Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Cognitive Neuroscience

First Advisor's Name

Aaron T Mattfeld

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Timothy Allen

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Fabian Soto

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Kim Tieu

Fourth Advisor's Committee Title

Committee member

Keywords

hippocampus, Striatum, mPFC, decision making, learning, memory

Date of Defense

7-28-2022

Abstract

In this dissertation, I investigate how the hippocampus, medial prefrontal cortex and striatum facilitate memory-guided decision making. While a great deal of human and animal research has been dedicated to solving this puzzle, much of this work has focused on “retrospective” mechanisms of this process. Although retrieval and deliberation are certainly fundamental elements of successful choice behavior, how these regions prospectively support memory-guided decision making is also worthy of further study. Here, I present: (1) elucidation of two distinct networks which support prospective and concurrent memory-guided behavior, (2) evidence hippocampal support to experience-based learning is a dynamic, evolving process, and (3) demonstration of prospective representational content using machine learning. In my first experiment, participants completed a visuospatial conditional associative task (vCAT1) in which correct conditional response was dependent on the preceding stimulus. Through both uni- and multivariate methods, I demonstrate evidence of two separate networks through which memory guides decision making behavior: (1) hippocampus (HPC), putamen (PUT), medial prefrontal cortex (mPFC), and other cortical regions which showed increased activation preceding successful conditional choice, and (2) dorsal anterior caudate (DAC), dorsolateral prefrontal cortex (dlPFC), and other cortical regions, which exhibited increased activation during successful choice execution. In order to address how these regions and their collaborative contributions may evolve across learning, I employed two learning analyses to determine how HPC and DAC support early and late learning. I observed decreased activation for DAC as performance improved and selective involvement of the HPC for late, but not early learning. These findings demonstrate dynamic contributions of the HPC as learning develops. In my second experiment, participants completed a more complex visuospatial conditional associative task (vCAT2) to reduce ceiling effects and prevent alternating response set. Here, I collected data for purposes of conducting a multivoxel pattern analysis to investigate neurobiological representations of prospective memory. Classifier accuracy for both FFA and PPA was better than would be expected by chance, but no statistically significant relationship was observed between classifier and subject performance. These findings provide evidence for prospective representational content which supports memory-guided decision making processes.

Identifier

FIDC010940

ORCID

0000-0003-0034-4586

Previously Published In

Hamm, A. G., & Mattfeld, A. T. (2019). Distinct neural circuits underlie prospective and concurrent memory-guided behavior. Cell Reports, 28(10), 2541–2553. https://doi.org/10.1016/j.celrep.2019.08.002

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