Computational models of the hippocampal formation, entorhinal cortex and prefrontal cortex will be used to simulate memory-guided behavior in both rat and human behavioral tasks. These simulations will extend previous modeling work in this laboratory (Hasselmo et al., 2002b;Fransen et al., 2002;Koene et al., 2003; Hasselmo, 2005a;Koene and Hasselmo, 2005;Hasselmo and Eichenbaum, 2005) to generate predictions about physiological data in a range of different memory-guided tasks. Selection of behavioral actions in the model depends on the encoding and context dependent retrieval of sequences of input stimuli (i.e. episodes). The models will generate predictions for specific research projects in the center, including: 1.) generation of predictions about the timing of neuron firing relative to stimuli and hippocampal theta rhythm during performance of the order recognition task with odors in rats, and the magnitude of fMRI activation associated with correct versus incorrect performance of an order recognition task in humans, 2.) generation of predictions about context-dependent properties and theta phase of neuronal firing in the odor sequence disambiguation task, and the magnitude of fMRI activation associated with choice in a disambiguation task in humans, 3.) generation of predictions about the delayed non-match to place (DNMP) task in the T-maze, concerning the timing of splitter cell responses and sequence readout relative to theta rhythm and behavior and the disruption of behavioral responses caused by stimulation at different phases of theta during different task periods. These simulations will use networks of neurons starting with threshold units and building to use of detailed compartmental biophysical simulations, to relate network dynamics to intrinsic currents and subclasses of neurons within the hippocampus and entorhinal cortex. The insights gained from this work will improve our understanding of the normal function of the hippocampus and associated cortex, potentially contributing to treatment of memory impairments in disorders such as Alzheimer's disease or schizophrenia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Specialized Center (P50)
Project #
5P50MH071702-04
Application #
7942806
Study Section
Special Emphasis Panel (ZMH1)
Project Start
Project End
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
4
Fiscal Year
2009
Total Cost
$320,733
Indirect Cost
Name
Boston University
Department
Type
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
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Brown, Thackery I; Hasselmo, Michael E; Stern, Chantal E (2014) A high-resolution study of hippocampal and medial temporal lobe correlates of spatial context and prospective overlapping route memory. Hippocampus 24:819-39
Prerau, Michael J; Lipton, Paul A; Eichenbaum, Howard B et al. (2014) Characterizing context-dependent differential firing activity in the hippocampus and entorhinal cortex. Hippocampus 24:476-92
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Brown, Thackery I; Stern, Chantal E (2014) Contributions of medial temporal lobe and striatal memory systems to learning and retrieving overlapping spatial memories. Cereb Cortex 24:1906-22
Kraus, Benjamin J; Robinson 2nd, Robert J; White, John A et al. (2013) Hippocampal ""time cells"": time versus path integration. Neuron 78:1090-101
Ross, Robert S; LoPresti, Matthew L; Schon, Karin et al. (2013) Role of the hippocampus and orbitofrontal cortex during the disambiguation of social cues in working memory. Cogn Affect Behav Neurosci 13:900-15
Erdem, U?ur M; Hasselmo, Michael (2012) A goal-directed spatial navigation model using forward trajectory planning based on grid cells. Eur J Neurosci 35:916-31
Brown, Thackery I; Ross, Robert S; Tobyne, Sean M et al. (2012) Cooperative interactions between hippocampal and striatal systems support flexible navigation. Neuroimage 60:1316-30
Lepage, Kyle Q; Macdonald, Christopher J; Eichenbaum, Howard et al. (2012) The statistical analysis of partially confounded covariates important to neural spiking. J Neurosci Methods 205:295-304

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