Predicting maladaptive aversive learning via computational modeling of insular single cell ensemble activity patterns
通过岛叶单细胞整体活动模式的计算模型来预测适应不良的厌恶学习
基本信息
- 批准号:10575313
- 负责人:
- 金额:$ 1.52万
- 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:2023-03-08 至 2023-03-31
- 项目状态:已结题
- 来源:
- 关键词:Adaptive BehaviorsAffectAlgorithmsAmericanAnimal BehaviorAnimalsAnteriorAnxietyAnxiety DisordersAssociation LearningAuditoryAversive StimulusAvoidance LearningBehaviorBehavioralBrainBrain regionCalciumCellsComplexComputer ModelsCuesDataDecision MakingDevelopmentDiseaseExhibitsExtinctionFreezingFrightFutureGeneralized Anxiety DisorderGoalsHealth Care CostsHomeostasisHumanImageImpairmentIndividualInsula of ReilInterventionLearningMaintenanceMediatingMediatorMemoryMental DepressionMental disordersModelingMusNeural Network SimulationNeuronsNoseOutcomePainPanic DisorderPatternPhenotypePhobiasPhotonsPopulationPositioning AttributePost-Traumatic Stress DisordersPre-Clinical ModelProcessPsychopathologyPunishmentRegulationResistanceRodentSafetySensoryShockSignal TransductionSocial Anxiety DisorderStressStructureSymptomsTaste PerceptionTestingThalamic structureTheoretical modelTrainingavoidance behaviorbehavioral outcomebehavioral phenotypingcomputerized toolsconditioned fearcopingcostefficacious treatmentfear memoryfeedingfunctional adaptationin vivomaladaptive behaviorneuralneural circuitneurobiological mechanismneuromechanismneurotransmissionnovelnovel strategiesresponsestress disordertheoriestreatment strategy
项目摘要
Project Summary
Anxiety disorders such as panic disorders, generalized anxiety disorder, and post-traumatic stress disorder
(PTSD) affect approximately 18% of the American population with a health care cost of more than $42 billion a
year, a significant burden to the US economy. Development and maintenance of anxiety disorders have been
attributed to persistent fear memories, inadequate fear extinction, and maladaptive avoidance behavior. Thus,
it is imperative to understand the neural mechanisms underlying aversive learning in order to be able to develop
efficacious treatments for these disorders. In this project, we will focus on understanding the involvement of the
insula, a brain region heavily involved not only in aversive learning in general but also processes determining
approach/avoidance behaviors. Specifically, using in-vivo single cell calcium imaging via miniscopes, we will
record activity patterns of insular single cell ensembles during fear learning when the aversive outcome
(footshock) is inescapable as well as when the aversive outcome is omitted (fear extinction; Aim1a) and when
it becomes escapable (avoidance learning; Aim1b). Finally, using a novel theoretical-computational approach
to functionally cluster fear learning single cell ensembles in the insula, we will predict whether mice will develop
extinction resistant fear or impaired avoidance learning (Aim2). Thus, in this proposal, we aim to investigate the
involvement of the insular single cell ensembles in aversive learning and develop a novel computational tool to
predict future maladaptive aversive learning phenotypes based on the neural signaling in the insula.
项目概要
焦虑症,例如恐慌症、广泛性焦虑症和创伤后应激障碍
(PTSD) 影响着约 18% 的美国人口,每年造成的医疗保健费用超过 420 亿美元
今年,给美国经济带来了沉重负担。焦虑症的发展和维持
归因于持续的恐惧记忆、恐惧消退不足和适应不良的回避行为。因此,
为了能够发展厌恶学习的神经机制,必须了解厌恶学习背后的神经机制。
对这些疾病的有效治疗。在这个项目中,我们将重点了解
岛叶,一个大脑区域,不仅与一般的厌恶学习密切相关,而且还参与决定性学习的过程
接近/回避行为。具体来说,通过微型显微镜使用体内单细胞钙成像,我们将
当厌恶结果出现时,记录恐惧学习期间岛状单细胞群的活动模式
(脚震)是不可避免的,以及当厌恶结果被忽略时(恐惧灭绝;目标1a)以及当
它变得可以逃避(回避学习;目标1b)。最后,使用一种新颖的理论计算方法
为了对岛叶中的恐惧学习单细胞群进行功能聚类,我们将预测小鼠是否会发育
抗灭绝恐惧或回避学习受损(Aim2)。因此,在本提案中,我们旨在调查
岛单细胞群参与厌恶学习并开发一种新颖的计算工具
根据岛叶的神经信号预测未来的适应不良、厌恶学习表型。
项目成果
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