Dj. Amit et N. Brunel, MODEL OF GLOBAL SPONTANEOUS ACTIVITY AND LOCAL STRUCTURED ACTIVITY DURING DELAY PERIODS IN THE CEREBRAL-CORTEX, Cerebral cortex, 7(3), 1997, pp. 237-252
We investigate self-sustaining stable states (attractors) in networks
of integrate-and-fire neurons. First, we study the stability of sponta
neous activity in an unstructured network. It is shown that the stocha
stic background activity, of 1-5 spikes/s, is unstable if all neurons
are excitatory. On the other hand, spontaneous activity becomes self-s
tabilizing in presence of local inhibition, given reasonable values of
the parameters of the network. Second, in a network sustaining physio
logical spontaneous rates, we study the effect of learning in a local
module, expressed in synaptic modifications in specific populations of
synapses. We find that if the average synaptic potentiation (LTP) is
too low, no stimulus specific activity manifests itself in the delay p
eriod. Instead, following the presentation and removal of any stimulus
there is, in the local module, a delay activity in which all neurons
selective (responding visually) to any of the stimuli presented for le
arning have rates which gradually increase with the amplitude of synap
tic potentiation; When the average LTP increases beyond a critical val
ue, specific local attractors (stable states) appear abruptly against
the background of the global uniform spontaneous attractor. In this ca
se the local module has two available types of collective delay activi
ty: if the stimulus is unfamiliar, the activity is spontaneous; if it
is similar to a learned stimulus, delay activity is selective. These n
ew attractors reflect the synaptic structure developed during learning
. In each of them a small population of neurons have elevated rates, w
hich depend on the strength of LTP. The remaining neurons of the modul
e have their activity at spontaneous rates. The predictions made in th
is paper could be checked by single unit recordings in delayed reponse
experiments.