Brain Waves: Is Synchrony a Sign of Higher Function? Is the EEG Basically Rhythmic?
Higher centers and higher animals seem to show more EEG synchrony than brainstem or nonmammalian forebrain. Yet sleeping and seizure states are thought to be excessively synchronized. In place of synchrony would some measure of extent and variety of forms of cooperativity correlate better with higher function? Despite more than 50 years of research, we still have little idea how much synchrony there is in the EEG, how that varies among states of the brain, parts of the brain and major groups of animals or how any other form of cooperativity is distributed among the diverse cellular and subcellular generators in a given volume. In most animals most of the time no obvious rhythms are widespread in the forebrain.
Among the opportunities and needs for EEG research, which include new attention to DC and infraslow shifts, not further developed here, I lift up the neglect of the semimicro-scale in space, from about 0.5 to 5 mm and the time domain from about 0.2 to 2 sec. I claim there is most probably an information-rich world in these dimensions. We urgently need many-channeled recording with wide-band amplifiers and novel analytical algorithms to tap this information, if not to decode and understand the local processing, then at least for descriptors that will reveal differences between states, parts and species. The EEG has evolved although we have recognized little evidence of it, aside from amplitude.
Our present methods are as limited as would be those of an anthropologist trying to distinguish commonalities from differences in the vocalizations of football crowds in Britain, bullfight crowds in Spain and chattering monkeys at the zoo by using microphones above the crowds and linear spectral analyses that treat epochs of several seconds as stationary. The analogy is chosen to include fluctuating tendencies for groups of individuals, scattered or all together, to synchronize their voices. Even given the advantage of synchrony, as distinct from the cocktail party, understanding depends on learning the rudiments of the languages; discerning the significant differences between the three kinds of sources depends on hearing many samples and learning the invariants. A parallel effort on the comparative study of brain activity, using high temporal and spatial resolution, on many samples, and human pattern recognizers in visual and auditory realms, pending the appropriate computer programs, might well turn up species-, state-and stage-specific features, or at least those which distinguish higher taxa (orders, classes and phyla) and major segments of the forebrain.
Scalp recordings cannot predict the EEG recorded intracerebrally or even subdurally, on the surface, since it filters in favor of low frequencies and in addition selects from the brain activity that which tends to be synchronous over the large cone of tissue “seen” by each electrode. Likewise, the subdural EEG cannot predict the intracortical micro-EEG which shows even more local sign. Evidence is cited to question the common view that the ongoing activity of the brain as recorded from the pial surface or from intracerebral electrodes is basically a mixture of sinusoidal oscillations. True rhythms may occur, such as alpha, theta and gamma waves in special conditions and places. The evidence for the usual micro-EEG points, instead, to a large number of small and local generators mainly emitting sharp-cornered events with broad spectra, such as synaptic potentials or abrupt transients that may, but need not be periodic.
Coherence of all bands in the subdural EEG tends to fall within millimeters to levels indistinguishable from noise; as it fluctuates with both space and time, all bands tend to decrease or increase in coherence together. Coherence for each band fluctuates with time, typically with from one to three apparent periods, usually in the range 0.3-0.03 Hz. Bispectrum and bicoherence analyses show that many frequencies are typically coupled, i.e. are much more often in phase than would be true by coincidence among independent oscillators but not unexpectedly if a significant part of the power comes from broad-band events which could be either transients or more or less regularly recurrent. The cross-bispectrum and cross-bicoherence results indicate, on preliminary evidence, that this form of nonlinear cooperativity among cellular generators constitutes a significant fraction of the cortical EEG power in both mammals and reptiles.
KeywordsPower Spectrum Slow Wave Time Structure Humpback Whale Brain Wave
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