grant

Circuit basis of social behavior decision-making in a subcortical network

Organization CALIFORNIA INSTITUTE OF TECHNOLOGYLocation PASADENA, UNITED STATESPosted 15 Aug 2021Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY2025AddressAggressionAggressive behaviorAlgorithmsAmygdalaAmygdaloid BodyAmygdaloid NucleusAmygdaloid structureAnimalsBehaviorBehavior ControlBehavioralBehavioral ManipulationBiologic ModelsBiological ModelsBrainBrain Nervous SystemCell BodyCell NucleusCellsCodeCoding SystemComputing MethodologiesDataDecision MakingEncapsulatedEncephalonEndoscopyEquilibriumFemaleFunctional ImagingGeneticGoalsHumanHypothalamic structureHypothalamusImageIndividualKnowledgeLogicMachine LearningMapsMeasurementMeasuresMedialMental disordersMental health disordersMesencephalic Central GrayMesencephalonMiceMice MammalsMid-brainMidbrainMidbrain Central GrayMidbrain structureModel SystemModelingModern ManMotivationMurineMusNerve CellsNerve UnitNeural CellNeurocyteNeuronsNucleusOrganismOutputPartner in relationshipPeriaqueductal GrayPhasePhenotypePhysiologic ImagingPopulationPopulation DynamicsPreoptic AreasPropertyPsychiatric DiseasePsychiatric DisorderPublic HealthReproductionReproductive BehaviorResearchResolutionRewardsRoleShapesSiteSocial BehaviorSocial ControlsSocial InteractionStructureSystemTestingVideo RecordingVideorecordingWorkamygdaloid nuclear complexannulus of the aqueductbalancebalance functionbehavior responsebehavioral controlbehavioral responsecell typecellular targetingcomputational methodologycomputational methodscomputer based methodcomputer based predictioncomputer methodscomputing methodendoscopic imagingexperimentexperimental researchexperimental studyexperimentshypothalamicimagingimaging studyin vivoinnovateinnovationinnovativeinsightliving systemmachine based learningmachine learned algorithmmachine learning algorithmmachine learning based algorithmmachine learning based classificationmachine learning classificationmalematemental illnessmidbrain central gray substanceneuralneural circuitneural circuitryneural controlneural imagingneural regulationneuro-imagingneurocircuitryneuroimagingneurological imagingneuromodulationneuromodulatoryneuronalneuroregulationnew approachesnovelnovel approachesnovel strategiesnovel strategyoptogeneticsperiaqueductal gray matterphysiological imagingpredictive modelingpreoptic regionprogramspsychiatric illnesspsychological disorderreproductiveresolutionssexsex identitysexual identitysocial rolesociobehaviorsociobehavioralsynaptic circuitsynaptic circuitryvideo recording system
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Full Description

Project Summary/Abstract
This proposal responds to an FOA (RFA-NS-18-030) calling for 1) “novel approaches to understand neural

circuitry associated with well-defined social behaviors;” 2) Distributed circuits that contribute to the coordination

of motivational states and reward behavior;” 3) “Empirical and analytical approaches to understand how

behavioral states are emergent properties of the interaction of neurons, circuits and networks.” The study of

subcortical circuits that control conserved, naturalistic behaviors is crucial to understanding brain function. We

aim to understand how dynamic interactions between different circuit nodes in the Hypothalamic-Extended

Amygdala Decision (“HEAD”) network control innate social behavior decisions, e.g., between aggressive and

reproductive behaviors. We propose an integrated approach to this problem that combines microendoscopic

imaging (MEI) of genetically identified neuronal subpopulations with automated, machine learning-based

classification of social behavior in freely moving mice, together with functional perturbations of neuronal activity

in vivo. Our broad, long-term objective is to understand how distributed activity among interconnected

structures in the HEAD network controls moment-to-moment decisions between competing goal-directed

behaviors that are crucial for the survival of animals and humans. The central objective of this proposal is to

understand how information flows through this network during social interactions, and is decoded to control the

decision to engage in reproductive vs. aggressive social behaviors. To understand how activity in “upstream”

nodes controls neural representations in “downstream” nodes, we will implement a novel approach combining

reversible chemogenetic inhibition of the former with concurrent imaging of neuronal population activity in the

latter. The rationale for this approach is that an understanding of the system requires characterizing the effects

of functional manipulations on both behavioral and circuit-level phenotypes. To achieve our objective, we will

first characterize the neural coding of behavior and conspecific sex identity in multiple nodes of the extended

amygdala, using single-site microendoscopic imaging and computational analytic approaches (Aim 1);

determine how perturbations in the activity of such nodes influence representations in hypothalamic nodes

(Aim 2); investigate the roles of intra- and inter-nuclear interactions in determining the balance of activity

between aggression and reproduction-promoting hypothalamic nodes (Aim 3); determine how this balance is

decoded by downstream mid-brain structures to determine the type of social behavior to express (Aim 4). This

contribution is significant because it represents a systems-level approach to understanding how a subcortical

network controls behavioral decision-making. The contribution is innovative because it integrates analysis of

neuronal population activity, quantitative measurement of naturalistic social behavior and functional

perturbations of activity in specific neuronal subpopulations to gain insight into how distributed neural circuits

control survival behaviors, in a context that is relevant to maladaptations causing human psychiatric disorders.

Grant Number: 5R01NS123916-05
NIH Institute/Center: NIH

Principal Investigator: David Anderson

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