Neural mechanisms of probability estimation during decision-making

决策过程中概率估计的神经机制

基本信息

  • 批准号:
    9224202
  • 负责人:
  • 金额:
    $ 13.01万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-09-16 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

Project Summary The ability to estimate the probabilities of different outcomes is a cognitive function critical for decision- making in uncertain environments. A pervasive feature of human decision-making is probability distortion: humans tend to overweight small probabilities and underweight large probabilities. For example, when individuals decide to purchase insurance or play the lottery, these decisions are influenced by how likely they perceive low probability outcomes to be. Decision-making is disrupted in psychiatric disorders including schizophrenia and bipolar disorder. Therefore, a circuit-level understanding of how the brain represents probabilistic outcomes during decision-making has enormous consequences for human health. I will use high-throughput behavioral training to develop behavioral paradigms for studying probability distortion in rats, enabling application of powerful tools to monitor and manipulate neural circuits (Aim 1, K99 phase). I have recently developed a system that enables cellular resolution imaging of large populations of neurons in rats performing cognitive behaviors during voluntary head-restraint. I will use this system, combined with newly developed transgenic rats expressing the calcium indicator GCaMP6f, to record from 100s-1000s of cortical neurons as behaving rats estimate probabilities (Aim 2, K99 phase). I will develop and apply decoding methods to explicitly test hypotheses about how neural populations represent probabilities. Combining the imaging data and decoding methods, I will determine the stage of cortical processing at which probability distortion emerges (Aim 2, K99 phase). Finally, I will perform optogenetic and pharmacological perturbation experiments to delineate the functional causal circuits underlying probability distortion (Aim 3, R00 phase). I will then combine optogenetics and two-photon imaging of interconnected brain regions, to evaluate how representations of probability propagate across and are represented by multiple brain regions. Together, these experiments will establish the rat as a cost-effective, tractable mammalian model for studying probability distortion, and will produce well-informed working models of the relevant circuits and mechanisms by which animals compute, represent, and distort estimates of probabilities. The rat voluntary head-restraint imaging system has been exclusively developed as part of a collaboration between the Tank and Brody laboratories, making Princeton the only place for me to learn these techniques. In addition, the strong, collaborative environment at the Princeton Neuroscience Institute makes it an ideal place for me to pursue these research goals. My training plan provides a detailed strategy for acquiring the necessary skills in the K99 phase from a team of co-mentors with extensive, proven expertise in the relevant techniques. Technical training, as well as frequent data presentations, attendance of professional courses, seminars, and conferences, and development of my writing and leadership skills, will allow me to transition to an independent position. In the independent R00 phase, I will use these acquired skills to complete the proposed aims and build a laboratory focused on the study of probability distortion and decision- making using innovative behavioral, imaging, computational, and optogenetic approaches.
项目摘要 估计不同结果的概率的能力是决策的关键认知功能- 在不确定的环境中。人类决策的一个普遍特征是概率失真: 人类倾向于高估小概率,低估大概率。例如当 个人决定购买保险或玩彩票,这些决定受到他们可能性的影响。 认为低概率的结果是。精神疾病患者的决策受到干扰, 精神分裂症和躁郁症。因此,在电路层面上理解大脑如何表现 决策过程中的概率结果对人类健康有着巨大的影响。 我将使用高通量行为训练来开发研究概率的行为范例 扭曲的大鼠,使应用强大的工具来监测和操纵神经回路(目的1,K99 阶段)。我最近开发了一种系统,可以对大量的 在自愿头部约束期间执行认知行为的大鼠神经元。我将使用这个系统,结合 用新开发的表达钙指示剂GCaMP 6 f的转基因大鼠, 作为行为大鼠的皮质神经元估计概率(目标2,K99阶段)。我将开发和应用解码 方法来明确测试关于神经群体如何表示概率的假设。结合 成像数据和解码方法,我将确定在哪个概率皮层处理阶段 出现失真(Aim 2,K99阶段)。最后,我将进行光遗传学和药理学微扰 实验来描绘潜在的概率失真的功能因果电路(目标3,R 00阶段)。我 然后,将结合联合收割机光遗传学和相互连接的大脑区域的双光子成像,以评估 概率的表示在多个大脑区域传播并由多个大脑区域表示。所有这些 实验将使大鼠成为研究概率的一种成本效益高、易处理的哺乳动物模型 扭曲,并将产生相关电路和机制的信息灵通的工作模型, 动物计算、代表和扭曲概率的估计。 大鼠自愿头部约束成像系统是作为 Tank和Brody实验室之间的合作,使普林斯顿成为我学习这些知识的唯一地方。 技术.此外,普林斯顿神经科学研究所强大的协作环境使其成为 是我追求这些研究目标的理想场所我的培训计划提供了详细的策略, 在K99阶段从一个具有广泛的,经过验证的专业知识的共同导师团队获得必要的技能, 相关技术。技术培训,以及频繁的数据演示,专业人员的出席 课程,研讨会和会议,以及我的写作和领导能力的发展,将使我能够 过渡到独立的位置。在独立R 00阶段,我将使用这些获得的技能, 完成提出的目标,建立一个实验室,重点研究概率失真和决策- 使用创新的行为,成像,计算和光遗传学方法。

项目成果

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Christine Marie Constantinople其他文献

Christine Marie Constantinople的其他文献

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{{ truncateString('Christine Marie Constantinople', 18)}}的其他基金

Neural circuit mechanisms of arithmetic for economic decision-making
经济决策算法的神经回路机制
  • 批准号:
    10002804
  • 财政年份:
    2020
  • 资助金额:
    $ 13.01万
  • 项目类别:
CRCNS: Inferring reference points from OFC population dynamics
CRCNS:从 OFC 人口动态推断参考点
  • 批准号:
    10675077
  • 财政年份:
    2020
  • 资助金额:
    $ 13.01万
  • 项目类别:
CRCNS: Inferring reference points from OFC population dynamics
CRCNS:从 OFC 人口动态推断参考点
  • 批准号:
    10261540
  • 财政年份:
    2020
  • 资助金额:
    $ 13.01万
  • 项目类别:
CRCNS: Inferring reference points from OFC population dynamics
CRCNS:从 OFC 人口动态推断参考点
  • 批准号:
    10462618
  • 财政年份:
    2020
  • 资助金额:
    $ 13.01万
  • 项目类别:
Neural mechanisms of probability estimation during decision-making
决策过程中概率估计的神经机制
  • 批准号:
    9894590
  • 财政年份:
    2019
  • 资助金额:
    $ 13.01万
  • 项目类别:
Neural mechanisms of probability estimation during decision-making
决策过程中概率估计的神经机制
  • 批准号:
    10064970
  • 财政年份:
    2019
  • 资助金额:
    $ 13.01万
  • 项目类别:
Neural mechanisms of probability estimation during decision-making
决策过程中概率估计的神经机制
  • 批准号:
    9816021
  • 财政年份:
    2019
  • 资助金额:
    $ 13.01万
  • 项目类别:
Neural mechanisms of probability estimation during decision-making
决策过程中概率估计的神经机制
  • 批准号:
    9353881
  • 财政年份:
    2016
  • 资助金额:
    $ 13.01万
  • 项目类别:

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