# Reconstructing networks of pulse-coupled oscillators from spike trains

## TL;DR

This paper introduces an iterative method to reconstruct neural oscillator networks from spike train data, accurately recovering node properties and connection strengths based on phase response curves and pulse interactions.

## Contribution

It presents a novel approach for network reconstruction of pulse-coupled oscillators from passive spike train observations, including phase response curves and connection strengths.

## Key findings

- Successfully reconstructs network properties from spike trains
- Recovers phase response curves and natural frequencies
- Determines directed connection strengths

## Abstract

We present an approach for reconstructing networks of pulse-coupled neuron-like oscillators from passive observation of pulse trains of all nodes. It is assumed that units are described by their phase response curves and that their phases are instantaneously reset by incoming pulses. Using an iterative procedure, we recover the properties of all nodes, namely their phase response curves and natural frequencies, as well as strengths of all directed connections.