Modeling multi-area dynamics during motor control

电机控制期间的多区域动态建模

• 批准号: 10224734
• 负责人: Laurence F. Abbott
• 金额: $ 32.64万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-25 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10224734
• 关键词: Address; Affect; Area; Basal Ganglia; Behavior; Behavioral; Biological; Brain; Brain region; Cerebellum; Complex; Conceptions; Corpus striatum structure; Coupled; Data; Generations; Goals; Hand; Learning; Link; Modeling; Monitor; Motor; Motor Cortex; Movement; Neural Network Simulation; Neurons; Neurophysiology - biologic function; Neurosciences; Output; Pattern; Play; Population; Process; Production; Research; Role; Series; Spinal Cord; Stereotyping; Structure; Substantia nigra structure; System; Test Result; Testing; Thalamic structure; Time; Work; arm; computational basis; design; experimental study; flexibility; insight; motor behavior; motor control; neural circuit; novel; operation; predictive modeling; recurrent neural network; relating to nervous system

Elucidating the neural basis of behavior is a fundamental goal of neuroscience. Progress towards this goal is complicated by the fact that most behaviors arise from interactions between a number of distributed and intercon- nected brain regions. Project 4 uses models that are tightly linked to experimental data to address this issue in the context of sequential motor behaviors. Many complex motor behaviors can be decomposed into sequences of stereotyped components or `motifs' that can be rearranged to produce a wide variety of other behaviors. To create a sequence from existing motifs, the motor system must generate the required neural activity while monitoring movement progress in order to time transitions between different motifs appropriately. This modeling project is aimed at developing and testing a model of interacting networks representing motor cortex, motor thalamus and input and output structures of the basal ganglia (i.e., striatum and GPi/SNr) that can autonomously generate a wide variety of motifs, string them together flexibly into sequences, and monitor ongoing activity to assure that transitions between motifs occur when they should. In this model, the loop between cortex and thalamus creates a single cortico-thalamic network for the execution of multiple behavioral motifs. Critically, this cortico-thalamic network is not a fixed entity but can be modified by the inhibitory output of the basal ganglia. The motif that the cortico-thalamic network produces at any given time is determined by which set of neurons in the motor thalamus is not being inhibited by GPi/SNr activity at that time. Different motifs will be selected by changing the pattern of activity in the GPi/SNr, thereby modifying the pattern of inhibition in the motor thalamus. Thus, the role of the GPi/SNr in the model is to maintain the current motif and to drive transitions to the next motif in a sequence. Models of the GPi/SNr will be used to study and propose mechanisms by which they sustain activity during a motif and switch it between motifs. Striatum will be modeled as a monitor of cortical activity with the role of deter- mining when one motif has ended and the next can begin. When an appropriate opportunity has been identified, transient activity in the striatum will trigger the system to switch from one motif to another through its projections to the GPi/SNr. This modeling project is tightly matched to the overall goal of this group proposal, a detailed, quantitative understanding of the production of behavior by the motor system. Because the model relates the activities of neural populations in multiple regions (motor cortex, motor thalamus, GPi/SNr and striatum), it will provide many predictions that will be tested using the experimental data produced by the other projects within this group proposal. The results of these tests will be used to refine the model and, in addition, predictions of the model will guide new experimental approaches. The cycle of deriving constraints from experiments and predictions from models will continue until we arrive at an illuminating and biologically plausible circuit-level de- scription that accounts for what we observe in experiments and lends new insight into how flexible sequential motor sequences are generated.

阐明行为的神经基础是神经科学的一个基本目标。实现这一目标的进展是