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Functional Brain Signal Processing: EEG & fMRI Lesson 4

This lecture explores different EEG bands and their implications in brain function and processing. It also introduces event-related potentials (ERPs), time-frequency analysis, and ERSP computation.

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Functional Brain Signal Processing: EEG & fMRI Lesson 4

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  1. M.Tech. (CS), Semester III, Course B50 Functional Brain Signal Processing: EEG & fMRILesson 4 Kaushik Majumdar Indian Statistical Institute Bangalore Center kmajumdar@isibang.ac.in

  2. Delta Band EEG • 0 – 4 Hz. Originates in frontal cortex, hippocampus and thalamus. • Associated with slow wave sleep. • Associated with declarative memory consolidation. • Implicated in attention during performance of a complicated mental task like artihmatic calculation.

  3. Theta Band EEG • 4 – 8 Hz. Associated with Rapid Eye Movement (REM) sleep. • Associated the mnemonic processes in our brain, where step by step detail of a process up to the sequential details has to be taken care of. • Implicated in working memory. • Implicated in long-term potentiation (LTP) leading to facilitation of long-term memory and learning.

  4. Alpha Band EEG • 8 – 12 Hz. Magnitude increases when eyes closed. Diminishes when eyes are open. • Alpha power often inversely varies as theta power in healthy brain. This indicates good cognitive ability. • Alpha power is positively correlated with brain maturity. • Alpha power is positively correlated with good memory performance and speed of information processing.

  5. en.wikipedia.org Mu Band EEG • 8 – 12 Hz. Originated from motor cortex and morphology is distinct from alpha. • It selectively augments and diminishes during motor related task demands. • Important for Brain Computer Interface implementation.

  6. Beta Band EEG • 12 – 30 Hz. Associated with waking stage in general and cognitive and emotional processes in particular. • Hyper beta activity at the sleep onset has been associated with insomnia.

  7. http://people.ece.cornell.edu/land/courses/ece4760/FinalProjects/s2012/cwm55/cwm55_mj294/http://people.ece.cornell.edu/land/courses/ece4760/FinalProjects/s2012/cwm55/cwm55_mj294/ Different EEG Bands

  8. Gamma Band EEG • 30 – 80 Hz. 40 Hz is considered representative (taken as 37 – 43 Hz). Implicated in sensory information processing. • It has been implicated in formation of memory, linguistic processing, internal thoughts (apparently without any outside stimuli) and behavior, particularly motor actions and planning for the actions. It has also been implicated in attention, arousal and object recognition.

  9. http://en.wikipedia.org/wiki/Event-related_potential Event Related Potential (ERP) http://cognitrn.psych.indiana.edu/busey/temp/eeglabtutorial4.301/maintut/data_averaging.html

  10. ERP: Definition • When the scalp potential is evoked in response to an event or stimulus presentation in the environment the evoked potential is called event related potential (ERP). Of course in scalp EEG ERP may be embedded in artifacts and neuronal activities not evoked by the event of interest.

  11. motorbehaviour.wordpress.com Single Trial and Trial-Averaged ERP

  12. Time-Frequency Analysis • Short-time Fourier transform. Epileptic ECoG of 500 time points Absolute value of FFT on 100 time points

  13. Event Related Spectral Perturbation (ERSP) • ERSP measures average dynamic changes in amplitude in the broad-band EEG frequency spectrum as a function of time. That is, the ERSP measure the average time course of relative changes in the spontaneous EEG amplitude spectrum induce by a set of external events.

  14. Plot generated by Pradeep D. Prasad with EEGLAB ERSP

  15. ERSP Computation • Choose a sliding temporal window with suitable size and overlap for the selected EEG epoch. • Do FFT in the window and determine the power spectral density for a frequency bin size of Fn (1 Hz or slightly larger). • Smooth by a moving average window of suitable size in order to eliminate the random jitters.

  16. ERSP Computation (cont) • All smooth window-wise spectral estimates obtained by 2 and 3 are to be normalized by dividing by the spectral estimate of the first window (EEG epoch to be selected such a way prior to 1 that this first estimate will correspond to a pre-stimulus or baseline spectrum).

  17. Measure of ERP Amplitude • Peak amplitude measure. • Mean amplitude measure.

  18. B D F A C E Peak Detection

  19. ERP Latency • Peak latency. • Fractional area latency.

  20. Peak Latency • Latency at which the peak is occurring. Has to be measured with following cautions: • Filter out the high-frequency noise in the EEG. • Rather than taking the maximum peak alone, take other local peaks also (possibly with some threshold), because the maximum peak may not always be due to an ERP waveform.

  21. Peak Latency (cont.) 3. When different waveforms are compared they must have similar noise level.

  22. Fractional Area Latency

  23. References • Majumdar, A brief survey of quantitative EEG (under preparation), Chapters 1 and 4, 2013. • S. J. Luck, An Introduction to Event-Related Potential Technique, MIT Press, Cambridge, Massachusetts, 2005.

  24. THANK YOUThis lecture is available at http://www.isibang.ac.in/~kaushik

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