Royston, Dylan
(2020)
Integrating Cortical Sensorimotor Representations Across Spatial Scales and Task Contexts.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
Abstract
Our understanding of how brains function is stratified between two very different scales: mesoscale (what function a given cortical area performs), measured with tools like fMRI; and microscale (what a given neuron does), measured with implanted microelectrodes. While extensive research has been done to characterize brain activity at both of these spatial scales, describing relationships between these two domains has proven difficult. Identifying ways to integrate findings between these scales is valuable for both research and clinical applications, but is particularly important for intracortical brain-computer interfaces (BCIs), which aim to restore motor function after paralysis or amputation. In humans, the brain is much larger than the available microelectrode arrays, so determining where to place the arrays is a critical aspect of ensuring optimal performance. BCIs preferentially target primary motor and somatosensory cortices, due to their direct relationship to motor control and critical role in skilled and dexterous movements. However, despite these areas displaying a relatively ordered spatial organization, it is difficult to accurately predict the behavior of neurons recorded from a given area for several reasons. Mesoscale activity is overlapping, with activity relating to multiple different movements observed in a single area. Additionally, neurons have flexible behavior, displaying different “tuning” to similar behavior under different contexts.
Here I present my research integrating neuroimaging-based cortical mapping with directly-recorded neural activity in human sensorimotor cortex. First, I examine how the large-scale organization of sensorimotor representations measured with fMRI is affected by contextual sensory information. I then examine how spatially separate neural populations recorded with intracortical microelectrode arrays encode different types of movement. Finally, I examine whether how population encoding changes to reflect contextual sensory information using the same task as in the fMRI study. Together, these results provide a foundation for reconciling neural activity across spatial scales and task contexts, and will inform the design and placement of more capable BCI systems.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
29 January 2020 |
Date Type: |
Publication |
Defense Date: |
15 November 2019 |
Approval Date: |
29 January 2020 |
Submission Date: |
19 November 2019 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
142 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Bioengineering |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
brain computer interface, neurotechnology, motor control, cortex, cortical activity, electrophysiology, neuroimaging, sensorimotor, intracortical, fMRI |
Date Deposited: |
29 Jan 2020 15:15 |
Last Modified: |
29 Jan 2020 15:15 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/37880 |
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Integrating Cortical Sensorimotor Representations Across Spatial Scales and Task Contexts. (deposited 29 Jan 2020 15:15)
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