Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity

Abstract

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.Neurons express a large diversity in terms of their biochemical, morphological and electrophysiological properties 1-4 . However, it is not clear if and under which conditions such diversity plays a functional role. It has been shown that selective stimulation of neurons of a given type expressing specific bio-markers can modulate different aspects of brain function 5 . For instance, selective stimulation of neurons changes the excitation/inhibition balance 6 , network dynamics 7,8 and computations performed by the network 9 , thereby leading to an altered animal behaviour. Moreover, noise introduced by intrinsic properties of neurons/synapses can have several effects. It can render the dynamics more robust to perturbations 10 and can improve the encoding and decoding of neuronal activity by reducing correlations 11 . These experiments provide strong support to the 'neuron doctrine' and motivate the search for novel bio-markers and specific functions of different classes of neurons 4,12 . However, experiments also suggest that stimulation of a certain neuron type may not cause any discernible change in the population activity and animal behaviour 13 . Moreover, detailed models of single neurons 14 and networks 15 have shown that multiple combinations of neuron and synapse parameters can lead to similar activity states 16 ; suggesting that exact neuronal properties are not crucial to obtain a specific dynamical network state and, hence, a specific function.These conflicting studies make it important to identify: (1) Changes in neuron properties that can affect network dynamics. (2) Dynamical states in which the network activity is susceptible to changes in a certain neuronal property. Here we focus on the effect of spike bursting on the network activity dynamics and vice versa. Spike bursting is a common electrophysiological descriptor of a neuron type 17,18 . The fraction of bursting neurons depends on the brain region 19 , and even in a given brain region the firing rate of spike bursts may change ...

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