CRCNS: Extracting Dynamical Structure Embedded in Motor Preparatory Activity
CRCNS:提取运动准备活动中嵌入的动态结构
基本信息
- 批准号:7488914
- 负责人:
- 金额:$ 34.23万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2005
- 资助国家:美国
- 起止时间:2005-09-01 至 2010-08-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAlgorithmsAmputationAmyotrophic Lateral SclerosisAreaBasic ScienceBehaviorBiological ModelsBiological Neural NetworksBrainCellsChronicCognitiveCommunicationCountCuesDataDegenerative DisorderDevelopmentDropsElectrodesExhibitsExperimental ModelsFigs - dietaryFire - disastersGoalsImplantIndividualLaboratoriesLearningLeftLocationMeasuresMethodsModelingMonkeysMotorMovementNatureNeuronsNon-linear ModelsOperative Surgical ProceduresOutputPatientsPerformancePopulationPositioning AttributePreparationPrincipal InvestigatorProcessProsthesisQuality of lifeRangeRateRecurrenceResearchResearch PersonnelSpeedSpinal cord injuryStandards of Weights and MeasuresStructureSystemTechniquesTechnologyTestingTimeUpper armVariantWorkbasedesigndesireimprovedinsightinterestneural circuitneural prosthesisneuromechanismneurophysiologyprogramsrelating to nervous systemresearch studytwo-dimensionalvector
项目摘要
DESCRIPTION (provided by applicant):
Spiking activity from neurophysiological experiments often exhibits dynamics beyond that driven by external stimulation, presumably reflecting the extensive recurrence of neural circuitry. Characterizing these dynamics may reveal important features of neural computation, particularly during internally-driven "cognitive" operations. For example, neurons in premotor cortex (PMd) are active during a "planning" period separating movement-target specification and a movement-initiation cue. Recent evidence suggests that PMd neural activity settles to a movement-specific state during this period. Can trial-to-trial variation in behavior be predicted from the dynamics of settling? Current methods to characterize recurrent neural dynamics on a trial-by-trial basis, and thus answer this and related questions, are limited. Standard methods average activity from different trials or different cells, and so cannot express variable dynamics. The proposed research will test the hypothesis that the dynamics underlying PMd plan activity can be described by a low-dimensional hidden non-linear dynamical systems (HNLDS) model, with underlying recurrent structure and stochastic point-process output. Such a model is capable of expressing rich dynamics, but the task of learning the model parameters from spike data is challenging. The proposed research will develop and validate algorithms for parameter estimation, and then characterize the dynamics in PMd data recorded from an electrode array while monkeys perform delayed-reach tasks. Single trial estimates of underlying dynamics can then be used to predict variation in details of reaching motor behavior.
The proposed research program will directly inform cortically-controlled neural prosthesis research in our laboratory and elsewhere. Such motor and communication prostheses could dramatically improve the quality of life for patients with upper spinal cord injuries, amputations, ALS and other neuro-degenerative diseases. The proposed research program will increase our understanding of how PMd rapidly prepares movements, and thereby help increase the speed and accuracy of prosthetic systems.
描述(由申请人提供):
神经生理学实验中的尖峰活动通常表现出超出外部刺激驱动的动力学,可能反映了神经回路的广泛复发。表征这些动态可能揭示神经计算的重要特征,特别是在内部驱动的“认知”操作期间。例如,前运动皮层(PMd)中的神经元在分离运动目标指定和运动启动线索的“计划”期间是活跃的。最近的证据表明,在此期间,PMD神经活动定居到一个特定的运动状态。试验与试验之间的行为变化能否从沉降动力学中预测出来?目前的方法来表征反复神经动力学的一个试验一个试验的基础上,从而回答这个问题和相关的问题,是有限的。标准方法平均来自不同试验或不同细胞的活性,因此不能表达可变的动态。拟议的研究将测试的假设,PMd计划活动的动态基础可以描述一个低维隐藏的非线性动力系统(HNLDS)模型,与潜在的经常性结构和随机点过程输出。这样的模型能够表达丰富的动态,但从尖峰数据学习模型参数的任务是具有挑战性的。拟议中的研究将开发和验证算法的参数估计,然后从电极阵列记录的PMD数据,而猴子执行延迟到达任务的动态特性。单次试验估计的潜在动力学,然后可以用来预测达到运动行为的细节的变化。
拟议的研究计划将直接通知我们实验室和其他地方的皮质控制神经假体研究。这种运动和交流假体可以大大提高上脊髓损伤、截肢、ALS和其他神经退行性疾病患者的生活质量。拟议的研究计划将增加我们对PMD如何快速准备运动的理解,从而有助于提高假肢系统的速度和准确性。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Krishna V Shenoy其他文献
Network-level effects of optogenetic stimulation in a computer model of macaque primary motor cortex
- DOI:
10.1186/1471-2202-15-s1-p107 - 发表时间:
2014-07-21 - 期刊:
- 影响因子:2.300
- 作者:
Cliff C Kerr;Daniel J O'Shea;Werapong Goo;Salvador Dura-Bernal;Joseph T Francis;Ilka Diester;Paul Kalanithi;Karl Deisseroth;Krishna V Shenoy;William W Lytton - 通讯作者:
William W Lytton
Krishna V Shenoy的其他文献
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{{ truncateString('Krishna V Shenoy', 18)}}的其他基金
CRCNS: Extracting Dynamical Structure Embedded in Motor Preparatory Activity
CRCNS:提取运动准备活动中嵌入的动态结构
- 批准号:
7109167 - 财政年份:2005
- 资助金额:
$ 34.23万 - 项目类别:
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