Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity
2016 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, 26029Article in journal (Refereed) Published
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.
Place, publisher, year, edition, pages
2016. Vol. 6, 26029
Neuronal networks, neuron types, spike bursting, oscillations
IdentifiersURN: urn:nbn:se:kth:diva-187474DOI: 10.1038/srep26029OAI: oai:DiVA.org:kth-187474DiVA: diva2:930447
QC 201605252016-05-242016-05-242016-06-10Bibliographically approved