Characteristics of the synchronization of brain activity imposed by finiteconduction velocities of axons

The electrical activity of neurons in brains fluctuates erratically both in terms of pulse trains of single neurons and the dendritic currents of popu lations of neurons. Obviously the neurons interact with one another in the production of intelligent behavior, so it is reasonable to expect to find e vidence for varying degrees of synchronization of their pulse trains and de ndritic currents in relation to behavior. However, synaptic communication b etween neurons depends on propagation of action potentials between neurons, often with appreciable distances between them, and the transmission delays are not compatible with synchronization in any simple way. Evidence is on hand showing that the principal form of synchrony is by establishment of a low degree of covariance among very large numbers of otherwise autonomous n eurons, which allows for rapid state transitions of neural populations betw een successive chaotic basins of attraction along itinerant trajectories. T he small fraction of covariant activity is extracted by spatial integration upon axonal transmission over divergent-convergent pathways, through which a remarkable improvement in signal-to-noise ratio is achieved. The raw tra ces of local activity show little evidence for synchrony, other than zero-l ag correlation, which appears to be largely a statistical artifact. Brains rely less on tight phase-locking of small numbers of periodically firing ne urons and more on low degrees of cooperativity achieved by order parameters influencing very large numbers of neurons. Brains appear to be indifferent to and undisturbed by widely varying time and phase relations between indi vidual neurons and even large semi-autonomous areas of cortex comprising th eir mesoscopic neural masses.