This project combines neuropsychological, neuroimaging, and eye tracking approaches in order to study the functional interactions of PFC and the hippocampus in supporting richly conditional behavior in humans. The experiments test our hypothesis that the hippocampus is critically involved in relational memory representations whereas PFC is involved in more abstract context-guided associative rules. Neuropsychological studies will provide evidence about the necessity of PFC and MTL regions in relational memory and context-dependent associations, and neuroimaging studies will provide evidence about the nature and timing of functional interactions between these regions. For each study, performance assessments will include not only explicit behavioral judgments but also eye movement-based assessment of memory, pioneered in our laboratory. This approach affords sensitive, implicit nr>easures of the strength of relational and context-dependent representations, based on preferential viewing patterns, as they change dynamically during each trial and across learning and retention. Experiments start with a "base" task in common with all the other empirical projects of the Center, and then graduate to more elaborate variants that systematically manipulate the amount and complexity of relational information or the complexity and abstractness of the context-dependent associative rules to be learned, in order to better determine the dependency of each of these aspects of memory on PFC, hippocampus, and their functional interactions, and further, on the directionality of their interactions.

Public Health Relevance

Understanding the roles of PFC and MTL, and their interactions has clear health relevance. Dysfunction of PFC and/or MTL is implicated in a range of mental health disorders, including schizophrenia, bipolar disease, ADHD, cognitive aging. Alzheimer's disease, and drug addiction. Moreover, recent theorizing about these disorders have suggested a conceptualization of them as involving network dysfunction, including dysfunction in PFC-MTL interactions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Specialized Center (P50)
Project #
5P50MH094263-04
Application #
8735991
Study Section
Special Emphasis Panel (ZMH1-ERB-S)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
4
Fiscal Year
2014
Total Cost
$241,944
Indirect Cost
$50,301
Name
Boston University
Department
Type
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Howard, Marc W; Eichenbaum, Howard (2015) Time and space in the hippocampus. Brain Res 1621:345-54
Wang, Jane X; Cohen, Neal J; Voss, Joel L (2015) Covert rapid action-memory simulation (CRAMS): a hypothesis of hippocampal-prefrontal interactions for adaptive behavior. Neurobiol Learn Mem 117:22-33
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
Erdem, Ugur M; Hasselmo, Michael E (2014) A biologically inspired hierarchical goal directed navigation model. J Physiol Paris 108:28-37
Brown, Thackery I; Whiteman, Andrew S; Aselcioglu, Irem et al. (2014) Structural differences in hippocampal and prefrontal gray matter volume support flexible context-dependent navigation ability. J Neurosci 34:2314-20
Wang, Jane X; Rogers, Lynn M; Gross, Evan Z et al. (2014) Targeted enhancement of cortical-hippocampal brain networks and associative memory. Science 345:1054-7
Hasselmo, Michael E; Stern, Chantal E (2014) Theta rhythm and the encoding and retrieval of space and time. Neuroimage 85 Pt 2:656-66
Eichenbaum, Howard (2014) Time cells in the hippocampus: a new dimension for mapping memories. Nat Rev Neurosci 15:732-44
Wang, Jane X; Voss, Joel L (2014) Brain networks for exploration decisions utilizing distinct modeled information types during contextual learning. Neuron 82:1171-82
Raudies, Florian; Zilli, Eric A; Hasselmo, Michael E (2014) Deep belief networks learn context dependent behavior. PLoS One 9:e93250

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