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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
Dynamics of two electrically coupled chaotic neurons: experimental observations and model analysis
P Varona1, J J Torres, H D Abarbanel
1Institute for Nonlinear Science, University of California, San Diego, La Jolla 92093-0402, USA. pvarona@lyapunov.ucsd.edu
Biological Cybernetics
|February 24, 2001
Summary
Researchers modeled lobster neurons to understand chaotic behavior. Coupling these models revealed how slow calcium processes synchronize chaotic neural activity, matching experimental results.
Area of Science:
- Neuroscience
- Computational Biology
- Biophysics
Background:
- Neurons in the lobster stomatogastric ganglion (STG) exhibit complex chaotic behavior.
- Existing models suggest intracellular calcium dynamics contribute to this chaos.
Purpose of the Study:
- To investigate the role of slow subcellular processes in the synchronized and regularized activity of coupled neurons.
- To compare computational model predictions with experimental data from electrically coupled STG neurons.
Main Methods:
- Developed conductance-based computational models of STG neurons incorporating calcium exchange with the endoplasmic reticulum.
- Simulated coupled model neurons with varying electrical (gap junction) connection strengths.
- Compared model outputs to experimental measurements of coupled biological neurons, where coupling strength was modulated by an artificial synapse.
Main Results:
- Model simulations quantitatively reproduced experimental observations of coupled neuron dynamics.
- A sequence of bifurcations was observed, transitioning from in-phase synchronization to uncorrelated chaotic oscillations, and finally to regular out-of-phase behavior.
- The model successfully captured the synchronization and regularization phenomena.
Conclusions:
- Slow subcellular processes, specifically calcium handling, are a plausible mechanism underlying the synchronization and regularization of chaotic neural activity in coupled STG neurons.
- Computational models incorporating these slow dynamics provide a powerful tool for understanding complex neural network behavior.
- The findings highlight the importance of intracellular dynamics in shaping network-level neuronal function.
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