Somatosensory feedback controlling a neuroprosthesis

描述（由申请人提供）：拟议的研究计划将服务于神经科学和神经工程的互补目标。神经科学的目标是进一步了解在多关节肢体控制中的躯体感觉反馈的作用和性质。工程目标是设计一个系统，用于从初级传入神经元的放电率调制中提取肢体状态信息（例如肢体位置和速度）。功能性电刺激系统的闭环控制需要状态反馈，功能性电刺激系统用于恢复因脊髓或其他中枢神经系统损伤而瘫痪的肌肉的动作。为了实现这些目标，我们正在使用最先进的技术，使大量的传入神经元能够在自然运动行为（如站立，行走和伸手）中同时和长期记录。多通道记录对于这项工作是必不可少的，因为关节运动有多个自由度，并且有几个不同的运动学和动力学状态变量，这些变量对于闭环控制应用是有意义的。这些数据还允许直接检查初级传入神经元在被称为本体感受的身体状态感知中的作用和性质，本体感受是通过整合多个初级传入神经元输入形成的。该提案将实现4个具体目标，每个目标都是实现上述更广泛目标的渐进式进展。具体目标1是使用信息理论量化在以下条件下由单个神经元传达的肢体状态信息：1）完整脊髓，2）急性横断脊髓，和3）慢性横断脊髓。这些结果将用于评估脊髓损伤前后初级传入神经元传递的信息的质量和可靠性的变化，脊髓损伤是一种已知导致脊髓神经元回路可塑性变化的疾病，可能会改变肌梭的反应特性。使用去脑猫准备，将研究后肢的以下状态变量：位置、速度、加速度、终点力（例如站立期间的地面反作用力）和站立阶段关节扭矩。神经记录将在连接到脚的机器人手臂施加的肢体运动期间进行。状态变量将在基于内在关节空间坐标（即节段间角度）或外在端点空间坐标（即脚趾相对于髋关节的笛卡尔坐标或极坐标）的参考系中测量，以比较传入神经元携带的状态信息依赖于所选参考系的程度。具体目标2是使用SA-1中收集的数据，开发数学模型，以解码来自同时记录的传入神经元集合的位置，速度，力和扭矩信息。具体目标3是解码近实时，肢体状态的传入神经元的合奏放电率记录在后肢步进运动诱发的被动运动和固定模式的电刺激在完整的脊髓和慢性脊髓去脑猫。具体目标4是实现在线状态反馈解码（SA-3）在有限状态控制系统的FES诱发的后肢步进完整的脊髓和慢性脊髓去脑猫。

DESCRIPTION (provided by applicant): The proposed research program will serve complementary objectives in neuroscience and neural engineering. The neuroscience objective is to further knowledge of the role and nature of somatosensory feedback in multi-joint limb control. The engineering objective is to design a system for extracting limb-state information (e.g. limb position and velocity) from the firing rate modulations of primary afferent neurons. State feedback is required for closed-loop control of functional electrical stimulation systems, which are used to restore action to muscles paralyzed by spinal cord or other central nervous system injuries. To achieve these goals, we are using state-of-the-art technologies that enable large numbers of afferent neurons to be recorded simultaneously and chronically during natural motor behaviors such as standing, walking, and reaching. Multichannel recordings are essential for this work, because there are multiple degrees-of-freedom for joint movement and several different kinematic and kinetic state variables that are of interest for closed- loop control applications. These data also permit the direct examination of the role and nature of primary afferent neurons in the perception of body state known as proprioception which is formed through the integration of multiple primary afferent neuronal inputs. This proposal will achieve 4 Specific Aims, with each Aim being an incremental progression toward fulfilling the broader goals stated above. Specific Aim 1 is to quantify, using Information Theory, the limb-state information conveyed by single neurons under the following conditions: 1) intact spinal cord, 2) acutely transected spinal cord, and 3) chronically transected spinal cord. These results will be used to evaluate changes in the quality and reliability of information transmitted by primary afferent neurons before and after spinal cord injury, a condition known to cause plastic changes in spinal neuronal circuitry potentially altering the response properties of muscle spindles. Using a decerebate cat preparation, the following state variables for the hindlimb will be studied: position, velocity, acceleration, endpoint force (e.g. ground reaction force during stance), and stance phase joint-torque. Neural recordings will be made during limb movements imposed by a robot arm attached to the foot. The state variables will be measured in reference frames based in intrinsic, joint-space coordinates (i.e. intersegmental angles) or extrinsic, end point-space coordinates (i.e. Cartesian or polar coordinates for the toe relative to the hip) to compare the extent to which state-information carried by afferent neurons depends on the chosen frame of reference. Specific Aim 2 is to use the data collected in SA-1, to develop mathematical models to decode position, velocity, force, and torque information from the ensembles of simultaneously recorded afferent neurons. Specific Aim 3 is to decode in near real-time, limb-state from ensemble firing rates of afferent neurons recorded during hindlimb stepping movements evoked by passive movement and fixed-pattern electrical stimulation in intact spinal cord and chronically spinalized decerebrate cats. Specific Aim 4 is to implement online state-feedback decoding (SA-3) in a finite state control system for FES-evoked hindlimb stepping in intact spinal cord and chronically spinalized decerebrate cats.