The goal of the proposed study is to investigate the neural mechanisms underlying the emotional modulation of hippocampal memory in healthy individuals and how alterations in the amygdala-hippocampal network contribute to the pathophysiology of Major Depressive Disorder (MDD). Major depressive disorder (MDD) is one of the most prevalent lifetime psychiatric disorders with a lifetime prevalence of 16.5%. It is characterized by a cluster of symptoms that range from depressed mood to suicidal ideation and persist for a period of over two weeks. Memory impairment is a core endophenotype of MDD and has been attributed to abnormalities in the hippocampus and amygdala, with both regions exhibiting changes in volume and functional activity. The hippocampus is generally believed to underlie our capacity for learning new declarative memories, while the amygdala is thought to play an important role in the emotional modulation of memories. The hippocampus (particularly the dentate gyrus and CA3 subfield) is critically involved in pattern separation, a computation by which similar or overlapping memories are orthogonalized using distinct neural codes, such that learning is possible despite the potential for interference. Pattern separation provides a robust empirical framework for testing hippocampal function by manipulating mnemonic interference. It can further be used as a platform for testing amygdala modulation of hippocampal memory if stimulus emotionality is included as a parameter. In addition to providing a better understanding of memory network dynamics in healthy brains, this framework can also be used to test hypotheses in depressed individuals and assess the functional integrity of various components of this network. To achieve these goals, we will use powerful high-resolution fMRI (1.5 mm isotropic) methods that are capable of dissociating subfield-specific signals, coupled with a parametric design manipulating interference and emotional content concurrently. We will use this design to examine emotional modulation of memory in the healthy brain, as well as abnormalities in these cognitive processes in MDD. We will also employ cutting-edge ultrahigh-resolution (<1mm) structural and diffusion imaging methods to better understand amygdala-hippocampal abnormalities in MDD. The proposed empirical framework for examining memory and emotion is highly innovative and the application to MDD has never been previously accomplished. Coupled with state-of-the-art neuroimaging techniques, this project will have a high impact on the science of learning, memory, and emotion as well as the neurobiological understanding of MDD. We use a Research Domain Criteria (RDoC) framework to investigate common pathophysiological mechanisms in depression and co-morbid anxiety, which will be assessed along continuous dimensions. Successful completion of this project will shed light on the neural basis of memory and emotional processing in the amygdala-hippocampal network and provide a better understanding of the network changes that occur in depression, paving the way to improving diagnosis and defining novel targets for intervention.

Public Health Relevance

Major depressive disorder (MDD) is one of the most pressing public health challenges our society faces today. It affects approximately 6.7% of the adult U.S. population with over 30% of these cases classified as severe. Elucidating the neural mechanisms underlying disruptions in emotional memory modulation MDD will enhance our understanding of the pathophysiology of the disease and pave the way to better diagnosis and intervention.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Neurobiology of Learning and Memory Study Section (LAM)
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Rumsey, Judith M
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University of California Irvine
Other Basic Sciences
Schools of Arts and Sciences
United States
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Leal, Stephanie L; Yassa, Michael A (2018) Integrating new findings and examining clinical applications of pattern separation. Nat Neurosci 21:163-173
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Leal, Stephanie L; Noche, Jessica A; Murray, Elizabeth A et al. (2017) Disruption of amygdala-entorhinal-hippocampal network in late-life depression. Hippocampus 27:464-476

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