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Principal Investigator: Salman Ehtesham Qasim
Organization: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
Fiscal Year: 2024
Award: $17,205
Funding agency: National Institute of Mental Health
PROJECT SUMMARY
How does decision-making influence memory to leave a long-lasting impact on human behavior? Answering this
question is critical to understanding how impaired decision making might lead to maladaptive memory outcomes,
such as rumination on negative events, susceptibility to false memories, or memory loss. In recent years, the
reinforcement learning (RL) framework has been particularly fruitful for describing impaired decision-making in
psychiatric disorders as well as identifying computational mechanisms linking decision-making and memory. The
overarching aim of this project is to identify the neurocomputational mechanisms that explain how the learning
processes driving decision-making also influence subsequent memory. To do so, the K99 phase of the proposed
study consists of a computational approach to identify how model-free reinforcement learning signals influence
both hippocampal and non-hippocampal recognition memory performance in humans (Aim 1), and a neurobiolog-
ical approach to identify the electrophysiological mechanisms underlying these RL-memory interactions (Aim 2);
the R00 phase of the study will deploy these approaches to study the contributions of model-based reinforcement
learning to these distinct memory processes (Aim 3). Specifically, Aim 1 will test how model-free RL signals such
as prediction errors might interact with the perceptual features of a stimulus to enhance both immediate (non-
hippocampal) memory and delayed (hippocampal) memory in healthy volunteers. Aim 2 will leverage intracranial
recording obtained from humans with epilepsy monitoring electrodes to test how neural activity in the frontal cor-
tex, hippocampus, and non-hippocampal medial temporal regions (such as parahippocampal gyrus) subserve
the influence of model-free RL processes on memory performance. Upon completion of Aims 1-2 (K99), the
candidate—a neuroscientist with a background in the neurobiology of human memory—will obtain new training
in computational modeling of reinforcement learning and decision-making and have a unique, multi-disciplinary
skillset to apply to Aim 3 (R00), to study how model-based RL processes influence mnemonic behavior and neural
activity. The candidate’s mentors are uniquely suited to provide the training for these Aims, given their expertise
in bridging computational modeling (Dr. Xiaosi Gu) and human neurophysiology (Dr. Ignacio Saez) to understand
human decision-making. These skills will also facilitate the candidate’s transition into an independent researcher
with the long-term goal of performing integrative behavioral, computational, and biological studies of how these
human decision-making and memory processes go awry in psychiatric disorders.
Terms: <Address><Affect><Ammon Horn><Assay><Automobile Driving><Behavior><Behavioral><Bioassay><Biological><Biological Assay><Biological Markers><Brain><Brain Nervous System><Cell Communication and Signaling><Cell Signaling><Cognition><Complex><Computer Models><Computerized Models><Cornu Ammonis><Decision Making><Disparate><Dysfunction><Electrodes><Electrophysiology><Electrophysiology (science)><Encephalon><Epilepsy><Epileptic Seizures><Epileptics><Event><Exhibits><Functional MRI><Functional Magnetic Resonance Imaging><Functional disorder><Goals><Gyrus Hippocampi><Gyrus Parahippocampalis><Hippocampal Gyrus><Hippocampus><Hour><Human><Image><Impairment><Intracellular Communication and Signaling><Intractable Epilepsy><Investigators><Knowledge><Learning><Link><Measures><Medial><Mediating><Memory><Memory Loss><Mental Depression><Mental disorders><Mental health disorders><Mentors><Mentorship><Mesencephalon><Mid-brain><Midbrain><Midbrain structure><Modeling><Modern Man><Monitor><Nerve Cells><Nerve Unit><Neural Cell><Neurobiology><Neurocyte><Neurons><Neurophysiology / Electrophysiology><Outcome><Parahippocampal Gyrus><Patients><Performance><Phase><Physiopathology><Play><Predisposition><Process><Psychiatric Disease><Psychiatric Disorder><Psychological reinforcement><Refractory epilepsy><Reinforcement><Research><Research Personnel><Researchers><Reversal Learning><Rewards><Seizure Disorder><Seizures><Signal Transduction><Signal Transduction Systems><Signaling><Sleep><Stimulus><Study models><Susceptibility><Techniques><Testing><Training><addiction><addictive disorder><bio-markers><biologic><biologic marker><biological signal transduction><biomarker><computational basis><computational modeling><computational models><computer based models><computerized modeling><depression><driving><drug-resistant epilepsy><electrophysiological><epilepsia><epileptogenic><fMRI><frontal cortex><frontal lobe><healthy volunteer><hippocampal><human subject><imaging><member><memory consolidation><memory decline><memory process><memory processing><memory recognition><mental illness><multidisciplinary><neural><neural mechanism><neurobiological><neuromechanism><neuronal><neurophysiological><neurophysiology><pathophysiology><psychiatric illness><psychological disorder><recruit><reward processing><ruminate><rumination><ruminative><skills><temporal measurement><temporal resolution><theories><time interval><time measurement>