Using an animal learning model of the hippocampus to simulate human fMRI data

Kohitij Kar; Ahmed Moustafa; Catherine Myers; Mark Gluck

doi:10.1109/NEBC.2010.5458266

Using an animal learning model of the hippocampus to simulate human fMRI data

Kohitij Kar^*, Ahmed Moustafa, Catherine Myers, Mark Gluck

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

1 Citation (Scopus)

Abstract

Recent human fMRI studies have shown that the hippocampal region is essential for probabilistic category learning, memory formation-retrieval and context based performance. We present an artificial neural network model that can qualitatively simulate the BOLD signal for these tasks. The model offers ideas on the functional architecture and the relationship between the hippocampus and other brain structures. We also show that symptoms of neurobiological diseases like Parkinson's disease (PD) and Schizophrenia can be simulated and studied using the model.

Original language	English
Title of host publication	Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010
DOIs	https://doi.org/10.1109/NEBC.2010.5458266
Publication status	Published - 2010
Externally published	Yes
Event	36th Annual Northeast Bioengineering Conference, NEBEC 2010 - New York, United States Duration: 26 Mar 2010 → 28 Mar 2010

Publication series

Name	Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010

Conference

Conference	36th Annual Northeast Bioengineering Conference, NEBEC 2010
Abbreviated title	NEBEC
Country/Territory	United States
City	New York
Period	26/03/10 → 28/03/10

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/NEBC.2010.5458266

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Kar, K., Moustafa, A., Myers, C., & Gluck, M. (2010). Using an animal learning model of the hippocampus to simulate human fMRI data. In Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010 Article 5458266 (Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010). https://doi.org/10.1109/NEBC.2010.5458266

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title = "Using an animal learning model of the hippocampus to simulate human fMRI data",

abstract = "Recent human fMRI studies have shown that the hippocampal region is essential for probabilistic category learning, memory formation-retrieval and context based performance. We present an artificial neural network model that can qualitatively simulate the BOLD signal for these tasks. The model offers ideas on the functional architecture and the relationship between the hippocampus and other brain structures. We also show that symptoms of neurobiological diseases like Parkinson's disease (PD) and Schizophrenia can be simulated and studied using the model.",

author = "Kohitij Kar and Ahmed Moustafa and Catherine Myers and Mark Gluck",

year = "2010",

doi = "10.1109/NEBC.2010.5458266",

language = "English",

isbn = "9781424468799",

series = "Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010",

booktitle = "Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010",

note = "36th Annual Northeast Bioengineering Conference, NEBEC 2010, NEBEC ; Conference date: 26-03-2010 Through 28-03-2010",

}

Kar, K, Moustafa, A, Myers, C & Gluck, M 2010, Using an animal learning model of the hippocampus to simulate human fMRI data. in Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010., 5458266, Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010, 36th Annual Northeast Bioengineering Conference, NEBEC 2010, New York, New York, United States, 26/03/10. https://doi.org/10.1109/NEBC.2010.5458266

Using an animal learning model of the hippocampus to simulate human fMRI data. / Kar, Kohitij; Moustafa, Ahmed; Myers, Catherine et al.
Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010. 2010. 5458266 (Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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T1 - Using an animal learning model of the hippocampus to simulate human fMRI data

AU - Kar, Kohitij

AU - Moustafa, Ahmed

AU - Myers, Catherine

AU - Gluck, Mark

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AB - Recent human fMRI studies have shown that the hippocampal region is essential for probabilistic category learning, memory formation-retrieval and context based performance. We present an artificial neural network model that can qualitatively simulate the BOLD signal for these tasks. The model offers ideas on the functional architecture and the relationship between the hippocampus and other brain structures. We also show that symptoms of neurobiological diseases like Parkinson's disease (PD) and Schizophrenia can be simulated and studied using the model.

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M3 - Conference contribution

AN - SCOPUS:77953077404

SN - 9781424468799

T3 - Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference, NEBEC 2010

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Y2 - 26 March 2010 through 28 March 2010

ER -

Using an animal learning model of the hippocampus to simulate human fMRI data

Abstract

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