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Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

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Dynamic range of hypercubic stochastic excitable media.

Vladimir R V Assis¹, Mauro Copelli

¹Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, 50670-901 Recife, PE, Brazil. vladimirassis@df.ufpe.br

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|March 21, 2008

Summary

This study reveals that excitable networks show optimal response at a critical transition point. Maximum sensitivity and dynamic range decrease with increasing network dimensions.

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External Excitation of Neurons Using Electric and Magnetic Fields in One- and Two-dimensional Cultures

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Published on: May 7, 2017

Area of Science:

Statistical Physics
Complex Systems
Network Science

Background:

Excitable networks are crucial in various natural phenomena, from neural activity to epidemic spread.
Understanding their response to external stimuli is key to predicting system behavior.
Previous work has explored network dynamics, but optimal response characterization remains an active area.

Purpose of the Study:

To investigate the response properties of d-dimensional hypercubic excitable networks under stochastic stimulation.
To determine how network dimension influences the dynamic range and sensitivity of the response function.
To identify conditions for maximized network responsiveness.

Main Methods:

Modeling sites using three-state susceptible-infected-recovered-susceptible (SIRS) systems or probabilistic Greenberg-Hastings cellular automata.
Applying continuous, independent external Poisson stimulation (rate h) to each site.
Employing simulations for d=1,2,3,4 and mean-field approximations (single-site and pair levels) for all d to obtain the response function (mean active site density rho vs. h).

Main Results:

The dynamic range and sensitivity of the response function are maximized at the nonequilibrium phase transition to self-sustained activity across all studied dimensions.
This optimization aligns with recent theoretical proposals regarding critical phenomena.
The maximum dynamic range achieved is inversely related to the network dimension (d).

Conclusions:

The nonequilibrium phase transition is a critical point for optimizing the responsiveness of excitable networks.
Network dimensionality fundamentally impacts the achievable dynamic range, with higher dimensions leading to reduced sensitivity.
Findings provide insights into designing or understanding systems where optimal signal detection is crucial.