Interval Timing and Motor Programming by Cortico-Striatal Ensembles

皮质纹状体整体的间隔计时和运动编程

• 批准号: 8298994
• 负责人: Miguel A. L. Nicolelis
• 金额: $ 50.94万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8298994
• 关键词: Address; Algorithms; Aphasia; Area; Attention deficit hyperactivity disorder; Behavior; Behavioral; Biological Neural Networks; Brain; Brain region; Characteristics; Clinical; Corpus striatum structure; Development; Devices; Disabled Persons; Discriminant Analysis; Disease; Dyslexia; Implant; Instruction; Knowledge; Learning; Life; Link; Macaca mulatta; Markov Chains; Medical; Methods; Modeling; Monkeys; Motor; Motor Activity; Movement; Neuronal Plasticity; Neurons; Neurosciences; Organism; Outcome; Parkinson Disease; Pattern; Population; Posture; Primates; Process; Prosthesis; Research; Schizophrenia; Self-Help Devices; Stroke; System; Testing; Time; Visual; area striata; arm; awake; base; mind control; nerve injury; nervous system disorder; neural prosthesis; neurodevelopment; neuromechanism; neurophysiology; novel; programs; relating to nervous system; restoration; therapy development; time interval; visual stimulus

DESCRIPTION (provided by applicant): Proper timing of movements is crucial for many behaviors of living organisms. Disorders of temporal processing have been linked to neurological diseases, such as aphasia, dyslexia and Parkinson's disease. Neurophysiological studies revealed the involvement of many brain areas in temporal processing, but the neural mechanism of behavioral timing remains poorly understood. This is in part because previous studies examined brain regions in isolation, whereas temporal processing may be fundamentally distributed. To address this problem, we propose a study in which we will apply the methods of multielectrode recordings and neural interfaces to elucidate the mechanisms of motor timing and their plasticity in corticostriatal ensembles. We hypothesize that corticostriatal ensembles simultaneously encode temporal and spatial parameters of motor activities and facilitate learning of new temporal contingencies. This hypothesis will be tested through three specific aims: 1. Identify neural modulations in corticostriatal ensembles underlying temporal programming of movements and their plasticity during learning. Rhesus macaques will be implanted with multielectrode arrays in multiple cortical areas and the striatum. Monkey arm-reaching motor tasks will require both interval timing and directional programming. Novel instructions will be used to introduce learning paradigms. We expect to find that spatial and temporal components of motor tasks are processed and modified conjointly by the corticostriatal system. 2. Develop neural decoders that extract spatial and temporal information from corticostriatal ensembles. We will use neural decoding algorithms (Wiener filter, Kalman filter, discriminant analysis and Markov chains) to extract both temporal and spatial characteristics of motor patterns from large populations of cortical and striatal neurons. We expect to find that overlapping populations of neurons contribute to the extraction of both temporal and spatial characteristics. 3. Develop a real-time paradigm in which temporal and spatial motor behaviors are learned and controlled through a neural interface. Rhesus macaques will perform the same tasks as in Aim 1, but through a neural interface which will use decoding algorithms developed in Aim 2. We expect that corticostriatal ensembles will plastically adapt to this direct brain control. As the outcome of the proposed study we expect to have uncovered essential features of corticostriatal control of temporal sequencing of movements and neural plasticity involved. Moreover, we expect to have created an interface that extracts temporal and spatial parameters of movements in real time. These findings will contribute to therapies of neurological disorders of temporal processing and to neural prosthetics that reproduce decoded motor patterns in assistive devices.

描述（由申请人提供）：适当的运动时机对生物体的许多行为至关重要。 时间处理障碍与神经系统疾病有关，如失语症、阅读障碍和帕金森病。 神经生理学研究揭示了许多大脑区域参与时间处理，但行为计时的神经机制仍然知之甚少。 这部分是因为以前的研究孤立地研究了大脑区域，而时间处理可能是基本分布的。 为了解决这个问题，我们提出了一项研究，在该研究中，我们将应用多电极记录和神经接口的方法，以阐明运动时序及其可塑性的皮质纹状体系综的机制。 我们假设皮质纹状体系综同时编码运动活动的时间和空间参数，并促进学习新的时间突发事件。 这一假设将通过三个具体目标进行测试：1。 确定皮质纹状体系综的神经调制运动的时间编程和学习过程中的可塑性。 将在恒河猴的多个皮质区域和纹状体中植入多电极阵列。 猴子手臂到达运动任务将需要间隔计时和方向编程。 新的指令将被用来介绍学习范式。 我们期望发现运动任务的空间和时间成分是由皮质纹状体系统共同加工和修改的。 2. 开发神经解码器，从皮质纹状体系综中提取空间和时间信息。 我们将使用神经解码算法（维纳滤波器，卡尔曼滤波器，判别分析和马尔可夫链），从大量的皮质和纹状体神经元中提取运动模式的时间和空间特征。 我们期望发现，重叠的神经元群体有助于提取时间和空间特征。 3. 开发一种实时范式，通过神经接口学习和控制时间和空间运动行为。 恒河猴将执行与目标1相同的任务，但通过神经接口，该接口将使用目标2中开发的解码算法。 我们预计皮质纹状体合奏将可塑性地适应这种直接的大脑控制。 作为拟议中的研究结果，我们希望已经发现皮质纹状体控制的动作和神经可塑性的时间序列的基本特征。 此外，我们希望创建一个接口，提取时间和空间参数的运动在真实的时间。 这些发现将有助于治疗神经系统疾病的时间处理和神经假肢，再现解码的运动模式的辅助设备。