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Contents

International Society for Neurofeedback and Research 2010-2011 BoardPresident Leslie Sherlin, PhD [email protected] President Thomas Collura, PhD [email protected] Elect Richard E. Davis, MS [email protected] Joy Lunt, RN [email protected] Anne Stevens, PhD [email protected] at Arms Noland White, PhD [email protected] at Large Deborah Stokes, PhD [email protected] at Large Rex Cannon, PhD [email protected]’l Member at Large Martijn Arns, MSc [email protected] Director Cynthia Kerson, PhD [email protected] & Conference Coordinator Ann Marie Horvat [email protected]

AAPB Neurofeedback Division 2009-2010 BoardPresident David Kaiser, PhD [email protected] President Jon Walker, MD [email protected]/Treasurer Richard Souter, PhD [email protected] MembersJeffrey Carmen [email protected] Cannon, MS [email protected] E. Davis, MS [email protected] Swingle, PhD [email protected] Site Coordinator David Kaiser, PhD [email protected] Committee Representative Kirtley Thorton, PhD [email protected]

NeuroConnectionsISNR Co-editor: Merlyn Hurd, PhD [email protected] Neurofeedback Division Co-editor: Roger H. Riss, PsyD [email protected] Editor: Cynthia Kerson, PhD [email protected] for MindFull: David Kaiser, PhD [email protected] Editor: Kimberly Weeks, MS [email protected]: International Society for Neurofeedback and Research [email protected]: Rosalie Blazej [email protected]

NeuroConnections is the official publication of the International Society for Neurofeedback and Research and the AAPB Neuro-feedback Division. Opinions expressed herein are those of the respective authors and do not necessarily reflect the official view of ISNR or AAPB. ISNR and AAPB are not responsible for the products or programs of private companies advertised herein.

ISNR 2008 Crowne Plaza Riverwalk San Antonio, Texas

August 28 – 31, 2008 W/additional Pre- and Post-Conference Workshops

Submission process begins early 2008 www.isnr.org (800) 847-4986

Become an ISNR Member! Membership Advantages

Subscription and online access to theJournal of Neurotherapy

Subscription to NeuroConnectionsjoint newsletter with the AAPB Neurofeedback Division

Listing your Member Profile on our Site Discounts to book and DVD purchases Discounts to the annual conference registration

http://www.isnr.org for fees and application

2007 Research Fund Awardees Mario Beauregard, PhD

Robert Coben, PhD Bojana Knezevic, BA Estate Sokhadze, PhD

$ $ $ $ Be Involved | Support Neurofeedback Research

Help the Field of Neurofeedback Grow Look for news about 2008 Fund Raisers

NeuroConnections is published four times a year and will consider all materials pertaining to the practice and/or promotion of neurofeedback.Copyright © 2010 International Society for Neurofeedback and Research and the AAPB Neurofeedback Division.All rights reserved. No part of this publication may be reproduced with-out written permission from ISNR and AAPB.Direct all correspondence and inquiries, including commercial advertising information and classified ads to:

ISNR 1925 Francisco Blvd. E. #12 San Rafael, CA 94901 Phone: (800) 488-3867 Fax: (415) 485-1348 Email: [email protected] ISSN 2151-6987 (print) ISSN 2151-6995 (online)

Letter from ISNR President . . . . . . . . . . . . . . . . . . . . . . . . 4

Letter from AAPB NFB Division President . . . . . . . . . . . . . 4

Letter from ISNR Co-Editor . . . . . . . . . . . . . . . . . . . . . . . . 4

Letter from AAPB Co-Editor . . . . . . . . . . . . . . . . . . . . . . . 5

Letter from AAPB Executive Director . . . . . . . . . . . . . . . . . 6

A Historical Introduction to LORETA . . . . . . . . . . . . . . . . . 9

LORETA Neurotherapy for Chronic Pain Related Suffering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

LORETA Z Score Biofeedback . . . . . . . . . . . . . . . . . . . . 14

Advancements in LENS Treatment Protocols . . . . . . . . . 19

Niels Birbaumer Award . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Small Group Discussions ISNR 18th Annual Conference . . . . . . . . . . . . . . . . . . . . 25

Dr . Othmer Restates His Comments from the Members’ Meeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Mindful . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

What Exactly Are We Doing? . . . . . . . . . . . . . . . . . . . . . 29

Helping the Brain Help Us . . . . . . . . . . . . . . . . . . . . . . . . 33

Research Foundation Update . . . . . . . . . . . . . . . . . . . . . 33

NeuroConnections WINTER2010

LetterfromISNRCo-Editor

Welcome to the winter edition which has as a focus the issue of LORE-TA. This powerful analysis has been available for sev-eral years, at least 15 to the researcher and clinician. It is a

free software program and when used with knowledge of brain operation, the localiza-tion of issues becomes much clearer than just looking at a QEEG analysis or looking at raw EEG. The intent of this edition is to bring together a discussion of what is LO-RETA and what are the practitioners using LORETA neurofeedback training finding.

Leslie Sherlin PhD provides a person-al and clear description of the development of LORETA. Even though Pascal-Marqui had described in 1994 the specific solution to the inverse problem to get from the raw EEG to LORETA images, the actualization of the program took several years to develop. When one first sees the images it is breathe taking… here is information from the scalp that gives more depth and detailed informa-tion on which to make clinician decisions and research more questions of localization. The first time I saw a demonstration by Dr. Lubar and David Joffe of the infant LORE-TA training module , the whole experience gave me chills… here was a method that could go to the heart of an issue it seemed and in very few sessions create change. We no longer were looking at the surface infor-mation and inferring the change due to am-plitude or connectivity. We were looking at current densities at a deeper cortical level. Through the years, the development of LO-RETA training has been always there slowly being perfected. This last year seemed to be

This first letter as the new ISNR president comes at a bittersweet mo-ment. This morn-ing we concluded the first conference committee meeting of the year and we reviewed the feed-back from attendees

at our recent Denver conference. By the overwhelming response in attendance and your words, this was the best conference we have held. With over 500 individuals in attendance, the hotel was sold out and our meeting space was filled with an excite-ment and an attitude of camaraderie that I don’t believe I’ve ever experienced. The speakers were absolutely impeccable deliv-ering their expertise with skill and clarity. There were so many people involved in the success of the conference.

At the banquet reception, I failed to name those individuals by name and I apologize because they deserve so much more recognition than I could provide. I’ll take this belated moment to thank the entire conference committee that includes myself as chair and Martijn Arns, John Carmichael, Debbi Elliott, Peder Fager-holm, Ann Marie Horvat, Cynthia Ker-son, Steve Rondeau, Hank Weeks, Noland White, and Dan Williams (alphabetically). Doreen Davie and Karen Trudeau were ex-emplary helping at the registration booth and bookstore. There were a number of on site volunteers, including Nick Colosi that we also rely on to facilitate your confer-ence experience and I extend gratitude to

LetterfromISNRPresident

ISNRMissionStatementTo promote excellence in clinical practice, educational applications, and research in applied neuroscience in order to better understand and enhance brain function. Our objectives are:• Improve lives through neurofeedback and other brain regulation

modalities• Encourage understanding of brain physiology and its impact on behavior • Promote scientific research and peer-reviewed publications• Provide information resources for the public and professionals • Develop clinical and ethical guidelines for the practice of applied neuro-

science

AAPBNeurofeedbackDivisionMissionStatementTo improve human welfare through the pursuit of its goals. The specific goals are:• The encouragement and improvement of scientific research and clinical

applications of EEG technology and neurofeedback.• The promotion of high standards of professional practice, peer review,

ethics, and education in neurofeedback.• The promotion of neurofeedback and the dissemination of information to

the public about neurofeedback.• The division is organized for the purpose of carrying on educational and

scientific objectives and is not to be operated for profit.

Neuroplasticity is the ability of the brain to rearrange itself in response to stimula-tion. When another helps facilitate these changes, when a more experienced individual such as a clinician, mentor, or

educator guide us toward better habits, it might be called guided neuroplasticity. In this day and age the number of individuals who guide the neuroplasticity of each and every child or adult is humbling to consid-er. We may have left the tribe but the tribe remains within, and to try to count (and name) every one of our guides is daunting, if not impossible to do.

But let’s try.And let’s start with teachers: I was

put into the hands of Miss White for first grade, my first non-family neuroplasticity guide. I don’t recall a principal, I hardly recall the walk to school, and how I got to and fro each day. Miss K was my 2nd grade teacher, and she was followed by Miss Har-vey in 3rd grade, who was my homeroom and social studies and reading teacher. I heard she married the principal the follow-ing year, a man who always reminded me to tuck in my shirt, my first male request for order. In retrospect I know I had gym teachers, art teachers, and music teachers who populated these years, and some of the faces are still floating in my head, but the names are gone forever, and these people influenced my brain and behavior in ways

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Continued on page 6 Continued on page 8

David Kaiser, PhD

Leslie Sherlin, PhD Merlyn Hurd, PhD

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LetterfromAAPBCo-Editor

LORETA neurofeedback and the case for neuroplasticity following EEG neurotherapy.

In the cur-rent issue, our con-tributors invite us to consider the past and potential future

impact of LORETA on the field of neuro-therapy. Originally conceived as a research and diagnostic tool to localize surface EEG source generators in a three dimensional plane, Low Resolution Electromagnetic Tomography was later adapted into a plat-form to allow researchers and clinicians to directly modify neural networks underly-ing cognitive and emotional regulation, and to observe the results of neuromodulatory training in real time.

Elsewhere in this issue, Leslie Sher-lin gives a personal eyewitness account of pioneering work with Dr. Lubar and fellow students Marco Congedo and Rex Cannon, at the University of Tennessee Brain Re-search Lab, which gave birth to this vision-ary new application for LORETA.

Dr. Thatcher’s authoritative contri-bution to the current issue briefly reviews the science underlying LORETA, as well as

current tools that have made it possible for LORETA neurofeedback to begin to move beyond the research laboratory and into the offices of clinicians.

A handful of studies now document the viability of LORETA neurofeedback for enhancement of cognition and remediation of clinical conditions, and this body of work will surely grow in coming years. However, an equally critical contribution of real-time LORETA neurofeedback is the scientific clarity and transparency that it brings to our understanding of the mechanisms which underlie neurofeedback outcomes.

Elsewhere in this issue Rex Cannon briefly discusses how his and other LORE-TA neurofeedback studies directly “dem-onstrated the strengthening/weakening of functional networks in the brain as a result of the neurofeedback procedure.” LORETA neurofeedback provides an affordable yet scientifically rigorous platform by which it can be demonstrated that the mode of ac-tion underlying neurofeedback training ap-pears to be direct induction of neuroplastic changes in neural networks supporting cog-nitive and emotional self-regulation.

A recent study receiving wide media attention also found neuroplastic change as a direct result of neurotherapy. In a collabo-ration between John Gruzielier’s laboratory and the Department of Neurology at Uni-versity of London, graduate students Tomas Ros, Diane Ruge and Moniek Munneke demonstrated that a half an hour of voluntary control of alpha brain rhythms was sufficient

to induce a lasting shift in cortical excitabil-ity. The researchers utilized noninvasive pre and post training repetitive transcranial magnetic stimulation (rTMS) to investigate whether changes at the neuronal level could be measured after a single session of neuro-feedback self-regulation training. Before and after training, they applied a short magnetic pulse externally to the scalp to stimulate the motor cortex, producing a muscle twitch proportional to the level of neural respon-siveness of the cortex. Ros and colleagues reported that, following a neurofeedback protocol which involved suppressing alpha band activity, enhanced cortical response to rTMS reflected a disinhibition of intracorti-cal synaptic function of up to 150%, which persisted at 20 minute follow-up, indicating to the authors a time-course indicative of neuroplastic change. Interestingly, the effect of a single training session was comparable in magnitude to the observed effects of ar-tificial forms of direct brain stimulation in-volving magnetic or electrical pulses.

A decade ago, the viewpoint that neurofeedback derives its efficacy by di-rectly inducing plastic changes in neurocor-tical networks was still quite controversial. However, this is indeed the picture that is emerging. Low Resolution Electromagnetic Tomography and LORETA neurofeedback training have played, and will continue to play, a crucial role in this unfolding story.

Roger Riss, PhD AAPB Co-Editor

Roger Riss, PhD

the time when more than one software pro-gram provided clinicians the ability to im-plement this training. I attended Dr. Lubar’s and subsequently Dr. Thatcher’s workshops on this type of training. What impressed me at each training was the need to be very sure of your data, information and type of train-ing. This training is not for the one size fits all clinician… this training calls for in depth knowledge of the working of the brain; cor-relates to behavior and how to assess the ef-fects of the training.

In this edition Dr. Robert Thatcher and Dr. Ozier discuss the use of LORETA training. Dr. Ozier discusses his use with pain clients and the journey of finding the correct training to bring relief to chronic pain clients. His discussion of Price’s mod-el of pain is worth reviewing especially if you have encountered or have chronic pain clients. Dr. Ozier takes us through the many steps he and his colleagues used to arrive at the appropriate training paradigms. His

findings are quite impressive and we will certainly hear more from this fine research-er and future clinician.

Dr. Thatcher states “An advantage of LORETA EEG biofeedback is that one can target anatomical regions related to “loss of function” or “weak” function related to the patient’s symptoms and complaints (Luria, 1973).” His article takes us through the ad-vantages of LORETA Z Score training. The steps to arrive at the appropriate training, use of the symptom check list (which I have found invaluable) and what/how the train-ing is delivered are provided. Dr. Thatcher is a researcher who is sympathetic to the clinician and is always ready to listen, re-search, propose and refine the work to be able to deliver the information needed to provide clients with relief. His article is one you will be glad you took the time to read, especially, if you wish to have a better un-derstanding of LORETA Z Score training.

D. Corydon Hammond, PhD, Sara

Hunt Harper, PhD, Jill O’Brien, DOM, & Nicholas Dogris, PhD have provided an ar-ticle regarding a new form of LENS treat-ment that is very powerful. As they state “Protocols now allow the clinician greater flexibility in individualizing treatment with the capacity to focus even more specifical-ly on problematic brainwave frequencies.” The protocols are 2 channels and the article traces the history of the development of dif-ferent types of 1 channel protocols which led to the present 2 channel protocols. This protocol calls for 4 sites on the scalp and shares some of the same features as bipo-lar training. They provided case studies and pre and post information that will probably encourage you to try this protocol.

There is as always more articles in this edition and I will stop here and let you get on with reading this edition and hope you find it informative and usefulMerlyn Hurd, PhD, BCIAC/EEG Fellow ISNR Co Editor

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ISNRPresidentContinuedfrompage�

them. Beyond these core staff and vol-unteers, there were countless students and others who volunteered their time in many capacities. Thank you spon-sors, exhibitors, speakers, and attend-ees. You are the ones who brought the warmth and positive attitude that brings us all back each year. This is the sweet-ness of which I mentioned.

I can’t begin to tell you how very honored I feel to have been elected to serve the ISNR organization and that I take this responsibility seriously. I will be supported by a group of esteemed colleagues who deserve an introduction. This year’s ISNR Board of Directors includes Tom Collura (Past President), Richard E. Davis (President Elect), Anne Stevens (Treasurer), Joy Lunt (Secretary), Noland White (Sergeant at Arms), Martijn Arns (Intl. Member at Large), Rex Cannon, and Deb Stokes (Members at Large) and, of course, our staff Cynthia Kerson (Executive Direc-tor) and Ann Marie Horvat (Conference and Membership Coordinator).

No sooner than we are a month away from such a re-warding conference experience, that we engage in our first Board meeting where topics included dis-cussions of the op-erations and longevity of our organization, and also how to ad-dress turmoil. We are now on the eve of the release of two stud-ies that raise concern since they are expect-ed to report null find-ings in double-blind placebo controlled experiments. There has been consider-able discussion on the various email forums and in phone conver-sations amongst us. I won’t speak now to this before we have the actual studies in hand, however, our organization is al-

LetterfromISNRED

I’m happy to announce that the acquisition for the fMRI/EEG/ERP project is almost com-plete and look forward to the findings. We are also embarking on two more projects – also with the ADHD popu-lation. These research

projects are sorely needed and I’m proud to be a part of them.

I was recently at the annual CHADD (Association for Children and Adults with ADHD) conference in Atlanta where I heard the results of the NIMH-funded study performed by Ohio State’s Eugene Arnold and Nick Lofthouse. Also a part of that panel was Lawrence Hirschberg, sent by us to discuss the findings and also continue the dialog that we’ve had with their Profes-sional Affairs Committee. Taken at face value, the findings of this perspective study are grim. But once we pointed out some of its weaknesses, they agreed that it would be prudent to consult with our best scientists on the larger study, hopefully to also be funded by NIMH. We’re looking forward to this challenge.

The IEEE project is off and running. The corporate members are preparing a draft standards document, which should be available in December and for our next IEEE meeting. This and the FDA project will begin to establish credibility for our devices—a responsible step towards re-spectability from other scientific commu-nities.

In his mission to educate, this year’s president, Leslie Sherlin hopes to make the Web site friendlier to the public. If you browse through it now, you’ll find a lot of pretty heady stuff, which may be very con-fusing to the public and your potential cli-ents. The PR Committee, headed by Sarah Prinsloo, is creating this new section. Look for it in a few months.

In JN 15(1), we will be publishing a position paper on standards for practice that the Standards Committee, chaired by Cory Hammond is crafting. We believe this to be the minimum standard of care and hope our members will adhere to it as doing so will help outside scientific communities recognize the practices of neuromodulatory modalities as legitimate and valuable. We

encourage all of our members to read the standards document carefully and practice within the scope of their practice and ex-pertise.

In some ways the inappropriate use of the terms biofeedback and neurofeed-back is flattery. For one to choose to use the terms suggest that they sell. This is very different than a few years back, in which one wouldn’t consider using them because no one knew what they meant. That said, we don’t want the misuse to create a public image that is less than optimal or to misrep-resent what treatment is being advertised. Recently, we have seen more of these ex-amples emerge and are carefully evaluat-ing what we can do to encourage their right use. As always, if you have any ideas, we are open to hearing from you.

Please remember to renew your mem-bership before the end of the year. There are many benefits to your ISNR membership including the Journal, NeuroConnections, discounts on books and DVDs and the an-nual conference registration.

I don’t know about you, but I’m looking forward to the holidays. Wishing you the best,

Cynthia Kerson, PhD, BCIA-EEG Executive Director, ISNR

Cynthia Kerson, PhD

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ready strategizing about how to respond in an even-tempered and professional man-ner; but we will not be ambiguous in point-ing out any flaws in methodology or reason. This is the bitterness that I mentioned.

It is my opinion and belief that we are so concerned, not because of our disbelief that neurofeedback is a viable or effective modality, but because there remains con-siderable ignorance about its mechanisms and potential by most people outside our organizations. We are thoughtful about the implications this may have for our clinical techniques and our business practices. It is my contention that we should take this op-portunity to direct attention to education. We should first educate ourselves. There is no direct path into this field we current-ly call neuromodulation or neurotherapy that contains neurofeedback. We are an eclectic group of professionals who have landed in a field that utilizes the methods and applications of neurofeedback. This diversity is our strength because we bring to the table such an array of education and expertise. However, this diversity can also be our weakness because the steps lead-ing to understanding the methods are un-clear and many, despite being involved for years, may not have a robust awareness. Without proper understanding of the foun-dations of this modality, we are destined to erroneously apply them and weaken our cause. To work toward a common founda-tion, I will be asking the conference com-mittee to investigate ways to implement core foundation training at our confer-ences and to consider other opportunities for providing education to the profession-als within our societies. In the meantime, I encourage us all to continue to seek con-tinuing education workshops and training being offered and to not only be looking forward to the next advanced technique, but to also not forget the basic elements of physiology and learning theory that serve as the basis of our modality. See Cynthia’s article on page 31 that asks this very ques-tion to which some of our esteemed col-leagues replied.

We secondarily must reach out to educate our colleagues. Several have criti-cized the scientists involved in the afore-mentioned studies as not being qualified or having expertise in the modality that they have chosen to investigate. While we can-not be responsible for the actions of all oth-ers, part of our professional mission is “to promote excellent in clinical practice, edu-

cational applications, and research…” Our community must step up and put forth the appropriate content and reach out to other professionals in effort to educate and pro-mote the modality. Largely, our efforts have increased and are gaining ground through publications such as this newsletter, our academic journals, and book and chapter publications. Let us keep and increase the good efforts.

Finally, we cannot forget the public. Educating the public is perhaps our great-est challenge because of the vastness and the bombardment of the information age. The public relations committee of ISNR, chaired by Sarah Prinsloo, has already swiftly taken initiative to find ways to reach the public, as I know the colleagues of our sister groups in the alliance have done (those being BCIA and AAPB). The most apparent resource is through the In-ternet. We are refacing the ISNR website to increase the user-friendly experience and navigability. We will utilize press releases and other media exposure to demonstrate the highest standards in our field that will provide the public an increased awareness of the legitimacy of neurofeedback and provide a resource to fact-check charlatans who may use our language to elude FDA and/or FTC regulations.

Even in all these efforts, we as in-dividuals are the best ambassadors to our field. You are the one in your professional network and the one most aware of the is-sues of concern. You are the one in your community and the one who has the most influence in your neighborhood. It is not up to our organizations to do the work for us. The organizations are limited in the services that they can provide. We should only rely on the organizations for structure and to provide the support and the collec-tion of individuals sharing similar bur-dens. The organization, remember, is only as strong as its members and therefore, it is ultimately on the shoulders of each and every individual to educate those around us. Anatole France once said, “To ac-complish great things, we must dream as well as act.” It has never been this group’s weakness to dream. It is the time for us to rise up together and I say to you, “to ac-complish great things, we must act as well as dream.”Leslie Sherlin, PhD ISNR President

no one can grasp fully. I estimate that I had 60 elementary and high school teachers, and another 40 in college the first four years. Graduate school was a different animal entirely, filled with end-less visiting professors, guest lecturers, and speakers. All combined, there were something north of 300 educators who guided my thoughts and feelings and behaviors, some better than others. And then there were coaches, physicians, store owners, and clergy, plus so many friends and family and strangers along the way.

Thinking back to earlier years, if only I had a 19-channel EEG recording or two for every year of my life. I could take these records and watch my brain change in response to all this stimula-tion and experience. If we had an EEG each year of our lives, we could use this information to help restore ourselves to those days, to the habits of our youth, reversing the process and debris of ag-ing one session at a time. We might not be able to reintroduce the entire mental pantheon of youth, but surely we could re-experience some of the rhythms of our youth and return us to simpler and healthier ways. What would it be like to be 10 years old once again, a time when I knew very little of the world, less about myself, and cared only for riding my bi-cycle and playing ball. Christmas morn-ing meant all promises might come true at any moment. And to taste 25 again, but able to appreciate it, the lengthy transition from adolescent to adult. It will not be difficult to use operant condi-tioning and neurostimulation techniques to reinstate, to some degree, our past brain states -- if the records exist. With LORETA and other inverse brain solu-tions we can use magnetic stimulation and EEG training to restore the most prominent brain currents of our youth. Some say alpha-theta training achieves this in a general way.

And considering this desire in my-self, I cannot stop but wonder what the world will pay to have an accurate and valuable roadmap back to their youth, along with a dozen ways to get there? I’d say not enough money has yet been printed.David Kaiser, PhD

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I am very pleased to be able to contribute to the NeuroConnections effort in coalesc-ing articles on the topic of LORETA. This analysis procedure has permeated our or-ganizations and those professionals who are utilizing tools the field of quantitative electroencephalography (QEEG) for the purposes of education, research and guid-ing interventions such as neurofeedback. I feel tremendous fortune to have been a part of this history in a small way by observing this growth within our community and to have contributed in some minor way to the use of LORETA in this capacity. There are many excellent writings both formal and less formal that describe the methods of LORETA. My intention isn’t to attempt to explain how this modality is calculated nor present to you the vast body of research of various populations of individuals but in-stead to summarize from a historical point of view the use of LORETA within our spe-cific community.

I hope to achieve this goal in an informal way by telling the story of the implementation of these methods from my perspective. For a bit more formal de-scription of the use of LORETA families and some examples you can see chapter 4 authored by myself (Sherlin, 2009) in the second edition of the book Introduction to Quantitative EEG and Neurofeedback edit-ed Budzynski, Budzynski, Evans & Arbar-banel. For the most formal and thorough listing of the LORETA techniques and it’s technical development I refer you to the au-thor of the method Roberto Pasucal-Mar-qui, PhD and the website of the Key Insti-tute for Brain-Mind Research (http://www.uzh.ch/keyinst/loreta.htm).

As many of you know I was lucky early in my college career by growing up and attending the state university, The Uni-versity of Tennessee in Knoxville. This af-forded me the serendipitous opportunity to end up in the class and in the laboratory of Joel Lubar, PhD as an undergraduate stu-dent. In 2000 I had the great privilege to visit with Roberto Pascual-Marqui PhD, the developer of the LORETA inverse solu-tion, with my colleague and fellow student Marco Congedo. At this time the LORE-TA-Key software (Pascual-Marqui, 1994, 1999), had not been widely distributed and utilized in the United States. Marco had

significant interest in using LORETA for visualizing brain activity and for exploring newer methods for neurofeedback and had many questions for Roberto. Interestingly Marco was so persistent finally Roberto refused any more electronic questions but made the invitation to visit to find the an-swers. So upon the invitation of Roberto, Marco found funding to travel to Zurich and learn the details and I happen to be standing in the right spot at the right time. I somehow knew this was an opportunity not to be missed. Roberto trained us exten-sively on how to use his software, named LORETA-Key, which had been already released as free academic software. The LORETA-Key software is a collection of independent modules that the user must run in sequence in order to get from raw EEG to LORETA images.

LORETA is a specific solution to the inverse problem. The method was origi-nally described in 1994 by Pascual-Marqui, Michel and Lehman (Pascual-Marqui et al., 1994) however it had been under develop-ment for years.

“This first paper presented the LO-RETA method as a new method for local-izing the electric activity in the brain based on scalp potentials from multiple channel EEG recordings. This model was in contrast to previously described models because it did not require a limited number of point sources or a known surface distribution. Instead it computes the distribution of the current source density (CSD), measured in microamperes, through the full brain vol-ume” (Sherlin, 2009, p.84).

The LORETA analysis is unlike other quantitative EEG analysis techniques because it is capable of determining the rel-ative activity of regions in the brain using surface electrodes (Pascual-Marqui, 1999). The EEG is a measure of electrical poten-tial differences and the LORETA method estimates current densities at a deeper cor-tical level.

Upon our return after learning the mechanics of performing an analy-sis, which was very labor intensive with many batch steps running many different modules, I wanted us to develop a macro of sorts that would perform the extensive steps necessary in the LORETA-Key soft-ware all at once taking care of all possible

options in a clear and understandable man-ner. The room for error was great and the user had to be tedious and detailed and still the process would take significant time. With some already existing programming skills Marco wrote a very clean and basic program that would run the LORETA-Key modules after the user had input the neces-sary data details. This program we called the Workstation (Congedo, 2000). Upon the recommendation of our professor and supervisor Joel Lubar, PhD, we formed a company to distribute this program to the larger clinical field of neurofeedback and QEEG providers. This very straightforward program was the first 3rd party software utilizing the LORETA-Key and was well received because it allowed clinically ori-ented users the ability to perform LORETA analysis with greater ease and the ability to utilize this incredible tool in performing and understanding the current source den-sity localization in their clients. Later there were several other software tools developed that were aimed at the neurofeedback com-munity. Since 2005, all of these softwares have been released as freeware, following Roberto’s lead, stating unequivocally that our goal was to make inverse solution tools as accessible as possible in the neurofeed-back community.

Newer methods were developed by Pascual-Marqui in 2002 and named stan-dardized LORETA or sLORETA (Pascual-Marqui, 2002). This new implementation had to its advantage the ability to localize test point sources with zero localization er-ror in the absence of noise, which had not previously been accomplished. Since my goal here is not to distinguish the differ-

AHistoricalIntroductiontoLORETALeslie Sherlin, PhD

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ence in the methods I will skip over these technical issues. It will suffice to say that despite the name, from a mathematical point of view sLORETA is very different from the old LORETA method, and much more accurate. The most recent release and development of this family of inverse solutions is Exact Low Resolution Brain Electromagnetic Tomography (eLORETA). eLORETA is not a linear imaging method but is a true inverse solution with exact and zero localization errors (Pascual-Marqui, 2007a, Pascual-Marqui et al., 2006). Since 2008 the sLORETA/eLORETA software has included analysis of microstates, in-dependent component analysis (ICA) and additionally contained the Brain Research Laboratories (BRL) normative comparison capability, still as freeware. “The norms, the software, and their validation have been de-veloped in collaboration with E. Roy John, Leslie Prichep, and Roberto Isenhart, from the Brain Research Laboratories (BRL), Department of Psychiatry, NY University School of Medicine, NY, USA” (Pascual-Marqui, 2010). The full details and techni-cal specifications of each of the aforemen-tioned methods can again be found at the website of Roberto Pascual-Marqui and the KEY Institute for Mind-Brain Research (Pascual-Marqui, 2007b) and in the cited publications.

It wasn’t long after a wider spread distribution of the LORETA software and use in the community of QEEG and neu-rofeedback that the natural question arose, “could the current source density of interior cortical areas be operantly conditioned in the same manner as the scalp neurofeedback was being conducted currently?” This was actually our first concern as announced dur-ing a workshop at ISNR by Joel Lubar, Mar-co Congedo, David Joffe and myself (Lu-bar, Congedo, Joffe, & Sherlin, 2001). The workshop was the starting point for a 3-year project that would be Marco’s disser-tation where he demonstrated and verified that in fact the deeper structures could be trained using “LORETA feedback” (Con-gedo, 2003). This work was published the following year in IEEE Trans. in Rehabili-tation Engineering and Neuronal systems (Congedo, Lubar and Joffe, 2004) and is still today a pioneering study in multi-chan-nel neurofeedback. Dr. Lubar’s lab, and in particular Rex Cannon, continued to pursue these techniques with additional validation

studies (Cannon et al, 2007, 2009). Cur-rently the method is used in several other universities and is becoming available in several neurofeedback systems offered to clinicians as an experimental module. I’ve been lucky to be involved in a number of these experimental clinical studies with the most recent very exciting work taking place at the University of Alberta in Canada by the principle author Douglas Ozier in the area of chronic pain utilizing the updated algorithm of sLORETA for feedback with exact localization. Ozier has contributed to this issue as well so I’ll direct you to his contribution for further details with publi-cations soon to follow.

It’s been fun and interesting to see the past ten years go by with the advances both in the technique but also to see the new applications and uses of LORETA. It was only a short time ago that this method was being developed and now it is practi-cally understood and a familiar part of most QEEG analysis. It is utilized by many of our colleagues in research in attempt to un-derstand variability in populations and has a real promise of impacting the way that we provide neurofeedback. As a final com-ment I’ll raise your awareness that many developments are continuing in the area of connectivity between cortical areas us-ing LORETA techniques. You might start looking forward to learning more about this particularly interesting aspect at the ISNR 2011 conference in Phoenix where Roberto Pascual-Marqui, a lifetime achievement award recipient, is planned to be a Keynote speaker.

References

Cannon R., Congedo M., Lubar J.F., Hutch-ens T. (2009). Differentiating a network of executive attention: LORETA neurofeedback in ante-rior cingulate and dorsolateral prefrontal cortices. Inter-national Journal of Neuroscience ;119, 404-441.

Cannon R., Lubar J.F., Congedo M., Thornton K., Towler K., Hutchens T. (2007)., The Effect of Neurofeedback Training in the Cognitive Division of the Anterior Cingulate Gyrus. , International Journal of Neurosci-ence;117(3), 337-57.

Congedo, M. (2000). Workstation (Version 1.0). Knoxville, TN: Nova Tech EEG, Inc.

Congedo, M. (2001). EEG Editor (Version 1.0). Knoxville, TN: Nova Tech EEG, Inc.

Congedo, M. (2003). Tomographic Neurofeedback; a new Technique for the Self-Regulation of Brain Electrical Activity. University of Tennessee, Knoxville.

Congedo M., Lubar J.F. (2003). Parametric and Non-Para-metric Normative Database Comparisons in Electro-encephalography: A Simulation Study on Accuracy. Journal of Neurotherapy 7(3/4), 1-29.

Congedo, M. (2004). sLORETA zero-localization error as seen in a point spread functions: an animation. Retrieved April 29, 2009, from http://www.lis.inpg.fr/pages_perso/congedo/sLORETA.htm

Congedo M., Lubar J.F., Joffe D. (2004). Low-Resolution Electromagnetic Tomography neurofeedback. IEEE Trans. on Neuronal Systems & Rehabilitation Engi-neering 12(4), 387-397.

Congedo, M. (2005). EureKa! (Version 3.0). Mesa, AZ: Nova Tech EEG, Inc.

Congedo M., Lotte F, Lécuyer A. (2006). Classification of Movement Intention by Spatially Filtered Electromag-netic Inverse Solutions. Physics in Medicine and Biol-ogy 51, 1971-1989.

Congedo M. (2006). Subspace Projection Filters for Real-Time Brain Electromagnetic Imaging. IEEE Transac-tions on Biomedical Engineering 53(8), 1624-34.

Congedo M., Joffe D. (2007). Multi-Channel Spatial Fil-ters for Neurofeedback. In Neurofeedback: Dynamics and Clinical Applications . (Ed) Evans J., Haworth Press, New York,

Lubar, J. F., Congedo, M., Joffe, D., & Sherlin, L. (2001, September). LORETA 3-D Neurofeedback, Normative Database and New Findings. Paper presented at the 9th Annual conference of the Society for Neuronal Regula-tion, Monterey, California, USA..

Ozier, D., Whelton, WSherlin, L., Mueller, H., & Lamp-man, D., & Sherlin, L. (unpublished). Comparing the efficacy of thermal biofeedback and sLORETA neuro-therapy as interventions for chronic pain. University of Alberta, Edmonton.

Pascual-Marqui RD, Michel CM, Lehmann D. (1994). Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. International Journal of Psychophysiology, 18:, 49-65.

Pascual-Marqui RD. (1999). Review of Methods for Solv-ing the EEG Inverse Problem. International Journal of Bioelectromagnetism 1, 75-86.

Pascual Marqui, R. D. (2002). Standardized low-resolu-tion brain electromagnetic tomography (sLORETA): technical details. Methods Find. Experimental Clinical Pharmacology 24(D), 5-12.

Pascual-Marqui, R.D., Esslen, M., Kochi, K., and Lehmann,D. (2002b). Functional imaging with low resolution brain electromagnetic tomography (LORE-TA): A review. Meth. Findings Exp. Clin. Pharmacol vol. 24C, pp. 91–95.

Pascual-Marqui, R.D., Esslen, M., Kochi, k., and Lehmann,D. (2002c). Functional imaging with low resolution brain electromagnetic tomography (LO-RETA): Review, new comparisons, and new validation. Jpn. Journal of Clinical Neurophysiology. vol. 30, pp. 81–94.

Pascual-Marqui, R. D. (2007a). Discrete 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. arXiv:0710.3341 [math-ph].

Pascual-Marqui, R. D. (2007b). LORETA: low resolution brain electromagnetic tomography., The KEY Institute for Brain-Mind Research, Zurich, Switzerland

Pascual-Marqui, R.D. (2010). Standardized & Exact low resolution brain electromagnetic tomography. Re-trieved from, http://www.uzh.ch/keyinst/loreta.htm on November 6, 2010.

Sherlin, L. (2009). Diagnosing and Treating Brain Func-tion through the use of Low Resolution Electromag-netic Tomography (LORETA). In T. Budzynski, H. K. Budzynski, J. Evans & A. Abarbanel (Eds.), Introduc-tion to Quantitative EEG and Neurofeedback, Advanced Theory and Applications (2 ed.): Elsevier, Amsterdam, The Netherlands.

Wagner, M., Fuchs, M., Kastner, J. (2004). Evaluation of sLORETA in the presence of noise and multiple sourc-es. Brain Topography vol. 16, no. 4, pp. 277-280.

HistoricalIntroductiontoLORETAcontinuedfrompage�

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The origins of my involvement with LO-RETA neurofeedback trace back to mid 2006. At the time I was actively looking for possible dissertation topics. As a PhD student in Counselling Psychology, my core research interest involves integrating cognitive neuroscience and psychotherapy, thereby improving therapy’s ability to less-en suffering.

Around this time I came across a neurofeedback study that had recently been conducted by DeCharms et al. (2005). These authors used fMRI neurofeedback to teach a group of chronic pain patients to self-regu-late their pain. DeCharms et al. took advan-tage of the strong spatial resolution of MRI in order to teach volitional down-regulation of cerebral blood flow in a small, pain relat-ed region of the dorsal ACC. The study pro-duced evidence of successful neural training effects. More impressively however, the

degree to which participants learned how to regulate dACC blood flow was strongly cor-related with how much pain regulation im-provement they showed, thereby implying a causal relationship between these two forms of self regulation.

The excitement that I felt when I first read these findings encouraged me to learn more about chronic pain. As I read, I began to appreciate the sheer scale of the suffer-ing that chronic pain causes. I learned how incredibly prevalent it is. I learned that it can negatively impact an individual’s abil-ity to function in virtually all areas of life. I was particularly impacted by the follow-ing passage from a qualitative study that describes what it can be like to live with constant pain; “The essence of participants’ experiences was unremitting torment by a force or monster … The future was unfath-omable” (Thomas, 2000, p.683).

At this stage I began to see how un-fortunate it was that the cost of MRI meant that the direct translation of DeCharms et al. findings into common clinical practice would probably remain impractical for many years. This made me curious if there was another neurofeedback modality that had enough localization ability that it could allow the approach of DeCharms et al. to be built on, but that was also modestly priced. This led me to discover Marco Congedo’s

LORETANeurotherapyforChronicPainRelatedSufferingDouglas Ozier, M.A., RCC


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ground-breaking work with LORETA neurotherapy (Congedo, Lubar & Joffe, 2004), and in turn, to my initial contact with Leslie Sherlin. From that first contact onward Leslie has unfailingly encouraged and supported my dissertation research.

Once our team (Ozier, Sherlin, Mueller, Lampman, & Whelton) had committed to this research idea, we turned our attention to decid-ing how to most effectively translate DeCharms’ et al’s MRI, BOLD-based paradigm to use with LORETA neurofeedback. Our choices in this regard were guided by current understandings of how chronic pain is instantiated in the brain. We were particularly influenced by Price’s (2002) incisive neural model of pain. Price’s model holds that input from various afferent pathways generates three basic streams of pain related information. Each stream is initially processed at distinct loca-tions before they are ultimately integrated. The first stream primar-ily involves information about the sensory aspects of pain. S1 plays a particularly key role in this function. The second stream involves “immediate pain unpleasantness”, or the coarse affective/motivational aspects of pain. The ACC is crucial to this level of pain processing. Finally, there is the “suffering” aspect of pain. Psychologically, pain related suffering correlates with rumination on the longer-term conse-quences or meanings of the pain for the person experiencing it (Price, 2002). Evidence suggests that the medial PFC plays a leading role in supporting the suffering element of chronic pain (Baliki et al., 2006).

Our first thought had been to directly echo DeCharms et al’s ap-proach by using LORETA neurofeedback to down train dACC activity in order to help our participants lessen pain unpleasantness. However, I am strongly influenced by a Complexity Theory based paradigm that stresses the vital role of psychological flexibility in determining mental health (Siegel, 2009). I think this paradigm makes a compelling case that a key to psychological well-being is the ability to flexibly switch between controlling problematic experiences when they can be ef-fectively controlled, and mindfully accepting them when they cannot (Hayes, Strosahl, & Wilson, 1999). From this perspective, strategies directed at regulating unwanted experiences continue to have strong value. However, complementary strategies directed at regulating one’s responses to these unwanted experiences now become at least as important. Mindfulness and acceptance based approaches may be particularly appropriate when working with chronic pain, since it is usually stubbornly resistant to eradication.

These considerations led us to the idea of training volitional down regulation of the mPFC as a means of regulating chronic pain related suffering. The appeal of this idea was strengthened by fMRI-based research into the effects of Mindfulness Based Stress Reduc-tion (MBSR) (Santorelli & Kabat-Zinn, 2002). MBSR is a mindful-ness-based intervention that has been associated with significant im-provements in a range of chronic pain related outcomes (Morone et al., 2008). At the same time, Farb et al. (2007) found that, relative to meditation naïve controls, MBSR trained participants demonstrated stronger deactivations of the mPFC when they were asked to enter a present focused, non-ruminative state of awareness.

On this basis, we conducted a preliminary study (Ozier, Sherlin, Mueller, Lampman, & Whelton, in preparation [a]) designed to help clarify our LORETA neurofeedback protocol. During this preparatory study we asked a sample of people living with mixed chronic pain conditions to consciously ruminate on the obstacles that their chronic pain created for them, while we monitored their full scalp EEG. We then contrasted this “SUFFER” condition with a cognitive control task. Using LORETA, we found qualitative evidence that, within the

Figure 1: Suffer- Cognitive Contrast in Low Gamma (30-50 Hz)

mPFC, the SUFFER condition was associated with increased activity in the excitatory Beta and Gamma bandwidths and with decreased Theta activity.

Following completion of this initial experiment, we con-ducted our neurotherapy study (Ozier, Sherlin, Mueller, Lamp-man, & Whelton, in preparation [b]) with a sample of eight chronic pain patients. Each participant received bi-weekly, one-hour training sessions over the course of six weeks (12 sessions total). Neurofeedback was conducted using a 19 chan-nel Electrocap, a Mitsar amplifier, Braintuner neurofeedback software (Mitsar Inc.), and a Dell personal laptop computer. Four five-minute, eyes-closed training periods were conducted during each training session. The goal was to train volitional deactivation of the targeted mPFC region. Specifically, the pro-tocol involved rewarding frontal Theta and Low Alpha within the targeted ROI (5 voxels centered in medial BA 10 at x: 0, y: 50, z: 0). We up-trained these bandwidths in response to our study 1 results, and also because frontal Theta and Low Alpha power increases are the most common EEG correlates of medi-tation. Delta (1-3 Hz) and Low Gamma (30-40 Hz) were inhib-ited in order to control EOG and EMG artefact respectively.

At pre and post training we conducted EEG/pain “con-trol tests.” As with training, these control tests were conducted

Figure 2

LORETAFeedbackcontinuedfrompage11

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using full cap EEG. The control tests began with a BASELINE block during which the participants sat in a neutral state for 4 min-utes. A 4 minute INCREASE block was then conducted during which the participants were provided with audio feedback from the training ROI and were instructed to increase the consistency and intensity of this feed-back. Pain ratings were taken following each of the blocks. These tests were designed: to test the development of volitional EEG con-trol from time 1 to time 2; and to investigate the relationship between improvements in volitional EEG control and improvements in pain regulation ability.

A detailed report of our results is beyond the scope of this article. However, we will outline them here in broad strokes. First, we found expected evidence that our participants successfully developed voli-tional control of the trained bandwidths over the course of training (see figure 2). Second, participants showed expected improvements in their pain regulation abilities, both dur-ing our control tests and during their daily lives. However, our findings around the hy-pothesized relationship between EEG con-trol and pain control were more equivocal. At the group level these associations were not, as we had expected them to be, signifi-cant. However, patterns within our data sug-gest that the anticipated associations may in fact have occurred, but that these brain-be-haviour relationships were obscured by the fact that our methodology did not allow us to effectively distinguish between two dif-ferent forms of Theta activity. The first va-riety, “Hippocampal Theta”, is produced in the Hippocampus and has been associated with anxiety and rumination (Mitchell et al., 2008). The second variety, “frontal midline Theta”, is produced in the mPFC near our training ROI. Frontal midline Theta is as-sociated with concentration and relief from anxiety (Mitchell et al., 2008), and has also been shown to be inversely correlated with

BOLD activity in the mPFC (Meltzer et al., 2009).

In sum, our results suggest that LO-RETA neurofeedback may have the po-tential to eventually become a clinically valuable, adjunctive chronic pain man-agement modality. However, much more work clearly needs to be done before this possibility can be confirmed. Specifically, larger n studies will need to be performed in order to replicate our apparent successes in training volitional EEG control. Fur-ther research into the association between trained EEG changes and changes in pain experience will also be crucial, given our equivocal results in this regard. Finally, our challenges in differentiating between Hip-pocampal and frontal midline Theta indi-cate how valuable it might be if LORETA neurotherapy were to be successfully com-bined with a technique like Independent Components Analysis (ICA), as Congedo & Joffe have suggested (2007).

As I approach the end of my disserta-tion research, I am filled with both grate-fulness and hope. I feel gratefulness for the generous support of my colleagues and mentors, and above all to our participants for making the work possible. The hope comes from my conviction that, through continued efforts to translate the findings of cognitive neuroscience into the work of front line clinicians, our field will continue to evolve increasingly powerful tools with which to help alleviate the suffering caused by chronic pain.

References

Baliki, M. N., Chialvo, D. R., Geha, P. Y., Levy, R. M., Harden, R. N., Parrish, T. B., & Apkarian, A. V. (2006). Chronic pain and the emotional brain: Specific activity associated with spontaneous fluctuations of intensity of chronic back pain. The Journal of Neuroscience, 26 (47), 12165-12173.

Congedo, M., Lubar, J. F., & Joffe, D. (2004). Low resolu-tion electromagnetic tomography neurofeedback. IEEE Transactions on Neural Systems and Rehabilitation En-gineering, 12 (4), 387-397.

Congedo M., Joffe D. (2007), Multi-Channel Spatial Filters

for Neurofeedback. In Neurofeedback: Dynamics and Clinical Applications , (Ed.) Evans, J. NY: Haworth.

DeCharms, R. C., Maeda, F., Glover, G. H., Ludlow, D., Pauly, J. M., Soeji, D., Gabriele, J. D. E., & Mackey, S. C. (2005). Control over brain activation and pain by using real-time functional MRI. PNAS, 102 (51), 18626-18631.

Farb, A. S., Segal, Z. V., Mayberg, H., Bean, J., McKeon, D., Fatima, Z., & Anderson, A. K. (2007). Attending to the present: Mindfulness mediation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience Advance Access. Retrieved September 7, 2007, from http://scan.oxfordjournals.org/cgi/reprint/nsm030v1.

Hayes, S.C., Strosahl, K.D., & Wilson, K.G. (1999). Ac-ceptance and commitment therapy: An experiental ap-proach to behavior change. New York: Guilford Press.

Meltzer, J.A., Fonzo, G.A. & Constable, T. (2009). Trans-verse patterning dissociates human EEG theta power and hippocampal BOLD activation. Psychophysiology. 46(1), 153-162.

Mitchell, D.J., McNaughton, N., Flanagan, D., and Kirk, I.J. (2008). Frontal-midline theta from the perspective of hippocampal “theta”. Progess in Neurobiology, 86, 156–185

Morone, N. A, Greco, C. M., and Weiner, D. K. (2007). Mindfulness meditation for the treatment of chronic low back pain in older adults: a randomized controlled pilot study. Pain, 134, 310 –9.

Price, D. D. (2002). Central neural mechanisms that inter-relate sensory and affective dimensions of pain. Mo-lecular Interventions, 2 (6), 392-402.

Santorelli, S., & Kabat-Zinn, J. (2002). Mindfulness-based stress reduction professional training: MBSR curricu-lum guide and supporting materials. Worcester: Uni-versity of Massachusetts Medical School.

Thomas, S. P. (2000). A phenomenological study of chron-ic pain. Western Journal of Nursing Research, 22 (6), 683-705.

Douglas Ozier, (M.A., RCC) is a fifth year PhD student in Counselling Psychology at the University of Alberta in Edmonton, AB. He received his Masters in Counselling Psych from the University of British Co-lumbia in 2005. He has long standing inter-ests in psychotherapy process research, the practice of experientially oriented psycho-therapy, and in integrating cognitive neuro-science into the practice of talk therapy. He currently works at the BC Cancer Agency in Vancouver, B.C., supporting individuals diagnosed with malignant brain tumours and their families. He can be reached at [email protected].

ErrataIn the Summer 2010 issue, we featured an article by Kirtley Thornton, PhD entitled The Coordinated Allocation of Resource (CAR) Model Intervention for Reading Problems in Two Clinics in which we in-advertenty did not list the second author. Please note that Christopher Carroll, PhD co-authored this papaer.

Dr. Christopher Carroll is a licensed Psychologist and Special Educator. He is an assistant professor in the School Coun-

seling Program at the New York Institute of Technology. During his career, he has also been a full-time faculty member at Adelphi University and Farmingdale State College. In addition to his full-time faculty appoint-ments, he has served as an adjunct faculty member at Fordham University, the CW Post campus of Long Island University, Molloy College, and Bank Street College of Education. He has taught more than 20 different courses in psychology, counsel-ing, and education at the undergraduate and graduate levels.

Dr. Carroll also maintains a private practice with offices in East Norwich and Glen Cove, NY. In his private practice, he combines his background in clinical and counseling psychology, career develop-ment, special education, and biofeedback to provide specialized services for individ-uals with Learning Disabilities, Attention Deficit Hyperactivity Disorder, and Autis-tic Spectrum Disorders and their families. His practice addresses these issues across the life span, from early childhood through adulthood.

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DearColleagues,

The senior ediTors of The Journal of neuroTherapy: invesTigaTions in neuromodulaTion, neuroTherapy and applied neuroscience hope ThaT you have noTiced and enJoyed The increased conTenT of The Journal. We Would like To remind all our friends ThaT We are diligenTly Working To geT The Journal medline-indexed. in order To accomplish This goal We need more submissions, especially of high level research. if you or any of your colleagues are Thinking abouT publishing your research We Would encourage you To submiT To The Journal.

To make a submission please go here: hTTp://WWW.isnr.org/auThors.cfm To learn more abouT The Journal, please look here: hTTp://WWW.isnr.org/JnTmasThead.cfm

more informaTion? [email protected]

randall lyle, phd and marTiJn arns, msc

Today we are riding the crest of a wave of converging new neuroscience knowledge that includes EEG Neuroimaging Biofeed-back (Thatcher, 2000; Congedo et al, 2004; Cannon et al, 2005; 2006; 2007; 2009). In the physics of source localization the for-ward solution is where a source inside a sphere determines the electrical potential on the surface as calculated using Maxwell’s 1864 equations. In contrast, the inverse problem is where the sources are unknown and the location of the sources are estimated by measuring the electrical potential on the surface (Malmivuo and Plonsey, 1995). To solve the inverse equation one must apply physiological constraints such as used in cardiology in the early 1900s and quantita-tive EEG (QEEG) in the 1980s (Malmivuo and Plonsey, 1995). Low Resolution Elec-tromagnetic Tomography (LORETA) uses

physiological constraints related to the hu-man electroencephalogram (EEG) includ-ing the use of distributed source smooth-ing (Pascual-Marqui et al, 1994). LORETA uses a 3D Laplacian spatial operator as a source smoothing constraint where simul-taneously active sources distributed in space are used to solve the inverse equa-tion. Importantly, the LORETA solution to the inverse problem was also linked to the standard co-registration used in all neuro-imaging modalities including PET, SPEC and fMRI. The linkage to 7 mm cube elec-trical source volumes co-registered to the standard normative MRI allows for real-time millisecond biofeedback of electrical sources with a similar spatial resolution as fMRI and sufficient for larger volumes such as Brodmann areas that range from 1 to 6 square centimeters (Brodmann, 1909).

High-speed computers are essential because the brain is organized in clusters of neurons called Modules and Hubs where groups of neurons are cross-frequency phase locked in re-enterant loops of bursting action po-tentials conducted by cortical white matter and temporally coordinated by the thala-mus and brainstem-limbic systems (Steri-ade, 2006; Vinogradova, 2001; Thatcher et al, 2008; Sauseng and Klimesch, 2008;

LORETAZScoreBiofeedbackRobert W. Thatcher, PhD

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Buzsaki, 2006). These important brain dy-namics are too fast for fMRI to measure directly.

This is important because structure and function are linked in biology and functional localization in the brain e.g., visual cortex and blindness, deafness and temporal lobe damage, etc, when linked to the patient’s symptoms aids in rendering a diagnosis and treatment for him or her. An advantage of LORETA EEG biofeedback is that one can target anatomical regions re-lated to “loss of function” or “weak” func-tion related to the patient’s symptoms and complaints (Luria, 1973). This approach has been followed in both LORETA EEG biofeedback (Cannon et al, 2005; 2006) and with fMRI (de Charms, 2008).

fMRI biofeedback involves operant conditioning of groups of neurons where increased action potential bursting is re-lated to dilation of the blood vessels and increased blood flow seconds after the neu-rons were active. In contrast, LORETA EEG has a sub millisecond time resolution with similar spatial resolution as fMRI (Pascual-Marqui, 1999). In addition to a higher time resolution, there are economic advantages of LORETA biofeedback vs. fMRI biofeed-back. For example, an fMRI 3T magnet costs about $3,000,000 with a $40,000 per month liquid helium bill vs < $20,000 for portable LORETA EEG biofeedback with no monthly maintenance costs.

Fig. 1- General structure-function linkages to Brodmann areas (Brodmann, 1909).

Fig. 2 – Example of deviant LORETA Z scores in a right hemisphere damaged patient. The patient’s symptoms included spatial neglect (from Thatcher et al, 2005).

LORETANormativeDatabaseandLORETAZScores

A Z score is a statistical measure of the dis-tance an individual is from a reference nor-mal population. The clinical value of EEG Z scores is similar to the clinical value of a blood test, e.g., if a patient is lethargic and jaundice and liver enzymes are 3 standard

deviations outside of normal then this helps a clinician link the patient’s symptoms to a possible physiological dysfunction. An advantage of real time Z score LORETA biofeedback is instantaneous feedback of age-matched comparisons to a refer-ence database of healthy individuals (Z scores) by which instantaneous deviations in Brodmann areas are linked to a patient’s symptoms and complaints. For example, LORETA raw current source density values for each of the 2,394 gray matter voxels was computed for the 678 individuals in the University of Maryland EEG normative database in the eyes open and eyes closed conditions. Means and standard devia-tions for groups of subjects separated by 6 months were computed from subjects at 2 months of age to 82 years of age (Thatcher, 2000; Thatcher et al, 2003; 2005). Figure 2 shows an example of significantly deviant LORETA Z scores in a patient with right parietal epidural hematoma linked to the patient’s symptoms of spatial neglect. SymptomCheckListandLORETAZScoreBiofeedback

Because of computational demands a reduc-tion is necessary in the total possible compu-tations at each instant of time. A reasonable method is to reduce the number of measures by the use of the scientific literature linking symptoms to functional specialization in the brain based on the fMRI, SPECT, PET

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LORETAZScorecontinuedfrompage1�

and EEG/MEG literature. For example, le-sions of the occipital cortex (Brodmann areas 17-19) produces blindness, lesions of the temporal lobes (Brodmann areas 20, 21, 38) effect auditory perception, lesions of the hippocampus effect memory (Brodmann area 30), lesions of the left frontal lobe ef-fect speech articulation (Brodmann areas 10, 45, 46), etc. Thus, the total number of EEG measures involved in real-time Z score bio-feedback can be reduced by forming apriori hypotheses based on the existing scientific literature. For example, a patient with a his-tory of dyslexia is expected to exhibit devia-tions in the left parietal lobe based on cyto-logical, MRI, fMRI and EEG/MEG stud-ies. Or a patient with auditory sequencing problems produces the apriori hypothesis of temporal lobe dysfunction, or short-term memory problems with hippocampal, tem-poral or frontal dysfunction, etc.

Thus, planned comparison statistics can be used to individualize LORETA Z score biofeedback of the brain regions (i.e., Brodmann areas) that are hypothesized to be related to the patient’s symptoms and complaints prior to training. The LORETA Z scores in the locations of the brain pre-dicted by the symptom checklist are labeled as ‘Matches’ of the weak systems and the “Mismatches” are more likely related to

compensatory systems. The idea is to iden-tify the most likely brain regions linked to the patient’s symptoms vs the least likely brain regions as an initial step toward re-storing homeostatic balance within the “weak” nodes and modules of the networks of the brain. The goal is to reinforce move-ments of consistently deviant brain systems linked to the patient’s symptoms toward Z

= 0, i.e., reinforce trends that shape behav-ior as in operant conditioning. Z = 0 is an abstract ideal and is never actually attained for all measures but operates like a set-point around which variations occur. The grand average of healthy normal subjects is a ho-meostatic average at each moment of time that serves as a reference to help identify high standard deviations in localized brain regions linked to the patient’s symptoms.

Another advantage of LORETA Z score biofeedback is the issue of co-mor-bidities that are often present in patients, for example, attention deficit disorder and anxiety. The advantage of linking symptoms to functional specialization in the brain pro-duces hypotheses with common brain re-gions involved in both an attention disorder and anxiety. For example, attention is medi-ated by the hippocampus for the creation of memories; the insula and anterior cingulate for attention shift and the bilateral frontal lobes for executive control. Failure of this system may in part be due to insular cortex deregulation which is also involved in anxi-ety disorders and/or obsessive compulsive disorders. Depression is another disorder that involves the anterior cingulate gyrus and the frontal lobes (Pizzagalli et al, 2002), etc. Thus, a symptom check list linked to neuroanatomy thereby provides deep and underlying hypotheses that can be used for purposes of biofeedback using the QEEG in the same manner as fMRI biofeedback but at a fraction of the cost.

Fig. 3- Example of Symptom Check List to create anatomical hypotheses linked to the patient’s symptoms and complaints. The match category is hypothesized as the “weak systems” and the mismatch category are hypothesized to be “compensatory” networks. From NeuroGuide 2.6.4

Fig. 4 – Example of LORETA Z Score Biofeedback Progress Chart. The top left are the percent of time that threshold has been met, bottom left are the average Z scores from different Brodmann areas. The right column are real-time Z scores from Brodmann areas selected by the symptom check list. From NeuroGuide 2.6.4

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References:

Brodmann, V.K., (1909). “Localization in the Cerebral Cortex: The Principles of Comparative Localization in the Cerebral Cortex Based on Cytoarchitectonics,” Translated by L. J. Garey, Springer, London, 1994.

Buzsaki, G. (2006). Rhythms of the Brain, Oxford Univ. Press, New York.

Cannon, R., Lubar, J., Thornton, K., Wilson, S., & Con-gedo, M. (2005) Limbic beta activation and LORETA: Can hippocampal and related limbic activity be re-corded and changes visualized using LORETA in an affective memory condition? Journal of Neurotherapy, 8 (4), 5-24.

Cannon, R., Lubar, J., Gerke, A., Thornton, K., Hutchens, T and McCammon, V. (2006). EEG Spectral-Power and Coherence: LORETA Neurofeedback Training in the Anterior Cingulate Gyrus. Journal of Neurotherapy, 10(1): 5 – 31.

Cannon, R., Lubar, J., Sokhadze, E. and Baldwin, D. (2008). LORETA Neurofeedback for Addiction and the Possible Neurophysiology of Psychological Processes Influenced:

A Case Study and Region of Interest Analysis of LORETA Neurofeedback in Right Anterior Cingulate Cortex. Journal of Neurotherapy, 12 (4), 227 - 241.

Cannon, R., Congedo, M., Lubar, J., and Hutchens, T. (2009). Differentiating a network of executive atten-tion: LORETA neurofeedback in anterior cingulate and dorsolateral prefrontal cortices. International Journal of Neuroscience. 119(3):404-441.

Congedo, M., Lubar, J., & Joffe, D. (2004). Low-resolu-tion electromagnetic tomography neurofeedback. IEEE Transactions on Neuronal Systems and Rehabilitation

Engineering, 12, 387–397.

deCharms, R.C. (2008). Applications of real-time fMRI. National Review of Neuroscience, 9(9): 720-729.

Luria, A.R., (1973). The Working Brain: An Introduction to Neuropsychology. The Penguin Press, Middlesex, England.

Malmivuo, J. and Plonsey, R. (1995). Bioelectromagne-tism: Principles and applications of bioelectric and bio-magnetic fields. Oxford Univ. Press, New York.

Michel, C.M., Koenig, T., Brandeis, D., Gianotti, L.R. and Waxkerman, J. (2009). Electrical Neuroimaging. Cam-bridge Univ. Press, New York.

Pascual-Marqui, RD. (1999) Review of Methods for Solv-ing the EEG Inverse Problem. International Journal of Bioelectromagnetism, 1:75-86.

Pascual-Marqui RD, Michel CM, Lehmann D., (1994). Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. International Journal of Psychophysiology 18:49-65.

Pizzagalli, D.A., Nitschke, J.B.,Oakes, T.R.,Hendrick, A.M., Horras, K.A.,Larson, C.L., Abercrombie, H.C.,Schaefer, S.M., Koger, J.V., Benca, R.M., Pas-cual-Marqui, R.D. and Davidson, R.J. (2002). Brain electrical tomography in depression: The importance of symptom severity, anxiety, and melancholic features. Biological Psychiatry, 2002. 52(2): p. 73-85.

Sauseng P and Klimesch W. (2008). What does phase in-formation of oscillatory brain activity tell us about cog-nitive processes? Neuroscience Biobehavioral Review, 32(5):1001-1013.

Steriade, M. (2006). Grouping of brain rhythms in cortico-thalamic systems. Neuroscience, 137: 1087-1106.

Thatcher, R.W. (2000). 3-Dimensional EEG Biofeedback using LORETA. Proceedings of the Society for Neuro-nal Regulation, Minneapolis, MN, September 23.

Thatcher, R.W., Walker, R.A., Biver, C., North, D., Cur-tin, R., (2003). Quantitative EEG Normative databases: Validation and Clinical Correlation, Journal of Neuro-therapy, 7 (No. ¾): 87 – 122.

Thatcher, R.W., North, D., and Biver, C. (2005). Evalua-tion and Validity of a LORETA normative EEG data-base. Clin. EEG and Neuroscience, 36(2): 116-122.

Thatcher, R.W., Biver, C. J., and North, D. (2007) Spatial-Temporal Current Source

Correlations and Cortical Connectivity, Clin. EEG and Neuroscience, 38(1): 35 – 48.

Thatcher, R.W., Biver, C. J., and North, D. (2007). Intel-ligence and EEG current density using Low Resolution Electromagnetic Tomography. Human Brain Mapping, 28(2): 118 – 133.

Thatcher, R.W., North, D., and Biver, C. (2008). Intel-ligence and EEG phase reset: A two-compartmental model of phase shift and lock, NeuroImage, 42(4): 1639-1653.

Vinogradova, O.S. (2001). Hippocampus as Comparator: Role of the Two Input and Two Output Systems of the Hippocampus in Selection and Registration of Informa-tion. Hippocampus, 11:578–598.

Robert W. Thatcher, PhD Applied Neuroscience Research Institute 7985 113th St., Suite 210 St. Petersburg, Fl 33772

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Abstract

New protocols have been developed that provide additional flexibility for the clini-cian using the Low Energy Neurofeedback System. Protocols now allow the clinician greater flexibility in individualizing treat-ment with the capacity to focus even more specifically on problematic brainwave frequencies. Other clinical innovations in-clude the capacity for two channel training, and the use of sequential training with one or two channels. Introduction

The Low Energy Neurofeedback System (LENS) (Hammond, 2007b; Larsen, 2006; Ochs, 2006) is a unique and passive form of neurofeedback producing effects through feedback that involve a very tiny electro-magnetic field with a field strength of 10-18 watts/cm2. This feedback is only 1/400th the strength of the input we receive from sim-ply holding a regular cell phone (i-Phones are much more powerful) to the ear. The feedback is delivered in one second inter-vals through the electrode wires while the patient remains as quiet as possible, usually with eyes closed. However, with extremely young children, individuals with autism or pervasive developmental disabilities, or at the clinician’s discretion, training can be done eyes open. The feedback is adjusted 16/second to remain a certain number of cycles per second (e.g., 2, 5, 10, 20) faster than the dominant EEG frequency. The LENSfeed-back is generated through an equation that determines the dominant frequency in the EEG and then adds an “offset” number. The offset is determined by the user and is usu-ally anywhere from 2-30 Hz. For instance, if the dominant frequency is 10 Hz and the offset is 2 Hz, then the feedback given to the person will be 12 Hz.

Preliminary research and clinical experience have found that LENS rivals

and in some cases may surpass more tra-ditional forms of neurofeedback in the treatment of conditions such as traumatic brain injury (Hammond 2007b; Hammond 2010; Schoenberger, Shiflett, Esdy, Ochs, & Matheis, 2001), fibromyalgia (Donald-son, Sella, & Mueller, 1998; Mueller, Don-aldson, Nelson, & Layman, 2001), ADD/ADHD, anxiety, depression, insomnia, and other conditions (Larsen, 2006; Larsen, Harrington, & Hicks, 2006). LENS has even been used to modify behavioral problems in animals (Larsen, Larsen, Hammond, Shep-pard, Ochs, Johnson, et al 2006).

In the past 5 years there have been significant refinements in LENS treat-ment protocols. This paper will introduce the reader to these advancements and their clinical applications.

ProtocolsFocusedonSpecificFrequencyBands

Dr. Nicholas Dogris created several special-ty LENS protocols that have been integrat-ed into the LENS system. The first group of these protocols, field tested by Nick and Cory with more than 70 patients, focused the feedback on specific EEG frequencies. These protocols focus the feedback on spe-cific frequency ranges. Thus instead of the feedback occurring in relation to the domi-nant frequency (e.g., between 1 and 42 cy-cles/second), the feedback is more focused on a specific frequency range. For instance, protocols have been created that variously concentrate on ranges 1-4 Hz, 1-8 Hz, 4-9 Hz, 7-12 Hz, 9-12 Hz, and 13-18 Hz. When excess EEG amplitude is found across a wide range of frequencies, or the patient seems more resistant to change, there are also two protocols that will successively give feedback based on multiple frequency bands. One of these protocols gives one second of feedback based on the dominant frequency in hertz ranges 1-4, 4-8, 9-12,

13-18, and a different program gives feed-back in ranges 1-4, 4-8, 9-12, 13-18, 19-25, 26-33, and 34-40 Hz, thus concentrating on a wider spectrum. There are even protocols that focus on single hertz frequencies from 1 to 8 Hz. for use when a patient particu-larly seems stuck on a plateau in treatment progress, and which can be selected from QEEG data.

When a QEEG assessment or ob-servation of moment-to-moment spectral frequency displays indicate to the clinician that the patient’s EEG activity is predomi-nantly in one of these ranges, LENS train-ing may be more individualized and spe-cifically focused on problem frequencies. An additional advantage is that in working with patients with chronic EMG activity and with children (e.g., with autism) where EMG and movement artifact is common, the artifact will not throw off the dominant frequency, and hence the feedback.

Case Illustration. A severely au-tistic 7 year old boy had been seen for 12 sessions of LENS training. He was show-ing mild progress, but due to EMG artifact the dominant frequency of his EEG on which feedback is given was often being distorted to much faster frequencies. After his very first session with a protocol fo-cused on the 1-8 Hz range he became sig-nificantly more verbal than his parents had ever observed, and his progress improved much more rapidly.

ProtocolsProvidingMultipleSecondsofFeedbackatVaryingOffsetFrequencies

The standard LENS program provides 1 second of feedback at different electrode sites, although more seconds can be provid-ed manually. Nick also created programs that provide 3 seconds of feedback (at off-


AdvancementsinLENSTreatmentProtocolsD. Corydon Hammond, PhD, Sara Hunt Harper, PhD, Jill O’Brien, DOM, & Nicholas Dogris, PhD

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set frequencies of 2, 4, and 6 cycles per second faster than the dominant EEG frequency of the patient). Additional feedback may be provided manually. TwoChannelLENSProtocols

Protocols have also been developed that allow two channel LENS training focused on different frequencies discussed above, with multiple seconds of feedback with different offset frequencies. We have used these proto-cols based on information obtained in QEEG evaluations and from clinical wisdom.LENSSequentialMontageTraining

By way of introduction, all neurofeedback uses an active electrode and a reference electrode. Standard LENS training uses what is called mono-polar or referential training, which means that the active electrode is on the head and a reference electrode is on an earlobe. In neurofeedback there is another way of working which is called bipolar (or sequential) training where both the active and reference electrodes are on the scalp. Sara Hunt Harper, Cory Hammond and Nicholas Dogris trained with one of the pioneers in tradi-tional neurofeedback, Margaret Ayers, who emphasized sequential/bipolar training. The early work of Barry Sterman was done with sequential/bipolar training, and the Lubars have done more work with sequential/bipolar train-ing than with referential or monopolar training.

LENS provides its feedback down all the electrode wires (active, reference, and ground). Sara decided to experiment with using sequential placement with LENS, and soon Jill and Cory began doing this as well. Re-sults seemed encouraging. We then enlisted Nick Dogris to provide us with 2 channel programs providing 3 seconds of feedback (at offsets of 2, 4,nd 6) for a dominant frequency of 1-8 Hz, 9-12 Hz, and 7-12

Hz. Our preliminary results were presented at the May 2010 LENS Conference and will be summarized below.WhatisSequential/BipolarTraining:AFurtherDescription

A bipolar or sequential electrode placement means that both the active and the reference electrodes are placed on the scalp. For example, instead of an electrode at Cz and a reference on an ear, you may have an electrode at Cz and the reference at Pz, with only a ground electrode on the ear. EEG measurements are always of the mathematical difference between the active andreference electrodes, irrespective of whether the reference electrode is on the ear lobe or on the head. AdvantagesofSequentialPlacementTraining

There are several advantages of training with a sequential/bipolar placement (Lubar, 2001; Putnam, 2001).1. Due to common mode rejection of noise (which means that activity

which is common or synchronous between the two sites is not seen in the output), artifacts are commonly in phase, such as EMG activity, body and eye movement, and are therefore not as influential.

2. Use of a sequential placement for training works the brain harder and allows the brain much more flexibility in how to change. With mono-polar training the brain is primarily challenged to change simply in close proximity to the electrode site. With sequential training the change can take place at the site of the active electrode, the reference electrode, or anywhere in between. Lubar (2001) provided an illustration with ADD/ADHD where there was excess theta and a deficit in beta activity: “For example, if the theta activity at the two measured locations FCZ and CPZ becomes more in phase [as a results of sequential training], the re-sultant activity will be a decrease in the microvolt levels of theta. If the

AdvancementsinLENScontinuedfrompage1�

Niels Birbaumer with his Career Achievement award. Since he wasn’t able to attend this year’s conference, Sarah Wyckoff accepted the honor for him and brought it back to Germany.

21


beta activity moves out of phase, there will be a resultant increase in the micro-volt levels of beta. As a result, bipolar or sequential training has the advantage in that there are many more options for learning such as changing the activity at any one of the electrode sites, anywhere in between them, or changing the phase relationships between the two electrode sites. In contrast, with referential train-ing there is only one way to learn and that is to change the parameters being trained at the electrode site. For this reason training over any locations with-in a hemisphere, whether it is on the midline or more lateral, will work and perhaps even better with bipolar than with referential configurations” (p. 96).

In addition, work between two dis-tant cortical sites “encourages the brain to have a conversation with itself” (Putnam, 2001, p. 53) and involves more mediation by subcortical thalamic centers of the brain. Sequential/bipolar training appears more likely to influence shifts in phase and in coherence, and one writer (Putnam, 2001) suggested that sequential neurofeedback training “may actually be coherence train-ing in disguise” (p. 53).

The two-compartment model of co-herence (Thatcher et al., 1986) indicates that there are short distance (meaning a few millimeters to a few centimeters) and long distance (meaning several centime-ters apart) connections for communicating within the brain. Longer distance connec-tions require reciprocal feedback loops to convey their signal, while short distance connections simply recruit localized neu-ronal ensembles close to the electrode site. In practical terms what this means is that sequential training is more likely to require involvement of the deeper subcortical tha-lamic regulatory processes to orchestrate the changes. Thus we believe that sequen-tial placement training influences and chal-lenges more of the brain than working at single sites, and at the same time it allows the brain greater flexibility in using more than just one way to facilitate change. Thus it is possible that sequential train-ing, whether with LENS or with traditional neurofeedback may be more beneficial in working with more resistant conditions. The authors further believe, as we will now explain, that 2 channels of sequential/bipo-lar training may have the potential to facili-tate even greater or more rapid changes.

LENSSequentialTrainingMayInvolveOneorTwoChannelBipolarTraining.

We have experimented with single channel LENS sequential training, and with 2 chan-nel LENS sequential training. Both seem to have potential, but we are particularly im-pressed with the potential of working with 2 channel sequential training.

An example of 1 channel LENS se-quential training would be to have electrodes

at Fz-Cz. This training could then use any of the LENS programs: (e.g., regular feed-back, or feedback focused on the dominant frequency in any of the frequency bands, or other protocols discussed above). An exam-ple of 2 channel LENS sequential training would be having a ground on each ear and electrodes at T3-Fp1 and T4-FP2, or at T3-C3 and T4-C4. Once again, any of the LENS 2 channel feedback programs may be used. Figure 1 illustrates this set-up.


Figure 2: Example of Results from the LENS 2 Channel Sequential Delta/Theta Protocol

Figure 1: Illustration of LENS 2 Channel Sequential Training Protocol for Depression

22


The top row of Figure 2 displays the baseline EEG at T3-C3 and T4-C4 in a chronic 17 year old migraine patient for whom medication treatments were ineffec-tive. The second row displays changes fol-lowing the patient receiving 21 seconds of feedback at all 4 electrode sites with the 2 channel 1-8 Hz protocol (where feedback is given at 2, 4, and 6 Hz offset from the dom-inant EEG frequency in the 1-8 Hz range). The bottom row displays the raw EEG fol-lowing 5 runs of the protocol, one right af-ter the other. This means that 21 seconds of feedback was being provided in each round at the 4 electrode sites, totaling 105 seconds of feedback for all 4 electrode sites.:

In the top row of Figure 3 you see the pre-treatment baseline EEG of a 14-year-old chronic headache patient who had dropped out of school due to the severity of symp-toms. Medication treatment had proven un-successful. The second row shows the raw EEG following 21 seconds of feedback at T3-C3 and T4-C4 using the LENS 2 chan-nel sequential 1-8 Hz training with multiple offsets. The last row displays the baseline EEG after two sessions of treatment (prior to administering the third treatment).

As we have mentioned, LENS se-quential training may also be done with a single channel. Figure 4 displays results where a LENS protocol focused on a domi-nant frequency of 1-9 Hz was used at P3-

P4 with a teenager who showed excessive 1-9 Hz activity on a QEEG which was most excessive in the parietal area. One minute of baseline EEG was measured with Neu-ropathways EEG equipment with elec-trodes placed just slightly outside the LENS electrodes. The EEG was then monitored during 91 seconds of LENS sequential 1-9 Hz training, and for 1 minute following the conclusion of LENS feedback.

The Law of Parsimony suggests that one should use the simplest and least com-plex method to get the job done. There-fore, we begin LENS training with the traditional method of evaluating the patient and doing a LENS map, followed by do-ing standard LENS treatment following the site sort. This allows us to determine hardiness, sensitivity and reactivity, and to judge patient progress. When patients are progressing adequately, there is no reason to consider other alternatives, whether they be sub-specialty LENS programs that focus on specific frequency bands, LENS sequen-tial training, or traditional neurofeedback modalities.

An indication for considering LENS sequential placement training is when the patient is not progressing as well as would be anticipated with traditional LENS pro-cedures. We also anticipate that sequential training will be more likely to be used with patients who are more chronic, complex, and multi-symptomatic. We particularly believe that the LENS 2 channel sequential applications should only be used with pa-

tients who have been determined to be har-dy and who are able to tolerate a significant amount of feedback. Some of us have each actually run 2 channel sequential training sessions where patients were given 147 seconds of feedback in a session (which is being received simultaneously at 4 scalp electrodes) with positive results.

Tentative contraindications would be a highly reactive patient, and also a patient where a sequential placement results in the EEG amplitude being extremely small (due to phase cancellation). When activity is too similar at both electrode sites, amplitudes will sometimes be very small. In these cas-es it is anticipated that regular, monopolar LENS training is more likely to produce results– a basic rationale recommended by Lubar (2001), who also believed that se-quential training “across the hemispheres is very difficult and probably counterpro-ductive” (p. 96) because homologous sites tend to be in phase. We also emphasize that strong programs (e.g., those giving feed-back based on the dominant frequency in several different frequency bands, one after another) should be used quite cautiously. With more reactive patients, single channel sequential LENS training may also be used rather than 2 channel training.ChallengeswithLENSSequentialPlacementTraining

There are two challenges with LENS se-quential training. First, when we do 2 chan-nel sequential training the LENS Report Generator cannot process this data, so the data is discarded. However, we have been assured that shortly we will be able to pro-cess this data. Thus temporarily if one is to evaluate changes in the EEG it is necessary to periodically re-do a LENS map (which gathers amplitude and variability data se-

AdvancementsinLENScontinuedfrompage21

Figure 3: Results in Chronic Headache

Figure 4: Indications & Contraindications for LENS Sequential Training


2�

quential at all 19 standard electrode sites). However, clinicians may take a screen shot of the baseline 2 channel sequential raw EEG, and then another screen shot of the raw EEG post-treatment. This provides feedback on immediate results.

A related challenge with LENS se-quential training is how do we select the electrode sites at which to work? We have been using several options for site selection:1. For practitioners who do quantitative

EEG (QEEG) assessments this informa-tion can guide where to focus. Thus, based on QEEG findings, Cory has done two channel sequential training with placements such as at T5-O1 and T6-O2 (with reading problems), and in other cases at F7-T5 and F8-T6, T5-P3 and T6-P4, O1-P3 and O2-P4, and F3-P3 and F4-P4.

2. It is important for practitioners to real-ize that an electrode site communicates the most with its homologous (identi-cal) site in the other hemisphere. This is the basis behind a discovery that was made by Margaret Ayers (who probably had more actual clinical experience than anyone in the field of neurofeed-back). She found that if you wanted to facilitate change in an area in one hemisphere (e.g., after stroke damage in that area), you could train for the first half of the session at the homologous sites in the other hemisphere before switching electrodes to work in the area of damage. Therefore, in LENS sequen-tial training you can select two parallel (homologous) areas to train in each hemisphere. For example, with a client presenting with a reading problem one

may train at T5-O1 and T6-O2, or at F7-T5 and F8-T6. With problems asso-ciated with general cognitive function, epilepsy, or problems associated with the sensorimotor strip, one could train at T3-C3 and T4-C4, (or in the expand-ed 10-20 system, at C3-C1 and C6-C2). Jill and Sara began experimenting with treating depression problems using T3-Fp1 and T4-Fp2, which has resulted in very impressive improvements. Cory has also found this clearly helpful with emotional control issues as well as de-pression and anxiety.

3. Relatedly, as has just been implied, the practitioner can use knowledge about the functional significance of areas of the brain that are correlated with patient problems as the basis for site selection.

Thus Cory has used the placement be-low O1-O2 (just barely above the inion ridge) to work with balance problems (Hammond, 2005). With difficult epi-lepsy cases, one may not only work at T3-C3 and T4-C4, but also later work at T3-F3 and T4-F4. Neurologist and epileptologist John Hughes (1999) de-scribed a mirror phenomenon that Mar-garet Ayers also found in her work with epilepsy. They discovered that if one only worked over the area of a seizure focus in one hemisphere, sometimes the seizure focus would shift to the homol-ogous area in the other hemisphere.

Summary

The new LENS protocols and clinical in-novations provide advancements that allow more specific targeting of problem frequen-

cies, control for undesirable EMG or move-ment artifact, and that may produce greater involvement of subcortical areas of the brain in facilitating change. Clinical experi-ences suggest that these methods may pro-duce more effective or rapid change.

References

Donaldson, C. C. S., Sella, G. E., & Mueller, H. H. (1998). Fibromyalgia: A retrospective study of 252 consecutive referrals. Canadian Journal of Clinical Medicine, 5 (6), 116-127.

Hammond, D. C. (2005). Neurofeedback to improve physi-cal balance, incontinence, and swallowing. Journal of Neurotherapy, 9(1), 27-36.

Hammond, D. C. (2007a). Can LENS neurofeedback treat anosmia resulting from a head injury? Journal of Neu-rotherapy, 11(1), 57-62.

Hammond, D. C. (2007b). LENS: The Low Energy Neuro-feedback System. New York: Haworth Press.

Hammond, D. C. (2010). QEEG evaluation of LENS treat-ment of TBI. Journal of Neurotherapy, 14, 170-177.

Hughes, J. R. (1999). EEG in Clinical Practice (3rd Edi-tion). Boston: Butterworth-Heinemann.

Larsen, S., (2006). The Healing Power of Neurofeedback: The Revolutionary LENS Technique for Restoring Optimal Brain Function. Rochester, Vt.: Healing Arts Press.

Larsen, S., Harrington, K., & Hicks, S. (2006). The LENS (Low Energy Neurofeedback System): A clinical out-comes study of one hundred patients at Stone Mountain Center, New York. Journal of Neurotherapy, 10(2-3), 69-78.

Larsen, S., Larsen, R., Hammond, D. C., Sheppard, S., Ochs, L., Johnson, S., Adinaro, C., & Chapman, C. (2006). The LENS neurofeedback with animals. Jour-nal of Neurotherapy, 10(2-3), 89-101.

Lubar, J. F. (2001). Rationale for choosing bipolar versus referential training. Journal of Neurotherapy, 4(3), 94-97.

Mueller, H. H., Donaldson, C. C. S., Nelson, D. V., & Lay-man, M. (2001). Treatment of fibromyalgia incorporat-ing EEG-driven stimulation: A clinical outcomes study. Journal of Clinical Psychology, 57(7), 933-952.

Ochs, L. (2006). The Low Energy Neurofeedback System (LENS): Theory, background, and inroduction. Journal of Neurotherapy, 10(2-3), 5-39.

Ochs, L. (2010). Personal communication, February 13, 2010.

Putnam, J. A. (2001). Technical issues involving bipolar EEG training protocols. Journal of Neurotherapy, 5(3), 51-58.

Schoenberger, N. E., Shiflett, S. C., Esty, M. L., Ochs, L., & Matheis, R. J. (2001). Flexyx neurotherapy system in the treatment of traumatic brain injury: An initial evaluation. Journal of Head Trauma Rehabilitation, 16(3), 260-274.

Thatcher, R. W., Krause, P., Hrybyk, M. (1986). Cortico-cortical associations and EEG

coherence: a two compartment model. Electroencephalog-raphy & Clinical Neurophysiology, 64, 123-143.

ThenewLENSprotocolsandclinical

innovationsprovideadvancementsthat

allowmorespecifictargetingofproblem

frequencies,controlforundesirableEMG

ormovementartifact,andthatmayproduce

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EffectsofMedicationontheQEEGFriday,October1

Leader: Dr. Cory Hammond 29 attendees

• Alcohol increases alpha in fronto-temporal regions.

• Anxiolytic medications increase beta especially frontally at 25-35 Hz, but also down to 15 Hz and there may be some decrease in alpha.

• Tricyclic antidepressants slow alpha mean frequency and increase alpha coherence and may decrease beta.

• SSRIs decrease alpha and increase beta.

• Imipramine may increase theta, delta and fast beta while decreasing alpha and alpha mean frequency.

• Trazadone may increase beta and theta (and interfere with deep delta restorative sleep).

• Opiates slow alpha and in some cases increase beat. Coffee reduces power in alpha and slow beta and has a withdrawal syndrome.

• Nicotine increases beta and alpha and decreases delta and theta (but perhaps not in posterior temporal ar-eas).

• Prednisone small increase in theta absolute power, Neurontin slows al-pha mean frequency and decreases aloha and increases theta, beta and delta.

• Allergy medications and antihista-mines increase beta and total power.

• Stimulants may increase beta and re-duce theta and should be discontin-ued 2 days before the QEEG.

• Cocaine initially increases alpha, beta and theta with increased dose alpha is inhibited and beta increased. With cumulative cocaine use, there

is increased theta mean frequency, decreased alpha mean frequency, decreased delta coherence and beta asymmetry. There is also progressive slowing of the EEG.

• XTC decreases frontal delta, theta throughout the head and frontal and posterior alpha while increasing beta in frontal and temporal areas. PCP increases slow and paroximal activ-ity.

• Marijuana increases alpha power, slows alpha mean frequency and in-creases interhemispheric coherence especially in frontal and central ar-eas. Chronic pot use daily after 15 years increases theta power and theta interhemispheric coherence.

NFTandPTSD:RationaleandOutcomesThursday,September�0

Leader: Dr. John Carmichael

• The nature of PTSD• The relevance of clinical concerns• What technology is available.

NFTandTBI:RationaleandOutcomesFriday,October1

Leader: Dr. Anne Stevens Note Taker: Eileen McDonald 11 attendees

Anne began by discussing events revisited and TBI and how she incorporated NFB into her clinical practice. The use of neuro-psych assessment to understand contribut-ed pathology was considered. Anne utilizes QEEG and connectivity data to make clini-cal decisions regarding NFB protocols.

Conversation then dovetailed into a discussion regarding the difficulties in do-ing research in this area of TBI and NFB. The difficulty with reducing the heteroge-neous patient population and the heteroge-neous injuries was considered. Designing

well-constructed research was also dis-cussed. The conversation then moved to treatment of actual military personnel and veterans who have sustained a TBI. Multi-factorial symptoms were described and the difficulty of making return to duty deci-sions was also examined.

NeurofeedbackTherapyandLD:PatternsandOutcomesThursday,September�0

Leader: Phillip Ellis 30 attendees

Many conference attendees were turned away for lack of space.

There was a brief discussion about definitions of LDs, dyslexia and methods of assessment. Discussion initially went to the wide range of methods that have used in this industry to treat/train learning dis-orders, learning disabilities and included power/amplitude neurofeedback with uni-polar and bipolar sites, Photo-Stim with NBF, slow cortical training, LENS and HRV Biofeedback. Then it went on to QEEG as-sessments and task-driven and activation methods using coherence training. We dis-cussed at some length the works of Kirtley Thornton, Jonathan Walker, Rob Coben and the contributions of their work utiliz-ing QEEG assessments of coherence. We noted the variation in methods being used to train coherence and how it varies among researchers and treatment centers. We then digressed to discuss the contributions of low frequency training (Othmer) and the belief by several in the group who have tried it with success. There seemed to be a wide range of methods being used with success and some frustration that it was difficult to find good compare and contrast studies of these meth-ods. The general consensus I polled after the discussion was that this kind of forum is helpful and should continue to be offered. Many who tried to attend were turned away for lack of seating.

SmallGroupDiscussionsISNR1�thAnnualConferenceNearDenver,Colorado

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One of our members felt that Dr. Othmer’s comment as recorded in the minutes from the members’ meeting in Denver was inaccurate-ly reflected. We went to him and asked that he restate his thoughts and this is his reply:

FromSiegfriedOthmer

It’s pretty clear that most of the audience was distressed upon hearing the presentation by Nicholas Lofthouse on the Ohio State Uni-versity study of neurofeedback. Over most of its history, this has been a largely clini-cally driven field, and it amazes me that we have allowed ourselves to be maneuvered into a position in which the influence of a clinician is treated as a contaminant to be minimized in the critical experimental de-sign by which neurofeedback is supposed to stand or fall. Should we not be raising vigor-ous objections to this assumption?

The issue of experimental design wraps around the vaunted placebo. And yet we are at this moment at the twentieth anniversary of Michael Tansey’s finding of nearly twenty point IQ improvement in some 21 mildly neurologically impaired

children. Within a year or so of his report, we published a replication with some 15 children. The results of the two studies were significantly correlated, which con-fers credibility on both. Beyond that, we had Dan Chartier’s report of a 40-point gain in IQ score in an MMR child, and Matt Fleischman’s report on five-year follow-up data on 20-point IQ score gains in MMR twins. There is no placebo model for such IQ improvements. There has to be a non-trivial cause.

In a Bayesian analysis, all such past studies could be used collectively to inform a determination of a false positive likeli-hood. By now, studies are available in suf-ficient number to render that likelihood to be negligible. No single study, good or bad, can significantly alter that appraisal.

As for controlled designs, they were in fact done at the outset. Sterman’s research covered that ground. It does not need to be covered again. Conventional wisdom has it that Sterman’s research was rejected at the time. But in fact it could not be realistically appraised in the science of the day. His was a case of “prematurity in science.” Looked

at in the modern perspective, the case for neurofeedback was not only solidly made in the very first experiment, but it is consis-tent with modern understandings of brain functional plasticity.

This entire history reflects an in-stitutional bias that a Type I error is to be avoided at all costs. But if neurofeedback is ephemeral, then at worst it represents a huge waste of money and resources. The implicit costs of a Type II error are not con-sidered at all. But imagine the impact on our society if Tansey’s original work had been recognized for its implications for the field of education at the time? We have spent two decades now in fear of a Type I error with respect to neurofeedback. That is a blunder of inestimable proportions.

According to a report on the field of education sponsored by the European Orga-nization for Economic Cooperation and De-velopment (OECD, 2002), “Education today is a pre-scientific discipline.” Our work in neurofeedback not only provides a scientific model but a practical and affordable remedy for educational failure. That proposition has already been adequately proved.

Dr.OthmerRestatesHisCommentsfromtheMembers’Meeting

Biofeedback and neurofeedback hold tremendous potential in sport and performanceapplications to train the body and mind to work together, but remain underutilized. AAPB‘snewest book, Biofeedback & Neurofeedback Applications in Sport Psychology will teachthe practitioner:

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to help the athlete/coach/trainer enhance mental skills such as focus and composure.• New strategies for the elimination of bad habits.

Written by top sport psychologists and experts in the field of biofeedback and neurofeedback,including case studies as well as illustrations and graphs that highlight the use of the authors’techniques, Biofeedback & Neurofeedback Applications in Sport Psychology is a must-havereference for today’s practitioner interested in helping clients reach their maximum potential.

Order your copy at www.AAPB.orgor telephone 800-477-8892.

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MindFull

Rare Earth, Rarer Brain

David Kaiser, PhD

NeuroConnectionsWINTER2010

It has yet to be proven that intelligence has any survival value – Arthur C Clarke

As I currently struggle with the 2nd most complex object in the universe, the U.S. tax code, using the most complex entity in the known universe, the human brain, I wonder whether I can remove “known” from this assertion. Is the human brain the most com-plex body in the universe? Certainly the so-lar system, but what are the odds that deep in space, in some distant corner of the An-dromeda or Milky Way galaxy, might we find an even more complex assemblage of energy production and regulation?

It is always difficult to estimate odds from a single instance, and we only have one brain to go on. For instance the New Orleans Saints won their first Super Bowl last year after losing out on the chance for 42 years in a row. Does this mean that the Saints have a 1 in 42 chance of repeating this year? Or a 1 in 32 chance of repeating as champions, the number of teams in the NFL? Or is it a forgone conclusion, a 1 in 1 chance?

The search for extraterrestrial intelli-gence (SETI) is a similar endeavor of odds-making. Since its inception in 1961 with Frank Drake’s formula, many astronomers and xenobiologists have attempted to work out the probability (odds) of overhearing a signal broadcast from an alien civilization. Toward this end Drake fashioned a formula to estimate the likelihood of intelligence appearing in ours or any other galaxy. The formula estimates the probability of an Earth-like planet orbiting a suitable star in each galaxy multiplied by the probability of life appearing on such a planet multiplied by the probability of life advancing to intel-ligence multiplied by the chance of being available for communication at the time of our search, now entering its 50th year of investigation. Carl Sagan estimated that be-cause the galaxy contains 400 billion stars and 100 billion galaxies, the probability of intelligent life beyond Earth was virtu-ally certain and that the universe might be densely populated with alien civilizations. But another well-known physicist, Enrico Fermi, wondered aloud whether this could be at all possible. If extraterrestrials are commonplace, where are they? They ought

to be sharing our school buses by now. Our solar system is a latter-born child in the larger scheme of things, born 10 bil-lion years after the Big Bang. Given the presumed head-start of a few billion years on our species, or even a few million years, any space-faring civilization worth its salt ought to have already colonized Earth and its environs by now. One way out of this timely conundrum is to consider how we may already be colonized but fail to notice. We may be in a protected nursery awaiting further species maturation before we join the upper crust of galactic society, or we are exhibits in a celestial zoo, a rare specimen left to its own devices in its natural habitat for science’s sake—look but do not disturb! Another option, if ET exists and has a 5-billion year head start on space travel, is it a case of been there, done that, with only a t-shirt to show for it? Our real estate is so far out of the way, a galactic backwa-ter, that we hardly notice the intrusions to our lifestyle when the colonizers do pop up now and again and leave a pyramid or two in their wake.

Fermi’s speculations were formed years ago, before we had the technology to survey nearby stars for evidence of planets. We have found many extrasolar planets, even terrestrial-sized ones (Earth-size) orbit-ing nearby suns. As of the latest count there are 495 planets orbiting distant stars, with the count to likely surpass 500 by the time you read this, with the nearest Earth-sized planet a mere 20 million light years away, a stone’s throw away in cosmic scales.

Drake’s formula asks for the proba-bility of suitable stars and earth-like planets around those stars. Of 1,000 nearby stars, 10% are known to have Jupiter-sized plan-ets and it’s predicted that as many as half of all sun-like stars are orbited by planets the size of the Earth. Initial surveys in the field of extrasolar astronomy revealed ex-otic systems where Jupiter-sized planets whizzed around their nearby sun in Mercu-ry-size orbits in environments unfriendly to terrestrial planets; but further surveys have found evidence that our Earth is not alone, even if its inhabitants are.

Next in his formula is the estimation for the probability of life. Simple life such

as microbes may be ubiquitous throughout the cosmos. Water plus chemicals plus time may produce life 100% of the time. We think this because life on our own planet emerged as soon as heavenly possible, as soon as the Earth cooled just enough to support stable metabolic processes within a cell mem-brane, which suggests it was a modest step from having carbon available on a planet’s surface to carbon-based reproduction.

But on the other hand, life may not be so simple, and unlikely to be a single step from inorganic matrices to biologi-cal ones. Life developed only once on this planet, and perhaps only at one site on all of Earth. We have only one DNA strand pres-ent on the planet, from ameoba to algae to Oprah. If organic from inorganic chemistry is a preordained conclusion, wouldn’t other DNA variants exist to this day?

Unicellular life can withstand high pressure as well as extreme temperature shifts, up to 160+ degrees Celsius, but mul-ticellular life is not so flexible. It requires stable pressures, small temperature ranges (0 to 50 degrees Celsius), and it takes an unknown and unique process that moves unicellular life to multicellular life. Single cell creatures appeared 3.8 billion years ago in our fossil record, but for 3.3 billion more years, multicellular life was but a dream. Whatever caused such anti-symbiotic in-ertia is beyond me? It’s been 550 million years since the apparent transition from one-celled creatures to colonies and divi-sion of labor before the human brain made the scene and that’s an awfully long time to keep a planet’s climate stable and relatively free of debris from space.

A stable environment, where water remains in liquid form for half a billion years or more, requires an amazing degree of balance and luck. Habitable zones are an improbable mix of mass, composition, po-sition, and timing. We live in the least prob-able of an improbable Goldilocks’ scenario: a world none too hot, none too cold, none too close to the parent star, but none too far; and we need a perfect parent star, one who hangs around a billion years without chang-ing its ways.


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Let me quickly run through the re-maining settings and variables that need to be reasonable in order for intelligent life to emerge on a planet:

1. Right galaxy: we need the stability of a spiral galaxy – no other will do, with enough heavy elements to allow formation of terrestrial systems, and this excludes most galaxies, which are too small, too elliptical, or too irregular to provide the stability of temperatures and radiation life needs to exist.

2. Right galactic position: We cannot live in the center, nor at the edge, nor in the halo. In fact we must live in only one place in a spiral galaxy, the co-rotational disk, and only here are we safe long enough for intelligent life to emerge. Anywhere else and the constant star formation will leave permanent scars on our atmosphere and wipe away any biosphere that happens to rear its head.

3. Right star: Only K, G, or M stars need apply. Not too much ultraviolet light, with a long enough lifetime and moderate metals, which means it has to be a third generation star or latter in composition, which Fermi did not know when he made his conjecture.

4. Right position from star: We must be within the habitable zone of our parent star, which is the range with-in which water remains liquid on a planet’s surface; and we also need to avoid tidal locking to the star, like Mercury or the Moon to us, and have a reasonably circular orbit to avoid excessive heating or cooling.

5. Right solar system: We need bounc-ers outside our fragile home to keep out the rift-raft, a stable Jupiter-sized neighbor that clears inward debris with its massive gravitational field. For every thousand asteroids or com-ets that want to fall inward towards the sun and possibly cross our path, we need Jupiter to take out 999 of them, else Earth would soon be rid-dled with holes. Any orbital chaos is a no-no, in fact; all planets must stay within their “assigned” lanes, unless we run the risk of stripping free our atmosphere and our satellite.

6. Right planetary mass: We need to live on a planet large enough to retain

an atmosphere and ocean, be heated from within (radiogenic heating) and possess a molten core to provide magnetism for life’s early years, a tall order for terrestrial planets.

7. Right planetary composition: Our planet’s crust must be broken at places and fluid to manage the CO2-silicate balance. Plate tectonics act as a thermostat in terms of heating. We need a moderately large ocean and enough carbon for life, but not enough for a runaway greenhouse ef-fect that would cook all the leggy life away. And we need a massive infu-sion of oxygen at right time, enough to swing the atmosphere over to a reasonable composition for animal life to emerge.

8. Right planetary tilt: We need to knock our planet on its side while still retaining its atmosphere, but not too much as we need seasonal varia-tion but not so severe that summers and winters are rare events.

9. Right terrestrial system: Finally we need a large mass watching over our shoulder, a satellite to stabilize our tilt, provide tidal forces to help shake nature’s chemistry beakers, and we need our moon to spiral away from planet, not inward, unless we want our lives cut short in our prime.We can estimate the odds for every

feature above, but who are we kidding? Suffice it to say that many of the situa-tions are uncommon to rare and let’s add them up. For instance, plate tectonics may be critical for intelligent life to evolve and of 83 planetary bodies in our solar system, Earth is the only planet with plate tecton-ics, although a moon or two also appear to have the right stuff. That we live in the co-rotational plane of our galaxy, away from the vibrant and deadly arms, where stars are born and die with regular periodicity and genocidal irradiation, is a necessity. If we lived closer to stellar nurseries, the mother arms of the Milky Way, we would not be here now, as every 10 million years or so a neighboring supernova would explode, wiping the counter clean in all directions with gamma radiation.

The most improbable event of our planet’s formation is in the final factor in understanding Earth’s fecundity -- our love-ly satellite. Reproduction without the moon is impossible, and not because would-be Romeos need its light to woo would-be Ju-rassic Juliets. Without the moon our planet

would wobble on our axis as much as Mars does, which flips from 0 degrees tilt of its axis to 90 degrees every 10 million years or so. Imagine a spider monkey species evolv-ing on such an Earth, having to adapt to the Sahara and a few million years later, the Antarctic, then back to the Sahara again. The Moon reduces our wobble to 2 1/2 de-grees, very tolerable, but how did we earn such a large prize?

According to the Apollo missions, the Moon and Earth are the collapsed frag-ments of an ancient collision between two proto-sized planets who struck each other at the right time at the right place and at exactly the right angle in the middle of the cosmic night. Normally such collisions leave a debris field that is reabsorbed by the larger planetary mass, much like Sat-urn’s rings and its many small satellites, but in our case, fortunately the larger orb (soon to be the Earth) wasn’t so hungry. Instead the moon coalesced in orbit around the center of its collision partner. Without our large moon, tidal pools do not exist, and multicellular life remains a fantasy. So what are the chances of another terrestrial planet possessing such a large satellite? Is it astronomical? Is it less than zero? Or possibly exactly zero. If it’s somewhere between a 1 in a billion and 1 in 400 bil-lion billion, we are faced with the reality that our fantasy is the only reality, that our dyadic planetary system known as the Earth-Moon is a unique event in the cosmos, far less likely to recur than hav-ing the New Orleans Saints win the World Series.

So what are the odds of an entity as complex as a brain existing on a distant pebble? Probably less than we’d care to imagine.

So in neurotherapy we are working with the best the universe has to offer, and it will be some time before Apple Comput-ers surpasses it in design in complexity and elegancy. It is a remarkable feat of evolu-tion, without equal and beyond compare, a product of perfect circumstances; which means that we may be the only parts of Creation that will ever read a sentence or initiate a thought. If Creation could hap-pen again, it couldn’t happen again. The brain is the decisive and definitive equilib-rium of cosmic proportions, all happening within us. Voltaire quipped that if God did not exist it would be necessary to invent Him. But if the brain did not exist, an end-less universe might still fail to invent one.

Mindfullcontinuedfrompage2�


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äCynthiaKerson,PhD

The behavioral changes that occur when we train the brain using a neuromodulatory modality are obvious; less obvious are the changes that occur organically. This is why I posed this question. I have been thinking quite a lot about this of late, firstly because I’m eager to see the group analyses from the fMRI/EEG/ERP data we acquired this year on ADHD and non-ADHD adults and secondly because the NIH offered the fol-lowing grant opportunity: Department of Health and Human Services/National In-stitutes of Health Basic Research on Self-Regulation (R21) Grant http://www07.grants.gov/search/search.do?&mode=VIEW&oppId=56526

When I presented the opportunity to the leaders of the Research Foundation, it seemed an interesting one, but discussion then went to well, what are we doing? How do we design a study to show this, when in fact we’re really not sure?

We operantly condition behavior; that’s a given. But behavioral and bio-logical changes are not always consistent. Many times, we see behavioral change, but no clinical shift or vice versa. If the be-havioral changes are due to specific thera-peutic reinforcement of self-regulatory mechanisms then why aren’t these changes always consistent with organic modifica-tions? This question looks the mind/brain problem smack dab in the eyes. I think it’s fair to say that we aren’t exactly sure. But we’re working on it – and that’s humbling.

äMerlynHurd,PhD

All quotes are from the NeuroGuide listserv

These are questions we have posed for years and our clients or soon to be clients ask with an intensity that has been driven by the num-ber of books on neurotherapy and the ease of finding information on the Internet.

First, we need to recognize that under the neurotherapy umbrella are many types of training that may not always look like

neurofeedback. For instance, David, Al-pha Stim, Heartmath, Roshi, TMS, rTMS, tDCs, HEG, Neurofield and LENS proto-cols certainly provide relief for anxiety, depression, sleep, …the list goes on and on, yet these are stimulation type therapies. Many of these were developed out of the work of clinicians who looked to expand the efficiency of the neurofeedback effects.

What exactly are we doing when we do neurotherapy? The most obvious general answer is relief of symptoms. The “exactly” is the point we are concerned about in this question. Dr. Joel Lubar wrote recently:

“Neurofeedback is clearly based on the main principles of op-erant conditioning. The basis of this goes back nearly 100 years includ-ing Thorndike’s work at the end of the 19th century and Guthrie’s law of effect developed in the early 20th century. The keystone of operant conditioning is based on the work of Skinner and his colleagues. I have been doing operant conditioning for neurofeedback since the early 1970s and accumulated a vast amount of evidence. Much of what I have pub-lished over the years indicates that discrete rewards, which are not too frequent, produce the best learning. I found that for children between 10 and 20 discrete rewards per minute seem to be optimal and for adults ap-proximately 7 to 15 discrete rewards per minute seem to work best.

However it is sometimes im-portant to provide information that tells patients that they are beginning to approximate the criteria for dis-crete rewards. For example, in my work with Thought Technology’s BioGraph a number of years ago, we developed a screen in which the background color of the EEG changed when all criteria were met for rewards and inhibits. IF the col-or change could be maintained for a specific period of time such as ½

second then that would produce a discrete reward in the form of either a tone or a point counter that would simply tell the individual that all the criteria have been met and sustained for a specific period of time.

I do not recommend complex, rapidly changing displays, especially displays that are combined with hand movements such as the Smart Brain system.

I wonder if discrete rewards are best in all situations. I think they are certainly advisable when the ob-ject is to teach the client to get to a particular state. I can see some situa-tions in which I would question this:

Suppose the client is already able to “get there” but he wants to learn to sustain the state. I am think-ing of the situation where one of our customers trained the top 23 execu-tives in a Fortune 500 company to sustain their focus. We provided a measure called “Run Time”, which was how long he could hold his focus above a fairly challenging thresh-old. These peak performance clients doubled the amount of time that they could sustain their focus in five train-ing sessions. They were learning to keep focusing despite distractions. With that aim, would discrete re-wards work as well? And, w What if you are trying to teach relaxation with neurofeedback? Do discrete re-wards work as well?”

Note: Joel did not mention this, but HEG does exactly what he is describing and the focus of the client is similarly increased and sustained outside the office.

At the same time Dr. Lubar noted that therapist variables are very important. He stated:

“There are few neurofeedback applications that stand completely alone in the sense that the patient

WhatExactlyAreWeDoing?Cynthia Kerson, PhD, Merlyn Hurd, PhD

There has been a lot of discussion of late about what exactly we do when we do neurotherapy. What are we affecting? What neuromodu-latory process occurs? Are we, in fact, rewiring neuropathways? If so, how do we know this?

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is connected to the machine and no therapist needs to be present. The therapist clearly has to be part of the feedback loop providing encourage-ment especially since feedback can be long and tedious in some cases.”

Considering the thoughts and facts stated by Dr. Lubar the “exactly what we are doing” with neurofeedback is train-ing clients to meet a criteria using operant conditioning. There must be a set goal, a reward for achieving or approximating the goal and a set length of time to sustain. The types of neurofeedback can be as sim-ple as a single channel training to increase or decrease amplitude to complex types of 19-channel Z score or LORETA training. All are based on the use of operant condi-tioning. Then how do we categorize neu-rofeedback, such as relaxation training or increasing the length of a state or LENS neurofeedback? All work and plenty of studies verify their effectiveness. Some-how each of them must have the same operant conditioning embedded or shad-owed in them. As technology continues to enable us to view the brain’s workings as tasks are being undertaken the answers to the latter will be forthcoming.

What are we affecting? So we have an idea of what we are doing, now what are we affecting? The Default Mode Network; Central Nervous System; Neural Pathways; particular parts of the brain; the whole cor-tex; deeper parts of the brain… the issue has many parameters.

Several years ago Mario Beauregard was presenting at ISNR his research on ADHD Neurofeedback training with chil-dren and he had used fMRI besides QEEGs to document the changes in the brain. When he showed the differences in the structures in the pre and post I got so excited…. Here was proof that the structure of the brain was changed with neurofeedback! So if the structure of the brain is affected, it would seem to indicate that all the above men-tioned areas are changed. Somehow when one is working with 100 billion neurons, it would seem logical that all these neurons have to have some kind of connection…. What a mess if they all were bouncing around in our brain independently.

Scott Decker recently wrote: “it seems to me neurofeedback is “setting the conditions” to increase or decrease an overt operant behavior, initially in the office and ultimately outside the office.”

Werner Van Den Bergh noted:

“That what we train in EEG is what we find as deviant parameters in it in “passive” condition, so one could say (as) related to the “default mode net-work” (DMN). The DMN is indeed a very important mode of activity of the brain (think about the default mode of a computer!) but by defini-tion it is not correlated with any ac-tive behavior of the subject. So what we are training in the EEG seems to be related to changing some aspects of functioning in its default mode.”

Terence McL Semple stated:

(T)hey (clients) need to be able to identify that they are “doing it,” identify the rewarding outcomes and attribute the goals achieved with their competent use of their training. Perception of contingencies does not have to be “conscious” to effect be-havior, even unconscious mispercep-tion of non-existent contingencies can effect behavior, cf. various forms of animal “superstitious” behavior.”

These views seem to point to the idea that the effect is not only on the mechanical pathways, neurons, etc but affect the cli-ent’s state of mind; behaviors and moods.

What neuromodulatory processes oc-curs? Are we, in fact, rewiring neuropath-ways? The answers to these questions are far beyond this article, for the understand-ing of the neuromodulatory processes and neuropathways are complex. Books and hundreds of articles have been published regarding these issues. Marvin Sams noted:

“It is impossible to train the Default Mode Network. We may well get “fall out” that stabilizes the DMN, but it is impossible to “train” direct. Task is task is task.”

Let us at this point take up the last two questions in another longer article.

How do we know we are doing what we say? The flip answer is that a lot of people have had their lives changed; clients come back for more years later; more stud-ies are showing changes and no matter how strong the attack against neurofeedback has been it continues to grow and become more precise and with shorter time frames for training with good outcomes.

More studies and more longitudinal studies will bring more information to the front and it will become harder for the ad-

vantages of neurofeedback to be dismissed. At this time, even with the hundreds of studies that have been conducted over the 40 years of neurofeedback the client is the strongest indicator of its effectiveness. More and more clients knock on our doors and more and more MDs and other health professionals refer to us, all indicators that neurofeedback is working.

äRexCannon,PhD

Neurotherapy does operate under the aus-pices of neuroplasticity and the individual’s ability to enhance or diminish network op-erations by operant learning. Cannon, et al., 2007ab, 2008 and 2009 have demonstrated the strengthening/weakening of functional networks in the brain as a result of the neu-rofeedback procedure. This is done through several mechanisms of behavior, reinforce-ment, reward and punishment. In its most basic element we are directly influencing neuronal mechanisms of self-regulatory processes. The works mentioned above with supporting fMRI feedback research (Anwar, et al., 2009; Caria, et al., 2007; deCharms, 2008; deCharms, et al., 2004; Eklund, et al., 2009; LaConte, Peltier, & Hu, 2007; Lee, Ryu, Jolesz, Cho, & Yoo, 2009; Nakai, Bagarinao, Matsuo, Ohgami, & Kato, 2006; Posse, et al., 2003; Weis-kopf, Mathiak, et al., 2004; Weiskopf, Scharnowski, et al., 2004; Weiskopf, et al., 2003) maintain this notion. In essence, we are performing integrative and differential network connectivity processes as they re-late to a normative, homeostatic state and non-normative, dysregulated state.Anwar, M. N., Bonzano, L., Sebastiano, D. R., Roccata-

gliata, L., Gualniera, G., Vitali, P., et al. (2009). Real-time artifact filtering in continuous VEPs/fMRI record-ing. J Neurosci Methods, 184(2), 213-223.

Caria, A., Veit, R., Sitaram, R., Lotze, M., Weiskopf, N., Grodd, W., et al. (2007). Regulation of anterior insu-lar cortex activity using real-time fMRI. Neuroimage, 35(3), 1238-1246.

deCharms, R. C. (2008). Applications of real-time fMRI. Nat Rev Neurosci, 9(9), 720-729.

deCharms, R. C., Christoff, K., Glover, G. H., Pauly, J. M., Whitfield, S., & Gabrieli, J. D. (2004). Learned regula-tion of spatially localized brain activation using real-time fMRI. Neuroimage, 21(1), 436-443.

Eklund, A., Ohlsson, H., Andersson, M., Rydell, J., Ynner-man, A., & Knutsson, H. (2009). Using real-time fMRI to control a dynamical system by brain activity clas-sification. Med Image Comput Comput Assist Interv, 12(Pt 1), 1000-1008.

LaConte, S. M., Peltier, S. J., & Hu, X. P. (2007). Real-time fMRI using brain-state classification. Hum Brain Mapp, 28(10), 1033-1044.

Lee, J. H., Ryu, J., Jolesz, F. A., Cho, Z. H., & Yoo, S. S. (2009). Brain-machine interface via real-time fMRI: preliminary study on thought-controlled robotic arm. Neurosci Lett, 450(1), 1-6.

NeurotherapyQuestioncontinuedfrompage2�


Nakai, T., Bagarinao, E., Matsuo, K., Ohgami, Y., & Kato, C. (2006). Dynamic monitoring of brain activation un-der visual stimulation using fMRI--the advantage of real-time fMRI with sliding window GLM analysis. J Neurosci Methods, 157(1), 158-167.

Posse, S., Fitzgerald, D., Gao, K., Habel, U., Rosenberg, D., Moore, G. J., et al. (2003). Real-time fMRI of tem-porolimbic regions detects amygdala activation during single-trial self-induced sadness. Neuroimage, 18(3), 760-768.

Weiskopf, N., Mathiak, K., Bock, S. W., Scharnowski, F., Veit, R., Grodd, W., et al. (2004). Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI). IEEE Trans Biomed Eng, 51(6), 966-970.

Weiskopf, N., Scharnowski, F., Veit, R., Goebel, R., Birbaumer, N., & Mathiak, K. (2004). Self-regula-tion of local brain activity using real-time functional magnetic resonance imaging (fMRI). J Physiol Paris, 98(4-6), 357-373.

Weiskopf, N., Veit, R., Erb, M., Mathiak, K., Grodd, W., Goebel, R., et al. (2003). Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. Neuroimage, 19(3), 577-586.

äJohnC.LeMay,MA,MFT,BCB

It is interesting to me how change and healing has been debated for centuries. Many times in history the path of healing is far different from the theory espoused by the practitioner. Humors have been changed, balances in per-sonal magnetism has been changed, bleed-ing has been employed to get the diseased blood out, and too often very intelligent deep thinking individuals have struggled to make the mystery healing understandable. Even in scientific process there is a no accounting for all of the independent variables that can ef-fect the outcome of our investigations.

Even now investigators are just be-ginning to understand the role of glia in the transmission process of thought, intention, and other processes after spending so much time and energy on understanding synap-tic processes. While there is no doubt that synaptic transmission is primary, the under-standing of resonant loops within the brain, along with tubule transmission of neuro-peptides, blood flow characteristics, the ef-fects of time of day, etc. are still not fully understood. We have some pretty good the-ories, some very consistent observations, but the jury is still out on exactly what neu-romodulatory processes occur, how we are effecting neuroplasticity, but the wonderful scientific process is the best tool we have now for investigation.

1. What are we affecting? In a variety of ways depending upon mode, place-

ment, feedback method, data col-lection and feedback style we are effecting the brains ability to orga-nize itself and its actions. This can be homeostatic, synaptic, or other process.

2. What neuromodulatory process oc-curs? The brain is brilliant, and ca-pable of decoding a broad amount of information. So many people have used multiple different methods with a variety of outcomes. Barry Sterman has very adeptly described methods of operant conditioning with SMR training. On the other hand there has been evidence of the effectiveness of a variety of “state training” exercises increasing alpha theta crossover pat-terns, broad band inhibits, z score trainings, coherence trainings, and on and on.

3. Are we, in fact, rewiring neuropath-ways? With mounting evidence of the physical manifestations of neuro-plasticity and life’s tendency to adapt and adjust, it would seem that we are. We can only know this through fur-ther exploration, and this is a great field full of people with a determined pioneering spirit. I am happy to be along for the ride of discovery.

äJoelF.LubarPhD

How does neurotherapy affect underly-ing brain processes? In one respect this is very difficult to determine. Of course we currently use quantitative EEG to look for changes following different types of neu-rotherapy interventions. There are literally hundreds of publications regarding this. However trying to determine what is ac-tually happening inside the brain is much more difficult. For example in the area of pharmacology there are many studies that show the effects of different substances such as cocaine, opioids and other classes of substances on different types of brain tis-sue or on intracellular, extracellular brain fluids based on in vitro assays. In the case of the living human brain about the only techniques we have are pet scans which re-ally look at oxygen and glucose utilization, fMRI and also some new techniques based on spectroscopy.

At present it would be very diffi-cult to determine the direct effects of neu-rotherapy in such areas of the brain that produce specific transmitters such as the

substantia nigra for dopamine, nucleus-basalis of Meynart for acetylcholine, the locus coerulus for norepinephrine, and the raphe nuclei in the brainstem that are important for producing serotonin. Very high Tesla MRI (9 or 11 Tesla magnets) can now visualize structures as small as .5 mm or less but this is still too gross to see detailed changes. Another possibility is to look at connectivity measures. At present we use phase and coherence changes that occur as a result of neurotherapy and more complex measures such as phase shift du-ration, phase reset etc.

The only visualization technique I’m aware of is diffusion tensor imaging which allows one to examine the migra-tion of water molecules along different white matter pathways. Normal diffusion is anisotropic which means that it follows the exact pathways and shows pretty de-tailed imagery of the white matter connec-tions. When there is damage to a connec-tion or a bundle of connections the water seems to be trapped in that area and the distribution based on the diffusion tensor is isotropic or spherical. The problem with showing differences before and after neu-rotherapy interventions using the diffusion tensor approach is the density of the con-nections. Only a small fraction of the total number of connections can be visualized at the present time. Even though we have approximately 100,000,000,000 neurons it is estimated that we have at least a qua-drillion connections or 10 to the 16 power. How then could one see subtle functional anatomical changes with this density of connections in the brain? Nevertheless we do believe that we may be affecting wir-ing in some way. We know that dendrites have spines for receiving information at axodendritic synapses. There are many basic studies in neuroscience that show that synaptic spine formation is affected by stimulation and therefore indirectly by changes in the environment. But again how do you measure this in vivo? For in-vitro studies using animals one could look for changes in synaptic spine densities in specific structures following neurofeed-back, which animals can learn quite eas-ily. So basically at this point in history we would have to turn to a number of animal studies utilizing neurofeedback to look at in vitro changes in terms of anatomy and neurotransmitter distribution and other measures that cannot be done in the living human brain.

NeurotherapyQuestioncontinuedfrompage�1


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This study will include up to 90 participants who will undergo either neurofeedback theta/beta ratio training or other comparison treatment, possibly sham or stimulant. It will include a 1-year follow-up.

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NeuroConnections Winter 2010

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