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Spatial EEG Patterns, Non-linear Dynamics and Perception: the Neo-Sherringtonian View

  • Author(s): Freeman, Walter J, III
  • Skarda, Christine A
  • et al.
Creative Commons Attribution 4.0 International Public License
Abstract

 Spatial analysis with preamplifier arrays and computers offers fresh perspectives on brain function. Realization of its potential depends on development of appropriate procedures for data processing and display, experimental paradigms to serve as benchmarks, and theories of brain function to predict what to look for and how to distinguish valid results from artifacts. Measurement of EEGs from arrays of 64 electrodes chronically implanted on the olfactory bulbs of rabbits that are trained to discriminate odorant conditioned stimuli show that the odorants induce spatially distinctive amplitude patterns of neural activity. The odor-specific information density is inferred to be uniform over the whole main bulb. The neural dynamics that produce these activity patterns emerge from the synaptically interactive sheet of excitatory mitral and inhibitory granule cells with distributed input and output tracts and with static non-linearities deriving from the nerve impulse mechanism. Excitatory synapses between mitral cells are subject to modification when odorants are paired with unconditioned stimuli, thus forming nerve cell assemblies. Odorant-specific information established by a stimulus locally in the bulbar unit activity is integrated with past experience by an assembly, disseminated over the entire bulb on the order of 100 mm2 in area in a time period of 2.5 ms, and sustained for a time period on the order of 0.1 s. An arbitrary spatial sample on the order of 20% of bulbar EEG activity captures the entire integrated information albeit at lesser resolution than the whole. This synaptic mechanism of local input and global output may be common to all of the cerebral cortex. The implications are discussed for neocortical sensory systems, motor pattern generators, and goal-directed behavior in the context of self-organizing non-linear dynamic systems.

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