State-space optimal feedback control of optogenetically driven neural activity.
State-space optimal feedback control of optogenetically driven neural activity.
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DOI：
10.1088/1741-2552/abb89c
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发表时间：
2021-03-31
影响因子：
4
通讯作者：
Stanley GB
中科院分区：
文献类型：
--
作者：
Bolus MF;Willats AA;Rozell CJ;Stanley GB
用于记录神经元种群和定向光遗传操作的工具的快速加速使大脑中神经元回路的实时反馈控制成为可能。测量神经元活动的连续分级控制提出了广泛的技术挑战，我们通过在清醒小鼠的丘脑皮质回路中实施的光遗传刺激和状态空间最优控制框架的组合来解决这些挑战。通过刺激头部固定小鼠体感觉丘脑中表达的通道视紫红质-2，实时实现神经元的闭环光遗传控制。采用一种状态空间线性动力系统模型结构来近似多电极阵列记录单神经元和多神经元场景下的光-峰输入-输出关系。利用这些模型通过线性二次最优控制来设计状态反馈控制器增益，并在线用于状态反馈估计，其中参数自适应卡尔曼滤波器对模型失配具有鲁棒性。实验证明，这种基于模型的控制方法对清醒动物丘脑单神经元放电速率的反馈控制是有效的。值得注意的是，这里使用的分级光学驱动并没有同步同时记录的神经元，但神经元群体的异质性导致了对刺激的不同反应。模拟的多输出反馈控制提供了对异质种群的更好控制，并演示了该方法如何推广到单神经元应用之外。据我们所知，这项工作代表了基于状态空间模型的光遗传刺激反馈控制的第一个实验应用。与线性二次最优控制相结合，这里的方法应该推广到涉及高度复杂神经回路控制的未来问题。更一般地说，神经元回路的反馈控制为自适应地与潜在的感觉、运动和认知信号的动态相互作用打开了大门，使我们能够更深入地了解回路功能，并最终控制损伤或疾病中的功能。
The rapid acceleration of tools for recording neuronal populations and targeted optogenetic manipulation has enabled real-time, feedback control of neuronal circuits in the brain. Continuously-graded control of measured neuronal activity poses a wide range of technical challenges, which we address through a combination of optogenetic stimulation and a state-space optimal control framework implemented in the thalamocortical circuit of the awake mouse. Closed-loop optogenetic control of neurons was performed in real-time via stimulation of channelrhodopsin-2 expressed in the somatosensory thalamus of the head-fixed mouse. A state-space linear dynamical system model structure was used to approximate the light-to-spiking input-output relationship in both single-neuron as well as multi-neuron scenarios when recording from multielectrode arrays. These models were utilized to design state feedback controller gains by way of linear quadratic optimal control and were also used online for estimation of state feedback, where a parameter-adaptive Kalman filter provided robustness to model-mismatch. This model-based control scheme proved effective for feedback control of single-neuron firing rate in the thalamus of awake animals. Notably, the graded optical actuation utilized here did not synchronize simultaneously recorded neurons, but heterogeneity across the neuronal population resulted in a varied response to stimulation. Simulated multi-output feedback control provided better control of a heterogeneous population and demonstrated how the approach generalizes beyond single-neuron applications. To our knowledge, this work represents the first experimental application of state space model-based feedback control for optogenetic stimulation. In combination with linear quadratic optimal control, the approaches here should generalize to future problems involving the control of highly complex neural circuits. More generally, feedback control of neuronal circuits opens the door to adaptively interacting with the dynamics underlying sensory, motor, and cognitive signaling, enabling a deeper understanding of circuit function and ultimately the control of function in injury or disease.
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