Synthetic reverberating activity patterns embedded in networks of cortical neurons

TL;DR

This paper presents a method to generate and analyze synthetic reverberating activity patterns in cortical neuron networks, exploring how delays and network dynamics affect these patterns.

Contribution

It introduces a novel experimental approach to create programmable activity patterns in neural networks and assesses their sensitivity to various parameters.

Findings

Reverberating activity patterns can be artificially generated in cortical networks.

Transmission delays influence the stability of activity patterns.

Ongoing network dynamics affect pattern robustness.

Abstract

Synthetic reverberating activity patterns are experimentally generated by stimulation of a subset of neurons embedded in a spontaneously active network of cortical cells in-vitro. The neurons are artificially connected by means of conditional stimulation matrix, forming a synthetic local circuit with a predefined programmable connectivity and time-delays. Possible uses of this experimental design are demonstrated, analyzing the sensitivity of these deterministic activity patterns to transmission delays and to the nature of ongoing network dynamics.