Adaptation reduces variability of the neuronal population code

Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calculate the interval and count statistics of superimposed processes governed by a slow adaptation variable. For an ensemble of neurons with spike-frequency adaptation, this results in the regularization of the population activity and an enhanced postsynaptic signal decoding. We confirm our theoretical results in a population of cortical neurons recorded in vivo.


Published in:
Physical Review E, 83, -
Year:
2011
Keywords:
Laboratories:




 Record created 2011-12-16, last modified 2018-03-17


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