Fraser, George Williams
(2011)
New frontiers in population recording.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The advent of reliable simultaneous recording of the activity of many neurons has enabled the study of interactions between neurons at a large scale: the number of observed pairwise interactions is proportional to the square of the number of recorded neurons. The dominant phenomenon in these pairwise interactions is synchronization, reflecting a system where many observed variables have in common a smaller set of latent variables. This permits the possibility that the complex signals observed in the brain might be reducible to a simpler system. We used this insight to design a better signal processing scheme for neuroprosthetics; to identify the same neurons in many recording sessions from their pairwise interactions; to show that the tuning functions of neurons in motor and premotor cortex do not reflect simple coordinate frame models; and to identify error as a dominant signal during continuous movements.
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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Unpublished |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: |
14 April 2011 |
Date Type: |
Completion |
Defense Date: |
4 April 2011 |
Approval Date: |
14 April 2011 |
Submission Date: |
13 April 2011 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
School of Medicine > Neurobiology |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
machine learning; neuroprosthetics; neuroscience; statistics |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-04132011-154920/, etd-04132011-154920 |
Date Deposited: |
10 Nov 2011 19:37 |
Last Modified: |
15 Nov 2016 13:40 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/7132 |
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