TitleMultiple memory systems involved in human probabilistic learning
NameDickerson, Kathryn Cain (author), Krekelberg, Bart (chair), Delgado, Mauricio (internal member), Tricomi, Elizabeth (internal member), Myers, Catherine (internal member), Davachi, Lila (outside member), Rutgers University, Graduate School - Newark,
DescriptionThis dissertation investigated the nature of interactions between multiple memory systems (MMS) in the human brain during probabilistic learning. How MMS interact in the brain is highly debated in the literature, with evidence supporting competition, cooperation, and parallel engagement observed across several species and various experimental paradigms (e.g., Poldrack et al., 2001; Poldrack and Rodriguez, 2004; Voermans et al., 2004; White and McDonald, 2002). In this dissertation, three functional neuroimaging experiments investigated the relationship between the medial temporal lobes (MTL), implicated in declarative learning, and the basal ganglia (BG), involved in nondeclarative learning, during probabilistic learning. Specifically, tasks which varied with respect to learning type (feedback, akin to nondeclarative learning and observation akin to declarative learning) and cue difficulty (e.g., easy, hard) were employed. Based on the evolutionary theory of MMS, neuroanatomical connections between these regions, as well as connectivity with midbrain dopaminergic centers involved in reward, memory, and reinforcement learning, it was hypothesized that rather than one specific relationship (e.g., competitive or cooperative), MMS operate in parallel during probabilistic learning – at times exhibiting parallel engagement, and at times interacting directly via cooperation or competition depending on the context of the learning situation. Interactions between memory systems were measured by the relative engagement of each system during learning (as measured by BOLD responses), simple correlation analyses, as well as functional and effective connectivity measures. Lastly, to examine putative dopaminergic influences during learning, reinforcement learning models were employed. Across all experiments, it was observed that a) patterns of activation in MMS during learning varied depending on the learning context; b) functional and effective connectivity existed across regions (MTL, BG); and c) a dopaminergic learning signal correlated with activity in both the BG and MTL. To conclude, the results of this dissertation support the hypothesis that multiple memory systems operate in parallel during probabilistic learning in humans. Understanding how such systems communicate during learning may inform treatment of several neuropsychiatric disorders which affect learning and memory in humans (e.g., Parkinson’s disease, schizophrenia, and MTL amnesia).
NoteIncludes bibliographical references
Noteby Kathryn Cain Dickerson
CollectionGraduate School - Newark Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.