Using an animal learning model of the hippocampus to simulate human fMRI data
Document Type
Conference Proceeding
Publication Date
6-8-2010
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. ©2010 IEEE.
Identifier
77953077404 (Scopus)
ISBN
[9781424468799]
Publication Title
Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference Nebec 2010
External Full Text Location
https://doi.org/10.1109/NEBC.2010.5458266
Recommended Citation
Kar, Kohitij; Moustafa, Ahmed; Myers, Catherine; and Gluck, Mark, "Using an animal learning model of the hippocampus to simulate human fMRI data" (2010). Faculty Publications. 6269.
https://digitalcommons.njit.edu/fac_pubs/6269
