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New frontiers in population recording

Fraser, George Williams (2011) New frontiers in population recording. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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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Status: Unpublished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:
CreatorsEmailPitt UsernameORCID
Fraser, George Williamsfraser.george.w@gmail.com
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairStrick, Peter Lstrickp@pitt.eduSTRICKP
Committee MemberSchwartz, Andrew Babs21@pitt.eduABS21
Committee MemberWeber, Douglas Jjw50@pitt.eduJW50
Committee MemberSahani, Maneeshmaneesh@gatsby.ucl.ac.uk
Committee MemberKass, Robert Ekass@stat.cmu.edu
Committee MemberLee, Tai Singtai@cnbc.cmu.edu
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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