grant
Value networks and hippocampal non-local representations
Organization UNIVERSITY OF CALIFORNIA, SAN FRANCISCOLocation SAN FRANCISCO, UNITED STATESPosted 1 Jul 2024Deadline 31 Jan 2029
NIHUS FederalResearch GrantFY2026AccelerationAdaptive BehaviorsAlgorithmsAmmon HornAnimalsAreaBackBehaviorBehavioralBrainBrain Nervous SystemCell BodyCell Communication and SignalingCell SignalingCellsChemicalsCodeCoding SystemCognitiveCommon Rat StrainsComplexCompulsive BehaviorComputer ModelsComputerized ModelsCornu AmmonisCorpus StriatumCorpus striatum structureDataDecision MakingDistantDopamineDorsalDorsumElectrophysiologyElectrophysiology (science)EncephalonEnvironmentEvaluationEventFutureHippocampusHistoryHumanHydroxytyramineImmobilizationImpairmentInfluentialsIntracellular Communication and SignalingLearningLocationMapsMedialMediatingMethodsModelingModern ManMonitorNerve CellsNerve UnitNeural CellNeurocyteNeuronsNeurophysiology / ElectrophysiologyObsessive-Compulsive DisorderObsessive-Compulsive NeurosisOutcomePatternPhasePlayPopulationPositionPositioning AttributeProcessPsychological reinforcementRatRats MammalsRattusRecording of previous eventsReinforcementRetrievalRewardsRoleRunningSignal TransductionSignal Transduction SystemsSignalingStatistical MethodsStriate BodyStriatumTechniquesTechnologyTestingTheta RhythmTimeUpdateVentral Striatumadaptation behavioradaptive behaviorbiological signal transductioncell typecomputational modelingcomputational modelscomputer based modelscomputerized modelingdensityelectrophysiologicalexpectationexperimentexperimental researchexperimental studyexperimentsflexibilityflexiblefrontal cortexfrontal lobehigh rewardhippocampalhistoriesinnovateinnovationinnovativeinsightlearning algorithmlearning networkneuralneural mechanismneuromechanismneuronalnoveloptogeneticsorthopedic freezingsimulationsocial rolestatistic methodsstriataltemporal measurementtemporal resolutiontime measurement
Description preview
SUMMARY / ABSTRACT
This proposal aims to reveal critical neural mechanisms for intelligent reward-driven learning and
decision-making. It is well established that animals, including humans, use internal models of the world to
guide their behavior. Model-based computations are especially vital in complex environments, where animals
often need to…
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