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Comodulation and Coherence in Normal and Clinical Populations

Comodulation and Coherence in Normal and Clinical Populations. Chagall Birthday. David A Kaiser, Ph.D. Rochester Institute of Technology. Defining my terms. Raw EEGs are voltages across time In time domain , we estimate amplitude (positive and negative values)

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Comodulation and Coherence in Normal and Clinical Populations

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  1. Comodulation and Coherence in Normal and Clinical Populations Chagall Birthday David A Kaiser, Ph.D. Rochester Institute of Technology

  2. Defining my terms • Raw EEGs are voltages across time • In time domain, we estimate • amplitude (positive and negative values) • at a sample rate (only positive) • In frequency domain, we estimate • magnitude (only positive) • phase (positive and negative) • at a frequency • Spectral power is magnitude squared

  3. How similar are two signals? • Cross-correlation reveals similarities in time between signals. (e.g., Barlow, 1951; Brazier & Casby, 1951) • Cross-spectral analysis reveals similarities in frequency… [next slide]

  4. How similar are two signals? • Cross-spectral analysis reveals similarities in frequency. • Signals may be similar in phase, magnitude, or both • phase analysis: coherence (Goodman, 1957; Walter, 1961) • magnitude analysis: comodulation (Pearson, 1896; Kaiser, 1994) For example, does cortical activity become more or less similar after treatment?

  5. Cross-spectral analysis Coherence estimates phase consistency Comodulation estimates magnitude consistency …between signals at each specified frequency across time Coh = average normalized cross-spectrum amplitude2 Comod = average normalized cross-product amplitude Coh range from 0.0 to 1.0 Comod range from -1.0 to 1.0 Confusing point: Tukey called “coherency” the square root of coherence

  6. Comodulation was invented to examine low spatial resolution concerns of EEG topography (e.g., volume conduction, Nunez, 1990) Does surface EEG reflect cortical potentials well? - if not, all neighbors will be equally correlated with each other - if so, correlations will be stronger within functionally-related areas

  7. …coherent if their phase relationship is stable …comodulated if their magnitude relationship is stable Signals are …

  8. Coherence analysis provides • Coherence (Coh) • Phase delay (+/-180o) • Comodulation analysis provides • Comodulation (Comod) • Proportion: Site 1/Site 2

  9. Functional model for dominant frequency • ...suggests common response • Multiple networks (related but dissimilar) organize neural activity • ...suggests common generator • Single network organizes neural activity

  10. Coherent but not comodulated Pacemaker network unified Primitive recruitment Synchronization Comodulated but not coherent Pacemaker network partly segregated by cortical feedback Complex recruitment Coordination

  11. Fastforward system Drivers Thalamocortical projections Fast, focal, strong (Momentary) Consciousness Feedback system Modulators Corticothalamic projections Slow, diffuse, weak Sustained consciousness (i.e., self-)

  12. Why comodulation analysis is performed on magnitude (mV) and not on power (mV2) • Brief history of power spectral analysis in EEG • Dietsch (1932) analyzed 7 EEG signals using Fourier (1831). • Cooley & Tukey (1965) invented FFT algorithm, reducing computer workload, allowing practical spectral applications • Dumermuth & Fluhler (1967) applied FFT to EEG • BUT ...

  13. Why assume brain rhythms and mental activity are related by a power function? Are changes in brain behavior actually associated with largerchanges in mental behavior (i.e. reason for using the power spectrum)? • Might brain and mind activity be more linearly related at this level of investigation (i.e., reason for using the magnitude spectrum)?

  14. Comodulation versus Coherence Data sets THANKS to Jolene Ross & Jim Caunt for ADHD, some of the AS data; Coralee Thompson for normal children

  15. EEG Comodulation and Coherence values are often very similar! Eyes Closed Replications Within subject, n=20 EC1 v 2: r = .91 Coh r = .84 Comod Being more reliable also can mean less sensitive to state differences • Dark bars = Comod Red/green bars = Coherence

  16. How to read our Comod & Coh maps Rho DATA Z-SCORE from norms

  17. If you build it (adult pattern of frontal lobe myelination), it still takes time for them to come… Typical Atypical(25 college students) (1 college student)

  18. MTBI patient Rage Disorder

  19. Autobiography dysfunction associated with reduced right anterior temporal pole connectivity (Asperger’s, Schizophrenia)

  20. Hypermodulations after stroke, 74yF (seen during math task only!)

  21. Autism as severe global disconnectivity

  22. Asperger v Child Norms8-12 Hz (in Std Error)

  23. ADHD v Child Norms 8-12 Hz (in Std Error)

  24. Life is about making connections... Global Comodulation by age19-site mean of 18 comparisons each site

  25. …but not too fast!... Beta hypercoherence between occipital and medial frontal cortex, esp. right-sided, during rest for Asperger children (resembles adult pattern)

  26. …in fact, slowing down the rate of connections at some times in your life may even do you some good!One form of Intelligence (neotenous) resists the natural neural integration trajectory Neural & “behavioral” (Ph.D) indices of neoteny

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