2026-09-21T15:06:07Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1299152026-06-06T00:54:30Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Ann Graybiel.
Rajan, Meena S.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2021-02-19T20:54:38Z
2021-02-19T20:54:38Z
2020
2020
https://hdl.handle.net/1721.1/129915
1237530662
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 60-61).
Animals have evolved to allow for decision-making based on rewarding and aversive features of the environment. This ability has been studied in mice and other species as well as the different neuropsychiatric and neurological disorders that undermine this ability. Previous work has shown that some of this decision-making is linked to the striatum, a part of the basal ganglia. There is also previous research that suggests this behavior is partly controlled by a set of distributed striatal microzones known as striosomes. We aim to study the neural activity of striosome and matrix cells in wild type and Huntington disease modeling mice and how they are linked to cost-benefit decision-making. This paper will analyze and model the neural data and train a classifier that can predict the mouse's behavior as it runs a T-maze. The paper finds some support for the claim that striosomes are correlated to the decision-making process.
by Meena S. Rajan.
M.Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
61 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Analysis of matrix and striosomal cell activity to explore and predict mouse behavior in 'T' maze
Thesis
application/pdf
2021-02-19T20:54:08Z
Publication
Master
EECS
unknown
unknown
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<Abstract>Animals have evolved to allow for decision-making based on rewarding and aversive features of the environment. This ability has been studied in mice and other species as well as the different neuropsychiatric and neurological disorders that undermine this ability. Previous work has shown that some of this decision-making is linked to the striatum, a part of the basal ganglia. There is also previous research that suggests this behavior is partly controlled by a set of distributed striatal microzones known as striosomes. We aim to study the neural activity of striosome and matrix cells in wild type and Huntington disease modeling mice and how they are linked to cost-benefit decision-making. This paper will analyze and model the neural data and train a classifier that can predict the mouse's behavior as it runs a T-maze. The paper finds some support for the claim that striosomes are correlated to the decision-making process.</Abstract>
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