Decoding ensemble dynamics from cortico-amygdalar circuits during social choice
在社会选择过程中从皮质-杏仁核回路解码整体动态
基本信息
- 批准号:10723932
- 负责人:
- 金额:$ 19.24万
- 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
- 起止时间:2023-08-01 至 2028-07-31
- 项目状态:未结题
- 来源:
- 关键词:Absence of pain sensationAcuteAlgorithmsAmygdaloid structureAnimalsAnteriorBayesian ModelingBehaviorBehavioralBehavioral ModelBehavioral ParadigmClinicalComputer ModelsComputing MethodologiesDataDecision MakingDimensionsEmpathyEnvironmentFDA approvedFeelingGoalsHealthHumanImpairmentInterventionJointsK-Series Research Career ProgramsMachine LearningMeasuresMediatorMentorsMethamphetamineMethodsMusNeuronsNeurosciencesNonlinear DynamicsNucleus AccumbensPainPartner in relationshipPharmaceutical PreparationsPost-Traumatic Stress DisordersPrimatesResearchResearch PersonnelRewardsRodentRoleSocial BehaviorSocial ChangeSocial EnvironmentSocial InteractionSocial ProcessesSpace ModelsStatistical ModelsStimulusStressStructureSubgroupSystemTestingTrainingbehavioral pharmacologycareercingulate cortexclinically significantdeep learningdeep learning modelecstasyexperienceexperimental studyindividual variationinnovationneuralneural circuitneural modelneuromechanismneuronal circuitryneuropsychiatryneurotransmissionnoveloptogeneticspharmacologicpreferenceresponseskillssocialsocial anxietysocial biassocial cognitionsocial learningsocial relationshipstoolvector
项目摘要
Project Summary
Social relationships are a key component of human health and survival and impairments in social
behavior have a major impact in many psychiatric conditions. Yet despite the importance of social
context to health, there remains no FDA-approved medications that target social cognition and
behavior. Social context is defined by the social stimuli available to an animal, is a key mediator
of behavior in rodents, and impacts social choices. Yet little is known about how neuronal circuits
encode social context and choice.In rodents, circuits in ACC that project to the amygdala (ACC-
BLA) and Nucleus accumbens (ACC-Nac) have been shown to be necessary for different aspects
of social information transfer. However, how neural activity in these regions encode social context
and choice is not known. We developed a social choice paradigm in which mice choose access
to a novel or a familiar/cagemate mouse. In this novel paradigm, mice consistently show
preference for a social target over a novel object, but they show variable individual biases in social
choice between a novel and cagemate conspecific. Recording neural activity from the ACC-BLA
and ACC-Nac circuits during this behavioral paradigm will allow for a more nuanced
understanding of the neural mechanisms underlying social choice. In order to better understand
how activity recorded during this and traditional social behavioral paradigms we will leverage
recently developed statistical models and inference algorithms to cluster nonlinear dynamical
neural responses into an unspecified number of functional sub-groups called Functional Encoding
Units (FEUs). We will also apply deep learning tools for behavioral analysis to engage in joint
modeling of neural and behavioral data. This will enhance our ability to predict social context and
enrich encoding of social behavior. Lastly, given the impact of 3,4-Methylenedioxy
methamphetamine (MDMA) on social behavior and empathy and its recent clinical significance in
post traumatic stress disorder, we hypothesize that MDMA paired social exposure will bias social
choice in our paradigm. We will apply deep learning to behavioral analysis of our paradigm in
order to test this hypothesis. Through this K-Award we will define how social stimuli are encoded
in a context-specific manner within ACC-BLA and ACC-Nac circuits during social choice and how
MDMA biases these social choices. In parallel, intensive mentoring, directed readings, and
structured coursework will enhance my skills and toolkit in computational modeling and machine
learning-based analysis of both neural and behavioral data, and behavioral pharmacology, setting
the stage for independence.
项目摘要
社会关系是人类健康和生存的关键组成部分,也是社会中的损伤
在许多精神疾病中,行为都会产生重大影响。然而,尽管社交媒体很重要
与健康相关的背景下,仍然没有FDA批准的针对社会认知和
行为。社会背景是由动物可获得的社会刺激来定义的,是一个关键的中介
影响啮齿动物的行为,并影响社会选择。然而,关于神经元回路是如何
编码社会背景和选择。在啮齿类动物中,ACC中的回路投射到杏仁核(ACC-
BLA)和伏隔核(ACC-NAC)在不同方面都是必需的
社会信息传递。然而,这些区域的神经活动如何编码社会背景
而选择是未知的。我们开发了一个社会选择范式,在这个范式中,老鼠选择进入
一只小说或一只熟悉的/笼子老鼠。在这个新的范例中,老鼠一直表现出
对社会目标的偏好超过对新对象的偏好,但他们在社会目标中表现出不同的个体偏见
在小说和笼子同种之间选择。记录ACC-BLA的神经活动
而ACC-NAC电路在此行为范例中将允许更细微的
理解社会选择背后的神经机制。为了更好地了解
在此期间记录的活动以及我们将如何利用传统的社会行为范式
最近发展起来的统计模型和推理算法来聚类非线性动力学
神经反应分为数量不定的功能亚群,称为功能编码
单位(FEU)。我们还将应用深度学习工具进行行为分析,以参与联合
神经和行为数据的建模。这将增强我们预测社会背景和
丰富社会行为的编码。最后,考虑到3,4-亚甲二氧基的影响
甲基苯丙胺对老年人社会行为和同理心的影响及其近期临床意义
创伤后应激障碍,我们假设MDMA配对的社交暴露会偏向社会
我们范式中的选择。我们将把深度学习应用到我们的范例的行为分析中
以检验这一假说。通过这个K奖,我们将定义社会刺激是如何编码的
在社会选择期间以特定于上下文的方式在ACC-BLA和ACC-NAC电路内以及如何
MDMA偏向于这些社会选择。同时,密集的指导、定向阅读和
有组织的课程工作将增强我在计算建模和机器方面的技能和工具包
基于学习的神经和行为数据分析,以及行为药理学,环境
独立的舞台。
项目成果
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