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Updated: Aug 9, 2025

3D Modeling of Dendritic Spines with Synaptic Plasticity
Published on: May 18, 2020
Noise-modulated multistable synapses in a Wilson-Cowan-based model of plasticity
Caroline A Lea-Carnall1, Lisabel I Tanner1, Marcelo A Montemurro2
1School of Health Sciences, Manchester Academic Health Science Centre, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.
Neural noise can optimize synaptic plasticity by influencing the stability of neural populations. Controlling noise intensity is key to regulating plasticity outcomes in brain stimulation.
Area of Science:
- Computational neuroscience
- Neural plasticity modeling
Background:
- Frequency-dependent plasticity is crucial for synaptic strength changes.
- The role of neural noise in plasticity remains unclear.
- Neural noise is inherent in brain function and relevant for brain stimulation.
Purpose of the Study:
- Investigate how neural noise affects synaptic plasticity in interacting neural populations.
- Explore the influence of noise on different stable states within the Wilson-Cowan model.
- Determine the impact of noise intensity on plasticity dynamics.
Main Methods:
- Utilized a Wilson-Cowan (WC) model of interacting neural populations.
- Incorporated activity-dependent synapses and periodic stimulation.
- Applied controlled noise intensity to simulate brain noise.
Main Results:
- Synaptic strength optimization observed within a specific noise variance range.
- Identified a triple-stable state for synaptic strength at certain noise intensities.
- Demonstrated that noise intensity regulates the probability of system state selection, controlling plasticity.
Conclusions:
- Neural noise significantly influences the outcome of stimulation-induced plasticity.
- Noise intensity acts as a critical parameter for controlling synaptic plasticity.
- Findings suggest potential for noise modulation in therapeutic brain stimulation.
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