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Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
Published on: October 18, 2015
10.1K
Modelling cortical network dynamics.
Gerald Kaushallye Cooray1,2, Richard Ewald Rosch3,4, Karl John Friston3
1Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
SN Applied Sciences
|February 1, 2024
Summary
Current-to-current coupling in neural networks enables semi-stable states, leading to dynamics akin to the Kuramoto model. This research models seizure propagation and could aid epilepsy surgery planning.
Area of Science:
- Computational Neuroscience
- Theoretical Neuroscience
- Systems Neuroscience
Background:
- Cortical columns, composed of neural masses, exhibit semi-stable states influenced by synaptic kernel interactions.
- Current-to-current coupling facilitates semi-stable states, unlike potential-to-current coupling.
Purpose of the Study:
- Investigate theoretical constraints of coupled cortical column interactions.
- Derive dynamics for collective activity in interacting semi-stable states.
- Develop a seizure propagation model for clinical applications.
Main Methods:
- Modeled neural populations as neural masses within cortical columns.
- Derived coupled phase and amplitude dynamics, extending the Kuramoto model.
- Developed a seizure propagation model using Laplace transform (Dynamic Causal Modelling).
Main Results:
- Identified current-to-current coupling as crucial for semi-stable states in cortical columns.
- Derived novel coupled equations for phase and amplitude dynamics, allowing dynamic connectivity.
- Turbulent phase dynamics correlate with observed changes in dynamic connectivity during epileptic seizures.
Conclusions:
- The derived model captures turbulent phase dynamics, mirroring epileptic seizure activity.
- The seizure propagation model, validated on simulated data, shows potential for predicting seizure evolution.
- Future work will focus on estimating connectivity matrices from empirical data for clinical use in epilepsy surgery.
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