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Related Experiment Video

Updated: Oct 23, 2025

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

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Published on: March 31, 2016

Modulation of the dynamical state in cortical network models.

Chengcheng Huang¹

¹Departments of Neuroscience and Mathematics, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.

Current Opinion in Neurobiology

|August 17, 2021

Summary

Understanding cortical neural responses requires identifying network dynamical states. This review covers models of state-dependent responses and their modulatory mechanisms for flexible circuit computations.

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Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Cortical neural responses are influenced by stimulus inputs and behavioral states.
Understanding circuit mechanisms is key to comprehending flexible computation in neural networks.

Purpose of the Study:

To review recent cortical models of state-dependent responses.
To explore predictions about underlying modulatory mechanisms.

Main Methods:

Review of existing literature on cortical models.
Analysis of models in stable and unstable dynamical regimes.

Main Results:

Identifying network dynamical state is crucial for predicting responses to stimuli and modulatory inputs.
Different analytic tools are needed for stable versus unstable dynamical regimes.

Conclusions:

State-dependent response models offer insights into neural flexibility.
Further research into modulatory mechanisms is warranted.