Electroencephalogram (EEG) and Event Related Potentials

(ERP) Lucy J. Troup

28th January 2008

CSU Symposium on Imaging

Electroencephalography (EEG)

• What is measured?– electrical changes in groups of neurons

• How is it measured?– Difference between two electrodes

• What types of changes can be measured?– Sleep-related; Certain neurological disorders

• How are these changes measured?– Frequency, Amplitude, Specific Wave-Types

• ERPs

– “Electrical Potentials associated with specific sensory, perceptual, cognitive, or motor events”

• From EEG to ERP…– Time-locked average of EEG from many trials

involving same ‘event’– Signal/Noise Ratio reduction; what is left is

‘related to the event’• EEG = 20-50v / ERP = 1-10 v

What are Event-Related Potentials?

Filter & Amplify

Average across Trials &

Individuals

Collapsed to form a “Grand Average” Or

mean of means

Electrical activity at the onset of a

stimulus recorded

Time-locking + Signal/Noise Ratio Reduction=

ERP derived from EEG

Single Trial: 100ms visual stimulus

Average of 200 trials to same stimulus

Where do potentials come from?• Not action potentials…

•ExcitatoryPostSynapticPotential’s

•InhibitoryPostSynapticPotential’s

•Most likely source

• ERP Components

– “Scalp-recorded neural activity that is generated in a given neuroanatomical module when a specific computational operation is performed”

– Peaks are not necessarily the same as components; “peaks are not special”

– Peaks are comprised of summation of latent components that are not observable, how we analyze our ERP data will relate to the validity and accuracy of our observations

How do we analyze ERP waves?

Classic Approaches to Analysis

• Parametric Statistical comparisions– Peak to Peak– Mean Amplitude– Peak Latency

• Covariation– PCA

• Source Localization– BESA

Well-studied ERP components

• Visual– C1, P1, N1, N170

• Auditory– BER, N1, MMN

• Cognitive– N2b, N2pc, P3, N400, ERN, FRN, RP, LRP

ERP precautions

• Can’t determine Where, only When

– Scalp Topography vs Source Analysis

• Doesn’t measure all neural activity

– Closed vs Open Fields

• Can only use when time-locking is practical

– Not applicable for all areas of psychology

• Artifacts– Eye blinks, mm. mvt, etc.– Lights, and other electrical sources

• Data Analysis Techniques– Artifact detection & rejection– Filtering– Reference electrodes (i.e. linked ears)– Time-locking (stim or resp?)– Segmenting (epochs, i.e. time windows)

Some potential problems

What information does a “component” provide for us?

Example from Troup, Pitts, Draper & Catellier (2007)

Electrical Geodesics Inc. 128 channel high density EEG

Example of a raw face

Example of a Gabor face

Experiment 1• N=19• Raw and Gabor Faces • Presented randomly • 3 blocks of 66 faces

ISI 500ms

Fixate 250ms

Face 1 250ms

Face 2 250ms

Response Time 1000ms

Example of Same Face Pair Example of Different Face Pair

Experiment 2• N=19• 7 Blocks 80 pairs per block• S’s respond with key press to “Same Face pairs”

Questions

• Does N170 differ in amplitude and/or latency for Gabor-filtered versus Raw face images?

• Does N170 differ in amplitude and/or latency for Gabor-filtered versus Raw for Scalp location?

• Does N170 differ in amplitude and/or latency under the manipulation of same/diff face pairs in a rapid judgment task?

Raw-Gabor Raw Same-Different

Scalp LocationScalp LocationFrontalFrontal

Left TemporalLeft TemporalRight TemporalRight Temporal

CentralCentralCenter OccipitalCenter Occipital

Behavioral ResponseBehavioral ResponseSame CorrectSame CorrectDifferent CorrectDifferent CorrectSame IncorrectSame Incorrect

Stimulus Stimulus typetype

Raw Raw GaborGabor

Amplitude and Latency

Same/Different Grand Average Data

Sig. Diff for Correct Vs Incorrect

Visual Sensory GatingTroup, Yadon, Pitts & Hafer-Zdral

(2007/2008)

• Sensory Gating– The process of “gating out’ or not responding to a

subsequent stimulus after the onset of the initial stimulus in rapid presentation

– Auditory Stimuli “clicks”– Visual Stimuli “Flashes”

• Term used interchangeably with “Habituation”• Are they fundamentally distinct or same

process?• Do people behave to visual stimuli in same way

as auditory?

ISI 500ms

Fixate 10s

Flash 1 12ms

Flash 2 12ms

ISI 500ms

Flash 6 80ms

ISI 1200ms

Flash 2 12ms

ISI 1200ms

Flash 6 80msFlash 1

12ms

Channel 75 (Oz)

Stimulus Overlap

Two differing Inter Stimulus Interval’s (ISI) Clearly show Stimulus overlap problems

ISI 500 ms

Flash

P100

P200

P300

ISI 1200 ms

Flash

P100

P200P300

Areas for Potential Collaboration

• The Stimulus overlap Problem– ADJAR techniques

• Principal components analysis of ERP data

• Raw EEG and Spectral analysis– Something I am hoping to look at in relation to

Gamma activity in the future

Thanks…• Colorado State University

– Dr Bruce Draper, Dr Ross Beveridge (Computer Science)

– Carly Yadon, MS – Graduate Student in Psychology (Perceptual and Brain Science)

– Dan Lopez, MS – Graduate Student in Psychology (Perceptual and Brain Science) Erin Catallier/Jessa Hafer-Zdral (REU Students)

– Logan Keech (Undergraduate RA)

• University of California, San Diego– Dr Mike Pitts (Hillyard Lab)