How Neurons May Respond to Temporal Structure in Their Inputs
The way in which a neuron responds to temporal structure in its synaptic input stream is an issue of fundamental importance in the study of nervous system function. One historically significant notion that has resurfaced frequently within the field of neuroscience entails that spiking neurons act as “coincidence detectors”, i.e. generating an output spike only when a sufficient set of inputs is activated quasi-synchronously. The biophysical justification for this notion is straightforward: any neuron whose time constant of integration is relatively short, and whose firing threshold is relatively high and sharp, would seem to qualify as a neuronal coincidence detector. Canonical exemplars of such cells have been found in the auditory brainstem specialized for detecting simultaneous arrival of action potentials from the left and right ears.  has argued for the utility of neuronal coincidence detection in his theory of “synfire chains”, which would allow long sequences of neuronal activation patterns to be preserved in the cortex. Recent discoveries of both oscillations and short-and long-rage correlations among spike trains in cerebral cortical neurons  has rekindled interest in temporal structure in neuronal spike trains, has led to a variety of physical models for the genesis of either oscillatory, random, and/or synchronous spike trains (e.g. ), and has motivated a variety of models for the possible functional roles of temporal structure in neuronal spike trains, such as for selective visual attention [9, 8], or visual awareness .
KeywordsSpike Train Selective Visual Attention Cerebral Cortical Neuron Voltage Trace Synfire Chain
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