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State-space optimal feedback control of optogenetically driven neural activity.
M F Bolus1, A A Willats1, C J Rozell2
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, United States of America.
Journal of Neural Engineering
|September 15, 2020
Summary
Researchers developed a novel feedback control system using optogenetics and state-space models for real-time brain circuit manipulation. This method effectively controlled neuronal firing rates in awake mice, advancing neuroscience research.
Area of Science:
- Neuroscience
- Control Systems Engineering
- Biomedical Engineering
Background:
- Advances in optogenetics and neuronal recording enable real-time brain circuit manipulation.
- Controlling neuronal activity with precision presents significant technical challenges.
- The thalamocortical circuit in awake mice serves as a model system for studying neural dynamics.
Purpose of the Study:
- To develop and experimentally validate a state-space optimal control framework for real-time, graded optogenetic manipulation of neuronal activity.
- To address challenges in achieving precise, continuous control over neuronal firing rates.
- To demonstrate the applicability of this control approach in the somatosensory thalamus of awake mice.
Main Methods:
- Closed-loop optogenetic control using channelrhodopsin-2 stimulation in the somatosensory thalamus.
- State-space linear dynamical system models to approximate light-to-spiking relationships.
- Linear quadratic optimal control for designing state feedback gains.
- Parameter-adaptive Kalman filtering for robust state estimation.
Main Results:
- Effective feedback control of single-neuron firing rate in the thalamus of awake animals was achieved.
- Graded optical stimulation did not synchronize simultaneously recorded neurons, highlighting population heterogeneity.
- Simulated multi-output feedback control demonstrated improved population control and generalizability.
Conclusions:
- This study presents the first experimental application of state-space model-based feedback control for optogenetic stimulation.
- The combined approach of state-space modeling and linear quadratic optimal control offers a robust framework for complex neural circuit control.
- This methodology enables adaptive interaction with neural dynamics, facilitating a deeper understanding of brain function and potential therapeutic applications.
