# Anticipated synchronization in neuronal circuits unveiled by a   phase-resetting curve analysis

**Authors:** Fernanda S. Matias, Pedro V. Carelli, Claudio R. Mirasso, Mauro, Copelli

arXiv: 1703.03444 · 2017-05-31

## TL;DR

This paper investigates the mechanisms of anticipated synchronization in neuronal circuits using phase-resetting curves, revealing the importance of a two-variable PRC approach for accurate predictions and understanding transitions between synchronization regimes.

## Contribution

It introduces a two-variable phase-resetting-curve method to better predict synchronization regimes in neuronal motifs, improving upon traditional single-variable approximations.

## Key findings

- Two-variable PRC is essential for accurate regime prediction.
- Single-variable PRC approximation fails at high inhibitory connectivity.
- The model explains transitions between delayed and anticipated synchronization.

## Abstract

Anticipated synchronization (AS) is a counter intuitive behavior that has been observed in several systems. When AS establishes in a sender-receiver configuration, the latter can predict the future dynamics of the former for certain parameter values. In particular, in neuroscience AS was proposed to explain the apparent discrepancy between information flow and time lag in the cortical activity recorded in monkeys. Despite its success, a clear understanding on the mechanisms yielding AS in neuronal circuits is still missing. Here we use the well-known phase-resetting-curve (PRC) approach to study the prototypical sender-receiver-interneuron neuronal motif. Our aim is to better understand how the transitions between delayed to anticipated synchronization and anticipated synchronization to phase-drift regimes occur. We construct a map based on the PRC method to predict the phase-locking regimes and their stability. We find that a PRC function of two variables, accounting simultaneously for the inputs from sender and interneuron into the receiver, is essential to reproduce the numerical results obtained using a Hodgkin-Huxley model for the neurons. On the contrary, the typical approximation that considers a sum of two independent single-variable PRCs fails for intermediate to high values of the inhibitory connectivity between interneuron. In particular, it looses the delayed-synchronization to anticipated-synchronization transition.

## Full text

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## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/1703.03444/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/1703.03444/full.md

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Source: https://tomesphere.com/paper/1703.03444