Orbitofrontal modulation of dopamine during value-based decision-making
Orbitofrontal modulation of dopamine during value-based decision-making
批准号:
10607543
负责人:
Andrew Mah
金额:
$3.65万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-01 至 2024-12-31
关键词:
Action PotentialsAddressAnimalsAxonBehaviorBehavioralBehavioral ModelBrainCalciumCellsCognitiveComputer ModelsCorpus striatum structureDataDecision MakingDevelopmentDissociationDopamineElementsEnvironmentFiberFutureGeneticGoalsInterneuronsKnowledgeLeadershipLearningLinkMachine LearningMaintenanceMeasuresMediatingMentorsMidbrain structureModelingNeuromodulatorNeurosciencesNew YorkNucleus AccumbensOutcomePathologyPhotometryPlayPositioning AttributePostdoctoral FellowPrefrontal CortexPresynaptic TerminalsPsyche structurePsychologyRattusResearchRewardsRoleSignal TransductionStructureSystemTechniquesTrainingUniversitiesViralWorkWritingbasecalcium indicatorcholinergiccollaborative environmentdesigndesigner receptors exclusively activated by designer drugsdopaminergic neuronexpectationexperienceexperimental studyimprovedinsightinterestneural circuitneuropsychiatric disordernovelrelating to nervous systemreward processingsensorskillssymposiumtheoriestool
中文摘要
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英文摘要
Project Summary
Dopamine is an important neuromodulator that mediates learning from previous outcomes (“retrospective”
learning) by encoding reward prediction errors — the difference between experienced and expected rewards.
However, recent work has suggested that dopamine might use the prefrontal cortex to encode more abstract
prediction errors, such as errors about the hidden state of a task or environment. The exact circuit mechanisms
underlying these abstract hidden-state prediction errors remains unclear. This proposal has two major goals.
First, I will characterize dopamine activity related to hidden-state inference in rats performing a task with partially
observable states. Second, I will identify the circuit mechanisms that generate dopamine state prediction errors
in this task. I will use computational modeling and state-of-the-art genetic and viral tools, including fiber
photometry to measure dopamine activity and projection-specific chemogenetic silencing of prefrontal cortex, to
address these goals. I will measure dopamine activity both at the level of cell-body calcium dynamics, as well as
at the level of axonal release, which can be dissociated. This proposal will describe the multi-regional neural
circuits that underlie the acquisition and maintenance of abstract representations of the environment. The results
will provide insight into the pathology and treatment of neuropsychiatric disorders, which are characterized by
disrupted reward processing.
My co-sponsors at New York University (NYU), Dr. Christine Constantinople and Dr. Paul Glimcher, have
complimentary experience in behavioral and systems neuroscience experiments in rats, and computational
modeling of decision-making, respectively. The training I will receive will allow me to pursue truly integrative
research that involves the close interplay between experiments and theory. The strong, collaborative
environment at NYU makes it an ideal place for me to pursue these research goals. My training plan provides a
detailed strategy for acquiring the necessary skills from a team of co-mentors with extensive, proven expertise
in the relevant techniques. Technical training, as well as frequent data presentations, attendance of professional
courses, seminars, and conferences, and development of my writing and leadership skills will equip me to
complete the proposed research, and transition to a post-doctoral position in my field of interest.
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