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Relating changes in cortical state to circuit structure and dynamics

Getz, Matthew P (2023) Relating changes in cortical state to circuit structure and dynamics. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Variability in neural activity is often tied to cognitive or behavioral substrates, yet in linking neural dynamics to behavior, most theoretical work has ignored changing cortical state. In this dissertation I will present two pieces of work which seek to explicitly relate cortical state changes to circuit structure and dynamics. We find the role of inhibitory interneurons appears to be a unifying theme in the interaction between cognitive variables and neural dynamics.

In the first part we ask what circuit properties underlie how cortical state affects information flow through a neural network. We find that for a linear decoder's performance to change as a function of state, it must be restricted to a subset of the population. Curiously, the decoder's performance change is shaped not by the population of cells being decoded but rather the collection of cells which project to the decoded population. This result has an interesting implication: understanding information flow through cortical circuits may rest on understanding inhibitory interneuron response properties.

In the second part I will turn to the correlation between normalization and attention and argue that, despite being a conspicuous relationship between a cognitive variable (attention) and a circuit-dynamic variable (normalization), it nevertheless is insufficient to adequately constrain circuit models. We instead find other correlated heterogeneities better constrain mechanistic models of attention and in particular point to the necessity of strongly recurrent networks in constructing these relationships. We then demonstrate network properties which support this collection of correlated heterogeneities showing how these depend on the structure of inhibition.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Getz, Matthew Pmpg39@pitt.edumpg390000-0002-4108-1041
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairDoiron,
Committee CoChairRunyan,
Committee MemberCohen, Marlene
Committee MemberSmith,
Committee MemberErmentrout, G
Committee MemberMaunsell, John
Date: 25 January 2023
Date Type: Publication
Defense Date: 30 November 2022
Approval Date: 25 January 2023
Submission Date: 6 December 2022
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 133
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Neuroscience
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Attention; cortex; excitation-inhibition; linear Fisher information; neural dynamics; normalization
Date Deposited: 25 Jan 2023 15:58
Last Modified: 25 Jan 2023 15:58


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