Neural and computational mechanisms underlying the assembly of motor skills
运动技能组装背后的神经和计算机制
基本信息
- 批准号:10293004
- 负责人:
- 金额:$ 2.74万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-15 至 2021-05-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAddressAnimalsArbitrationAutomobile DrivingBasal GangliaBehaviorBehavior DisordersBehavioralBrainBrain regionCodeComplementComputer AnalysisComputer ModelsCore FacilityCorpus striatum structureDevelopmentDiagnosticDiscriminationDopamineEducational CurriculumElementsEnvironmentFellowshipFutureGenerationsGoalsHeadHuntington DiseaseIndividualInternationalInvestigationLaboratoriesLaboratory ResearchLearningLearning DisordersLearning SkillLesionLettersLimb structureMental disordersMentorsMethodsModelingMolecularMonitorMotorMotor CortexMotor SkillsMovementNeuronsObsessive-Compulsive DisorderParkinson DiseasePatientsPatternPhasePositioning AttributeProcessProductionRattusResearchResearch Project GrantsResolutionRodentRoleScientistSpecific qualifier valueStructureSystemTechniquesTechnologyTestingTherapeuticTrainingUniversitiesVertebral columnWorkWritingappendagearm movementbasecareercareer developmentcareer networkingdopamine systemexperiencehuman diseaseimprovedinsightinterestkinematicsmeetingsmotor disordermotor learningmotor skill learningneural modelneuromechanismnoveloptogeneticspreventprofessorprogramsrelating to nervous systemresearch and developmentskillsspatiotemporaltoolundergraduate student
项目摘要
From typing on a keyboard to driving a car, motor skills are essential for our daily lives. Skills are modularly composed from a smaller set of natural motor elements – for instance individual keystrokes or arm movements – but little is known about the neural mechanisms that support this modular composition of motor elements into learned skills. The aim of this proposal is to understand how this modularity is achieved by interactions between the dorsolateral striatum and its motor cortical and dopaminergic inputs. We will gain new insights into this process through the development of a new technique, CAPTURE, which allows us to continuously track the position of a rat’s head, trunk, and limbs with superlative spatiotemporal resolution. By aligning motor elements across a skilled motor task and natural behaviors, CAPTURE allows us to precisely describe how a motor skill is assembled from pre-existing motor elements in an animal’s natural behavioral repertoire (Aim 1). We pair CAPTURE with a method recently developed in our laboratory that allows for continuous multi-unit neural recordings, a combination that allows us to precisely characterize how neural representations are reshaped across learning of a skill (Aim 2). Using this highly precise description of the skill learning process, we can then perform brain lesions and optogenetic stimulation to precisely identify the role of the motor cortex and phasic dopamine transients in skill learning (Aim 3). Completion of our aims should power new computational models of the neural basis of movement and skill learning and establish a new quantitative experimental platform for future studies. It should also provide new directions in the search for the circuit basis of human diseases of movement and behavior such as Parkinson’s disease and Obsessive Compulsive disorder. To guide my research and career development, I will by advised by a team of experienced mentors and experts in the basal ganglia, dopamine, and computational analysis. This team will advise my research project and career development through frequent meetings and be complemented by the tremendous scientific environment at Harvard University, which has numerous core facilities, scientists, and formal coursework to support my work. I will have the ability to grow as a mentor through undergraduate advising, and access to a broad curriculum in professional development. I will develop my professional network, presentation, and writing skills by presenting at local and international scientific meetings and writing scientific articles. My overall career goals are to establish a research laboratory at a major academic center and this mentored research project will establish new, unique experimental platform to differentiate my research program and develop several unique directions for research.
从在键盘上打字到驾驶汽车,运动技能对我们的日常生活至关重要。技能是由一组较小的自然运动元素组成的模块-例如个人的动作或手臂运动-但对支持运动元素模块化组合成学习技能的神经机制知之甚少。这个建议的目的是了解这种模块性是如何实现的背外侧纹状体和它的运动皮层和多巴胺能输入之间的相互作用。我们将通过开发一种新技术CAPTURE来获得对这一过程的新见解,该技术使我们能够以最高的时空分辨率连续跟踪大鼠头部,躯干和四肢的位置。通过在熟练的运动任务和自然行为中对齐运动元素,CAPTURE使我们能够精确地描述运动技能是如何从动物自然行为库中预先存在的运动元素中组装出来的(目标1)。我们将CAPTURE与我们实验室最近开发的一种方法配对,该方法允许连续的多单元神经记录,这种组合使我们能够精确地描述神经表征如何在技能学习过程中重塑(目标2)。使用这种对技能学习过程的高度精确描述,我们可以进行脑损伤和光遗传学刺激,以精确识别运动皮层和阶段性多巴胺瞬变在技能学习中的作用(目标3)。我们的目标的完成应该为运动和技能学习的神经基础的新的计算模型提供动力,并为未来的研究建立一个新的定量实验平台。它还将为寻找帕金森病和强迫症等人类运动和行为疾病的电路基础提供新的方向。为了指导我的研究和职业发展,我将由一个经验丰富的导师和基底神经节,多巴胺和计算分析专家团队提供建议。该团队将通过频繁的会议为我的研究项目和职业发展提供建议,并得到哈佛大学巨大的科学环境的补充,该大学拥有众多的核心设施,科学家和正式的课程来支持我的工作。我将有能力成长为一个导师,通过本科生的建议,并获得广泛的专业发展课程。我将通过在当地和国际科学会议上发表演讲和撰写科学文章来发展我的专业网络,演讲和写作技巧。我的总体职业目标是在一个主要的学术中心建立一个研究实验室,这个指导研究项目将建立新的,独特的实验平台,以区分我的研究计划,并开发几个独特的研究方向。
项目成果
期刊论文数量(0)
专著数量(0)
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Jesse D. Marshall其他文献
Differential kinematic coding in sensorimotor striatum across species-typical and learned behaviors reflects a difference in control
跨物种典型行为和习得行为的感觉运动纹状体的差异运动编码反映了控制的差异
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Kiah Hardcastle;Jesse D. Marshall;Amanda Gellis;Ugne Klibaite;William Wang;Selimzhan Chalyshkan;B. Ölveczky - 通讯作者:
B. Ölveczky
Jesse D. Marshall的其他文献
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{{ truncateString('Jesse D. Marshall', 18)}}的其他基金
Neural and computational mechanisms underlying the assembly of motor skills
运动技能组装背后的神经和计算机制
- 批准号:
9806054 - 财政年份:2019
- 资助金额:
$ 2.74万 - 项目类别:
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