Contribution of non-canonical dopamine pathways to model-based learning
非典型多巴胺通路对基于模型的学习的贡献
基本信息
- 批准号:10607923
- 负责人:
- 金额:$ 58.23万
- 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:2023-04-15 至 2028-01-31
- 项目状态:未结题
- 来源:
- 关键词:Adaptive BehaviorsAddressAlgorithmsAmygdaloid structureAutomobile DrivingBasic ScienceBehaviorBehavior assessmentBehavioralBrain regionClinicalCoupledCuesDataDecision MakingDesire for foodDevelopmentDiagnosisDissectionDistalDopamineEmotionalEnvironmentEventExposure toFrightFunctional disorderFutureGeneticGoalsHypothalamic structureIndividualKnowledgeLateralLearningLinkMeasurementMediatingMemoryMental disordersMethodsMidbrain structureModelingModernizationNeural PathwaysNeurobehavioral ManifestationsNeuronsNeurosciencesOpticsOutcomePathologicPathway interactionsPhasePoliciesProcessPsyche structurePsychological reinforcementResearchRewardsRoleSensorySignal TransductionStimulusStructureSubstance Use DisorderSystemTechniquesTestingVentral Tegmental AreaWorkcatalystcell typedirectional celldopaminergic neuronfeedingflexibilityinnovationinterestmodel developmentneuralneural circuitnext generationnoveloptical imagingoptogeneticspreventprospectiveresponsesensortheoriestool
项目摘要
PROJECT SUMMARY
Model-based learning affords individuals the ability to contemplate the specific outcomes of actions or events. This
facilitates flexible decision making. While we know of brain regions that contribute to model-based learning, the
wider pathways and circuits that facilitate development of these flexible representations in these regions are less
explored. Given that substance use disorders are characterized by deficits in model-based decision making, a gap
in the knowledge of the neural circuits contributing to model-based learning prevents us from making clinical
advances in the treatment of these deficits. The overarching goal of this proposal is, thus, to expose the neural
circuits that mediate model-based decision making.
Recent evidence from our team and others has implicated ventral tegmental area dopamine neurons (VTADA)
as critical to driving model-based learning. This was surprising because phasic VTADA activity was typically
restricted to assigning general value to cues, which prevents this signal from contributing to more flexible
associative relationships characterizing model-based learning. This work acts as our catalyst to investigate how
this dopamine signal is used in the circuits necessary for model-based learning. We are particularly interested in
the dopamine pathways to the basolateral amygdala (VTADABLA) and lateral hypothalamus (VTADALH). We
have shown that BLA and LH are important for the development of model-based associations. However, while the
BLA and LH both contribute to model-based learning about cues proximal to rewards, the function of these regions
diverge when it comes to more distal predictors. Specifically, the BLA remains important for using distal predictors
to predict rewards, while the LH opposes learning about distal predictors. It is unknown how VTADA projections to
BLA or LH facilitate reinforcement learning generally, or model-based learning specifically. Thus, we hypothesize
that midbrain dopamine projections to the BLA and LH mediate the encoding of detailed model-based associative
memories that allow prioritization of information most relevant to rewards.
Capitalizing on the overlapping and complementary expertise and perspectives from two labs, we will uncover
the function of these two non-canonical dopamine circuits in model-based learning. We will use a symmetrical and
multifaceted approach using modern cell-type and projection-specific manipulation and recording techniques in the
context of sophistical behavioral tasks to reveal the function VTADA projections to BLA and LH in proximal and distal
learning. We will use cell-type and projection-specific optogenetic inhibition, stimulation, and recording of the
VTADABLA and VTADALH pathways to expose the role of these pathways. We will use next-generation
dopamine sensors to provide novel measurements of dopamine release in BLA and LH. Finally, we
chemogenetically inhibit VTADA projections to BLA or LH while optically imaging BLA or LH neuronal activity to
elucidate the contribution of dopamine input to learning- and decision-related activity.
项目概要
基于模型的学习使个人能够思考行动或事件的具体结果。这
有利于灵活决策。虽然我们知道有助于基于模型的学习的大脑区域,
促进这些地区灵活代表发展的更广泛途径和回路较少
探索过。鉴于物质使用障碍的特点是基于模型的决策存在缺陷,因此存在差距
对基于模型的学习的神经回路的了解阻止了我们进行临床研究
治疗这些缺陷的进展。因此,该提案的总体目标是揭示神经网络
调解基于模型的决策的电路。
我们团队和其他人的最新证据表明腹侧被盖区多巴胺神经元(VTADA)
对于推动基于模型的学习至关重要。这是令人惊讶的,因为阶段性 VTADA 活动通常是
仅限于为提示分配一般值,这阻止了该信号有助于更灵活
表征基于模型的学习的关联关系。这项工作是我们研究如何
该多巴胺信号用于基于模型的学习所需的电路中。我们特别感兴趣的是
多巴胺通路通往基底外侧杏仁核(VTADABLA)和外侧下丘脑(VTADALH)。我们
已经表明 BLA 和 LH 对于基于模型的关联的发展非常重要。然而,虽然
BLA 和 LH 都有助于基于模型的学习,了解接近奖励的线索以及这些区域的功能
当涉及到更远端的预测变量时,会出现分歧。具体来说,BLA 对于使用远端预测因子仍然很重要
预测奖励,而 LH 反对学习远端预测因子。目前尚不清楚 VTADA 如何预测
BLA 或 LH 通常有助于强化学习,特别是基于模型的学习。因此,我们假设
中脑多巴胺投射到 BLA 和 LH 介导基于模型的详细联想的编码
允许优先考虑与奖励最相关的信息的记忆。
利用两个实验室重叠和互补的专业知识和观点,我们将发现
这两个非规范多巴胺回路在基于模型的学习中的功能。我们将使用对称和
使用现代细胞类型和投影特定操作和记录技术的多方面方法
复杂的行为任务背景,揭示近端和远端 BLA 和 LH 的 VTADA 功能预测
学习。我们将使用细胞类型和投射特异性的光遗传学抑制、刺激和记录
VTADABLA 和 VTADALH 通路揭示这些通路的作用。我们将使用下一代
多巴胺传感器提供 BLA 和 LH 中多巴胺释放的新测量。最后,我们
化学遗传学抑制 VTADA 对 BLA 或 LH 的投射,同时对 BLA 或 LH 神经元活动进行光学成像
阐明多巴胺输入对学习和决策相关活动的贡献。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Melissa Sharpe其他文献
Melissa Sharpe的其他文献
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{{ truncateString('Melissa Sharpe', 18)}}的其他基金
Investigating the Recruitment of Lateral Hypothalamic Circuits for Encoding Fear Memories Following Experience with Reward Learning
奖励学习经验后调查下丘脑外侧回路编码恐惧记忆的情况
- 批准号:
10581650 - 财政年份:2022
- 资助金额:
$ 58.23万 - 项目类别:
The role of the lateral hypothalamus in the balance of learning and behavior towards relevant stimuli
下丘脑外侧在平衡学习和针对相关刺激的行为中的作用
- 批准号:
10522247 - 财政年份:2022
- 资助金额:
$ 58.23万 - 项目类别:
Investigating the Recruitment of Lateral Hypothalamic Circuits for Encoding Fear Memories Following Experience with Reward Learning
奖励学习经验后调查下丘脑外侧回路编码恐惧记忆的情况
- 批准号:
10453103 - 财政年份:2022
- 资助金额:
$ 58.23万 - 项目类别:
The role of the lateral hypothalamus in the balance of learning and behavior towards relevant stimuli
下丘脑外侧在平衡学习和针对相关刺激的行为中的作用
- 批准号:
10814113 - 财政年份:2022
- 资助金额:
$ 58.23万 - 项目类别:
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