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Thalamic Contributions to Motor Learning and Performance.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Thalamic Contributions to Motor Learning and Performance./
作者:
Sibener, Leslie Joan.
面頁冊數:
1 online resource (167 pages)
附註:
Source: Dissertations Abstracts International, Volume: 84-10, Section: B.
Contained By:
Dissertations Abstracts International84-10B.
標題:
Developmental biology. -
電子資源:
click for full text (PQDT)
ISBN:
9798379413798
Thalamic Contributions to Motor Learning and Performance.
Sibener, Leslie Joan.
Thalamic Contributions to Motor Learning and Performance.
- 1 online resource (167 pages)
Source: Dissertations Abstracts International, Volume: 84-10, Section: B.
Thesis (Ph.D.)--Columbia University, 2023.
Includes bibliographical references
Movement is the key to animal behavior. From fighting off predators to reaching for food, our survival relies on movement. Losing the ability to move the body through the world in a purposeful way would be dire. We learn to perform a wide variety of actions, which require exact motor control. How are such skilled actions refined over time? The neural mechanism of motor learning has been posited to arise from integrating neuronal signals about motor commands, environmental context, and outcome through the cortico-basal ganglia-thalamic loop. Here, I investigate the role of two thalamic nuclei - the parafascicular (Pf) and ventroanterior/ventrolateral (VAL) -in the process of motor learning. In an introductory Chapter 1, I introduce some key behavioral signatures of motor learning and the distributed neural circuity for movement through the cortico-basal ganglia-thalamic network. Pf and VAL are at the center of this network. Both receive basal ganglia output but differ in primary projection patterns. Pf sends large excitatory projections directly to the striatum (the main input area of the basal ganglia), while VAL projects back to the cortex. Despite their critical place in the movement system, little is known about their changing roles in motor learning. In Chapter 2, I highlight a novel skilled forelimb joystick target task for mice; the JTT. In the JTT, head-fixed mice learn reaches to spatial targets in 2D space by moving an unrestricted joystick without visual feedback. This task allows for multiple windows of learning and refinement of various reaches in space. Over the learning of targeted reaching movements, mice increase their accuracy and individual trajectories become less variable, showing that they have learned the location of the target in space, and also refine the reaching movements. In Chapter 3, I use 2-photon calcium imaging of the forelimb-related areas of Pf and VAL to investigate how their activity changes over learning of forelimb reaching actions. Both Pf and VAL are highly engaged during movements. Neural population engagement of Pf decreases over time, suggesting a specific role early in learning. Additionally, the underlying neural dynamics of Pf and VAL shift and occupy different state spaces over learning, as shown through principal component analysis. To investigate if neural activity in Pf or VAL encodes behavioral information, we used a ridge regression model to predict the initial direction of movements from neural data. We were able to predict the initial direction from Pf activity on early training days, but not from VAL. In Chapter 4, I performed pre and post-learning lesions to Pf or VAL to investigate if they are needed for learning and/or performance of targeted reaches. Results show that Pf is needed for learning, but not the performance of accurate spatial reaches. VAL, on the other hand, does not affect the learning or performance of target reaches, but does affect the speed of movements. In a discussion-based Chapter 5, I summarize these above experiments, which suggest different roles for PF and VAL over learning of multiple targeted reaches, and reflect on future directions of my findings in the broader context of motor learning research in neuroscience. In particular, my findings highlight a novel and critical role for Pf in learning and processing directional information during early skill learning. This work demonstrates that the thalamus is an essential node of the brain networks involved in motor learning.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798379413798Subjects--Topical Terms:
669036
Developmental biology.
Subjects--Index Terms:
Motor learningIndex Terms--Genre/Form:
554714
Electronic books.
Thalamic Contributions to Motor Learning and Performance.
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Movement is the key to animal behavior. From fighting off predators to reaching for food, our survival relies on movement. Losing the ability to move the body through the world in a purposeful way would be dire. We learn to perform a wide variety of actions, which require exact motor control. How are such skilled actions refined over time? The neural mechanism of motor learning has been posited to arise from integrating neuronal signals about motor commands, environmental context, and outcome through the cortico-basal ganglia-thalamic loop. Here, I investigate the role of two thalamic nuclei - the parafascicular (Pf) and ventroanterior/ventrolateral (VAL) -in the process of motor learning. In an introductory Chapter 1, I introduce some key behavioral signatures of motor learning and the distributed neural circuity for movement through the cortico-basal ganglia-thalamic network. Pf and VAL are at the center of this network. Both receive basal ganglia output but differ in primary projection patterns. Pf sends large excitatory projections directly to the striatum (the main input area of the basal ganglia), while VAL projects back to the cortex. Despite their critical place in the movement system, little is known about their changing roles in motor learning. In Chapter 2, I highlight a novel skilled forelimb joystick target task for mice; the JTT. In the JTT, head-fixed mice learn reaches to spatial targets in 2D space by moving an unrestricted joystick without visual feedback. This task allows for multiple windows of learning and refinement of various reaches in space. Over the learning of targeted reaching movements, mice increase their accuracy and individual trajectories become less variable, showing that they have learned the location of the target in space, and also refine the reaching movements. In Chapter 3, I use 2-photon calcium imaging of the forelimb-related areas of Pf and VAL to investigate how their activity changes over learning of forelimb reaching actions. Both Pf and VAL are highly engaged during movements. Neural population engagement of Pf decreases over time, suggesting a specific role early in learning. Additionally, the underlying neural dynamics of Pf and VAL shift and occupy different state spaces over learning, as shown through principal component analysis. To investigate if neural activity in Pf or VAL encodes behavioral information, we used a ridge regression model to predict the initial direction of movements from neural data. We were able to predict the initial direction from Pf activity on early training days, but not from VAL. In Chapter 4, I performed pre and post-learning lesions to Pf or VAL to investigate if they are needed for learning and/or performance of targeted reaches. Results show that Pf is needed for learning, but not the performance of accurate spatial reaches. VAL, on the other hand, does not affect the learning or performance of target reaches, but does affect the speed of movements. In a discussion-based Chapter 5, I summarize these above experiments, which suggest different roles for PF and VAL over learning of multiple targeted reaches, and reflect on future directions of my findings in the broader context of motor learning research in neuroscience. In particular, my findings highlight a novel and critical role for Pf in learning and processing directional information during early skill learning. This work demonstrates that the thalamus is an essential node of the brain networks involved in motor learning.
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