Phase-locked states in oscillating neural networks and their role in neural communication

©2019 Elsevier B.V.All rights reservedThe theory of communication through coherence (CTC) proposes that brain oscillations reflect changes in the excitability of neurons, and therefore the successful communication between two oscillating neural populations depends not only on the strength of the signal emitted but also on the relative phases between them. More precisely, effective communication occurs when the emitting and receiving populations are properly phase locked so the inputs sent by the emitting population arrive at the phases of maximal excitability of the receiving population. To study this setting, we consider a population rate model consisting of excitatory and inhibitory cells modelling the receiving population, and we perturb it with a time-dependent periodic function modelling the input from the emitting population. We consider the stroboscopic map for this system and compute numerically the fixed and periodic points of this map and their bifurcations as the amplitude and the frequency of the perturbation are varied. From the bifurcation diagram, we identify the phase-locked states as well as different regions of bistability. We explore carefully the dynamics of particular phase-locking regimes emphasizing its implications for the CTC theory. In particular, we study how the input gain depends on the timing between the input and the inhibitory action of the receiving population. Our results show that naturally an optimal phase locking for CTC emerges, and provide a mechanism by which the receiving population can implement selective communication. Moreover, the presence of bistable regions, suggests a mechanism by which different communication regimes between brain areas can be established without changing the structure of the network.This work has been partially funded by the Spanish grants MTM2015-65715-P, MDM-2014-0445, PGC2018-098676-B-100, the Catalan grant 2017SGR1049 (GH, AP, TS), the MINECO-FEDER-UE MTM-2015-71509-C2-2-R (GH), and the Russian Scientific Foundation Grant 14-41-00044 (TS). GH acknowledges the RyC project RYC-2014-15866. TS is supported by the Catalan Institution for research and advanced studies via an ICREA academia price 2018. AP acknowledges the FPI Grant from project MINECO-FEDER-UE MTM2012-31714.Peer ReviewedPostprint (author's final draft