Neural Network Model for Apparent Deterministic Chaos in Spontaneously Bursting Hippocampal Slices

TL;DR

This study presents a neural network model that mimics hippocampal bursting, showing that observed complex dynamics may not necessarily indicate true deterministic chaos, urging caution in interpreting experimental data.

Contribution

The paper introduces a neural network model reproducing bursting behavior and demonstrates that similar UPO-like trajectories can arise without true chaos, challenging previous interpretations.

Findings

Model exhibits UPO-like trajectories similar to experiments

Control methods and surrogate analysis produce comparable results

Results question the interpretation of experimental data as deterministic chaos

Abstract

A neural network model that exhibits stochastic population bursting is studied by simulation. First return maps of inter-burst intervals exhibit recurrent unstable periodic orbit (UPO)-like trajectories similar to those found in experiments on hippocampal slices. Applications of various control methods and surrogate analysis for UPO-detection also yield results similar to those of experiments. Our results question the interpretation of the experimental data as evidence for deterministic chaos and suggest caution in the use of UPO-based methods for detecting determinism in time-series data.