Low dimensional motor neural structure of freely moving ambulation and reaching
Abstract/Contents
- Abstract
- Motor systems neuroscience is an interdisciplinary field that studies how the brain controls voluntary movement. Mechanistic and correlational understandings gained from decades of animal studies have been translated into brain machine interfaces, devices that can potentially help individuals with motor injury. However, most of these studies have been done in classically constrained settings. There is growing theoretical evidence, but limited experimental proof, that suggests that these models of neural control may not generalize to naturalistic settings. Thus, there is a knowledge gap in both mechanistic understanding and clinically translatable findings of how the brain controls unconstrained behavior. My PhD work focuses on bridging this knowledge gap by exploring the neural control of free locomotion and unconstrained reaching, broken up into 3 main projects: 1. Building a platform that collects wireless neural data and full-body markerless kinematics to study naturalistic behavior. 2. Performing computational analyses on a reach-walk task to quantify the neural differences of similar behaviors performed under different levels of cognitive difficulty. 3. Decoding locomotion to quantify the neural relationships between the gait cycle and total body position. My experimental work and computational analysis advance the field of motor systems neuroscience by representing a novel experimental platform to uncover the structure of ambulatory control. Many results from my freely moving experiments can only be captured with this platform, and show that previous constrained experiments are limited in their ability to capture the full activity of the motor cortex. My research is foundational for subsequent studies that may inform human clinical studies leveraging new insight about free movement.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Ling, Alissa Sachiko |
|---|---|
| Degree supervisor | Nuyujukian, Paul |
| Thesis advisor | Nuyujukian, Paul |
| Thesis advisor | Delp, Scott |
| Thesis advisor | Osgood, Brad |
| Degree committee member | Delp, Scott |
| Degree committee member | Osgood, Brad |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Alissa Ling. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/hn362bj9550 |
Access conditions
- Copyright
- © 2023 by Alissa Sachiko Ling
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