Dynamic Brain Sources of Visual Evoked Responses

Minue Kim

Clinical Neuropsychology LabSeoul National University

S. Makeig, M. Westerfield, T.-P. Jung, S. Enghoff, J. Townsend, E. Courchesne, T.J. Sejnowski

Science, 2002

Scalp Topography

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Electroencephalography (EEG)

• EEG provides a continuous recording of overall brain activity

• There are predictable EEG signatures associated with different behavioral states

Gazzaniga et al. (2002)

ERP is a tiny signal embedded in the ongoing EEG

By averaging the traces, investigators can extract this signal, which reflects neural activity that is specifically related to sensory, motor, or cognit

ive events

ERP 는 특정한 정보를 내포하고 있는 자극을 제시한 다음 자극 제시와 관련하여 일정 시간동안 일어나는 뇌의 전기적 활동을

의미한다 .

사건관련전위는 다른 정신생리적 측정 방법 , 예를 들면 fMRI 나 PET 등과는 달리 자극을 제시함과 동시에

자극의 처리 과정을 실시간으로 관찰할 수 있다는 장점을 갖고 있다 .

즉 , 시간 해상도 (temporal resolution) 가 우수하다 .

Event-Related Potentials (ERP)

The Relationship Between EEG and ERP

The Forward Solution and the Inverse Problem

• Forward Solution: Creating a model head, and extracting the model data is simple. The dipolar charge created electrical currents that flow to the surface of the sphere, creating a distinct pattern of electrical voltages in the surface

• Inverse Problem: A given pattern observed on the surface of the scalp can result from many possible locations of underlying neural generators

Basic Components of ERP

• Peak, Polarity, Latency

• 처음 나온 ERP 부터 1,2,3 이라는 이름을 붙여 나간다 (P1, P2, N2). 혹은 latency 를 가지고 명명하기도 한다 (P300, N400)

– Early peak (N100, N200) – Late Cognitive Component (P300, N400, P600, P800)

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Peak

Polarity

Latency

Examples of ERPs

• N100, N200– 피험자가 주의를 주지 않고 무시한 자극에 비해 주의를 준 자극에서 의미 있게

큰 진폭의 N100, N200 이 관찰된다는 것을 보고하였다 . N200 은 유입된 자극이 이전 자극과 동일 혹은 다른가를 탐지하기 위해 자극을 확인하고 분류하는 과정에 관여한다고 알려져 있다 .

• N400– semantic processing 을 반영한다고 알려져 있다 . 또한 N400 이 장기

기억으로부터 정보를 인출하는 과정 혹은 장기 기억 내의 정보를 탐색하는 과정(memory search processing) 을 반영한다고 한다 .

• P600, P800– 문법의 적합성과 관련 있다 .

Two Hypotheses for ERP Generation

Traditional View:

• The averaged event-related potential (ERP) evoked in humans reflects neural activity within discrete, functionally defined brain regions

• Response averaging removes background EEG activity (considered to be noise), whose time course is presumed to be independent of experimental events

(Relatively) Modern View:

• ERP features arise from alterations in the dynamics of ongoing neural synchrony generating the scalp EEG

• ERP features are produced through stimulus-induced resetting of the phase of ongoing field potential oscillations

Early Components of ERP

• N1

• 자극 제시 100-150ms 사이에 관찰되는 정점인 N100 은 주의력과 관련이 있다 . 피험자가 주의를 주지 않고 무시한 자극에 비해 주의를 준 자극에서 의미 있게 큰 진폭의 N100 이 관찰된다는 것을 보고하였다

• 일반적으로 , N1 은 “ alpha ringing” 현상을 동반하는데 , 이 이름은 EEG의 alpha wave (8~12Hz) 와 유사한 양상을 보이기 때문에 붙여진 것이다

Hillyard et al. (1973); Knight et al. (1981)

Methods

Methods

• Five 1.6-cm2 square outlines indicating possible stimulus locations were permanently displayed 0.8 cm above a central fixation cross

• Each 76-s block of trials, one outline was colored green, indication the target location for that block of trials

• Stimuli were briefly flashed white circular disks each presented for 117ms in a randomly selected stimulus location

• Interstimulus interval was randomly selected from 250 to 1000ms

• 15 adult subjects

• EEG date were collected from 29 scalp plus two periocular sites

• Nontarget visual stimuli presented to the left visual field

Power Spectra of ERP and EEG

Difference Between Expected and Actual Amplitude of ERP

Power Spectra of ERP and EEG

• The power spectrum of single-subject average-ERP waveforms resembled that of the unaveraged EEG

• Below 20 Hz the mean spectral amplitude of the poststimulus averaged ERP was up to five times larger than that expected from the EEG spectrum of the single-trial responses

• This implicates that some other factor, other than signal amplitude, contributes to the generation of ERP

Event-Related Spectral Perturbation and Intertrial Coherence

ITC Plot of Unaveraged EEG

Event-Related Spectral Perturbation and Intertrial Coherence

• The near 15 decibel increase in alpha power in the ERP waveforms beginning during the N1 interval was not accompanied by any significant increase in alpha power in the single trials

• Event-related intertrial coherence (ITC): A measure of the consistency across trials of EEG spectral phase at each frequency and latency window

• During the N1 period, the phase distribution was weighted toward the dominant phase

• This partial “phase resetting” occurred in all scalp channels and EEG frequencies below 20 Hz

• Mathematically, the poststimulus ERP could be accounted for by the phase resetting of the EEG activity

Alpha Phase-Sorted ERP-Image Plots

Alpha Phase-Sorted ERP-Image Plots

• Are ERPs sums of a sequence of brief fixed-latency, fixed-polarity potential events?

• Single-trial EEG epochs from each subject was sorted according to their poststimulus (0~293 ms) power at the peak alpha frequency (10.25 Hz) and separated the bottom and top 10% into two trial subsets

• Highest 10%: Alpha phase of these trials was unevenly distributed from 200 ms before stimulus onset to 700 ms after stimulus onset

• Lowest 10%: ERP average is too small, too small to have been evoked by a fixed-latency, fixed-polarity potential events

ICA Results: Eight Clusters

• Independent Component Analysis (ICA) results indicate 31 maximally independent components

• To determine which independent components were common across subjects, cluster analysis was performed

• Cluster analysis resulted in eight clusters, as shown on the left

Characteristics of Four Contributing Clusters

Characteristics of the Contributing Clusters

• Two lateral posterior clusters (αLP, αRP): accounted for the early lateral-occipital positive (P1) as well as for part of the early part of the broad frontal N1. Resemble projections of single equivalent current dipoles in lateral occipital cortex

• Central-posterior alpha components (αCP): made dominant contributions to alpha ringing without accompanying increases in alpha power. Resemble signals of left and right calcarine cortices

• Two centrolateral clusters (μ LC, μ RC): accounted for separate left and right μ rhythms and the late N1. Consistent with single compact cortical sources in the hand representation area of sensorimotor cortex

• Frontocentral components (FC): exhibited phase coherence both in the theta and alpha bands that accounted for half the N1 variance at anterior channels. Resemble signal at left dorsal anterior cingulate cortex, according to the inverse dipole model

Inverse Dipole Modeling?

• Developed to solve the inverse problem

• Assumption: Neural generators can be modeled as electrical dipoles, conductors with one positive end and one negative end

• Computer creates a model of a spherical head and places a dipole at a certain location. The forward solution is then calculated to determine the distribution of voltages that this dipole would create on the surface of the sphere

• This predicted pattern is compared to the actual data

• If the difference is small, the model is supported; if not, then the model is rejected

Grand-mean ERP data

• The eight component clusters accounted for 77% of variance in the grand-mean ERP N1 as well as 79% of ERP variance in the subsequent alpha ringing period

Conclusion

Phase resetting explains…

1. Why the ERP average of epochs with low single-trial alpha energy is so small

2. Why the strong, ~10 Hz “alpha ringing” peak in the power spectrum of the ERP need not be accompanied by an event-related increase in alpha band EEG power in single trials

3. Why the latencies of the resulting ERP peaks need not match the 50~100 ms latency of initial neural activation in visual areas

Summary

• ERP signals: Do they reflect increased neural activity within discrete, functionally defined brain regions, or are they the result of stimulus-induced resetting of the phase of ongoing field potential oscillations?

• Experimental results show us, at least in <20 Hz domain, partial phase resetting is responsible for the ERP signals for the following reasons:

1. ERP average of epochs with low single-trial alpha energy is so small2. The peak in the power spectrum of the ERP need not be accompanied by an

event-related increase in alpha band EEG power in single trials3. The latencies of the resulting ERP peaks need not match the 50~100 ms

latency of initial neural activation in visual areas

• So, the “background” EEG signals should not necessarily be considered as noise!

References

Gazzaniga, M.S., Ivry, R.B., & Mangun, G.R. (2002). Cognitive Neuroscience: The Biology of the Mind. New York: W.W. Norton & Company, Inc.

Hillyard, S.A., Squires, K.C., Bauer, J.W., & Lindsay, P.H. (1971). Evoked potential correlates of auditory signal detection. Science, 172, 1357-1360.

Knight, R.T., Hillyard, S.A., Woods, D.L. & Neville, H.J. (1981). The effects of frontal cortex lesions on event-related potentials during auditory selective attention. Electroencephal

ography and Clinical Neurophysiology, 52, 571-582.