisease progresses, increasingly higher doses of L-dopa at an in-creasing frequency is required for the patient to experience thesame level of benefit, and eventually side effects result whichcan deteriorate the patient’s quality of life. Stereotactic surgeryreturned as a treatment for tremor in the mid-1970s with an in-crease in the number of thalamotomies performed. In the 1980s,the technique of DBS was introduced to treat movement disor-ders and has remained effective in pharmacologically resistantpatients and useful in decreasing the amount of L-dopa a patientneeds for satisfactory tremor control.

With the improvement of stereotactic surgical methodsthrough the introduction of stereotactic frames and atlases,targeting deeper brain structures for neuromodulatory electricalstimulation became a tangible reality [3]–[5]. (For a moredetailed description of the history of functional neurosurgeryin movement disorders, please see [6]). Although deep brainelectrical stimulation was reportedly used in isolated instancessince the mid-20th century [1], [7], it was not until 1987,when Benabid et al. demonstrated the efficacy of VIM nu-cleus stimulation for the treatment of Parkinson’s disease,that DBS started gaining popularity [8]. In their study, tremorwas compared between Parkinson’s disease patients who hadundergone unilateral thalamotomy and contralateral placementof a DBS electrode in the VIM nucleus of the thalamus. Whilethese results showed that thalamotomy was more effective in

decreasing tremor than stimulation, Benabid et al. surmisedthat the results would have been different if stimulation wasdelivered at a sufficiently high frequency. Further studiesby Benabid’s group using optimized stimulation parametersshowed a decrease in tremor in 88% of patients undergoingthalamic DBS [9].

Experimentation with a primate model of Parkinsonism elu-cidated further targets for stimulation. Bergman et al. in 1990and Aziz et al. in 1992 demonstrated the efficacy of creatingselective bilateral STN lesions to treat Parkinsonism in primatestreated with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahy-dropyridine (MPTP) [10], [11]. MPTP selectively destroysdopaminergic neurons, including those in the substantia nigra,which re-creates the symptoms of Parkinson’s disease in hu-mans and nonhuman primates. Both studies described effectsnot only on tremor and rigidity but also on the primate’s facialexpressions, akinesia, and other nonmotor symptoms of Parkin-sonism. Building on this work in animal models and takingadvantage of the development of implantable battery-powereddevices for other medical uses, the initial studies of long-termbilateral STN stimulations in Parkinson’s disease brought DBSinto the modern era [12]–[14].

B. Principles of Targeting in Deep Brain Stimulation

Selection of the appropriate target and accurate localiza-tion are the first critical steps in DBS [15]. The placement ofthe stimulating electrode in the appropriate region based onanatomic and physiological targeting is essential to improvinga patient’s neurological symptoms through the modulation ofactivity in central nervous system (CNS) structures, which isprecisely the purpose of functional neurosurgery. The targetsare chosen based on neurophysiological studies that show theaffected brain regions for a specific disease.

The current indications for DBS use are the three afore-mentioned neurological diseases: PD, ET, and dystonia. Theassociated deep brain targets are most commonly the subtha-lamic nucleus (STN), the ventral intermediate nucleus of thethalamus (VIM) and the internal segment of the globus pallidus(GPi). These neuronal structures are believed to subserve theprimitive motor pathways of the basal ganglia which modulateconscious movement. Alterations in the electrochemical outputfrom these nuclei due to upstream dopaminergic cell loss insubstantia nigra create the constellation of symptoms seen inParkinson’s patients. However, no specific neurotransmitterchanges have been identified in ET or dystonia. Thus, DBSis less likely to act upon a specific neurotransmitter systemas it is to alter the electrical firing behavior of neurons in thestimulated region. Since the lesioning and stimulation practicesthat preceded modern-day DBS were effective in stoppingtremor whether the motor cortex, basal ganglia, or thalamuswere targeted, it seems that DBS is preventing pathologicalactivity in the basal ganglia from propagating through the tha-lamocortical loop in which it is involved [16]–[18]. While thecomplexity of the neural circuits involved in these neurologicaldisorders and seemingly conflicting results have hindered thedeciphering of the exact mechanism by which DBS operates,studies have shown the suppression of oscillatory activity by


DBS; this same oscillatory activity seems to increase with PDand decrease with movement onset in normal human subjects[19]–[22].

Identifying appropriate DBS targets has been greatly aided bythe development of functional MRI. By monitoring activity-re-lated changes within the brain through fMRI, clinicians have theopportunity to peer into the neuronal depths and identify areas ofabnormal brain activity related to psychological abnormalitiesin addition to motor functional impairments. Therefore, fMRIprovides clinicians with the capability to discover new targetsfor a variety of diseases previously not considered amenable toneurosurgery.

C. Considerations of Current Clinical Indications

As engineers design DBS systems, it is important to keepin mind disease characteristics and what symptoms are beingaffected. The following sections provide an overview of cur-rent and potential DBS indications and the aspects relevant totargeting and the efficacy that can be achieved through DBStherapy.

1) Parkinson’s Disease: Idiopathic Parkinson’s disease af-fects approximately 1% of the population over the age of 65. Itis marked by four cardinal features: resting tremor, rigidity, pos-tural instability and akinesia. Other features include a simian orstooped posture, shuffling gait, autonomic instability, maskedfacial expression, low volume speech and small handwriting.Since the 1970s, the mainstay treatment following the initial di-agnosis has been prescription medication containing levodopa.In fact, failure of any symptoms to respond to adequate dosesof levodopa ingestion precludes the diagnosis of idiopathic PD;consequentially, patients whose symptoms do not respond at allto levodopa therapy are not candidates for DBS.

Prior to surgery, a common question from patients and theirfamilies relates to the expectation of function after surgery.The benefit of DBS is best evaluated by the proportion of eachday the patient spends in “on” time without disabling dyski-nesias. We define the “on” time as the period after ingestinganti-Parkinsonian medication during which the patient is fluidand receiving pharmacological benefit. This contrasts withthe “off” time which is the period during which the patientexperiences no pharmacological benefit. Unfortunately, manyadvanced PD patients suffer from dyskinesias, uncontrollablewrithing movements of the arms, legs, head or torso resultingfrom long term effects of levodopa ingestion. Additionally,many patients with PD suffer from motor fluctuations, in whichfrequent fluctuations between “on” and “off” states occurduring the course of the day, making it difficult to participatein daily activities.

Approved by the Federal Drug Administration (FDA) in Julyof 2002 for advanced Parkinson’s disease, DBS has offered adramatic improvement in the functional capabilities of manysuch patients. Appropriate candidates for surgery include thosepatients with the following characteristics: 1. the disease is ad-vanced; 2. patient’s symptoms are definitively responsive to lev-odopa; 3. patient is able to ambulate in the “on” state; 4. patientmotor fluctuations or dyskinesias are unresponsive to medica-tion; 5. patient exhibits minimal or no cognitive or behavioral

difficulties. There is no age requirement, but in general olderpatients tend to possess greater cognitive difficulties, more com-plex co-morbidities, and are more likely to be so advanced as notto benefit from surgery.

A randomized trial of bilateral STN-DBS with best med-ical management confirmed the significant benefit of DBS overpharmacotherapy at six months [23]. Improvements were ev-idenced in assessments of mobility, activities of daily living,emotional well-being, stigma, and bodily discomfort. In addi-tion, although serious adverse events were greater in the surgerygroup, the less significant adverse events were increased in thepharmacotherapy group.

Results from the Deep Brain Stimulation for Parkinson’s Dis-ease Study Group revealed an increase in the percentage of timepatients identified as being in an “on” state without dyskinesiasfrom 27% per day at baseline to 74% at the six month postop-erative evaluation [24]. According to the study, the percentageof “off” time also reduced from 49% to 19% of the day, whichalso reflects the reduction in motor fluctuations.

Overall, patients undergoing subthalamic nucleus stimula-tion found approximately 50% improvement in both the motorand activities of daily living subsection scores of the UnifiedParkinson’s Disease Rating Score (UPDRS). These effectswere also found to last long-term. Five-year post-operative datafor bilateral STN-DBS reveal approximately 50% improvementin motor and activities-of-daily-living off-medication scoresand significant improvement in on-medication dyskinesias [25].However, over the course of five years, this study showed thatspeech, postural instability and freezing worsened. Therefore,patients with predominant postural instability and freezing arenot considered ideal candidates for DBS.

Patients with PD also benefit from a reduction in medicationrequirements without change in functional capacity where thesubthalamic nucleus (STN) is targeted; when the globus pal-lidus interna (GPi) was targeted, patients experienced no sig-nificant change in medication dosage [26]. Early investigationscomparing the benefit of DBS in the STN versus the GPi con-firm more stable improvement in UPDRS scores and decrease inmedication needs for the STN group [69]. In addition, for neu-rosurgeons, there is also the benefit of relative ease with respectto targeting the STN versus the GPi due to the size of the targetnucleus and improved neurophysiological feedback.

VIM thalamus is located anterior to the Ventral-caudal (Vc)thalamus which sends major neuronal processed to the sensorycortex and posterior to the ventral oralis anterior and poste-rior thalamus (Voa/Vop) which send processes to the supple-mentary motor area. VIM itself sends major projections to themotor cortex including the premotor and supplementary motorregions. The key to neurophysiologically identifying the VIMis monitoring the feedback to the sensory cortex during stim-ulation when stimulating in Vc along with increased activityof Vc recording when brushing the awake patient’s face andarm. In addition, microelectrode recordings in the VIM will ex-hibit so-called “tremor cells” whose activity matches the pa-tient’s hand tremor frequency. During VIM-DBS, the micro-electrode is advanced from a location 10 to 20 mm above targetdepending on surgeon’s preference. Due to the angle of trajec-tory, the Voa/Vop first will be identified where the density of


spontaneously active neurons is low, where cells fire in a char-acteristic bursting fashion, and where cells respond to volun-tary movement. As the microelectrode is passed posteroinferi-orly the VIM is entered where kinesthetic cells are identifiedwhich respond to passive movement and tremor. In the case ofET, which is a kinetic tremor, the tremor cells can be identifiedonly if the hand is elevated or active. Traversing more posteroin-feriorly the Vc will be identified by the presence of tactile cellswhich respond to light touch on the contralateral face or arm.Final location of the DBS electrode should be in VIM about 2mm anterior to Vc border where electrical stimulation producestremor arrest and minimal side effects.

DBS of the globus pallidus is performed primarily fordystonia but is also effective for Parkinson’s disease. GPi,or globus pallidus interna, is the specific target within theglobus pallidus for treatment of both diseases. Major inputsto the GPi are the striatum and the subthalamic nucleus andthe major output is the thalamus. Microelectrode advancementfrom dorsolateral to posteroventral provides identification ofhigh-frequency (70–120 Hz) globus pallidus cells. The GPineurons can be easily discriminated from electrical silenceof the internal capsule [67]. The initial trajectory for MERtargets the dorsolateral border of the optic tract which shouldalso approximate 21.5 mm lateral to AC–PC line. MER shouldrecord at least 6 mm of GPi prior to exiting its ventral border. Inaddition, once the microelectrode exits the ventral GPi, testingof the location of the optic tract can be performed by flashing alight in the patient’s eyes and assessing the presence of visualevoked potential responses obtained. Final DBS placement willensure that the patient experiences minimal side effects suchas would occur through stimulation of nearby internal capsulefibers [68].

PD is the most common indication for DBS and the mostfrequent target is the STN. GPi is the major output from theSTN which received most input from the globus pallidus ex-terna; the latter has been suppressed by reduced striatal inhibi-tion due to dopamine depletion and permits increased excita-tory (glutamate) output from the STN. Anatomically, the STNis bounded superiorly by the thalamic outflow tract know as thezona incerta, inferiorly by the substantia nigra, anterolaterallyby the internal capsule and posteriorly by the medial lemniscus(Fig. 2). Understanding these relationships is important in per-forming MER for STN-DBS. Recording electrode angular tra-jectory is approximately 15 deg. in the coronal plane and 60 deg.from the horizontal (AC–PC) plane. Similar to the techniquesdescribed above, MER is initiated 10–15 mm above target andduring advancement of the microelectrode, thalamic dischargeis recognized. Passing through the zona incerta electrical silenceis encountered as it is a white matter tract and identification ofSTN and its neuronal discharge is usually well defined.

Frequency of STN neuronal output is generally between 30and 50 Hz. In addition, STN cells subserving motor activity arelocated in the dorsolateral region of the nucleus and respond topassive movement of the contralateral limbs. This kinestheticresponse is important in identifying this region of the STN.More medially placed stimulation may cause untoward cogni-tive side-effects and should be avoided. Exiting the STN, an-other white matter tract is encountered before entering the sub-

Fig. 2. Anatomic relationship of STN with surrounding structures.�� capsule �� lemniscus [285].

stantia nigra with its defined spontaneous discharge rate in therange of 60 to 80 Hz. Test stimulation with a DBS in the STNprovides feedback as to the electrode location and potential forside-effects if the DBS is left in place. Tonic contractions of thecontralateral limb, difficulty speaking or conjugate eye devia-tion at low voltages ( V, 185 Hz, 60 s pulse width) mayreveal an electrode too anterior or lateral near the internal cap-sule and prominent paresthesias may indicate the electrode istoo medial or posterior near the medial lemniscus. In addition,a clinical response such as reduced rigidity and/or tremor mustbe identified during stimulation, although some response mayalready be experienced due to a “lesion-effect” caused by me-chanical forces of the DBS electrode. Later sections describe theintraoperative techniques involved in localizing the DBS targets.

2) Essential Tremor: FDA approval of DBS for essentialtremor (ET) emerged in 1999 and is the surgical treatment ofchoice due to reversibility, adjustability, and bilaterality. It hasbeen estimated that up to 3.9% of the population suffers fromET as the most prevalent movement disorder worldwide (Louiset al., Mov Disord 1998, vol. 13, pp. 5–10). It is identified bya 4–12 Hz regular tremor associated with movement (posturaltremor) as opposed to the tremor of PD which is seen at rest(pill-rolling) and physiological tremor which is irregular andin the 8–12 Hz range. It also may affect the head, trunk, legsand voice. Frequently there is a family history of the tremorwhich improves with the ingestion of alcoholic beverages. Pa-tients with ET are on average older than those with PD andin their retirement years. In addition, most patients experiencemild symptoms and are able to carry on daily activities withoutsignificant disability.

DBS for ET is an extremely effective treatment and is rec-ommended when first-line pharmacotherapies fail in a disabledindividual. Studies confirm approximate 50% improvement intremor severity after DBS [27]. The electrode arrays are placedin the ventral intermedial thalamus (VIM) nucleus under stereo-tactic guidance. Compared with VIM lesioning procedures per-formed historically, the VIM DBS procedure can be performed


bilaterally without significant side effects, the most significantof which is difficulty with speech but may also include cognitivedisturbance and impaired balance.

Although ET is expressed as a bilateral disease, patients mayhave more difficulty with function in the dominant hand andmay also complain of significant trunk and head tremor. Uni-lateral VIM-DBS alone may be sufficiently effective to treat thedominant tremor. Bilateral DBS is necessary to treat axial (heador trunk) tremor [28].

The effects of VIM-DBS are durable. Sydow et al. revealedpersistence of tremor control six years following implantationfor both bilateral and unilateral implanted patients [70]. Activ-ities of daily living scores were significantly improved at sixyears compared with baseline (preoperative) scores and stimula-tion “off” scores. These investigators also identified an increasein the mean voltage requirements (from 2.0 V to 2.6 V) and cor-responding increase in mean rate (156 to 172 Hz) and decreasein mean pulse width (103 to 89 s).

3) Dystonia: Dystonia is a general term for a disparategroup of neurological diseases characterized by sustainedmuscle contractions resulting in twisting, writhing movementsand abnormal postures. The category of dystonias include“benign” conditions, such as writer’s cramp, or as severe asprimary generalized dystonias resulting in severe disabilitybeginning generally in childhood. Secondary dystonias resultfrom central nervous system lesions (stroke, trauma, cerebralpalsy, degenerative disease) or medications (tardive dystonia).Focal or neck dystonias may respond for long periods of time tobotulinum toxin injection but dystonias affecting larger musclegroups or sections of the body would not be affected. Thereare no long-term effective medical treatments for the severestforms of dystonia, prompting investigation of DBS for thisdisease entity.

The mechanism by which DBS in the nucleus of the GPiameliorates the symptoms of dystonia is not understood as therole of pallidal pathophysiology in dystonia has not been identi-fied. GPi-DBS for dystonia is highly effective and life-changingfor those patients with primary generalized dystonia and tar-dive dystonias. Overall improvement in dystonia scores aver-aged about 50% for the primary generalized dystonia patientswith greater improvement for younger patients especially withDYT-1 positive type dystonia [29]. The latter group is definedby abnormality in the protein product dystonin. They may ex-perience complete resolution of symptoms following DBS, aconsiderable change given the severe disability experienced bythese young patients [30]. Response following GPi-DBS fordystonia varies depending on disease type. Patients with cer-vical dystonias in general experience some improvement (40%)in symptoms following GPi-DBS and patients with tardive dys-tonias have shown dramatic benefits (90%) from GPi-DBS [31].

Treatment of dystonia patients with DBS carries with it cer-tain complexities not present in the use of DBS for PD or ET.Target localization in the GPi is difficult due to the fact that somedystonia patients are quite young and may not be able to tolerateawake surgery, the definitive neurophysiological thumbprint atthe target has not been clearly defined, and intraoperative teststimulation reveals no changes in the disease state. In fact, pa-tients do not immediately respond to changes in programming of

the implantable pulse generator, as do patients with other move-ment disorders. It may take up to six months before evidence ofDBS efficacy is apparent, making it difficult to program thesepatients as well.

D. Considerations of DBS as a Potential Treatment for NewIndications

DBS is not likely to be restricted to treating neurologicaldisorders that result in motor dysfunction. Diseases of ner-vous system ranging from those traditionally treated withpsychotropic medications to those for which there is no currentmedical treatment other than behavioral or physical rehabili-tation are already being investigated as future indications forDBS and a handful of studies have already revealed positiveresults [32]–[36]. Investigational indications include depres-sion, obsessive-compulsive disorder, and Tourette syndrome.Addictive behavior, minimally conscious states, and obesityare also being considered for investigation as DBS indicationsfarther down the road.

Although the mechanisms underpinning DBS’ benefit ispoorly understood, it is reasonable to define the mechanismas an alteration in output of an abnormal circuit by electricalintervention at one of the neuronal nodes of the circuit. Asour understanding of the brain circuitry is enhanced especiallythrough the use of functional MRI and positron emissiontomography (PET), improved methods of using DBS willcontinue to emerge. Anecdotal reports have highlighted thepotential of DBS to be of benefit to patients with such varieddiseases as Tourette’s syndrome, obsessive-compulsive dis-order (OCD), depression, obesity, addictive behavior, epilepsyand minimally conscious states. Final results of a multi-insti-tutional investigation applying anterior thalamic stimulationfor epilepsy are pending. Upcoming multi-institutional clinicaltrials are also planned for depression and OCD followingearly reports showing improvement with small numbers ofpatients [36]–[38]. Certain of these diseases with respect toDBS therapy are highlighted below.

1) Treatment-Resistant Depression: Major depression is acommon health problem affecting about 18 million people inthe U.S. with a lifetime individual risk of 17% [39]. It createssignificant disruption to an individual’s quality of life and eco-nomic viability and significant cost to society. Despite certaineffective treatments for major depression, substantial numbersof major depression patients will suffer from treatment-resistantdepression (TRD). It is defined as “the lack of a clinical responseafter adequate pharmacotherapy has been attempted.” [40]. Ef-fective neurosurgical treatments in the past have consisted oftargeted lesioning procedures such as stereotactic limbic leu-cotomy, subcaudate tractotomy, and anterior cingulotomy butthe side-effects of a permanent lesion may be intolerable andoff-target lesions may be devastating [41].

Based on fMRI studies and animal investigations a variety ofprotocols were developed to assess the benefit of DBS in certainbrain regions associated with processing of affective stimuli.Some of these protocols have been employed in small-cohorthuman trials. These include the nucleus accumbens and ventralstriatum [38], the subgenual cingulated cortex (Brodmann’sarea 25) [42], and the inferior thalamic peduncle [43]. Based


Fig. 3. Patient prior to sterile preparation of the scalp.

on some evidence of success in a six-patient study involvingDBS in area 25, a larger cohort of 14 patients were implantedand the results were encouraging [42]. The study determinedthose patients who achieved a response to DBS (defined asa 50% or greater reduction in the Hamilton Rating Scale forDepression (HRSD-17) and those who were in remission (aHRSD-17 score of seven or less). One month after surgery 35%of patients were responders, and 10% were in remission. Sixmonths after surgery, 60% of patients were responders and 35%were in remission. These dramatic results were maintained atthe 12-month mark.

2) Obsessive-Compulsive Disorder (OCD): Expression ofOCD is variable in that patients with a mild form of the diseaseare able to participate in most activities of daily living with min-imal limitation. However, in its severe form, OCD sufferers aredramatically impacted in many aspects of their life and unfortu-nately are unable to find relief despite conventional behavioralor pharmacological therapies. Some have benefited from abla-tive therapies such as anterior capsulotomy and cingulotomy[37]. Although a few small studies were undertaken evaluatingdifferent locations, in all of them, the ventral anterior limb of theinternal capsule and nearby ventral striatum (VC/VS) was tar-geted [44]. Four neurosurgical centers were used to assess thebenefit of VC/VS DBS for severe OCD. A total of 26 patientswere enrolled with an average Yale-Brown Obsessive Compul-sive Scale (YBOCS) of 34 (severe OCD is defined as YBOCSscore of 26). At last follow-up 73% of patients had at least a25% reduction in YBOCS and a large majority of those im-provements were 35% or greater in YBOCS reduction.

E. DBS Surgical Technique

1) Stereotactic Surgical Technique: Most DBS procedurestoday are performed with the patient awake in the semi-sittingposition (Fig. 3). Initially, the head frame is affixed to the skullusing four pins in order to provide a frame of reference for thebrain anatomy (Fig. 4). Anterior commissure (AC), posterior

Fig. 4. Leksell head frame and arc (courtesy of Medtronic, Inc.).

commissure (PC), and midline structures are identified using animage guidance system. The radiologic estimate of target loca-tion is refined by microelectrode neurophysiologic localization[45] and the DBS electrode is placed in the target that best fitsthe radiologic and physiologic data.

The surgical technique is designed to place the DBS electrodewithin a specific grouping of neurons with a motorically signif-icant result. Although the subthalamic nucleus (STN) is small(approximately 6–7 mm in maximum dimension) the more an-terior and medial regions subserve associative and limbic func-tions. Within the dorsolateral aspect of the nucleus which is theSTN target, the neurons are arranged in a homunculus. This factpermits accurate targeting through the intraoperative identifica-tion of limb motor and sensory feedback.

There are three techniques used to identify the appropriatelocation within the target grouping of neurons (STN, GPi orVIM): anatomic targeting, intraoperative neurophysiology(kinesthetic/somasthetic feedback), and awake test stimulation.This “triple-check” system allows accurate targeting as mis-placement of the DBS electrode by as small a margin, as 2 mmcan result in suboptimal results with the potential for insuffi-cient clinical benefit or significant on-stimulation side-effects.

Anatomical targeting involves the computer-aided localiza-tion of the anatomic target based on visualization of the targetitself and a coordinate system relative to certain easily identi-fiable brain structures. The anterior and posterior commissuresof the brain are easily identifiable on MRI and define the an-terior and posterior margins of the third ventricle, respectively.Prior to the advent of MRI, a pneumoencephalogram (injectionof air into the ventricular cavities followed by X-ray) was per-formed and the dimensions of the third ventricle could be visu-alized. In most cases, a head frame is fixed to the patient’s skull


Fig. 5. Stealth image guidance system (courtesy of Medtronic, Inc.).

prior to surgery and a fiducial array is secured to the frame. Thisprovides a three-dimensional frame of reference for the imageguidance system. There are a number of image guidance sys-tems (Stealth, BrainLab) and frame/fiducial systems (Leksell,CRW) (Fig. 5).

Ventriculography as a means of locating the AC–PC line haslargely been replaced by CT and MRI scanning. CT scanning isas accurate as ventriculography [46] and does not carry the risksof ventricular puncture and instillation of air or contrast mediuminto the ventricles. MRI scanning is slightly less accurate thanCT scanning with errors of approximately 2 mm on average and4 mm at maximum [47]–[49]. These errors are due to artifactsrelated to inhomogeneities in the magnetic field and nonlinear-ities in the gradient field—the position-dependent variation inthe magnetic field [50]. These artifacts can be induced by metalor magnetic susceptibility artifacts—produced at the interfacebetween materials (e.g., air and bone) which have different ten-dencies to affect the magnetic field in a region.

Attempts to decrease errors in MRI scans due to these arti-facts include software modifications and overlapping (fusion) ofthe MRI database with the CT database, which is not prone tothese types of artifacts [51]. Patients undergo imaging first witha 3T MRI of the brain prior to surgery. During the day of surgerya CT is taken with the Leksell frame in place. Then CT and MRI

are fused by the computer software (Medtronic Stealth station).Targeting can then be accomplished by computer programs thatrelate atlas maps of anatomy to the radiologic anatomy. Theseprograms display atlas maps transformed either to match theAC–PC line in isolation [52] or to match the AC–PC line andother structures, such as the margins of the third ventricle or theinternal capsule [53].

2) Microelectrode Recording: Intraoperative neurophys-iology or microelectrode recording (MER) is employed tomonitor the neuronal activity in a target region and its imme-diate surroundings. MER involves microdrive advancementof a fine recording microelectrode (platinum-iridium alloy ortungsten/epoxylite) through deep brain structures to providevisual and auditory recording feedback to the surgeon regardingmicroelectrode tip location. Each of the three major targets(STN, GPi and VIM) can be identified by the telltale neuronaldischarge and many neurosurgeons employ microelectroderecording to optimize DBS electrode placement.

Radiologic targeting can be further refined by identifying thedifferent basal ganglia nuclei (STN and GPi) and thalamic nu-clei (VIM, Vop, and Vc) on the basis of their electrophysiologicproperties. These properties are defined in terms of spontaneousactivity, neuronal response to passive and active movements,and sensory responses to natural or electrical stimulation. Phys-


Fig. 6. Microdrive assembly.

iologic localization has been carried out by stimulation with amacroelectrode (impedance ), or by stimulation andrecording with a semi-microelectrode (impedance k )or a microelectrode (impedance k ).

Microelectrodes for physiologic monitoring and recordingare designed to isolate single action potentials [54], [55].Typically these characteristics are achieved by constructingelectrodes from a platinum-iridium alloy or from tungsten, pro-ducing a tapered tip, and insulating with glass [54], [56]–[60].The electrode impedance is usually.[61] greater than 500 k[54], [62]. A high-impedance microelectrode is required toisolate single units [54]. Passing current through the electrodeduring microstimulation will degrade insulation and lowerimpedance, which makes it harder to isolate single units.

The assembled electrode is attached to a piezoelectric micro-drive (Fig. 6) and mounted on the stereotaxic frame. Some mi-crodrive systems incorporate a coarse drive so that overlyingstructures can be traversed quickly. The tip is then retracted intoa protective cylindrical housing while the whole assembly is ad-vanced to a new depth [61]. The microdrive may then be usedfrom this new depth for detailed exploration of deeper struc-tures. Another option is to use the microdrive throughout thetrajectory by advancing it each time it reaches the end of its tra-verse [54].

The signal from the microelectrode is amplified and filtered.Multiple neuronal discharges of various sizes may be seen onan oscilloscope and heard by use of an audio monitor. The “allor none” principle of neuronal discharge provides that an actionpotential signal of constant shape and amplitude will be pro-duced from any one neuron. Therefore, a window discriminatormay be utilized to isolate individual neuronal firing activity. Thecontinuous signal may be stored for offline analysis.

In addition to recording, micro-stimulation of subcorticalstructures through the microelectrode may be employed inphysiologic localization. Current may be delivered throughthe same electrode that is used for recording by disconnectingit from the preamplifier and connecting it to the output of acurrent-isolation stimulator. Micro-stimulation is delivered in

biphasic, square wave pulse trains of 0.1 to 0.3 ms pulses fortimes up to 10 s at a frequency of 300 Hz [63]. The current usedin stimulation determines the amount of local current spread.Stimulation in Vc or lemniscal pathways will evoke somaticsensations [64], while stimulation in STN or VIM may alterthe ongoing Parkinsonian or Tremor symptoms. Furthermore,stimulation in areas too medial or lateral to the STN will elicitoculomotor side effects or capsular effects such as musclecontractions.

F. Engineering Applications in the Advancement of DBSTechnology

DBS systems have been able to borrow from engineeringtechnology used in cardiac pacemaker design because of theanalogous system components: microelectronic circuits whichgenerate and control the output current pulse trains, a hermet-ically sealed implantable device which contains the circuitry,mechanical leads with electrical contacts and connections tothe implanted device, and an external programmer which cancommunicate wirelessly with the internal hardware. (Readersinterested in a further technical summary of DBS systems mayrefer to Liker [6]). However, the mechanisms of DBS are muchless understood than those of cardiac pacing. DBS systems lackthe predictability of outcome that pacemakers provide, sinceEKG (electrocardiograms) can easily reveal whether the latterhas been successful in producing the desired effect. More to thepoint, the desired electrophysiological output is known for a car-diac pacemaker and readily monitored. Because the underlyingneurophysiology of DBS’s clinical efficacy is still not well un-derstood, DBS is much more difficult to control to produce re-liable effects.

In the meantime, engineers have taken on the challenge ofmaking flexibility a feature of DBS systems, so that the elec-trical stimulation can be adjusted for each patient. Leads come indifferent lengths and with different inter-contact spacing. Elec-trical current can be delivered on monopolar of bipolar set-tings through any of the four available contacts. The amplitude,pulse width, and pulse rate of the electrical current can be setto one of thousands of combinations. At present, such param-eters are set through a painstaking process in which the clin-ician attempts various settings, looking for immediate observ-able clinical effects; once a programmable setting is decided,the patient must wait until the next visit to the doctor, and theclinician must rely on the patient’s assessment of the effective-ness for feedback when deciding how to readjust stimulationparameters. Thus, neurologists eagerly await the developmentof a closed-loop system in which continuous DBS control andadaptation is based upon information provided by quantitativeneurophysiological feedback.

The first step in designing closed-loop DBS control is deter-mining what electrophysiological “biomarkers” could be moni-tored and used to relay feedback regarding the effect the stimula-tion is eliciting in the neuromotor network. While some studiesimply that the key neurophysiologic change that DBS shouldachieve to be effective is suppression of GPi firing rates, othersimply that a more informative biomarker might be the amount ofoscillatory activity in pertinent frequency bands, and others still,


that it is the synchronization of oscillatory activity between STNor other neurons which is a key indicator of clinical symptomsof PD [65]–[68]. However, biomedical engineers and scientistshave already begun to draw implications from their research forDBS closed-loop control [20], [69], [70].

Optimizing DBS control also will depend upon studieswhich show how these biomarkers, and hence clinical symp-toms, change with variation in DBS stimulation parameters.Progress has been hindered by the difficulty in conducting awell-controlled study in large numbers of patients. Each patienthas an individualized regimen for medication and can suffergreat discomfort and disability when taken completely offmedication. Since DBS electrodes sit in different locations ineach patient, the effect of altering which electrode (or electrodepair in a bipolar setting) would be difficult to study withoutknowing precisely where each electrode is located with respectto the anatomical target. The tolerance to a given amplitudeof DBS current varies from patient to patient. Because ofthese difficulties in obtaining consistent results in human DBSstudies, computational models still play an important role inthe understanding and development of DBS therapy. With thehelp of models of basal ganglia neurophysiology and pathologyintegrated with those of high frequency ( Hz) electricalstimulation, engineers can devise well formulated hypothesesto test in clinical studies [71], [72].

Aside from optimizing electrical stimulation itself, ensuringthe accuracy of electrode placement is also a challenge. En-suring that the electrode is implanted in the correct anatomicallocation would be helpful to doctors who are trying to decide thebest course of action in calibrating each patient’s therapy, espe-cially in the selection of which contacts to use. One outstandingquestion to determine how effective current steering might beis how sensitive the clinical outcome is to anatomical targeting;or in other words how precisely does a given electrode contactneed to be placed in order to produce the desired effect. Findingthe answers to such questions might be aided by high-resolu-tion, non-EMI (electromagnetic interference) inducing imagingwith integrated software algorithms to compute the distance be-tween electrode contacts and selected anatomical locations.

Also, as alluded to previously, DBS indiscriminately deliverscurrent to extracellular space without regard to different neuro-transmitter systems. The future design of DBS systems wouldbe aided by studies which test whether DBS therapy can pro-duce more predictable, consistent results if it can more specif-ically target certain types of neurons. One hypothesis on themechanism of DBS postulates that the high frequency regularpulse trains block pathological activity that would normally betransmitted through basal ganglia circuitry [73]. Such a mech-anism leads to the question: if instead of affecting more gener-ally the level of firing in the local population of neurons, wouldDBS be more effective communicating desired information todownstream neurons rather than communicating no informa-tion, as hypothesized in [73]? Brain-machine interface researchhas looked at how biomimetic devices might restore impairedfunction by replicating neural circuitry output [74]. A closed-loop system would enable the DBS control algorithm to de-liver patterns of electrical stimulation according to a model ofan input-output system of the nondiseased basal ganglia targets.

Although with advances in surgical technique overall com-plications are low, important side effects and the consequencesof potential complications of DBS must be discussed with thepatient. These adverse events include intracranial hemorrhage,wire erosion or breakage, wound infection potentially requiringDBS removal, post-operative confusion, and re-operation due topoor placement of the electrode array [75]. However, the mostserious of these complications, intracranial hemorrhage, is at anincreased risk of occurrence in patients with hypertension [76],[77]. Nonetheless, DBS can be made a safer and more reliabletherapy with improvements in hemostatic agents should hemor-raghing occur and intraoperative MRI to allow real-time image-guided electrode placement rather than requiring a second op-eration should the lead placement need to be adjusted.

G. Summary

DBS has become a preferred treatment for certain types ofneurological motor dysfunction, as well as the subject of in-vestigational study into other neurological diseases, particularlythose related to more primitive limbic structures. In the lack ofknowledge of the precise mechanism of its effectiveness, DBSstrategies to treat various diseases have revolved around tar-geting those brain structures which are believed critical in theneuropathology with high frequency electrical stimulation. En-gineering advances to aid functional neurosurgical techniqueshave been a critical part of the development of DBS in the pastand will continue to be so in the ongoing development of DBStechnology to provide effective, more reliable therapy to a widevariety of neurological diseases.

III. SITE-SPECIFIC DELIVERY OF DRUGS TO THE BRAIN FOR

TREATMENT OF PARKINSON’S DISEASE

A. Introduction

Aside from the advances in the use of DBS (Section II) to treatParkinson’s disease (PD), recent advances in engineering tech-nology have made it possible to potentially treat neurodegener-ative diseases such as PDusing computer-controlled pump andcatheter technology for site specific delivery of drugs into dis-crete brain areas. Such drugs at present cannot be administeredusing traditional drug delivery approaches. These technologies,pioneered by Medronic, Inc., have traditionally been used fortreatment of chronic pain by infusing morphine or baclofen intothe spinal cord. One type of computer-controlled pump, onetype of catheter and the wireless pump programmer can be seenin Fig. 7.

As stated in Section II of this review, PD is the secondmost common neurodegenerative disease ( million peopleaffected in the U.S.), which is characterized mainly by im-pairment of motor function, due largely to a progressivedegeneration of dopamine neurons in the substantia nigra thatinnervate the striatum [78]. The loss of the neurotransmitterdopamine leads to the cardinal symptoms of PD: resting tremor,cogwheel rigidity, bradykinesia (slow movements), and loss ofpostural stability. Therapeutic strategies for treating PD includereplacing striatal dopamine using the dopamine precursorlevodopa/carbidopa (Sinemet) or dopamine receptor agonists,or both, and additional drugs to help control the symptoms of


Fig. 7. Synchromed-II™ computer-controlled infusion pump with one designof a catheter shown with the wireless pump programmer. Photograph reprintedby permission from Medtronics, Inc., Minneapolis, MN.

the disease. As the disease worsens, patients usually becomeless responsive to pharmacological treatments and may chooseto undergo surgical treatments, such as DBS (see previous Sec-tion II). These treatments provide symptomatic relief, but donot slow or halt continued degeneration of dopamine neurons.One approach that could potentially slow or reverse the pro-gression of neuronal degeneration in parkinonsonian patientsinvolves administration of drugs known as neurotrophic factors,which are difficult to administer to the brain because at thepresent time they cannot be made in a form to be taken orallyor intravenously to reach brain targets.

Neurotrophic factors are endogenous proteins required forneuronal differentiation, guidance and survival during develop-ment, and often for the maintenance of the adult nervous system.Neurotrophic factors are produced and secreted by target cellsand then taken up by the innervating nerve terminals to exertboth local effects and, via retrograde axonal transport, trophiceffects in neurons [79]. These factors may not only slow thedegeneration of nigral dopaminergic neurons due to their neu-roprotective properties, but may also enhance the function ofresidual dopamine neurons or even repair/restore function to in-jured dopamine neurons. Little evidence has been found sup-porting that deficiencies of trophic factors are associated withthe etiology of PD [80]. However, considerable effort has beendevoted to the search for neurotrophic factors with survival-pro-moting properties on dopamine neurons that could potentiallybe used to treat PD. Several factors have been shown to producesignificant beneficial effects in the laboratory [81]. Only glialcell line-derived neurotrophic factor (GDNF) has been shownto dramatically protect and enhance the function of dopamineneurons in animal models of PD [82]–[84].

GDNF was identified as the first member of a new familyof cytokines in the transforming growth factor (TGF- ) su-perfamily. GDNF was originally isolated and purified from theconditioned medium of cultured rat glial cells from the B49 cellline [85], and the monomeric form of this heparin binding pro-tein consists of 134 amino acid residues. The biologically activeform is a glycosylated homodimer of kDa [86].

This section is a review of studies carried out in a nonhumanprimate model of PD and in humans with PD involving site-spe-cific delivery of GDNF by computer-controlled pumps coupledto infusion catheters [84]. While this work focuses on studiesof GDNF and its potential use in treating PD, these studies laythe foundation for the site-specific delivery of many drugs to thebrain that may be beneficial for treatment of neurodegenerativediseases and brain disorders. In addition, this section highlightslong term drug delivery strategies that can be combined in thefuture with microelectrode technologies (Section II) and bothinvasive and noninvasive BCI technologies to make the nextgenerations of devices to improve brain function in neurodegen-erative diseases and brain disorders, such as epilepsy.

B. Effects of GDNF in Non-Human Primates: Proof of Concept

Data collected in cell culture [85]–[87] and in rodent modelsof PD [88]–[92] showed that GDNF can be both neuroprotectiveand neurorestorative for dopamine neurons providing supportfor the use of GDNF in treating PD. Studies involving GDNFtreatment in rodent models are limited in their relevance to thehuman as rodents have a much smaller nervous system that dif-fers significantly in numerous neuroanatomical and neurochem-ical parameters from humans. In contrast, nonhuman primatespossess a central nervous system and behaviors much closer tohuman.

The late stages of human PD can be modeled using rhesusmonkeys (Macaca mulatta) administered 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP, [93]–[95]), which is a toxinthat also produces parkinsonism in humans. MPTP inducesbehavioral features very much analogous to idiopathic PD. Ourgroup has carried out an extensive series of experiments tostudy the restorative effects of GDNF in nonhuman primatesexpressing hemiparkinsonian features as a result of infusionsof 2.4 mg MPTP per animal into the right carotid artery [96].

From prior studies it is difficult to distinguish between the re-sults from protection and restoration because GDNF treatmentis initiated in the hours to days following a lesion, while the in-jury sequelae are still unfolding after the lesion. Another issue isthe level of biologically available GDNF necessary to producebeneficial effects. For instance, while significant beneficial ef-fects can be seen from viral vector GDNF transfection [97] thelevels of biologically available GDNF producing these effectsare unclear. Therefore, to determine the amount of biologicallyavailable GDNF necessary to produce beneficial effects, a seriesof experiments were undertaken in our laboratory to study thesafety and efficacy of chronically infusing computer-controlleddoses of GDNF into the primate brain using implantable, pro-grammable pumps (Medtronic Inc., Minneapolis MN).

All our studies were conducted using the SynchroMed™Model 8616-10 pumps and a SynchroMed™ Model 8820


computer. The pump can dispense drugs in a variety of ways(e.g., continuous, bolus/timed infusion). The model 8616-10pump is a round titanium disk (one inch thick and three inchesin diameter with a 10 ml capacity). The implantable pump isconnected to a catheter, which is usually made of polyurethane.The catheters are stereotactically implanted into the brain asper previously described procedures [98]. Prior studies haveused different types of catheters (1 mm O.D.) for each of thethree targets studied in our experiments: the lateral ventricle,the putamen and the substantia nigra. The choice of cathetertype and pump programming of the different catheters is amajor technical issue, which has not been fully studied. Theventricular catheter had a hole in the tip with two adjacentside holes for drug delivery (model 8770AS). Three differentcatheters have been used for intraparenchymal delivery todate in nonhuman primates. To chronically deliver GDNF intothe putamen, we used a porous tip catheter (model 8770IP3)or a multiport catheter with a radiodense-closed tip (model8770IP24A). The multiport catheter was composed of sixlaser holes that are placed radially over each 90 degrees of thecatheter’s circumference over a longitudinal distance of 3 mm,for a total of 24 laser holes ( or 37.5 m in diameter).The most proximal set of radial holes were positioned 0.5 mmfrom the catheter tip. For placement into the substantia nigra,we used catheters having a single opening ( or 250 min diameter) at the tip (model 8770IP1A).

The catheter was usually surgically positioned into the brainafter a minimum of two months following MPTP administra-tion, which allows for stabilization of the parkinsonian featuresof the animals. The catheter is then seated in the groove of anL-shaped nylon device anchored against the skull using twonylon screws, and connecting tubing is tunneled to the pumpthat is subcutaneously implanted in the lateral abdominal regionof the nonhuman primate [98].

A large portion of dopamine-containing fibers from the sub-stantia nigra extend to the striatum. GDNF is believed to beretrogradely transported and as such application of GDNF tothe lateral ventricle adjacent to striatal dopamine fibers or di-rectly into the striatum has been the focus of prior studies innonhuman primates [99]. These two targets were studied usingthe programmable pump technology.

Large proteins like GDNF diffuse slowly in brain tissue andcan be rapidly degraded by proteases. Strategies for rapidly dis-tributing the trophic factor through tissue to the targeted cellpopulations may be important for brain delivery. Convectionenhanced delivery (CED) is one approach that uses bulk flowto significantly enhance tissue penetration and distribute macro-molecules over larger volumes in the brain [100]. Thus, in addi-tion to a basal infusion rate of 0.033 l/min (i.e., 2 l/hr), whichwas necessary to keep the pumps operating properly, the pumpswere programmed to deliver brief pulses at a CED rate of 10.5

l over 30 s (equivalent to 21 l/min), once every hour, for atotal volume of 300 l per day. We demonstrated that chronicinfusions of 7.5 or 22.5 g/day GDNF into the lateral ventricleor the putamen for 3 months promoted restoration of the nigros-triatal dopaminergic system and significantly improved motorfunctions in MPTP-treated rhesus monkeys [101]. The func-tional improvements were associated with a pronounced up-reg-

ulation and regeneration of nigral dopamine neurons and theirprocesses innervating the striatum. First, we observed a %bilateral increase in substantia nigra dopamine neuron cell size.Second, a % bilateral increase in the number of substantianigra cells expressing the dopamine marker tyrosine hydroxy-lase were seen. Third, we saw a % bilateral increase, indopamine metabolite levels in the striatum and a % bilat-eral increase in these markers in the globus pallidus. Fourth, weobserved 233% and 155% increases in dopamine levels in theperiventricular striatal region and in the globus pallidus, respec-tively, on the MPTP-lesioned side. Finally, we saw a five-foldincrease in tyrosine hydroxylase positive fiber density in theperiventricular striatal region on the MPTP-lesioned side [101].

All of the effects from chronic administration of GDNFwere greater than those previously seen from our prior workon single injections of GDNF in MPTP-lesioned rhesus mon-keys [99]. Data from our nonhuman primate studies providedsupport that chronic, intraparenchymal delivery of GDNF bycomputer-controlled pumps promotes restoration of the nigros-triatal dopaminergic system and significantly improves motorfunctions in MPTP-lesioned hemiparkinsonian rhesus monkeysmodeling the advanced stages of PD. These studies laid thefoundation for using this technique in PD patients.

C. Site-Specific Brain Delivery of GDNF in Humans withParkinson’s Disease

1) Bristol, England Phase-I Trial: The control achieved bycomputer-controlled pumps and infusion catheters in animalmodels of PD [101], [102] made this approach the best forcontinued trials in humans. In a preliminary study conductedin England [103], five advanced PD patients with a previoushistory of good responses to levodopa underwent unilateral

or bilateral insertion of drug infusioncannulae surgery into the dorsal putamen. Human recombi-nant GDNF (14.4–43.2 g per day) was chronically infusedvia an indwelling 0.6-mm intraparenchymal catheter(s) andSynchroMed™ pumps implanted in the subject’s abdominalregion. Patients were assessed pre- and post-operatively (3, 6and 12 months) according to the core assessment program forintracerebral transplantations (CAPIT), in order to documentchanges in disease severity and medication requirements [104].

Chronic GDNF infusion resulted in improved motor functionin all patients in this Phase I trial [103]. After one year, therewas an average 39% improvement in the OFF-medicationmotor scores (UPDRS III) and a 61% improvement in theactivities of daily living (UPDRS II) scores in these subjects.The overall dyskinesia scores were significantly reduced byover 60% while on medication. The patients also underwent [F]dopa positron emission tomography (PET) scans at baseline,6, 12, and 18 months after GDNF infusion. GDNF infusionwas associated with an average 28% increase in [ F]dopauptake around the catheter tip after 18 months, supporting anincrease in dopamine storage in the putamen, and possiblydopamine function, following GDNF treatment. The chronicGDNF infusion was apparently well tolerated in all patientsand limited side effects were observed. There was no nausea,anorexia, vomiting or weight loss reported. Patients did ex-perience tingling passing from the neck down the arms while


flexing the neck (Lhermitte’s sign), which was mild, intermit-tent and this was not troubling to the patients. After 2 years ofGDNF infusion, there were still no serious clinical side-effectsand patients improved even further showing an average 57%improvement in their OFF-medication motor scores and 63%improvement in their activities of daily living scores [105].

2) University of Kentucky FDA-Approved Phase-I Trial: Theinitial trial in the U.K. was followed in the U.S. at the Universityof Kentucky, with an FDA-approved open-label Phase-I safetytrial in ten patients with advanced bilateral PD who underwentunilateral putamenal administration of GDNF for six months[106]. Each patient had an MRI-based stereotactic implantationof an intraputamenal multiport catheter (1.65 mm O.D. diam-eter, 40 holes, 4 per 0.5 mm placed every 90 , 5 mm length;Model # 10532, Medtronic, Inc.), which was inserted into themedial putamen contralateral to the most affected side. TheSynchroMed infusion pump (Model # 8626L-18, Medtronic,Inc.) was implanted subcutaneously in the ipsilateral lowerabdominal wall and tubing was tunneled with to connect thepump to the indwelling intraputamenal catheter. The pump wasprogrammed to infuse at a continuous basal infusion rate of2 l/hour. Small bolus CED injections (21.3 l delivered in117 s) were delivered every six hours to increase the brain areaaffected by the drug. Each subject was placed on a dose-esca-lation regimen of GDNF: 3, 10, and 30 g/day at successiveeight-week intervals, followed by a one-month washout period.Behavioral testing was conducted in an operationally definedOFF-medication condition: medications were withheld for 2.5times the duration of each drug’s predicted serum half-life.No changes were made in the patient’s anti-PD drug regimensduring the study.

Following 6 months of GDNF administration, total UPDRSOFF- and ON-medication scores were significantly improved33% and 34%, respectively. In addition, both motor UPDRSOFF- and ON-medication scores were significantly improvedby 30% at 6 months compared to baseline values. All signif-icant improvements of motor function continued through theone-month washout period similar to findings in nonclinicalstudies in nonhuman primates [107], [108]. The only side effectobserved was transient Lhermitte’s symptoms in two subjects.In addition, improvements were bilateral as measured by bal-ance and gait and increased speed of hand movements. Bilateraleffects from unilateral GDNF administration have been seen innonhuman primates [99], [108]. The neural circuitry responsiblehas been partially worked out and likely involves pathways fromthe substantia nigra pars reticulata to the thalamus, thalamo-cor-tical projections and bilateral glutaminergic cortico-striatal pro-jections [109], but this needs to be more fully investigated.

These promising results obtained in all 10 patients in ouropen-label Phase-I study, together with those described by Gilland colleagues [103] in five additional patients, led to an FDA-approved Phase 2 study.

3) Amgen-Sponsored FDA-Approved Phase-2 Mulit-Center,Randomized, Placebo-Controlled Trial in Humans With PD:Largely based on the Phase-I trials, an FDA-approved Phase-II,multicenter, randomized, double-blind, placebo-controlledstudy was conducted to evaluate the efficacy and safety ofintraputamenal GDNF infusion by catheters and programmable

pumps in PD patients [110]. The primary end point was thepercentage change from baseline in the UPDRS OFF-medi-cation motor score after 6 months of treatment with baselinescores being recorded after 12 hours without antiparkinsonmedication. Also, patients underwent [ F] dopa PET scans atbaseline and 6 months after GDNF infusion.

Thirty-four patients were enrolled in the trial and were di-vided in two treatment groups: GDNF- and vehicle-treatments.Analogous to the Bristol study, bilateral single-port intra-parenchymal catheters (Model 8760, Medtronic, Inc.) werestereotactically implanted into the posterior dorsal putamen andattached to separate SynchroMed® infusion pumps (Medtronic,Inc.) placed in the patient’s abdomen. The pumps infused 15

g/putamen/day at a continuous rate of 6.25 l/hour. Dueto failure to tolerate the scanning protocol and head motionartifacts, [ F]dopa uptake was only analyzed in 22 subjects.GDNF-treated patients showed a median increase of23.1% in the posterior putamen compared with a median re-duction of % in the placebo group for a betweengroup difference of % after 6 months of infusion. How-ever, despite increased [ F]dopa uptake, the mean percentagechange in UPDRS OFF-medication motor scores was only 10%in the GDNF group compared with 4.5% in the placebo group.This treatment difference was not significant. This is in sharpcontrast with the two Phase-I trials in a total of 15 PD patients[103], [106].

The lack of effects in the Phase-II trial relative to the appar-ently successful Phase-I trials may be explained by differencesin patient selection and treatment strategies, including drugdosage and infusion methods. First, the patients enrolled inthe open-label trials had generally milder disease than thoseenrolled in the Phase-II trial. Second, baseline UPDRS OFFmotor scores were determined under different conditions: base-line scores in the Phase-II trial were recorded after medicationswere withheld for 12 hours whereas baseline scores in theKentucky Phase-I trial were determined after medications werewithheld for 2.5 times the duration of each drug’s predictedserum half-life (i.e., hours in some cases). Third, thepatients in the Phase-II trial received a lower dose of GDNF(15 g/putamen/day) during the study, whereas the patients inthe Phase I studies received up to 30 g/putamen/day [106]and 43.2 g/putamen/day [103]. Fourth, the Phase-II studyemphasized point source delivery of GDNF using single-portcatheters and a low infusion rate (0.1 l/min), whereas theKentucky Phase-I study emphasized tissue distribution usinga multi-port catheter and bolus infusion (21.3 l/min, onceevery 6 hrs) and the Bristol studies used a smaller catheterand drug infusion rates that likely achieved a better volume ofdistribution through CED. Thus, the volume of GDNF distri-bution in the brain parenchyma needed to induce functionalimprovements may have been insufficient in the Phase-II trial.Finally, the different clinical results could be due to a placeboeffect since both the Bristol and Kentucky Phase-I trials wereconducted in an open-label fashion. However, this seems un-likely considering that the double-blind study did not reveala significant placebo effect [110], and because progressiveclinical improvements were observed for up to 3 years in thePhase-I [103], [106], [111].


D. Point Source Concentration of GDNF May Explain Failureof Phase II Clinical Trial

There were major technical differences between the threeclinical trials in the catheters and infusion protocols used toevaluate intraputamenal infusion of GDNF for the treatment ofPD [112]. We have recently tested the hypothesis that GDNFbioavailability in the brain was not optimal in the Phase-IIstudy and may have contributed to the failure to replicateresults from the Phase I trials and animal studies. To determineif problems in drug bioavailability could have contributed tothe discrepancies between Phase I and II studies, we haveanalyzed the distribution of intraputamenally infused GDNF inthe nonhuman primate [113]. -GDNF was unilaterally in-fused into the putamen of three adult rhesus monkeys using thedelivery system and infusion protocol followed in the Phase-IIclinical trial [110]. Three age-matched animals received vehicleinfusions following identical procedures.

The volume of distribution (Vd) of GDNF around the catheterwas determined by immunocytochemical methods. After sevendays of treatment, GDNF was found to be concentrated aroundthe catheter tip with distribution ranging from a low of 87 mmin one animal to 369 mm in the monkey with the highest Vd.Considering that the normal volume of the human putamen inone hemisphere ranges from 4000 to 5000 mm [114]–[116],the limited Vd of GDNF seen in nonhuman primates would onlycover between 2–9% of the average human brain putamen. Thisstudy provided a snapshot at one time of treatment. However,available data suggests that the Vd for GDNF would not in-crease over time. The range of infusion in our study was nearlyidentical with the limited Vd found using the same catheterfor infusing GDNF into the nonhuman primate substantia nigra[102]. This is in sharp contrast to the much greater distributionachieved with multiport catheters and pulsatile delivery some-what analogous to the Kentucky Phase-I trial [106], [117]]. Thedelivery protocol and catheter used in the Phase-II GDNF in-traputamenal infusion study should be considered as significantfactor in the failure of this clinical trial to replicate the results ofnumerous animal studies and the two Phase-I trials.

E. Concerns Over Two Safety Issues Derail All GDNF Trials

Since the completion of the Phase-II clinical trial, two safetyconcerns have emerged, which led, in part, to the discontinu-ation of the use of human recombinant GDNF in PD patients.First, antibodies to GDNF have been identified in the blood ofsome patients. The presence of neutralizing antibodies, whichcould potentially cross-react with endogenous GDNF, has beendetected in three patients enrolled in the Phase-II trial [110] andone patient enrolled in the Kentucky Phase-I trial [106], [111].Although the long-term consequences of these observations areunknown, GDNF antibody-induced problems have not been de-tected in these patients at this time.

Second, 4 of 15 rhesus monkeys receiving high doses of 100g GDNF per putamen/day during a 6-month toxicology study

presented with focal cerebellar injury [110], [112], but with noobserved behavioral abnormalities. Interestingly, all but one an-imal had been withdrawn from GDNF for 3 months prior to ter-minating the study. The lesions were characterized by multiseg-mental Purkinje cell loss associated with variable atrophy/dis-

ruption of the overlying molecular layer and a variable loss ofunderlying granule cells. At this time, it is not clear whetherabrupt GDNF withdrawal contributed to the cerebellar lesionsseen in the toxicology study or whether the lesions were the re-sults of an experimental artifact [112]. Clearly, additional toxi-cology studies are needed to address these questions.

After the Phase-I trial conducted at the University of Ken-tucky was halted by the sponsor due to the safety concerns men-tioned above, all 10 patients were monitored for an additionalyear to evaluate the effects of drug withdrawal [111]. The de-livery system was reprogrammed to deliver sterile saline at thebasal infusion rate of 2 l/h. Benefits from treatment were lostby 9 to 12 months after the GDNF infusion was halted. Anti-bodies to GDNF have developed in seven patients but with noevidence of clinical sequelae. In addition, there was no evidenceof GDNF-induced cerebellar toxicity, as evaluated using MRIanalysis and clinical testing [111].

F. Summary

Trophic factors are proteins with great therapeutic potential inthe treatment of neurodegenerative diseases such as PD. Novelmethods for direct site-specific sustained delivery of GDNF intothe nigrostriatal pathway have been studied in nonhuman pri-mates and in humans. The current data from the Phase I andPhase II trials of the delivery of GDNF to the putamen in pa-tients with PD are unequivocal and additional Phase II studies,using drug delivery parameters more analogous to the Phase Istudies, are needed to determine if this is a viable approach fortreating PD. The potential safety risks of GDNF antibodies andcerebellar injuries are unknown and should be carefully evalu-ated. The major difficulty with risk assessment at this time isthe failure to carry out a Phase-II trial replicating the successfulPhase-I trials in dose and methods of trophic factor delivery. Inaddition, the Phase-II trial may have been statistically under-powered [118]. Thus, before any definitive conclusions can bemade regarding the use of GDNF as a therapy for PD, a prop-erly designed, adequately powered multicenter Phase-II clinicaltrial should be conducted in PD patients to fully evaluate its po-tential. However, the novel drug delivery technology employedwas well tolerated in all the patients tested, which totaled 49.This work lays the foundation for site-specific delivery of otherdrugs, which cannot be easily administered to the brain that mayaid in the treatment of severe brain disorders and neurodegener-ative diseases. In addition, this technology can be coupled withother devices in the future to better control diseases and disor-ders of the CNS.

IV. CNS ELECTRODE TECHNOLOGIES

Electrodes provide a means to stimulate and record electro-physiological and chemical activity of neurons [119]–[122].This section deals with an overview of electrodes that are im-planted directly into the brain to measure action potentials fromsingle cells, neurochemical activity from nerve terminals andfor electrical stimulation of neurons. This is a major growth areafor sensor technologies. In addition, measures from subduralor epidural strips of electrode arrays used to record corticalpotentials will be discussed, as these are the most extensivelyused in humans for surgery and research on epilepsy.


Fig. 8. Photomicrograph of silicon-based microelectrode arrays constructed at the University of Michigan. Michigan probe photos provided by David Anderson atthe University of Michigan Center for Neural Communication Technology, a NIH/NCRR Resource Center. (Used with permission from Encyclopedia of Sensors,Burmeister and Gerhardt, 2006.)

Microelectrodes are enabling technologies that allow infor-mation from the brain to be recorded to provide input and con-trol of BCI devices [119], [120], [122]. Without these deviceswe cannot transfer information from the brain that can be usedto control BCI instrumentation. As such, it is too often assumedthat microelectrodes for research and BCI applications are fullyworked out and ready to use. In reality, there is a great need fornew types of electrode technologies to further pursue BCI appli-cations. We will discuss numerous current designs but suggestto the reader more comprehensive reviews of this technology[119]–[121]. The major future challenges will be discussed atthe end of this section.

A. Microelectrode Arrays

It is widely known that photolithographic methods employedin the microcircuit industry are used for the mass fabricationof microelectrodes [119], [121]. Recording surfaces as smallas 5–10 microns can be routinely produced and in the futuremicroelectrode features as small as 0.1 microns will likely beachieved [122]. This rivals the smallest traditional glass-tippedmicroelectrode for patch-clamp or intracellular recordings.More recently less expensive screen-printing methods havegained popularity to fashion features as small as 50–100 mi-crons and this is any area, which will likely have continuedgrowth. In addition, many designs can be simultaneously pat-terned on the same substrate, allowing for large numbers ofmicroelectrodes designs and reductions in development costs.Micro-machining procedures may be used to construct micro-electrodes with multiple recording sites in spatial arrangementsthat may be used to record from layered brain structures.While smaller surfaces may be useful for certain applicationsinvolving chemical sensing, electrophysiological recordingsand neurochemical recordings, electrode impedance is a majorissue that must be addressed for each application and may haveto be empirically determined for given electrode design, due tothe materials used and the recordings surfaces employed (seebelow).

There are four basic layers of most microelectrodes con-structed using thin film techniques. The substrate is thefirst layer, which is composed of silicon, ceramic, silicon,silica/glass, or polyimide. An insulating layer such as siliconnitride often covers the substrate when a silicon substrate isused. An adhesion layer of titanium or chromium is applied to

the substrate to allow the active metal to adhere to the substratesurface if needed. Photolithography or screen-printing is usedto pattern microelectrode recording sites, connecting lines andbonding pads using Noble metals such as Au, Pt, or Ir. Aninsulating layer such as polyimide, silicon nitride or alumina isapplied to the connecting lines [119], [121]. After applicationof an insulating layer, only the recording sites and bonding padsare exposed. Microelectrodes constructed using eight or morephoto masks with very specialized layers have been reported[121], [124]–[126]. The final shape of the microelectrodes isachieved by chemical etching, laser cutting, or diamond sawprocedures. Finally, the bonding pads of the individual micro-electrodes are wire bonded to a larger printed circuit board(PCB) holder or flexible connector for connection to recordingequipment.

B. Silicon-Based Microelectrodes

Silicon was the first substrate and is currently the most widelyused to construct semiconductor-based microelectrodes. Therehave been numerous reports of such microelectrodes for brainrecordings and brain tissue stimulation [122], [124]–[132].Individual microelectrodes can be formed from a single sub-strate simultaneously without the need for laser machining orsawing using chemical etching procedures. Very small featuressuch as channels in the substrate can be constructed and verythin microelectrodes can be fashioned by etching to reduce thesubstrate thickness. Substrates as thin as 6–15 microns havebeen reported [121], [133]–[135]. However, a very thin siliconsubstrate is flexible and fragile. Flexibility is both desirable anda liability. One must realize that long thin flexible silicon elec-trodes can be difficult to implant. In addition, an insulating layerbetween the metal and the silicon substrate may be necessaryto reduce electrical cross-talk between adjacent recording sitesbecause silicon is a semiconductor [121], [133]–[137]. Thesemiconductor properties of silicon can be altered by doping[124], [125], [137]. Silicon is very compatible with on-boardcircuitry. Thus, silicon has many features that have madeit widely used as the foundation for forming microelectrodearrays. Photographs of some silicon-based microelectrodes con-structed at the Center for Neural Communication Technologyat the University of Michigan are shown in Fig. 8, [123]–[125],[133]–[135]. These represent many of the current designs thathave been used for BCI applications in rats and nonhuman


primates. In addition, this grouping of microelectrodes showssome of the versatile designs afforded by this approach.

A very promising silicon-based electrode array design hasbeen developed by the VSAMUEL consortium (EuropeanUnion, Grant #IST-1999-10073 termed ACREO (ACREO AB,Sweden) microelectrode arrays [138], [139]. These micro-electrodes have 1 to 8 recording shafts, are very versatile andflexible and appear to have very promising insertion mechanics[138]. These also represent a major microelectrode manufac-turing capability in the European Union.

Additional novel devices can be integrated onto the electrodesusing silicon-based microelectrodes. Holes have been etchedinto the substrate to aid in securing the microelectrode into braintissue and to perhaps better integrate the electrode into the brainextracellular matrix [131], [128], [129], [140]. Multiple flowchannels for the delivery of chemicals/drugs, while performingelectrophysiological recordings, have been etched into the sil-icon probe substrate [121], [141], [142]. Integrated Ag/AgClreference electrodes have been included on microelectrode ar-rays [121], [142]. An integrated polysilicon micro-heating de-vice has been constructed [144]. On-electrode amplification andsignal processing may be achieved by including VLSI chips onthe silicon substrate [143], [145]–[147]. One of the merits ofsilicon-based microelectrodes is that it allows hybrid microelec-trode designs to be developed.

Extensive microarrays with 100 recording sites have beendeveloped to provide an interface for prosthetics in brain andspinal cord, which is the foundation for the work of Normann,Donoghue and coworkers [122], [127], [148]–[151]. These de-signs are currently being used in humans and represent the firstBCI microelectrode arrays that have been sterilized and usedin both nonhuman primate and human trials. From the 10 10mm planer substrate individual microelectrode ‘shafts’ extend1.5 mm. The shaft tips are metalized with Pt over doped siliconfor conduction down the shaft. The conducting doped silicon isinsulated using glass and silicon nitride. Fig. 9 shows an SEM ofone of the Utah electrodes. Similar three dimensional microelec-trode arrays can be constructed by combining many planar sil-icon multi-shank microprobes (see Fig. 10) [125], [152]. Planarmicroelectrode arrays have been used to map neuronal commu-nication in brain slices [153].

C. Polyimide-Based Microelectrodes

Polyimide films (Kapton (Dupont, Circleville, OH), havebeen used as a substrate as well as the top insulator for mi-croelectrodes used for intra-cortical implantation. Besidespolyimide, the polyimide precursor, parylene (Dupont), canbe spun onto surfaces as a liquid then polymerized at hightemperatures (200 C). Microelectrodes less than 20 microns inthickness have been constructed [154]. Polyimide as a substrateis very structurally flexible. Fig. 12 shows a photomicrographof a three dimensional multi-shank microelectrode designedfor intra-cortical implantation. Although the flexibility of poly-imide can make implantation difficult, a flexible microelectrodemay, in certain cases, contribute to less tissue damage. Guideincisions in the neural tissue are often needed to prevent themicroelectrode shaft from buckling upon microelectrode im-plantation [154]. Polyimide microelectrodes have even been

Fig. 9. SEM of Utah Electrode Array (UEA) for visual prosthetics. The arrayconsists of 100 individual microelectrode ‘shafts’ that extend 1.5 mm from the10� 10 mm planer substrate. SEM provided by R. A. Normann, Department ofBioengineering, University of Utah, Salt Lake City. (Reprinted with permissionfrom Encyclopedia of Sensors, Burmeister and Gerhardt, 2006.)

Fig. 10. Photomicrograph of a multi-shank probe formed using several sil-icon-based microelectrodes. There are multiple recording sites on each shaft forrecordings at different brain depths. These Michigan probe photos are providedby the University of Michigan Center for Neural Communication Technology,a NIH/NCRR Resource Center. (Reprinted with permission from Encyclopediaof Sensors, Burmeister and Gerhardt, 2006)

driven through tissue using surgical suture [155]. Interestingly,the substrates can be folded to provide rigidity [156]. Perfo-rations in the polyimide have been used to help secure themicroelectrodes in place [155]. Multiple layers can be used toconstruct useful microelectrodes. Indentations or wells may beconstructed by leaving a via open in a polyimide layer [154].

D. Ceramic-Based Microelectrodes

Ceramic (alumina (Al O ) has been used as a substrateto reduce cross talk between adjacent connecting lines onmicroelectrodes [121], [136], [157], [158]. Ceramic is mechan-ically strong, allowing for development of microelectrodesthat can access much deeper brain structures (up to 5–6 cmversus 2–4 mm for silicon). Placement of the microelec-trode in tissue without flexing or breaking can be achieved.Multisite microelectrodes on ceramic substrates for use inanimal models have been constructed [135], [158]. In addition,


Fig. 11. Shown are photomicrographs of numerous ceramic-based multisitemicroelectrode designs. (A) 100 �m Serial—10� 10 �m recording sites, (B)400 �m Serial—20� 20 �m recording sites, (C) 2500 �m Serial-50� 50�m recording sites with 400 �m center-to-center spacing, (D) 5000 �mSerial—100� 50 �m recording sites, (E) 7500 �m Serial—150� 50 �mrecording sites, (F) 2500 �m Pairs—100� 25 �m recording sites, (G) 4500�m Pairs—300� 15 �m recording sites, 30 �m spacing, (H) 7625 �mPairs—305� 25 �m recording sites (I) 4500 �m Eliminator—300� 15�m recording sites. Photographs courtesy of Mr. Peter Huettl at the Centerfor Microelectrode Technologies, University of Kentucky, Lexington, KY.(Reprinted with permission from Encyclopedia of Sensors, Burmeister andGerhardt, 2006.)

Fig. 12. Magnification of several recording sites on a polyimide-based micro-electrode with perforation holes to help secure the microelectrode in tissue.Adapted from [155]. Used with permission from Elsevier Publishing. (Also inEncyclopedia of Sensors [Burmeister and Gerhardt, 2006]).

multisite microelectrodes on ceramic substrates have been con-structed for electrochemical measures of neurochemicals [121].These microelectrodes were developed for quantifications ofcompounds that are not readily measured at carbon fiber micro-electrodes such as glutamate, glucose, and choline [158]–[160].Nano-porous anodic aluminum oxide has been reported asa substrate material for enzyme-coated microelectrodes withenhanced surface area [136].

Microelectrodes must be mechanically cut from the substratewafers because ceramic is not compatible with etching proce-dures. Laser machining is the most flexible way to cut the mi-croelectrodes from the bulk wafers and complex shapes can beformed. However, due to the stepping of the laser, laser ma-chining can produce rough edges that may cause potential prob-lems with insertion of the microelectrodes into tissues. Much

Fig. 13. Photograph of a polyimide-based microelectrode array for intracor-tical implantation. The semitransparent polyimide substrate can be folded toachieve multi-shank arrays. The metal connecting lines are visible. Photographprovided by Daryl Kipke of the University of Michigan Center for Neural Com-munication Technology. (Reprinted with permission from Encyclopedia of Sen-sors, Burmeister and Gerhardt, 2006.)

smoother microelectrode edges may be formed using a diamondsaw, which polishes as it cuts. Minimal CNS tissue damage is re-quired to study the biology of the intact brain. In addition whenusing a diamond saw it is more difficult to form complex shapesbecause saws generally cut in straight lines. The use of excimerlasers may provide smoother edges than conventional laser ma-chining. Thinner microelectrodes may be achieved by polishingthe ceramic substrate [18].

Numerous 4 and 5 site PT microelectrodes on ceramic sub-strates have been developed. The versatility of the lithographicmethods can be seen in Fig. 11. In general, recording sites areeither grouped in side-by-side pairs or in a linear arrangement.Two recent designs have the microelectrodes configured in alinear arrangement similar to the previously reported 50 50micron microelectrodes [158]. The new designs have largerPt recording sites of 50 100 and 50 150 microns in orderto investigate whether larger recording sites can record bettersingle unit activity or lower detection limits for chemicalrecordings. The other two new designs have two sets of micro-electrodes arranged in a side-by-side arrangement: 25 100and 25 300 microns. Recording site dimensions vary from10 10 microns to 25 300 microns depending upon theapplication. Other designs (dimensions in m) include 10 10serial (200 spacing), 20 20 serial (200 spacing), 50 50serial (200 spacing), 25 100 pairs (15 spacing), 50 100serial (200 spacing), 50 150 serial (200 spacing), 25 300pairs (15 spacing), 25 300 pairs (30 spacing), 50 50 serial(400 spacing), 15 300 “eliminator,” and 15 300 “T-elimi-nator.” This also shows the versatility of such microelectrodefabrication approaches. Although the ceramic-base multisitemicroelectrodes were originally intended to be disposable (onetime use), a cleaning procedure has been developed to allowfor multiple uses for in vitro and acute in vivo recordings, dueto the durability of the materials in vivo [121], [159].


Fig. 14. Subdural ECoG micro-grid for epidural recordings. (Reprinted withpermission from D. Moran.)

E. ECoG Strip Electrodes

A promising area of study involves the use of Electrocortio-graphic (ECoG) recordings for BCI [161]–[163]. This is a tech-nology that grew out of clinical EEG recordings through thework of Jasper and Penfield. This technology has been primarilyused by surgical teams to record from cortical areas in patientswith drug refractory temporal lobe and frontal lobe epilepsy todetermine the best surgical targets for transection. We will notreview this extensive area as applied to epilepsy surgery. Rather,we will discuss the electrodes that are available for such record-ings in humans as these electrodes, while invasive, may possessmany of the features that make them perhaps ideal for BCI ap-plications. First, the safety of the technology, at least acutely,has been tested in thousands of human subjects. Second, ECoGhas higher spatial resolution than EEG (tenths of millimetersversus centimeters) and newer electrode designs (see Fig. 14)possess spatial resolution closer to that of direct penetratingelectrode recordings. Third, the signals recorded from the sur-face of the brain exhibit higher amplitudes with broader bandwidths. Fourth, patients undergoing epilepsy surgery comprisea large test-bed for investigating BCI technology that is startingto be investigated in the United States and Europe. Finally, suchproven technologies may have better long-term stability in vivo,but this is left to be determined.

One of the largest manufacturers of ECoG electrodes forhuman recordings is Ad-Tech Medical Instrument Corporation(Racine, WI). They design and manufacture % of the ster-ilized ECoG electrodes used throughout the world. Ad-Tech isan FDA and ISO13485 registered manufacturer of high qualitymedical devices. Ad-Tech has been active in the design, devel-opment, manufacture and marketing of intra-cranial monitoringstrip type, grid type, depth type and other related electrodes forover 22 years and successfully distributes in over 40 countries.These electrodes are used primarily by epilepsy centers world-wide and major institutions/medical centers that provide brain

mapping in their neurological programs. These electrodes aremade of implant silicone or polyurethane with micro-conduc-tors attached to stainless steel or platinum contacts (usually7 or 10 mm disks) that populate the dielectric area. Fig. 15shows several Ad-Tech ECoG strip electrodes ranging in sizefrom 4 to 64 recording sites. Proprietary connectors/cablesattach these electrodes to commercial monitoring equipment.Over 100 medical journal papers have been written on the useof Ad-Tech’s products for the treatment of epilepsy and otherneurological disorders and diseases [164], [165], (Ad-Tech(http://www.adtechmedical.com/articles.htm).

F. Major Challenges for Implantable Microelectrodes forLong-Term Use in Vivo

There are major questions that need to be addressed for thedevelopment of invasive microelectrodes for use in the labora-tory and for practical applications of BCI technology. These areas follows.

• What is the biocompatibility of the microelectrodes andhow is biocompatibility defined?

• How long do current microelectrodes routinely last invivo?

• How do we develop microelectrode systems that last forca. 5–20 years?

• Do we need special engineered materials to better integrateinto the CNS?

• How do we develop a systematic and scientific approach todevelop “implantable microelectrodes?

One of the largest challenges in the area of implantable elec-trodes for laboratory and BCI applications is the developmentof electrode arrays that will function in vivo for 5–20 years.The longest recordings from the CNS of individual unit activityin the context of BCI technology have been achieved by theuse of micro-wire arrays. In fact, over 1 1/2 years of recordinghave been reported in 2003 using micro-wire arrays [166].This has not been reliably achieved by methodology involvingthe silicon, ceramic or polyimide-based multi-electrode arraysthat have many advantages for future recordings involvingBCI technology. In the context of multi-electrode arrays, theresearch groups that have achieved the greatest success arethose of the University of Michigan and the University ofUtah. Drs. Schwartz and Kipke have been able to record from

functional silicon microelectrode channels with over 90high-quality recording spikes from an awake monkey as partof BCI control of a mechanical limb for over one year. This isground-breaking work that demonstrates the ability of the BCIto control a mechanical limb through recordings of the indi-vidual unit activity involving multi-single unit array electrodesof the silicon type by Donoghue, Normann, and others [122],[149], [167]. In addition, Dr. Kipke and colleagues have beensome of the first to push for the standardization for evaluatingmicroelectrode designs and performance through the Centerfor Neural Communication Technology at the University ofMichigan. As explored in this review, the field of microelec-trode technology can learn valuable lessons learned from thefield of DBS (Section II), drug delivery systems (Section III)


Fig. 16. (A) Diagram of monkey reaching and grasping in different places in space. Upper left shows example multiple spike trains recorded from area M1using multi-electrode array (in this case, � � �� units). Center bottom shows example EMGs recorded from muscles of contralateral arm and hand (in this case,� � ��). (B) Block diagram of model structure. Multi-spike train input nonlinear Volterra kernel analysis (second order) is followed by an exponential activationfunction to output a single time-series EMG; analysis is repeated for multiple EMGs to reach a MIMO model.

Fig. 15. Four to 64-site ECoG recording strip electrodes. (Reprinted with per-mission from Ad-Tech Medical Instruments.)

and noninvasive BCI technologies (Section VI), all of whichhave had a history of use in patients.

V. BRAIN-IMPLANTABLE NEURAL PROSTHESES

A. Motor System Prostheses

1) Population, Ensemble Coding: With the development ofinvasive arrays of electrodes of the type described in the pre-vious section, it became possible to investigate the simultaneousactivity of small – populations of neurons duringbehavior, with the intent of determining the “state” of a neuralpopulation that under normal circumstances controls a motormovement or a sensory response to a stimulus event. Then, usingthat measure of the dynamic response of the population duringthe behavior or during the sensory stimulation, a “substitute”stimulation would be created to function as a surrogate for thephysiological response. Take the example of creating a neuralprosthesis for lost upper limb function (upper arm, elbow, wrist,hand, and fingers): the goal is to create a prosthesis that wouldallow an animal to reach to a particular place in 2-D or 3-Dspace. Early studies by Georgopoulos and others in intact mon-keys have shown that neurons in the M1 region of motor cortexhave a “preferred direction”, i.e., they will fire at their max-imum rate when an intact animal reaches to a particular place[168], [169], [177]. The firing rate of a given neuron gradu-ally decreases as the animal reaches to progressively more dis-tant locations from that preferred place. However, the “response


Fig. 17. Supinator EMG predicted by various Volterra models versus time with scatter plots versus actual EMG.

fields” of different neurons overlap substantially, so the phe-nomenon of a preferred direction is a statistical one, and canbe represented by a “population vector” for the cells in question[168], [169]. Chapin, Nicolelis, Schwartz, Donoghue, Taylor,and others have since been able to demonstrate that a populationvector or some other statistical measure of neural population dy-namics, can provide an accurate description of the kinematicsof a monkey’s behavior during trained reach and grasp/touchfor food or drink reward, and that whatever measure is usedcan be predicted based on population activity recorded in realtime [170]–[184], [286]. Some of those modeling methods thathave used successfully include principal components analysisand multivariate linear regression, among others. Thus, thereare now robust methods for translating multi-neuron record-ings into a continuous prediction of ongoing limb movementfor a given subject. This also is true for reach-and-grasp in 3-Dspace, provided monkeys have real-time visual feedback of theirbrain-controlled arm/hand trajectories (closed-loop condition)[184]. M1 cell tuning properties change when used for brain-controlled movements. By using control algorithms that trackthese changes, subjects can learn intended movement control in3-D space with a higher accuracy and fewer neurons than in anopen-loop condition.

2) “Brain Control” of a Robotic Device: The fact that pre-dictions about animals’ reach behavior can be made in real timeraised the possibility for an animal’s brain representation ofmotor commands to actually control an external device, suchas a robotic arm. The latter was originally demonstrated byChapin in rats [177], and later by several other labs in monkeys[178]–[184]. These original demonstrations showed that whileanimals learned to press a bar or manipulate other controls in re-turn for reward, animals either learned serendipitously or weretrained explicitly that they could be rewarded for generating thebrain signal alone, in the absence of a behavioral response to thecue. In other words, if an animal was trained to touch a targetregion on a screen, the population dynamics for reaching to thetarget location is generated by the animal’s M1 cells a few hun-dred ms prior to arm/hand movement. The training paradigmcould be configured, however, such the animal was rewardedwhen the M1 brain response was generated, but before the an-imal moved. Thus, the animal would eventually learn that brainsignals alone would generate reward, and that the animal’s envi-ronment could be manipulated by “intentions” alone, or at leastby the brain signals associated with intentions. This finding isvery important because it opens the door for application of thesedevices and systems as neural prostheses: some fundamental


Fig. 18. Conceptualization for a hippocampal prosthesis. Hippocampus indark blue and in the temporal lobe as it is located in the human and sub-humanprimate. Red “X” is to represent damage to internal circuitry of hippocampus.Functional properties of the damaged region are mathematically modeled andinstantiated in VLSI device (to be mounted on surface of skull). Multi-siteelectrode arrays record activity from populations of neurons “upstream” fromthe damage, and transmit continuous spatio-temporal patterns of activity tothe inputs of the prosthetic device. Outputs from the hardware model aretransmitted through a second set of multi-site electrode arrays to hippocampalregions “downstream” from the damaged region, to drive hippocampal outputregions to the appropriate spatio-temporal “state” for the current input.

device actions, such as “on” and “off”, can be brought undercontrol of the patient. Just as important, patients can generatecontrol over their environment using the same thoughts and in-tentions used previously before the loss of limb. Although thereclearly is a learning curve to gaining control over a robotic de-vice, at least the patient does not have to learn an entirely novelset of internal “control commands”.

Several groups also have observed that after animals switchfrom arm control to brain control of a robotic device, roboticarm movements dissociate from the real arm. Since the animalis rewarded only for movement of the robotic arm, movement ofthe real arm becomes more variable and less accurate over time.Interestingly, the accuracy of monkeys with respect to brain con-trol of a robotic device continues to improve as the accuracy ofthe real arm diminishes. This effect appears to be context-de-pendent, because animals movement of their real arms returns tonormal as soon as they are returned to their home cages. Again,all of this bodes well for the eventual attempt to develop andapply such technology to humans.

Controlling a robotic device in 3-D space also has beendemonstrated in monkeys by tying both hands/arms down toimmobilize them [184]. Using these conditions, monkeys canlearn to feed themselves with a robotic system that a givenmonkey can control with intended reach-and-grasp for food,and intended return of the food to that monkey’s mouth.

3) Sensory Feedback: One of the critical problems facingdevelopment of a motor cortical prosthesis is the mechanismfor including sensory feedback from the robotic device to the

patient. The motor prosthetic systems developed to date haveall depended on visual feedback for control and guidance. Ulti-mately this will not be sufficient, as visual feedback alone doesnot include somatosensory input, which is critical for transmit-ting information about touch and force. Tactile information pro-vides the only route for accurate, efficient and rapid manipu-lation of objects: we often manipulate objects without contin-ually observing them through the entire act of manipulation;we depend on tactile identification of critical surfaces and sur-face irregularities to guide our manipulations. Information aboutthe material and structural features of the object, as well as the“tightness” of the grip is essential for applying the optimal forceto both prevent dropping and prevent crushing the object. Poten-tial solutions currently being explored include electrical stimu-lation of somatosensory cortex to provide “graded” or “coded”somatosensory input from sensors on the robotic hand. It is un-likely that it would be necessary to develop sensors to replicateall of those found in the human hand. Certainly a tactile sensoris a possibility, and Loeb and colleagues [287] have developedsome intriguing prototypes for coding proprioceptive informa-tion.

4) Prosthetic Limbs in Humans: This strategy of restoringlost motor function by routing movement-related signals fromthe brain around damaged parts of the spinal cord to externaleffectors such as a robotic system recently has been extendedto use in humans [185]–[188]. Donoghue et al. have shown asuccessful application in a tetraplegic human [185], [186]. Neu-ronal ensemble activity was recorded through a 96-microelec-trode array implanted in primary motor cortex. Using behav-ioral training paradigms like those described above, they foundthat intended hand movement was associated with changes inprimary motor cortical activity, and that these effects occurredthree years after spinal cord injury. Neuronal decoders were cre-ated, providing a “neural cursor” with which the patient openedsimulated e-mail and operated devices such as a television, evenwhile conversing. Furthermore, the patient used neural controlto open and close a prosthetic hand, and perform rudimentaryactions with a multijointed robotic arm.

These results suggest that movement signals must persist incortex after spinal cord injury, and be engaged by movementintent long after sensory inputs and limb movement are absent.If so, then why not consider activating paralyzed limbs ratherthan translating intended movements to control of a cursoror robotic arm? If the information for intended movementswere decoded in terms of the EMGs required for the specificmuscles underlying the movements, then activation of eachmuscle with the requisite amplitude-time course EMG could,in theory, recreate the desired movement. Two componentsof this solution to cortical control of paralyzed limbs are indevelopment. First, the technology for electrically stimulatingindividual muscles independently with a time-varying inten-sity that mimics the EMG—the BION™—is in clinical trialsand nearing commercialization [189]. Other FES systems forstimulating movement of the paralyzed arm and hand of thehuman also are being developed by Taylor [190]. Second,recent experiments using recorded ensemble M1 unit activity


Fig. 19. Diagrammatic representation of the anatomy of the hippocampus of the rat. Left, bottom: Hippocampus as it sits in relation to other brain structures (theoverlying neocortex has been removed. Middle: The hippocampus as it is removed from the brain and prepared for slicing. Left, top: Idealized series of slicescut transverse to the longitudinal plane, throughout the length of the hippocampus. Right: Diagrammatic representation of one transverse slice of hippocampus,illustrating its intrinsic organization: fibers from the entorhinal cortex (ENTO) project through perforant path (pp) to the dentate gyrus (DG); granule cells of thedentate gyrus project to the CA3 region, which in turn projects to the CA1 region; CA1 cells project to the subiculum (SUB), which in the intact brain then projectsback to the entorhinal cortex.

and simultaneously recorded EMGs from multiple arm andhand muscles while monkeys reached to various positions in3-D space have been analyzed using newly developed andnovel mathematical modeling methods [196]–[199]. The abovedata consist of a wide range of multiple spike-encoded “com-mand” signals from motor cortex, and a correspondingly widerange of multiple continuous, amplitude varying “muscle”signals generated by muscle contractions [Fig. 16(A)]. Usinga multiple-input multiple-output (MIMO) nonlinear dynamicmodeling method [Fig. 16(B)] [196]–[199], we have beenable to demonstrate highly accurate predictability of multipleEMGs as a function of arbitrary multiple spike train inputs(Fig. 17). Combining multiple cell recording, the BION™ andMIMO modeling technologies could lay the foundation for athought-driven, EMG-based re-activation of paralyzed limbs.

There is always the possibility that damage-induced synapticplasticity could radically change the connectivity or the func-tional properties of M1 neurons so as to prevent a basis for aneural prosthesis system as rudimentary as this one. In furtherstudies with implanted tetraplegic humans, Donoghue’s grouphas shown that a large percentage of M1 neurons in tetraplegicswere tuned to velocity % and/or position % , and

that these properties of M1 neurons are present both duringreal movement (nonhuman primates) and during imaginedmovements (tetraplegics). In addition, Fetz and colleagueshave shown that co-activation of motor cortical cells can leadto activity-dependent plasticity [286], a property which mayhelp re-organization of motor cortex after spinal cord damage.Rehabilitation-induced potentiation of motor cortical neuronsfor paralyzed limbs may lead to “recruitment” of additional cir-cuitry to strengthen or otherwise alter cortical representationsfor the development of new neural strategies for limb control.In total, these findings support the position that intra-corticalneuronal ensemble spiking activity could provide a valuablenew neurotechnology to restore independence for humans withparalysis.

B. Cognitive/Memory Prostheses

There is only one major attempt that can be identified to de-velop a neural prosthesis for replacement of memory functionlost due to central brain region damage or disease [191], [192].That project first started at the University of Southern California(USC) and now involves collaborative efforts with Wake ForestUniversity (WFU) and the University of Kentucky (UK). The


project focuses on the hippocampus, the part of the brain re-sponsible for long-term memories [194]. Compromised struc-tural and functional properties of the hippocampus are consis-tently associated with stroke, epilepsy, and Alzheimer’s disease.Patients with severely damaged hippocampi are incapable offorming new long-term memories, leaving them highly depen-dent on family or health staff to manage daily life.

The goal of the project to develop a memory prosthesisis to replace damaged regions of the hippocampus with amicrochip-based system that mimics the functional propertiesof the lost tissue [191], [192]. The replacement silicon sys-tems would have functional properties specific to those of thedamaged hippocampal cells, and would both receive as inputsand send as outputs electrical activity to regions of the brainwith which the intact hippocampus previously communicated(Fig. 18). Specifically, multisite electrode arrays would recordactivity of neuronal populations that normally provide inputto the damaged region and transmit that information to the“biomimetic” prosthetic device. A second set of multisiteelectrode arrays would transmit the output from the biomimeticdevice to brain regions that normally receive efferents fromthe damaged region, and as electrical stimulation, would drivethose target regions to the required output state. Thus, theprosthesis would replace the computational function of thedamaged region of hippocampus and restore the transmissionof that computational result to appropriate regions of the brain.

1) Proof of Concept in the Hippocampal Slice: Giventhe complexity of this task, the first step taken was to at-tempt a “proof of concept” in a reduced preparation of therat hippocampus—the hippocampal slice (Fig. 19). The basicobjective is illustrated in Fig. 20. The major intrinsic circuitryof the hippocampus consists of an excitatory cascade of thedentate, CA3, and CA1 subregions (dentate-to-CA3-to-CA1)[Fig. 20(A)] and is maintained in a transverse slice preparation.Our proof-of-concept hippocampal prosthesis consists of (i)surgically eliminating the CA3 subregion; (ii) replacing thebiological CA3 with a VLSI-based model of the nonlineardynamics of CA3 [Fig. 20(B) and (C)]; and output to theVLSI model and transferring VLSI-model output to the inputsof CA1 [Fig. 20(C)]. The definition of a successful imple-mentation of the prosthesis is the propagation of temporalpatterns of activity from dentate VLSI model-to-CA1, whichreproduces what is observed experimentally in the biologicaldentate-to-CA3-to-CA1 circuit.

The USC-WFU-UK group was able to accomplish all ofthe steps outlined above. One important point is that the coreof the prosthesis is a nonlinear dynamic model of CA3—asingle-input single-output method based on the same nonlineardynamic modeling methods similar to the MIMO methodreferred to above in relation to modeling motor cortical-EMGactivity. This model utilizes a combined experimental–the-oretical approach to capture the input–output properties ofthe neural system studied [192], [204]–[206]. An importantassumption is that information is carried in the time betweenspikes, i.e., in a temporal pattern, so that the response of agiven neuron depends not just on the most current input, butalso on the time since prior inputs. For characterization of thehippocampus, the USC-WFU-UK investigators electrically

Fig. 20. Strategy for replacing the CA3 region of hippocampus with a VLSImodel of its nonlinear dynamics, and interfacing the VLSI biomimetic devicewith the remaining, active slice through a conformal, multi-site electrode array,thus restoring whole-circuit dynamics. (A) Diagrammatic representation of thetrisynaptic circuit of the hippocampus. (B) Conceptual representation of re-placing the CA3 field with a VLSI-based model. (C) Hippocampal slice in whichthe CA3 field has been removed. Overlaid is an integrated system in whichimpulse stimulation from an external source is used activate dentate granulecells and is delivered through one component of a multi-site electrode array. Asecond component of the electrode array senses the responses of dentate granulecells and transmits the responses to the VLSI-based model. The VLSI deviceperforms the same nonlinear input/output transformations as biological CA3neurons, and transmits the output through the multi-site electrode array to thedendrites of CA1 neurons, thus activating the last component of the trisynapticpathway.

stimulated the inputs to the dentate with a random intervalimpulse train and simultaneously recorded outputs from thedentate, CA3, and CA1. Both the inputs and the outputs ofCA3 were recorded, and their relationship was modeled using aVolterra functional power series approach [202]. The result is amodel that allows the output of CA3 to be accurately predictedfor any arbitrary CA3 input (sequence of impulse intervals, ortemporal pattern) (Fig. 21). The USC-WFU-UK group went onto show that, in response to random interval impulse stimula-tion of dentate input, the output of CA1 was nearly identical


Fig. 21. Example of CA3 model prediction �� % for a slice experiment in which random impulse train stimulation was delivered to excitatoryinputs of the dentate gyrus. Dentate granule cells excite CA3 pyramidal neurons, which in turn excite CA1 pyramidal cells. Population spike field potentials wererecorded from the dentate, CA3, and CA1 regions simultaneously during stimulation. To develop a CA3 model, population spike amplitudes of the dentate and theCA3 regions were used: dentate data was considered input to CA3; CA3 data was considered output of CA3. Thus, a single-input, single-output nonlinear modelof CA3 was computed using these data. Data shown here are for predicted CA3 population spike amplitudes. (A) Predicted population spike amplitudes (blue) andtheir differences from the corresponding measured population spike amplitudes (red). (B) Segment of the CA3 Model Prediction. (C) The corresponding segmentof the measured CA3 population spike amplitudes. The shaded rectangles highlight two areas for comparison between model predicted values and recorded values.

for normal, intact slices and “hybrid” slices in which the CA3region was replaced with a hardware model of CA3 dynamics(VLSI field programmable gate array [FPGA]) (see Fig. 22).

2) A Hippocampal Neural Prosthesis for the Behaving An-imal: With this proof of concept completed, the group becamefocused on developing a hippocampal prosthesis for the be-having rat. This essentially requires extending the input-outputmodel to multiple slices, or circuits, along the longitudinal axisof hippocampus (Fig. 19). Achieving this goal also requires de-veloping the input-output model from recordings of populationsingle-cell activity (extracellular “spikes”) in the behaving rat as

the animal performs a memory task that demands normal hip-pocampal function.

To this end, we extended our approach to in vivo multi-electrode recording during a “delayed nonmatch-to-sample”memory task in the rat (Fig. 23). During this task, a rat ispresented with one of two “sample” stimuli; the rat mustremember that stimulus and provide evidence of that memoryby responding after a variable delay period (0–60 s) to theopposite stimulus of the sample. Multiple single-cell record-ings were obtained from an array of electrodes in CA3 and asecond array of electrodes in CA1. The modeling task was to


Fig. 22. Comparison of population synaptic potentials (fEPSPs) recorded from the CA1 region during random impulse train stimulation (as above, Fig. 21). Dataare shown for the intact slice (pink; “CA1 trisynaptic”), and for the hybrid slice in which a hardware model of CA3 has replaced the biological CA3 (blue; “CA1replacement”). Data are shown for only 50 of the 1 200–1 500 impulses delivered to each slice. Hardware implementations were either field programmable gatearrays (FPGAs) or VLSI microchips.

determine the nonlinear input-output properties for the CA3(input)—CA1 (output) population data, where both the inputand the output are multiple-point processes. In other words,the goal is for the model to predict how the activity of eachoutput neuron depends on 1) the temporal pattern of activity ofeach of the input neurons, and on 2) the interactions betweenthe temporal patterns of the input spike streams (Fig. 24). TheUSC-WFU-UK group successfully developed a multiple-input,multiple-output model for transformation of population CA3 topopulation CA1 spatiotemporal patterns [196]–[199]. Fig. 25shows one such result, in this case for a 16-input, 7-outputneuron recording. Because there were 7-output neurons, 7multiple-input, single-output models were constructed. Eachmodel included a multiple-input, third-order kernel componentrepresenting the effects of mechanisms of synaptic transmissionand dendritic integration (K), the somatic membrane potential(u), a noise term to represent spontaneous activity , the spikethreshold , and a spike-triggered after-potential (H). Resultsshowed that the model faithfully predicts the spatio-temporalpattern of action potentials in CA1 of the behaving animalbased on the spatio-temporal pattern of action potentials inCA3: see color plots in Fig. 25 and matching distributions of

interspike intervals for observed and predicted data sets (upperright plot).

With this established, the USC-WFU-UK group is now devel-oping a preparation in which the disrupted hippocampal is re-placed by the interaction between the multi-input, multi-outputmodel and the residual hippocampal function. In first-gen-eration studies, Deadwyler’s laboratory trained a group ofanimals on the DNMS task, and in addition to implantingthe usual array of CA3 and CA1 recording electrodes, alsoimplanted an osmotic mini-pump that could infuse substancesinto the hippocampus. Initially, animals were trained withonly saline in the pump. The spatio-temporal patterns of CA3and CA1 neurons were recorded, analyzed by USC/Berger’slaboratory, and stored. These data provided a description of thespatio-temporal “codes” used by the animal to create long-termmemories for each trial. In the next phase of the experiment,the same animals continued to be trained, but with the NMDAchannel blocker, MK-801, in the mini-pump. The presenceof MK-801 disrupted learning-related hippocampal activityin both hemispheres, preventing the formation of “memorycodes,” and blocking memory-dependent behavior (data notshown). Still in the presence of MK-801, the CA3-CA1 memory


Fig. 23. Hippocampal CA3-CA1 ensemble activity recorded from the rat during delayed, nonmatch-to-sample (DNMS) behavior. During this task, a rat is pre-sented with one of two “sample” stimuli: a lever on the left or a lever on the right. The rat must press the lever presented, and must quickly form a memory of thatsample. Then the rat must move to the opposite wall of the chamber and poke its nose into a small hole in the wall when a light above the hole is “on”. A delayperiod is initiated ranging from 0 to 60 s during which time the animal must sit facing the wall from which the levers appear. After the delay period is completed,both levers protrude through the wall, and the rat must press the lever the lever opposite from the one that appeared as the sample. If the animal’s choice is correct, itis rewarded with water. Animals generally respond at approximately 90% accuracy with 0–5 s delays, and with decreasing accuracies as the delay period lengthens;animals reach chance levels of accuracy with approximately 45 s delays. Multiple single-cell recordings are obtained from an array of electrodes in CA3 and asecond array of electrodes in CA1. Right: Spatio-temporal patterns of activity recorded during different phases of the DNMS task. Three-dimensional plots of firingrate (y-axis) by electrode location (x-axis) by time with respect to the behavioral response (z-axis)show that each of the four major phases of the task: the sampleperiod (left, right), and the nonmatch period (left, right) when the animal responds following the delay, is associated with different and unique spatio-temporalpatterns (“memory codes”) of hippocampal activity. Although data from both CA3 and CA1 cell fields are shown together here, it is the spatio-temporal firingpatterns of CA1 that must be predicted as a function of the spatio-temporal firing patterns of CA3, in real time.

codes previously recorded in the presence of saline were nowused to electrically stimulate CA1 pyramidal neurons so as toreproduce the “appropriate” spatio-temporal patterns for giventrials (data not shown; electrodes previously used for recordingwere now used for stimulation). Initial results show that an-imals’ memory-dependent behavior is returned by electricalstimulation, even in the presence of MK-801 (Deadwyler andBerger, unpublished observations). These data strongly suggestthat neural prostheses also may be developed to replace highercognitive functions lost due to damage or disease.

C. Summary

The progress made during the last decade in developing brain-implantable neural prostheses has been remarkable. What is per-haps most stunning has been the ability to decipher the codingschemes used by the brain to represent external events and re-lationships between external events. Although not trivial, the

mathematical models required to understand these first-genera-tion brain codes are not highly complex. In the future, of course,this is likely to change. In total, initial findings for motor corticaland hippocampal memory neural prostheses strongly suggestthat these goals are worth pursuing, and may be tractable. Addi-tional progress will require substantial breakthroughs in minia-turization of computational devices to be mounted on the headsof patients; future generations of prostheses will most likely in-clude recordings from many more neurons than seen to date,and will require complex protocols of simultaneous recording,computation, stimulation, and error correction loops.

VI. NONINVASIVE BRAIN–COMPUTER INTERFACES

The advantage of brain-implantable neural prostheses isthat sensing electrodes can be placed in close proximity tothe neurons generating the electrical activity coding motormovements or cognitive engrams. Thus, not only can the neuralsignals be large in amplitude (relative to the electronic noise)


because of close proximity to the neuron, but they also canbe very specific to individual muscle movements or cognitivetasks. As described in the previous section, neurons in motorand pre-motor cortices have very specific neural correlates formuscular movement or positions in three dimensional space,and the hippocampus encodes spatial and task specific maps.The ability to implant multiple electrodes in several brainareas could thus in theory enable fine control of prostheticlimbs or cognitive commands from neuronal populations,which intrinsically encode movement or cognition. However,brain-implantable neural prostheses are invasive by definition,as they involve penetrating the skin, skull, dura and othermeningeal tissues surrounding the brain, and thus, exposingthe brain and the patient to the possibility of infection or otherdeleterious consequences of surgery. Therefore, there existsa need for noninvasive brain–computer interfaces, which canextract neuronal activity information without piercing the skin.

Despite the fact that electrical signals generated by neo-cortical neurons degrade in amplitude rapidly as a functionof distance, they do, however, reach the brain surface andare transmitted through the skull. These scalp-recorded elec-troencephalograms (EEGs) represent summations of electricpotentials whose sources stem from neuronal activity at dif-ferent locations in the brain. As such, they encode underlyingbrain activity, from motor and sensory information processing,to cognitive states, such as attention, emotions, and wakeful-ness. The signals are broadly diffuse potentials whose sourcesare often hard to localize accurately, and which are affected to alarge degree by electromagnetic noise. Nonetheless, medically,EEG signals are commonly used for clinical evaluations ofsleep, monitoring anesthesia, and detecting epileptic seizures.When appropriately decoded, quantitative EEG (qEEG) can becorrelated to underlying sensory and volitional brain activity,and as such offer a useful noninvasive brain–computer inter-face for controlling computers or robotic devices. In addition,cognitive states, such as attention, workload, and fatigue canalso be extracted from EEG signals and used for augmentingthe efficiency of information exchange between humans andcomputers. Furthermore, humans can learn to modulate theirEEG signals, and the underlying control of brain activity isthe premise of several neurofeedback therapeutic applications,from ADHD [207] to epilepsy [208]. These applications,however, require sensors that are continuously wearable forlong-term, ambulatory applications. New electrode technolo-gies are emerging that will enable noninvasive and unobtrusiverecordings of brain activity in real-world environments.

A. BCI Applications

A variety of studies have demonstrated that changes in scalp-recorded EEG signals can be used as the basis for brain–com-puter interfaces, and thus can provide an alternative to the inva-sive methodology based systems. In fact, noninvasive BCIs atthis point are more advanced than invasive systems in the sensethat they are essentially ready for home patient application.

Patients with high cervical transections that eliminate volun-tary movement of all external limbs can still observe a cursor ona computer monitor; movement of that cursor can be controlledby changes in features of the patients’ EEG. Through “practice”

of mental imagery with sensory feedback, the patients learn tomanipulate their EEG state, and thus the ensuing features of theEEG, resulting in volitional control of the system’s output, inthis case, x-y position of the cursor. Positioning the cursor overdifferent icons allows for different “choices,” or outcomes. Ingeneral, all BCI systems consist of: 1) sensors that record theneural activity; 2) signal processing that extracts desired fea-tures from the neural recordings; 3) an algorithm or algorithmsthat create commands based on the extracted features to controla computer or robotic device; and 4) a display screen or otherresponse system that completes the action or feedback.

Non-invasive BCI systems differ from invasive ones in termsof the neural features that are extracted from the EEG and thebehavioral paradigms that are used to gain control over thosefeatures. EEG signal is recorded simultaneously from multipleelectrodes placed at specified locations on the scalp, and usu-ally sampled around 256 Hz. Several different implementationsof noninvasive BCI have recently been developed: DependentBCIs utilize sensory (visual or auditory) evoked responses todrive a dependent EEG response, which can be modulated by thesubject’s attention or volition, whereas independent BCIs can bedriven solely by mental imagery or thinking. Synchronous BCIsanalyze changes in EEG patterns in relation to specific synchro-nizing events or external triggers, whereas asynchronous BCIscontinuously analyze EEG signal in search of internal volitionalchanges in activity.

Unlike implantable electrodes, which can extract several pop-ulation vectors to encode continuous movement, speed, gripstrength, etc., the signals extracted from EEG usually enablesingle discrete switching. The user is able to select betweentwo states, which are used to select an action to execute or not.Pseudo-continuous control can be generated by repeatedly de-coding the switch signal over short time windows and concate-nating the output. The continuous decoding of EEG can be en-ergetically expensive and may lead to increased false positiverates; asynchronous BCI algorithms are therefore being devel-oped to enable users to self-pace the detection and to decidewhen to turn it off and back on [209]–[211].

There are two general EEG classification methods in use forBCI applications: one relies on changes in spectral power in spe-cific bands of interest, the other relies on slow changes in scalppotential related to cortical activation. Depending on the typeof BCI, EEG power or response latency or amplitude can beextracted for classification. The practical application of thesequantitative analytical methods and interpretation of EEG sig-nals enable the use of various cognitive or motor imagery forthe intended control task. Furthermore, topographical analysisof spatio-temporal relations and asymmetries between signalsat various electrode locations can be used to map sources andrelate them to different cognitive modalities [212]. A variety ofsignal features currently used in BCI applications are describednext.

1) Slow Cortical Potentials: Scalp potentials vary slowly andinversely with cortical activation, whereby negative potentialsare associated with increased cortical activation, and vice-versa.These potentials changes occur on the time scale of 0.5–1 s andare therefore referred to as Slow Cortical Potentials (SCP) orsometimes DC potentials. SCPs can be related to cognitive or


sensory-motor events or thoughts and are amenable to operantconditioning; as such they can be used for BCI control [213].Two types of SCPs are have thus far been used for BCI imple-mentations:

Bereitschaftpotentials are negative scalp potentials thatoccur during planning stages of a volitional movement,preceding the first detectable relevant muscular contraction(Fig. 26, Left). Though these DC shifts are very small in ampli-tude ( V), and the signals need to be properly cleaned andcarefully aligned and averaged to be visually distinguishable,several groups are trying to use Bereitschaftpotentials forsingle-trial, real-time decoding of intent [214]. Two advantagesof this independent signal are that it does not require anylearning, nor does it necessitate any actual movement to beeffected.

Contingent negative variations, or Readiness Potentials,are slow and small, mostly negative scalp potentials recordedaround half a second preceding an anticipated external eventand after a warning stimulus [215]. Subjects can learn to modifyand control these potentials through neurofeedback methods,and they have been thus been used for BCI applications.Fig. 26 (Right) shows an example of EEG trace recordingsafter training, where healthy subjects are able to shift theircontingent negative variation positively or negatively [213].This method was then used to enable paralyzed patients tocommunicate by using their classified potential shifts to controla computer spelling device [216].

2) Evoked Potentials: Sensory stimulation can be used toelicit responses that can manifest in EEG signals with appro-priate spatio-temporal resolution.

Visually, somatosensory, or auditory Evoked Potentials(VEP, SEP, or AEP) can be used to elicit Evoked Potentials inthe EEG signal. These dependent signals are time locked to thestimuli, and often phase locked as well. They are usually verysmall in amplitude and therefore generally necessitate averagingof several trials in order to be unmasked from noise. EvokedPotentials have mostly clinical and neurosurgical applications;however some groups have harnessed these potentials for BCIcontrol.

Steady-State Evoked Potentials consist of rhythmic activityin the EEG, which arises with repetitive presentation of visual orsomatosensory stimulation (SSVEP or SSSEP). The signal con-tains spectral peaks that match the fundamental frequency of thestimulation and its harmonics. Furthermore, the spatial distribu-tion of SSVEP power is related to the stimulus frequency [217].When several targets are presented at different frequencies, theattended target can thus be determined from the power spectrumof the EEG. Furthermore, the Steady state visual stimulation hasbeen used for BCI applications from two- to four-state discrimi-nation [218] to dialing a phone pad [219]. The advantage of thissignal is that it is fast, large bandwidth, and does not require anytraining. It does however require attentiveness to the stimulus,and therefore for at least for SSVEP, gaze-shifting and func-tional eye muscles. However, somatosensory evoked potentialsare being developed to mitigate this requirement, [220] as wellas systems with overlapping visual stimuli [221].

3) Event Related Potentials: Beyond sensory responsiveevoked potentials (ERP), considerable BCI work has been

accomplished with Event Related Potentials, which involvehigher mental processing associated with the stimuli, such asattention, memory, or decision. Responses are usually time andphase locked to the stimulus, and are characterized by theirlatency and phase.

P300 is a positive deflection in the EEG signal following thepresentation of a stimulus which a subject or patient was ex-pecting. The peak has a latency of around 300 ms, and often re-quires averaging of multiple responses to unmask it from back-ground noise. The P300 is often detected during an oddball par-adigm, where the stimulus of interest is infrequently presentedbetween many distracter stimuli. P300 has been used exten-sively for BCI spellers, where letters are arranged in a 6 6matrix and rows and columns are highlighted sequentially, al-lowing for relatively rapid and accurate identification of the at-tended letter [222], [223]. P300 has also been used for mousecontrol [224], [225], and has been successfully used by patientswith severe motor disabilities or advanced ALS [226], [227]. Amajor advantage of P300 based BCIs is that they do not requirelearning or training classifiers, and recent algorithms have suc-ceeded in single-trial classifications [228], and in asynchronousimplementation [229].

There are numerous other ERPs that are associated with dif-ferent higher cognitive tasks [213]: N170 is a negative poten-tial that peaks at 170 ms and is associated with face recogni-tion [230]. P600 is a positive deflection associated with rule vi-olations, linguistic and mathematical [231]. N400 is a negativedeflection that follows 300–500 ms after unexpected linguisticor semantic structure [232]. Error Potentials (ErrP) [233] andError Related Negativity (ERN) [234] have also been used inBCI applications to reduce error rates. These single trial errorsignals are manifest when subjects detect an error they or theinterface committed, which enables immediate correction.

4) Event-Related Synchronizations and Desynchroniza-tions: Spontaneous rhythmic activity is changed by thoughtand movement: Event-Related Synchronization (ERS) refersto an increase in synchronization in relation to an externalor internal event, whereas Event-Related Desynchronization(ERD) is a decrease in synchronous oscillations [235]. Motorrelated rhythmic activity in the range of 8–12 Hz, referred toas Mu-Rhythm, is readily amenable to conscious modificationand has thus been used for several BCI applications, from thecontrol of cursor movement [236], [237], to spelling [209], andthe control of a wheelchair in a virtual environment [238], thecontrol of a prosthetic hand [239], and even by amyotrophiclateral sclerosis (ALS) locked-in patients [240].

B. Need for Wearable EEG Systems

Severe motor disabilities such as ALS, brainstem stroke, cere-bral palsy, and spinal cord injury reduce or eliminate neuromus-cular control and deprive affected patients of communicationand control that is vital to their mental and physical health. Re-cent advances in noninvasive EEG-based BCI algorithms, suchas the ones described above, have given these disabled patientsnew hope for communication and control of their environment.EEG-based BCIs are effective and useful in the daily lives ofthe severely disabled, helping them to regain independence, andimproving their quality of life [240]. In addition, EEG-based


Fig. 24. MIMO model is accomplished by reducing it to a set of multi-input, single-output (MISO) models (Left). Internally, each multi-input, single-output modelconsists of what is shown in the left, bottom. Multiple point-process inputs, x, are modeled using third order Volterra kernels, with outputs of kernels for all inputscombined to equal �, the equivalent of soma membrane potential. To this sum is added the output of a noise term, to capture the stochastic effects �� of cell firingthat give rise to spontaneous activity, and also to capture the effects of unknown, unobserved inputs. The resulting activity level is subjected to a threshold �� toproduce a spike output, �. In addition, each spike output event activates a first-order feedback, � , which represents the effects the multiple sources of feedback,such as feedback inhibition, calcium-activated � conductances, etc., A MISO model is computed for each output neuron too achieve a full MIMO model.

Neurofeedback technology is being used for more therapeuticapplications, from ADHD [207] to epilepsy [208]. In a lessmedical setting, brain activity is being monitored and used tofor augmented cognition applications, whereby cognitive statesof mental workload, engagement, or fatigue are classified fromneurophysiological signals to enhance human-computer inter-actions, and augment mental capabilities [241].

Beyond BCI, EEG-based brain imaging is an invaluable toolfor neurologists in diagnosing their patients in hospitals orclinics [242]. However, it is often desirable to monitor patientson an on-going basis, such as to detect and localize brainseizures, to evaluate the efficacy of anti-depressants, or forlong-term sleep monitoring. Currently these require expensivehospitalization, or repeated clinical visits. Wearable EEG sys-tems could enable at-home monitoring of several conditions. Apotential new direction is in ambulatory detection of early signsof brain trauma, by monitoring Cortical Spreading Depression[243].

Neuroscientists are currently not able to conduct studies onlarge populations due to the prohibitive cost and time neces-sary to monitor each individual. There are numerous instanceswhere such investigations could provide information not readilyobtainable in a laboratory setting. For example, monitoring cog-nitive states and brain activity during learning and daily ac-tivity could provide rich insight into the development of var-ious learning disabilities or mental imbalances in children. Brainimaging research into dyslexia, ADHD, depression, or othermental disorders [244], [245] currently requires bringing thesubjects to a controlled research environment and conductingtime-limited imaging studies; likewise, investigation of sleep

disorders or neurodegenerative diseases such as Alzheimer’s orParkinson’s usually require a clinical setting [246].

All these applications require brain activity monitoring sys-tems that are easy to don and doff, wearable for extended periodsof daily operation, do not require extensive maintenance, robustto environmental noise, and unobtrusive to the patients or users.

C. Challenges for Long-Term Wearable Brain MonitoringSystems

There are several technologies currently in use for imagingbrain activity, from EEG to fMRI and MEG. All of thesemethodologies, however, have technical or logistical caveatsthat limit their potential utility for daily portable brain mon-itoring, whether for research, medical, or life-improvementapplications.

1) Portability and Wearability for Extended Daily Use:While improvements to MRI and MEG analytical algorithmshave improved the spatio-temporal resolutions of the technolo-gies, the practical restrictions of these contact-free methodsfor long-term and deployable use present an insurmountableobstacle for portable applications. Currently it is not possible toconduct brain imaging on large numbers of individuals in theirnatural environment. MEG, PET, fMRI, and MRI for magneticfields all require very large and expensive equipment that is notfield deployable and requires technical expertise for operation.

Clinical EEG systems provide adequate signal quality, butthey were never designed to be worn day after day as assis-tive devices. They were designed for routine one-hour EEGs inhospitals to screen for epilepsy or other neurological disorders


Fig. 25. Example multi-input (CA3), multi-output (CA1) model, which in this case consisted of 16 inputs and 7 outputs. Left: relative locations of recordingsites on hippocampi of the two hemispheres. Middle: MISO model as explained in Fig. 24. Each model is evaluated using a Kolmogorov–Smirnov test which theobserved inter-spike interval distribution with the predicted inter-spike interval distribution.

Fig. 26. Left: Bereitschaft Potential plot [277]. Waveforms of Bereishafts Potentials (BP) from a single normal subject averaged over 98 self-initiated left wristextensions. Early BP starts 1.7 s before the onset of EMG activity of the left extensor muscle, and is maximal at the central midline electrode (Cz); while late BPstarts 300 ms before the EMG, and is larger on the contralateral hemisphere. N-10 and N-50 are negative peaks which correspond toor motor potential (MP) andthe frontal peak of motor potential (fpMP). Right: Contingent Negative Variation shifted voluntarily positively or negatively after neurofeedback training (the first2 s are a passive period, the last 500 ms of which defines the baseline, the second 2 s phase is the active shifting phase) [211].

or for laboratory research. Current EEG electrodes most oftenconsist of Ag, AgCl or Au disk electrodes filled with conductinggels. After scrubbing the scalp with mild abrasives, electrodesused to be attached to the scalp with colloid glue or conduc-tive paste. The setup and breakdown of is time consuming andrequires washing the hair and scalp after each use. Head capshave been developed to aid in the rapid placement of 64 to 256EEG electrodes along the standard 10–20 configuration system(Fig. 27, Left) These elastic cap positioning systems, however,apply steady pressure to the hard plastic electrode case onto the

scalp, which produces mild to severe discomfort in most usersafter short periods. Furthermore the daily repeated use of adhe-sive electrodes can cause painful skin abrasions [247].

A key finding of an international assessment of research andtrends in Brain Computer Interfaces is that the developmentof dry electrodes is a necessity for the future of BCI adoption[248]. Having dry electrode technology as a standard part of theBCI research protocol would allow the researcher or caregiverto spend substantially less time with preparation and clean up.Thus, more time would be available for valuable communica-


Fig. 27. Left: g.Tec mobile EEG system consisting of headcap, electrodes, amplifiers and portable digital assistant for recording data [278]. Right: BioSemi ActivePin electrodes that contain a first stage amplification circuit [279].

Fig. 28. Left: QUASAR capacitive sensors for measurement of ECG or EOG[257]. Right: QUASAR hybrid sensors for through-hair measurement of EEG[280].

tion and data collection. In addition, an estimated 75% of ap-proximately 450 research participants have expressed some dis-satisfaction with the current wet electrodes. Complaints includegeneral physical discomfort, pain associated with pressure fromthe electrode caps, the wet and messy feeling associated withthe electrolyte gel, and the gel residue that must be washed outof the hair after each BCI session.

2) Technical and Electronic Requirements for AmbulatoryRecording: Wet electrode preparations are plagued by severalother problems: a): degradation of coatings required for goodelectrical contact (typically silver chloride); b) polarization ofthe electrode-scalp junction leading to noise and amplifier insta-bility; c) tarnish and build up of residues from gels and cleaningproducts that impair conductivity (even in salt-free electrodessuch as tin); d) drying of the electrolyte during prolonged useand associated loss of conductivity; and e) bridging of closely-

spaced electrode leads when the electrolyte gel leaks into thespace between electrodes. An additional problem with wet elec-trodes is that care must be taken to ensure that impedances areuniformly low on all electrodes. Recordings of unacceptablylow quality can result if the electrodes and gel are not makingproper contact with the scalp. It is particularly difficult to traincaregivers to recognize this and take corrective actions.

Finally, for truly mobile and portable brain activity moni-toring, it is necessary to digitize and either store or transmitthe data. To eliminate the need for a cable bundle to a separateunit, and to minimize the impact on mobility and pickup of ex-ternal noise, the entire recording system should be comfortablymounted on the head. Portable systems must therefore enablerecordings during subject motion. This is generally a difficultrequirement as motion artifact can mask the brain signal.

Accordingly, it is critical to develop a head mounted systemsspecifically for in-motion monitoring, if dynamic monitoringof brain activity in natural environments is to be studied andexploited. It is important to note that these various sources ofdata degradation enter the system at the electrode input alongwith the brain signal, and therefore must be either eliminatedby correct design, or independently measured and cancelled insoftware, to be subtracted from the data input before featureextraction and classification algorithms. Noise and interferencepicked up by the system downstream of the first stage electrodeamplifiers is straightforward to eliminate by correct electronicdesign and is fully addressed in most current systems.

D. Solutions for Long-Term Brain Activity Monitoring

Emerging new dry EEG electrode and functional Near-In-fraRed (fNIR), and B-field monitoring technologies may resolvesome, if not all, of the above challenges for long-term noninva-sive brain interfaces.

1) Dry EEG Electrodes: Advancements in microfabricationhave enabled the design and construction of first stage ampli-fication at the electrode, which reduces environmental electro-magnetic noise. BioSemi (Amsterdam, The Netherlands) pro-duces commercially such active electrodes, which allow EEG


Fig. 29. Left: Measurement of EEG using QUASAR hybrid sensors during different levels of ambulation [281]. Right: Measurement of EEG using BioSemipreamplified surface electrodes [282].

recording outside a Faraday cage; however, these electrodes stillrequire gels for adequate low impedance skin contact.

Capacitive “pasteless” bioelectrodes were developed in thelate 1960s for electrocardiagraphic (ECG) recordings [249],[250]. These electrodes enabled the measurement of bioelectricsignals without the use of conductive gels. Unlike conventionalECG electrodes that use a resistive contact and high-inputimpedance amplifiers, capacitively-coupled electrodes detectsmall charge variations on the electrode produced by nearbybioelectric activity. In recent years, the advent of lower ca-pacitance electrodes and novel electronic circuitry designs hasenabled recordings at a standoff from the skin, and even throughlayers of fabric [250]–[253]. For EEG recording, capacitiveelectrodes were not of sufficient fidelity, and had to be pressedagainst the scalp. In one implementation, a small four-elementcapacitive array automatically selected the electrode in bestcontact with the skin for recording [254].

Most recently, ultrahigh-impedance EEG electrodes havebeen developed by several groups [256]–[258]. The circuitryin these sensors allows recording of EEG signal of comparablequality to that acquired with wet electrodes, without skin prepa-ration or the use of conductive gels. Quantum Applied Scienceand Research (QUASAR, San Diego, CA) has been developingthrough-hair, wearable systems based on such high-impedancesensors. QUASAR’s advanced electronics and noise suppres-sion algorithms enable real-world ambulatory EEG-recording[259]. Fig. 29 compares EEG data collected using QUASAR’shybrid bioelectrodes to BioSemi’s Active electrodes duringdifferent levels of physical activity. QUASAR’s electrodeseffectively eliminate motion artifacts even during running.

Efforts to reduce the high-impedance requirement of theseelectrodes and skin noise have been aimed at producing elec-trodes with carbon nanotubes at their tip to penetrate throughthe skin [260]. While these electrodes have enabled recordingof high quality EEG in clinical trials [261], there is consider-able concern on the invasive use of carbon nanotubes in humans[262].

2) Functional Near Infra-Red (fNIR) Spectrometry: Func-tional Near Infra-Red (fNIR) spectrometry can be used to mea-

Fig. 30. The Opto-Temporal Imaging System (OTIS), electronics enclosure,emitter and detectors [265].

sure brain activity related changes in optical properties of thebrain and blood oxygenation [263]–[266]. NIR light is trans-mitted through the skin and skull and differentially absorbedand scattered by neural tissue depending on activity, and in re-lation to deoxy/oxy-hemoglobin concentration. There are threemethods of fNIR: continuous wave, frequency domain, and timeresolved, which allow detection of different dynamics of the un-derlying activity. Archinoetics (Honolulu, USA) has developeda commercial, head-wearable fNIR system (Fig. 30) [267]. ThisOpto-Temporal Imaging System (OTIS) is being used for BCIand Augmented Cognition applications [268]. In addition, fNIRbased BCIs have been used for successfully by patients suf-fering from ALS [269]. Furthermore, prefrontal cortex activityhas been measured from a distance of 5 meters with telescopicfNIR imaging [270].

3) E-Field Measurement: In order to increase the spatial res-olution of a portable system without increasing the number ofelectrodes, sensors that can detect a more localized field arenecessary. Measurement of the complete, 3-component electric(E-) field vector produced by the brain has very recently becomepossible through the development of sensors that can measurefree-space electric potential at the sub-microvolt level [271],[272]. The relative benefits of the normal E-field in comparisonwith the scalp EEG are illustrated in Fig. 31. The electric field


Fig. 31. Comparison of scalp potential on radial E-field on head. Results fromfour-sphere model have been stretched to fit the contours of the head. Each con-tour represents a 10% reduction from the signal maximum [283].

shows an increased localization with respect to the scalp poten-tial. In this figure, the results from a four-sphere model (i.e.,concentric spheres corresponding to the brain, cerebro-spinalfluid, skull and scalp) have been plotted on a simulated head.The normal electric field possesses a spatial resolution that is asgood as, or better than, the spatial resolution of MEG and scalpEEG with respect to the depth of EEG sources in the brain. Thistechnology is still nascent but holds promise for future imple-mentations into wearable brain interfaces.

4) Thermometry: Despite the low spatial resolution of ther-mometry, facial skin or brain core temperature can also be usedto distinguish cognitive or emotional responses [273], [274].Brain core temperature can be related to rapid changes in mentalworkload [275] There are numerous methods for noninvasivemeasurement of brain core temperature [276]; however, only afew are amenable to ambulatory applications. Zero-heat flow isone such method to measure brain temperature from the skin. Inprinciple, as heat passes from deeper within the body, throughthe outer tissue and out to the environment, a reliable measure ofheat flux combined with a measurement of skin surface temper-ature can be used to derive core body temperature [277]. Thismethod has recently been implemented in wearable configura-tions [278].

E. Summary

EEG is currently the method of choice for long-term nonin-vasive monitoring of brain activity, for BCI applications, neuro-feedback, augmented cognition, and longitudinal neurophysio-logical research and medical investigations. Current EEG tech-nology is not amenable for such daily prolonged and ambulatoryapplications. There is therefore a great need to be served by thedevelopment of viable, comfortable, and wearable dry-electrodeEEG technology or alternatives for long-term mobile recording.

VII. CONCLUSION

We have reviewed here recent historical developments in fivecutting edge areas of medical rehabilitation to which biomed-ical engineering is making leading contributions: 1) deep brainstimulation; 2) infusion of neurologically active compounds intospecific sites within the brain; 3) micro-electrode technologiesfor recording and stimulation of brain tissue; 4) utilization ofmicro-electrode arrays and computational devices to “read-out”neural codes to identify “brain states” for the control of external

devices or to control brain stimulation to induce additional brainstates; 5) noninvasive brain–computer interfaces to accomplishthe same goals as in 4). These are highly aggressive goals, re-quiring re-definition of the content and limits of each of thefields of biomedical engineering, electrical engineering, mate-rials science, neuroscience, and medicine individually, and rev-olutionary paradigms for interactions among the disciplines toachieve integrated solutions to the targeted problems. The land-scape is changing so rapidly that it is difficult to draw too manyconclusions without resorting to speculation. We can, however,see several trends that motivated this review.

First, the field of DBS is likely to expand remarkably in thecoming years, not just in terms of number of Parkinson’s pa-tients implanted, but perhaps more importantly, in terms of therange of disabilities treated, and thus, the number of brain re-gions in which electrical stimulation is applied for treatment.Although the mechanism of successful DBS remains unclear, italso is becoming clear that dysfunctions other than motor disor-ders are treatable with the DBS paradigm; and dysfunctions withlarge patient groups such as depression and obesity. It is remark-able that such apparently complex disorders can be successfullymodified with such a straightforward treatment. This findingalone, however, justifies concerted clinical programs to test thepossibility of stimulation-induced reversal of other, nontremor,nonmotor disorders, and demands a better understanding of therelationship between stimulation parameters and clinical ben-efit.

Second, the use of implantable neural prostheses raises thepossibility of active feedback between a current brain state and a“desired” brain state: closed loop control. Thinking of how DBSfor Parkinsonism would be strengthened just by the inclusion offeedback from the nigra-striatal-pallidal circuit to a monitoringmicrochip: apply stimulation only when dysfunction is detectedand correction is required; apply different stimulation patternsdepending on the current, dysfunctional state. A prosthetic de-vice could be programmed with different stimulation parame-ters depending on the desired “state” for the nigra-striatal-pall-idal system. The work with hippocampal prostheses that are pro-grammed to emit different spatio-temporal output patterns de-pending on the current spatio-temporal input patterns stronglysuggests a future of highly sophisticated interactions betweenimplanted devices and brain system functioning. Surely, the fu-ture of brain stimulation to correct dysfunctional brain states liesin understanding the relationship between stimulation parame-ters, stimulation sites, and clinical outcome.

Thus, and third, the relevance and importance of the rad-ical advances being made in micro-machining multi-site elec-trode arrays. These arrays push further a paradigm shift in neu-rotechnology by incorporating both electrical stimulation andelectrophysiological recording with the same electrode. More-over, it now has been demonstrated in animal paradigms that dif-ferent spatial distributions of electrode tips will allow limitingrecording to particular neural populations, and will allow lim-iting stimulation current to known neural populations. Althoughwe still have much to learn about the relationship between theextent of tissue activated, stimulation parameters, materials, re-action of neural tissue, etc., the degree of control exhibited withcurrent, existing devices argues strongly that much of the needed


technology is already available, and that future neurotechnologywill forge a path in the direction of controlling clinical benefitthrough a detailed “reading” or “sensing” of spatio-temporalpatterns of recorded activity to identify brain functionality or“state,” and a detailed manipulation of spatio-temporal patternsof electrical stimulation to modify ongoing brain functionalityso that the desired state is achieved. Although this may seemlike a remarkable “jump” from where we are today, it should beclear that the pieces of the solution are already here, and that thefield is already heading down this path.

Fourth, site-specific, intra-cranial injection of drugs can beconceived of within the same framework, i.e., alteration of brainstate at a population level. In this case, we considered drugsthat generated outgrowth of new fibers and synaptic connec-tions, so “brain state” was altered from a fundamental stand-point of system architecture. Just as easily could be consid-ered drugs that modify the activity levels of neurons on a msbasis, e.g., allosteric agonists for glutamatergic and GABAergicsynapses. From this perspective, site specific, intracranial injec-tion of drugs could readily be combined with implantable neuralprostheses: injected drugs could alter the “state” of the system,with recording and stimulation imposed on this new systembaseline. Nonetheless, site-specific drug injection technologieshave already reached the point of clinical trials and should wit-ness a more widespread use in the near future.

Fifth, and finally, noninvasive brain computer interfaces(BCIs) should see an accelerated rate of dissemination becauseseveral paradigms for achieving control over environmentalevents are now well-established. Moreover, the technology forhome use is nearly achieved, and the need is great. The lackof a requirement for surgical intervention remains a strongmotivator for its widespread use. Clearly a major obstacleremains the lack of a “dry” electrode.

In total, we see the neurotechnologies reviewed here ashaving highly complementary uses and applications. We alsosee them as on the threshold of achieving a prominent presencethrough a period of accelerated application, with the accelera-tion due to a new level of maturity in the system technologiesnow available, and an increasing number of demonstrations ofthe effectiveness of those technologies.

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Theodore W. Berger (A’03–M’03–SM’04) re-ceived the Ph.D. degree from Harvard University,Cambridge, MA, in 1976; his thesis work receivedthe James McKeen Cattell Award from the New YorkAcademy of Sciences. He conducted postdoctoralresearch at the University of California, Irvine from1977 to 1978, and was an Alfred P. Sloan FoundationFellow at The Salk Institute from 1978 to 1979.

He joined the Departments of Neuroscience andPsychiatry at the University of Pittsburgh in 1979,being promoted through to Full Professor in 1987.

During that time, he received a McKnight Foundation Scholar Award, twicereceived an NIMH Research Scientist Development Award, and was elected aFellow of the American Association for the Advancement of Science. Since1992, he has been Professor of Biomedical Engineering and Neuroscience atthe University of Southern California, and was appointed the David PackardChair of Engineering in 2003. Currently, he is the David Packard Professor ofEngineering, Professor of Biomedical Engineering and Neuroscience. He is alsothe Director of the Center for Neural Engineering at the University of SouthernCalifornia. While at USC, he has received an NIMH Senior Scientist Award,was given the Lockheed Senior Research Award in 1997, and was elected aFellow of the American Institute for Medical and Biological Engineering in1998. Dr. Berger also received a Person of the Year "Impact Award" by theAARP in 2004 for his work on neural prostheses, was a National Academy ofSciences International Scientist Lecturer in 2003, and an IEEE DistinguishedLecturer in 2004-2005. Dr. Berger was elected a Senior Member of the IEEEin 2004, received a “Great Minds, Great Ideas” award from the EE Times in thesame year, and in 2006 was awarded the USC Associates Award for Creativityin Research and Scholarship. Dr. Berger became Director of the Center forNeural Engineering in 1997, an organization which helps to unite USC facultywith cross-disciplinary interests in neuroscience, engineering, and medicine. Dr.Berger has published over 200 journal articles and book chapters, and is theco-editor of Toward Replacement Parts for the Brain: Implantable BiomimeticElectronics as Neural Prostheses (MIT Press, 2005), as well as the lead co-ed-itor of Brain-Computer Interfaces (Springer, 2008). Dr. Berger’s research fo-cuses on several goals sharing the common fundamental of a basis on biologi-cally realistic nonlinear dynamic models of the nervous system: 1) developmentand application of next-generation methodologies for mathematical modeling ofnonlinear, nonstationary neurobiological systems and processes; 2) developingbrain-implantable biomimetic microelectronics to function as neural prosthesesfor the replacement of cognitive functions (e.g., memory) lost due to damage orneurodegeneration; 3) discovery of novel drug compounds that act as agents toenhance higher cognitive functions and identified on the basis of compartmentalmathematical models of glutamatergic synaptic transmission; 4) application ofmathematical models of neural processing to temporal pattern (acoustic) recog-nition problems involving real-world signals. Translation of some of these re-search interests have led to commercialization efforts through two companies:Safety Dynamics, Inc. and Rhenovia Pharma, LLC.

Greg Gerhardt received the Ph.D. degree inchemistry in 1983 from the University of Kansas,Lawrence. He received postdoctoral training inpharmacology, neuroscience, and psychiatry at theUniversity of Colorado Health Sciences Center inDenver from 1983 to 1985.

He is currently Professor in the Anatomy andNeurobiology, Neurology, and Psychiatry depart-ments at the University of Kentucky (UK) ChandlerMedical Center, Lexington, KY. He is the directorof the Morris K. Udall Parkinson’s Disease Re-

search Center of Excellence and director of the Center for Sensor Technology(CenSeT), both at UK. He is also the Editor-in-Chief, Americas and Aus-tralasia, of the Journal of Neuroscience Methods. He holds one U.S. patentand several patent applications are in progress. He has authored or coauthoredmore than 240 peer-reviewed papers and book chapters and more than 300scientific abstracts. His laboratory focuses on growth factors and their effectson the central nervous system (CNS), as applied to studies of normal aging andrepair of the brain in Parkinson’s disease. In addition, his laboratory developsmicroelectrode recording methods to study the dynamics of neurotransmitterrelease in the CNS and to develop neuronal interface devices.

Dr. Gerhardt has received numerous awards, including a Research ScientistDevelopment Award (RSDA Level II from NIMH).


Mark A. Liker received the bachelor’s degreein mechanical and aerospace engineering fromPrinceton University in Princeton, NJ, and M.D. de-gree (summa cum laude with distinction in research)from the State University of New York—DownstateMedical Center.

He is a Clinical Assistant Professor in the De-partment of Neurosurgery at the Keck School ofMedicine of the University of Southern California(USC), Los Angeles, CA, where he completedneurosurgical residency and chief residency in neu-

rosurgery. He specializes in deep brain stimulation technologies for a varietyof neurological disorders. He completed a post-doctoral fellowship in theDepartment of Cell and Neurobiology under the guidance of Drs. M. Jakowecand G. Petzinger in basal ganglia plasticity in animal models of Parkinson’sdisease and the application of stem cells in these models. He is the author ofmore than 40 journal publications, book chapters, and abstracts on a variety ofneurosurgical topics and has addressed a variety of national and internationalaudiences as an invited Guest Lecturer.

Dr. Liker is a member of American Association of Neurological Surgeons,Congress of Neurological Surgeons, and American and World Society of Stereo-tactic and Functional Neurosurgery among other medical and neurosurgical or-ganizations.

Walid Soussou, was born in Beirut, Lebanon in1975. He received the B.S. degree in biochemistryfrom Boston College, Chestnut Hill, MA, in 1995,and the Ph.D. degree in neuroscience from theUniversity of Southern California, Los Angeles, CA,in 2005.

He has interned at Harvard Medical School andworked as a Research Technician at Boston Univer-sity. He has also worked as a research consultantfor World Technology Evaluation Center, where heevaluated Brain-Computer Interface research and

technology commercialization in the U.S., Europe, and Asia. After postdoc-toral training at the Burnham Institute for Medical Research, La Jolla, CA,he has taken a position as research scientist at Quantum Applied Science andResearch (QUASAR), San Diego, CA, where he is developing applications forQUASAR’s dry-electrode technologies. He is author on several research papersand book chapters and has presented his research at numerous conferences.

Dr. Soussou is a member of the Society for Neuroscience and is a recipient ofthe 2005 MIT Arab Student Organization’s Science and Technology GraduateStudent Award, and the Teaching Assistant Excellence Award from the USCBiology Department.

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