biophysics of eeg

Biophysics  of  EEG    

Outer  Surface  of  Human  Brain

Gray Matter = Neuron cell bodies & dendrites

White Matter = Myelin (=fat)- covered axons

Cortex = Outer layer of gray matter

Gyri

Sulci

Axial Slice through Human Brain Front

Back

Closed  and  Open  

Electrical  Fields

Single pyramidal cell in cortex

For brain electrical activity to be detectable through skull, must be strong signal summed over many neurons - All behaving similarly at same time - All oriented in same way - So negative and positive don’t cancel each other out when summed Pyramidal Cells in the cortex have the right properties

Pyramidal  Cell  Orientation  in  Cortex

Pyramidal Cells mostly oriented in same direction relative to cortical surface, pointing out toward surface - Electrical activity from gyri more detectable at scalp than activity from sulci

Tangen'al  Dipole  

Radial  Dipole  

Magne'c  Field  

Electrical  Field  

Electrical  and  Magne.c  Fields  Generated  by  Dipoles  

DIPOLE  

Recording Brainwaves = Electroencephalography (EEG)

Digitize = Take samples of continuous input at regular intervals (e.g., every 5 msec = 200 Hz)

= Timing of critical “events” - Used in extracting Event-Related Potentials (ERPs) from ongoing EEG

Easy Cap

Alpha Waves

EEG  Rhythms  

Left front to back Right front to back

Left front to back

Right front to back Midline front to back  

Left front to back Right front to back

Left front to back

Right front to back Midline front to back  

“Inverse  Problem”  in    

EEG  Source  Localization •  Electrical fields are “volume-conducted” throughout

head o  Conducted better through some kinds of tissue

•  E.g., Cerebrospinal fluid vs bone

•  And summate o  Both boosting and canceling

•  So cannot assume activity generated directly under where it’s detected on scalp

•  Patterns detected at scalp could be produced by many different combos of generators o  So insufficient by itself to reveal locations of sources

Event-­‐‑Related  Activity  

Recording “epochs” Scale & Polarity (Negative Up!!!)

- Input range = 40-50 microvolts (uV) -  Activity of interest often only 1-5 uV, so buried in higher amplitude activity that’s not of interest

(We record continuously & pull epochs out later)

Averaging  Event-­‐‑Related  Potentials  (ERPs)

“Oddball” Paradigm = 1 stimulus appears more often (X) than than another (O)

Typically see large “P3 (P300)” in response to “oddball” stimulus

P300 can sometimes be big enough to see in individual trials - Not true for N400

Alpha Waves (8-12 Hz)

Idealized  Auditory  ERPs

Electrical potential from a single source in left thalamus volume-conducted through white matter

Some  ERP  Peaks  Related  to  Language

N400 = ERP “component” related to meaning - Bigger when word’s meaning doesn’t fit context - Bigger for unfamiliar words - May reflect amount of work required to integrate with context

P600 = ERP “component” related to form - Bigger when word not of expected type for a position in a sentence - May be a type of P300 - Sometimes called Syntactic Positive Shift (SPS)

Can evoke both at once

Alternative Signal Representations and Transformation

•  Signal representation in a suitable domain for information extraction,….

Examples: o  Fourier Transform for spectral analysis o  Hilbert Transform in envelop detection o  KLT(PCA) for optimal function approx. o  Laguerre basis function o  Numerous other transforms( DCT,Radon,…)

Two Domains for Signal Representation

Different projection spaces different signal representa-tions

Signal Domain

Projection space, Basis functions

Transformed Domain Transformation

Main Stages in Signal Analysis Signal domain basis functions Transformed domain, Coeffs

Transforma)on  

Analysis  

 Reconstruc)on  

Signals

Recon Signal

basis functions

Modified Coefficients

Information

extraction

 Representation in Time f(t)

 Representation in Freq F(ω)

Time Domain Studies Frequency Domain Studies

Fourier Transform