Neural Basis of Magnitude Representations and Metric Error Monitoring in Mice

间隔计时是在秒到分钟范围内跟踪间隔的能力，而计数是枚举离散事件的能力。计时和计数行为具有共同的可变性特征，表明计时/计数机制以相似的加工动态运作，甚至可能起源于一个共同的神经位点。人类和非人类动物在决策过程中解释了这种可变性（CCV 32,45,49,62），这表明时间/计数的内源性不确定性是认知上可获得的。为了支持这一说法，我最近发现人类可以监控时间、数值和空间误差的方向和大小（例如CCV 5,20,42）。这一发现（度量误差监测- MEM）为我的长期（20年）研究计划目标提供了新的理论基础；也就是说，阐明大脑是如何量化表现中的经验和错误的，这是基于我独特的行为、计算和神经科学方法的结合。我的一些短期目标（5年）将为我的长期目标奠定基础：1)小鼠MEM的研究：我将训练小鼠在最短的时间内保持杠杆的压抑状态，或者直到经历最小数量的信号。我将根据释放杠杆后奖励预期期间的反应率，推断出关于计时/计数表现错误的判断。我还将研究度量误差判断如何转化为随后的行为调整。2)利用光遗传学研究小鼠MEM的神经基础：我假设在该任务中，早于目标幅度和晚于目标幅度的反应分别由中脑皮层负多巴胺能奖励预测误差（dRPE）和正多巴胺能奖励预测误差（dRPE）发出信号，dRPE幅度编码了行为与目标的接近程度。3)检查小鼠计时和计数之间的机制重叠，以了解幅度处理的总体神经计算：我将测试黑质致密部多巴胺能神经元活动的光遗传调节是否对时间和数字判断有类似的偏差。通过检查关于诱导偏差的度量误差判断，我还将测试我基于模型的断言，即MEM来自感知和运动系统中大小的独立处理（CCV 42）。在这些目标的支持下，我的NSERC项目将导致对基于因果证据的大脑量化能力的全面和总体理解，并对行为神经科学和认知科学中量级表征和错误处理的概念化产生预期的变革性影响。我将对hqp进行尖端行为、计算和神经科学方法方面的培训，并整合这些方法，以研究大脑的不同功能，并在学术界内外获得有影响力的研究职位。

Interval timing is the ability to keep track of intervals in seconds to minutes range while counting is the ability to enumerate discrete events. The timing and counting behaviors have common variability features, suggesting that timing/counting mechanisms operate with similar processing dynamics and may even originate from a common neural locus. Humans and non-human animals account for this variability during decision-making (CCV 32, 45, 49, 62), suggesting that the endogenous uncertainty about time/counts is cognitively accessible. In support of this claim, I recently discovered that humans can monitor the direction and size of temporal, numerical, and spatial errors (e.g. CCV 5, 20, 42). This discovery (metric error monitoring - MEM) provided a new theoretical basis for the long-term (20 yrs) objective of my research program; namely the elucidation of how the brain quantifies experiences and errors in performance based on my unique combination of behavioral, computational, and neuroscientific methods. Some of my short-term objectives (5 yrs) that will lay the foundation for my long-term objective are 1) Investigation of MEM in mice: I will train mice to keep a lever depressed for a minimum duration or until a minimum number of signals is experienced. I will infer judgments about the errors in timing/counting performance based on response rates during the reward anticipation period following the release of the lever. I will also examine how metric error judgments are translated into subsequent behavioral adjustments. 2) Investigation of the neural basis of MEM in mice using optogenetics: I hypothesize that in this task responses that are earlier and later than the target magnitude are signalled by mesocortical negative and positive dopaminergic reward prediction error (dRPE), respectively and that the dRPE amplitude codes for the proximity of the performance to the target. 3) Examining the mechanistic overlap between timing and counting in mice to inform an overarching neurocomputational account of magnitude processing: I will test whether the optogenetic modulation of the activity of dopaminergic neurons in substantia nigra pars compacta biases temporal and numerical judgments similarly. By examining metric error judgments about induced biases, I will also test my model-based assertion that MEM is derived from the independent processing of magnitudes in the perceptual and motor systems (CCV 42). My NSERC program buttressed by these aims will lead to a comprehensive and overarching understanding of the quantification capacity of the brain based on causal evidence with an expected transformative impact on the conceptualization of magnitude representations and error processing in behavioral neuroscience and cognitive science. I will train HQPs in cutting-edge behavioral, computational, and neuroscience methods and their integration for studying different functions of the brain, and securing impactful research positions in and outside academia.