Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons



Asynchronous activity in balanced networks of excitatory and inhibitory neurons is believed to constitute the primary medium for the propagation and transformation of information in the neocortex. Here we show that an unstructured, sparsely connected network of model spiking neurons can display two fundamentally different types of asynchronous activity that imply vastly different computational properties. For weak synaptic couplings, the network at rest is in the well-studied asynchronous state, in which individual neurons fire irregularly at constant rates. In this state, an external input leads to a highly redundant response of different neurons that favors information transmission but hinders more complex computations. For strong couplings, we find that the network at rest displays rich internal dynamics, in which the firing rates of individual neurons fluctuate strongly in time and across neurons. In this regime, the internal dynamics interact with incoming stimuli to provide a substrate for complex information processing and learning.

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Figure 1: Instability of the asynchronous state in a network of LIF neurons.
Figure 2: Instability of the asynchronous state in a network of Poisson neurons.
Figure 3: Strong synaptic couplings lead to highly fluctuating instantaneous firing rates of individual neurons.
Figure 4: Temporal inputs are processed differently in the two types of resting asynchronous activity.
Figure 5: Influence of network parameters on asynchronous activity.


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The author is grateful to N. Brunel, V. Hakim, D. Martí and M. Stern for discussions and feedback on the manuscript. This work was supported by France's Agence Nationale de la Recherche ANR-11-0001-02 PSL* and ANR-10-LABX-0087.

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Ostojic, S. Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons. Nat Neurosci 17, 594–600 (2014).

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