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The temporal structure of neural population activity in motor cortex

Grigsby, Erinn M P (2022) The temporal structure of neural population activity in motor cortex. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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We are able to make robust movements, like walking and reaching, without a thought. Yet despite our ease with such coordinated movements, the underlying neural processes are subtle and intricate. A hallmark of neural information processing in the cerebral cortex is the evolution of neural activity over time. It has been proposed that temporal structure in neural activity is the result of network connectivity. If so, modification of this structure would require modifying network connectivity, which is difficult to do over short timescales. This work examines the temporal structure, or dynamics, of population neural activity to test a key hypothesis: that dynamical structure is inherent to the circuitry of motor cortex. We leveraged population analysis methods and brain-computer interface (BCI) paradigms to causally probe neural activity in the motor cortex. Rhesus monkeys performed BCI tasks in which their recorded neural activity controlled the position of a computer cursor. We established two aspects of motor cortex dynamics. First, we examined whether the characteristic time courses of neural activity persist in the motor cortex in the absence of overt movement. This would suggest that there are dynamical properties that emerge from the neural circuitry in the motor cortex rather than only being present when the muscles are being controlled. We found that dynamics did persist in the absence of movements. Second, we examined whether the animals could violate these dynamics if we gave them incentive to do so. We found that even under this pressure to change their behavior, these dynamics still persisted. These results imply that the underlying network imposes strong constraints on the time course of population activity. This supports the view that neural trajectories reflect underlying network mechanisms. By understanding these mechanisms we may gain insight into neural control of movement. Such insight may be valuable in the efforts to engineer improvements to movement following cortical or spinal injury.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Grigsby, Erinn M Pemg90@pitt.eduemg900000-0002-8378-6488
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBatista, Aaronaaron.batista@pitt.eduaaron.batista0000-0002-1719-0061
Committee CoChairYu,
Committee MemberCollinger, Jennifercollinger@pitt.educollinger
Committee MemberGandhi, Neerajneg8@pitt.eduneg8
Committee MemberLoughlin, Patrickloughlin@pitt.eduloughlin
Committee MemberTorres-Oviedo, Gelsygelsyto@pitt.edugelsyto
Date: 16 January 2022
Date Type: Publication
Defense Date: 25 August 2021
Approval Date: 16 January 2022
Submission Date: 13 October 2021
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 116
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, BCI, motor cortex, dynamics, nonhuman primates
Date Deposited: 16 Jan 2022 14:32
Last Modified: 16 Jan 2024 06:15


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