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Related Experiment Video

Updated: Jul 26, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

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Published on: March 2, 2015

Multistability in neural systems with random cross-connections.

Jordan Breffle¹, Subhadra Mokashe¹, Siwei Qiu^2,3

¹Neuroscience Program, Brandeis University, 415 South St, Waltham, MA 02454.

Biorxiv : the Preprint Server for Biology

|June 19, 2023

Summary

This summary is machine-generated.

Neural circuits can exhibit multiple stable states (multistability) through network interactions, not just self-excitation. This network effect is crucial for complex cognitive functions supported by neural systems.

Keywords:

Attractor basin bistable fixed points mean field

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Area of Science:

Computational Neuroscience
Systems Neuroscience
Cognitive Neuroscience

Background:

Neural circuits with multiple attractor states are hypothesized to underlie cognitive tasks.
Previous models often assume individual units possess sufficient self-excitation for bistability.

Conclusions:

Network interactions are a key mechanism for achieving multistability in neural systems.
The structure of neuronal connectivity and unit properties critically determine the emergence of multiple stable states.
These findings provide insights into the neural basis of cognitive flexibility and information processing.