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PROJECT SUMMARY (See instructions): Project 2 will combine functional magnetic resonance imaging (fMRI) with functional and effective connectivity methods to examine the interactions between regions of the prefrontal cortex (PFC) and medial temporal lobe (MTL) in humans during tasks requiring context-dependent learning and retrieval. We will use fMRI paradigms in context-based associative and context-based inference tasks closely related to tasks used in patients with selective PFC or MTL lesions (Project 1), in monkeys (Project 3), and in rodents (Projects 4 and 5). Since the homology between the human and non-human primate neuroanatomy provides a framework for our proposed human experiments, we have closely matched the human neuroimaging tasks to the tasks in Project 3. The first aim is to use fMRI in combination with functional and effective connectivity analysis methods to examine differences in interactions between the MTL and PFC regions during the learning and retrieval phases of a context-based associative memory task. The second aim will examine interactions between the MTL and PFC regions during a context-based inference task. The third aim will examine MTL and PFC interactions using a relational-load task. We will examine patterns of blood oxygenation level (BOLD) activity and functional and effective connectivity associated with different behavioral periods within trials (sample, delay, choice). In addition to using standard univariate fMRI methods for data analysis, addifional functional and effective connectivity methods will be employed to examine functional interactions between PFC and MTL regions. By comparing results in related tasks across rodents, monkeys, and humans, these experiments allow us to examine PFC-MTL interactions and functional homologies across species. The experimental results will guide the development of computational models that integrate these findings across species (Project 6), and the effective connectivity analysis and modeling will be done in conjunction with the Analysis Core.
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