Biophysics Division Kwang Sup Soh Subcoordinator, CKC-Biophysics CKC Biophysics Division.
Biophysics of EEG
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Transcript of Biophysics of EEG
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Biophysics of EEG
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Outer Surface of Human Brain
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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
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Closed and Open
Electrical Fields
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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
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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
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Magne'c Field
Electrical Field
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Electrical and Magne.c Fields Generated by Dipoles
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DIPOLE
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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
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Easy Cap
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Alpha Waves
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EEG Rhythms
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Left front to back Right front to back
Left front to back
Right front to back Midline front to back
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Left front to back Right front to back
Left front to back
Right front to back Midline front to back
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“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
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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)
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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)
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Idealized Auditory ERPs
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Electrical potential from a single source in left thalamus volume-conducted through white matter
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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
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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,…)
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Two Domains for Signal Representation
Different projection spaces different signal representa-tions
Signal Domain
Projection space, Basis functions
Transformed Domain Transformation
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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
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Representation in Time f(t)
Representation in Freq F(ω)
Time Domain Studies Frequency Domain Studies
Fourier Transform