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Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
Published on: June 29, 2018
Nonlinear dynamical model based control of in vitro hippocampal output
Min-Chi Hsiao1, Dong Song, Theodore W Berger
1Department of Biomedical Engineering, University of Southern California Los Angeles, CA, USA.
Frontiers in Neural Circuits
|February 23, 2013
Summary
This study introduces a novel control strategy for hippocampal prostheses, aiming to restore CA1 responses by optimizing electrical stimulation. This method accurately mimics natural neural activity, paving the way for advanced brain-computer interfaces.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Computational Neuroscience
Background:
- Damage to hippocampal regions like CA3 necessitates methods to restore downstream CA1 responses.
- Current approaches lack precise control over hippocampal output for prosthetic applications.
Purpose of the Study:
- To develop and validate a modeling-control paradigm for precise control of hippocampal CA1 output.
- To reinstate CA1 responses using optimized stimulation, bypassing damaged neural circuitry.
Main Methods:
- Utilized a predictive DG-CA1 nonlinear model (trajectory model) and an inverse CA1 plant model.
- Formulated Laguerre-Volterra kernel models to construct the DG-CA1 trajectory and CA1 plant models.
- Derived an inverse CA1 plant model to determine optimal stimulation parameters from desired outputs.
Main Results:
- The developed paradigm successfully optimized stimulation signals for CA1 region.
- Rat hippocampal slice preparations demonstrated that optimal stimulations accurately replicated control CA1 responses.
- The method effectively reinstated CA1 responses, mimicking those from an intact trisynaptic pathway.
Conclusions:
- The proposed modeling-control paradigm offers a viable strategy for controlling hippocampal output in prosthetic development.
- This approach shows promise for restoring neural function in conditions affecting the hippocampus.
- Validation in ex vivo preparations supports the potential clinical translation of this technology.
