P3: Internal Brain States

摘要/摘要：项目3，内部大脑状态 我们合作的最新研究表明，啮齿动物的感官决策依赖于 时变的内部状态，在不同的状态下采用不同的决策策略。我们有 开发了一个统计模型，用于仅从决策行为中识别这些状态，并发现， 老鼠在数十到数百次任务试验的时间尺度上在策略之间切换。这一发现提出了一个重大的 这对传统的决策模型提出了挑战，传统的决策模型假设经过训练的动物依赖于一个单一的 证据积累策略在一个会话中相对固定。此外，我们发现， 只有在某些状态下，纹状体的活动才影响动物的选择;在其他状态下，决定不受纹状体的影响。 纹状体失活，表明小鼠依赖于不同的神经回路在不同的状态下做出决定。 这个项目将跟进这一惊人的发现，以调查背后的神经机制 整个大脑的内部状态。 目标1将集中在表征的神经基础的内部状态支配的感觉 决策和工作记忆。我们将使用因果扰动和大规模神经记录， 表征种群活动如何在不同状态下变化，并使用闭环光遗传失活 研究不同的大脑区域如何在不同的状态下做出决策的实验。 目标2将观察大脑内部，从神经活动的动态中识别内部状态。我们将 开发新的模型，以表征内部状态如何在单次试验的时间尺度上演变， 列车数据然后，我们将使用这些模型来表征大脑之间的状态依赖通信 大规模多区域电生理记录中的区域。 目标3将集中于确定我们的模型所识别的认知决策状态如何关联 生理上定义的内部状态，如口渴，饥饿和觉醒。这将使我们能够连接我们的 关于决策策略的研究结果与生理内部状态的大量文献相结合。为了测定 唤醒时，我们将测量瞳孔直径，并使用纤维光度法测量去甲肾上腺素能神经元的活性。 蓝斑神经元和基底前脑胆碱能神经元。作为饥饿的神经读出器， 口渴时，我们将测量相关下丘脑神经元群体的活性。这些测量将是 与我们模型中的内部状态相比。 我们期望在这个项目中的实验和建模工作能够实质性地推进两个优先事项 BRAIN倡议的领域：证明因果关系和确定基本原则。

Summary/Abstract: Project 3, Internal Brain States Recent work from our collaboration has revealed that sensory decision-making in rodents relies on time-varying internal states, with distinct decision-making strategies employed in different states. We have developed a statistical model for identifying these states from decision-making behavior alone, and find that mice switch among strategies on the timescale of tens to hundreds of task trials. This finding presents a major challenge to traditional models of decision-making, which assume that trained animals rely on a single evidence-accumulation strategy that is relatively fixed within a session. Furthermore, we found that inactivation of the striatum affects the animal’s choices only in some states; in other states, decisions are not affected by striatal inactivation, suggesting that mice rely on distinct neural circuits for making decisions in different states. This project will follow up on this startling discovery in order to investigate the neural mechanisms underlying internal states throughout the brain. Aim 1 will focus on characterizing the neural basis for the internal states governing sensory decision-making and working memory. We will use causal perturbations and large-scale neural recordings to characterize how population activity varies across states, and use closed-loop optogenetic inactivation experiments to examine how different brain regions contribute to decision-making in different states. Aim 2 will look inside the brain to identify internal states from the dynamics of neural activity. We will develop new models to characterize how internal states evolve on the timescale of single trials using spike train data. We will then use these models to characterize state-dependent communication between brain regions in large-scale multi-region electrophysiological recordings. Aim 3 will focus on determining how the cognitive decision-making states identified by our model relate physiologically-defined internal states such as thirst, hunger, and arousal. This will allow us to connect our findings about decision-making strategies to the extensive literature on physiological internal states. To assay arousal, we will measure pupil diameter and use fiber photometry to measure activity of noradrenergic neurons in the locus coeruleus and cholinergic neurons in basal forebrain. As a neural readout of hunger and thirst, we will measure activity in relevant hypothalamic neuron populations. These measurements will be compared to internal states derived from our models. We expect the experiments and modeling efforts in this project to substantially advance two priority areas of the BRAIN Initiative: demonstrating causality and identifying fundamental principles.