Abstract
A neuronal network inspired by the anatomy of the
cerebral cortex was simulated to study the
self-organization of spiking neurons into neuronal
groups. The network consisted of 100 000 reentrantly
interconnected neurons exhibiting known types of
cortical firing patterns, receptor kinetics, short-term
plasticity and long-term spike-timing-dependent
plasticity (STDP), as well as a distribution of axonal
conduction delays. The dynamics of the network allowed
us to study the fine temporal structure of emerging
firing patterns with millisecond resolution. We found
that the interplay between STDP and conduction delays
gave rise to the spontaneous formation of neuronal
groups -- sets of strongly connected neurons capable of
firing time-locked, although not necessarily
synchronous, spikes. Despite the noise present in the
model, such groups repeatedly generated patterns of
activity with millisecond spike-timing precision.
Exploration of the model allowed us to characterize
various group properties, including spatial
distribution, size, growth, rate of birth, lifespan,
and persistence in the presence of synaptic turnover.
Localized coherent input resulted in shifts of
receptive and projective fields in the model similar to
those observed in vivo.
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