Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits

Abstract

Macroscopic oscillations of different brain regions show multiple phase relationships that are persistent across time and have been implicated routing information. Various cellular level mechanisms influence the network dynamics and structure the macroscopic firing patterns. Key question is to identify the biophysical neuronal and synaptic properties that permit such motifs to arise and how the different coherence states determine the communication between the neural circuits. We analyse the emergence of phase locking within bidirectionally delayed-coupled spiking circuits showing global gamma band oscillations. We consider both the interneuronal (ING) and the pyramidal-interneuronal (PING) gamma rhythms and the inter coupling targeting the pyramidal or the inhibitory interneurons. Using a mean-field approach together with an exact reduction method, we break down each spiking network into a low dimensional nonlinear system and derive the macroscopic phase resetting-curves (mPRCs) that determine how the phase of the global oscillation responds to incoming perturbations. Depending on the type of gamma oscillation, we show that incoming excitatory inputs can either only speed up the oscillation (phase advance; type I PRC) or induce both an advance and a delay the macroscopic oscillation (phase delay; type II PRC). From there we determine the structure of macroscopic coherence states (phase locking) of two weakly synaptically-coupled networks. To do so we derive a phase equation for the coupled system which links the synaptic mechanisms to the coherence state of the system. We show that the transmission delay is a necessary condition for symmetry breaking, i.e. a non-symmetric phase lag between the macroscopic oscillations, potentially giving an explanation to the experimentally observed variety of gamma phase-locking modes.

arXiv comment35 pages, 9 figures

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• Phase-locked states in oscillating neural networks and their role in neural communication
• Pulse shape and voltage-dependent synchronization in spiking neuron networks
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• Paradoxical phase response of gamma rhythms facilitates their entrainment in heterogeneous networks