CRCNS: Circuit mechanisms of priors and learning during decision making

CRCNS：决策过程中先验和学习的循环机制

基本信息

批准号：
10610167
负责人：
Guangyu Yang
金额：
$ 38.78万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-05 至 2025-07-31
项目状态：
未结题

项目摘要

When learning a new task, both rats and humans exhibit suboptimal behaviors plagued with superstitious ticks and idiosyncratic biases. One prominent example of such suboptimality are sequential effects: animals tend to bias their choices based on previous decisions and outcomes, hindering performance in common laboratory tasks using independent trials. Recurrent neural networks (RNN) have become a common tool to study potential neural mechanisms of cognition. Yet, RNNs typically behave much closer to optimality in laboratory tasks than real subjects. We suggest this behavioral difference is rooted in the fundamental discrepancy between how animals and current RNNs learn: unlike animals before learning, RNNs before training are tabula rasa and their connectivity is adjusted exclusively to the local contingencies of the task. We hypothesize that animals’ learning of simple laboratory tasks builds mostly on pre-existing programs, namely structural prior, that have been shaped by evolution for the species’ fitness in a given ecological niche. Sequential effects are a manifestation of such pre-wired strategies, which may ultimately support learning. To test this, we will characterize sequential effects during learning of a set of perceptual tasks and identify their underlying neural circuitry. We will compare animals’ behavior with RNNs which, after being equipped with structural priors, can mimic the animal’s ability to learn new tasks. Objectives Objective 1. Compare sequential effects in humans and rats with those developed by RNNs. Objective 2. Characterize the role of the corticostriatal circuit mPFC --> DMS in the tasks and the site of plasticity necessary for task learning. Objective 3. Characterize the neural mechanisms underlying the representation of relevant variables in the brain of the rat and in RNNs.

在学习新任务时，老鼠和人类都暴露于迷信的次优行为壁虱和特质偏见。这种次优性的一个突出的例子是顺序效应：动物倾向于根据先前的决策和结果来偏向选择，从而阻碍表现使用独立试验的常见实验室任务。复发性神经网络（RNN）已成为研究潜在神经机制的常见工具认识。然而，与真实主题相比，RNN的行为通常更接近实验室任务的最佳性。我们表明这种行为差异植根于动物与动物之间的基本差异当前的RNN学习：与动物不同之前，培训前的RNN是Tabula Rasa及其连接性专门调整为任务的本地意外事件。我们假设动物对简单实验室任务的学习主要建立在现有的计划上，即结构性先验，这是根据该物种在给定生态中的适应性的进化而塑造的利基。顺序效应是这种前线策略的表现，最终可能支持学习。为了测试这一点，我们将在学习一组感知任务时表征顺序效应并确定其潜在的神经回路。我们将将动物的行为与RNN进行比较配备了结构先验，可以模仿动物学习新任务的能力。目标目标1。将人类和大鼠的顺序效应与RNN开发的效应进行比较。目标2。表征皮质纹状体电路MPFC的作用 - > dms在任务和位置任务学习所需的可塑性。目标3。表征相关变量表示的神经机制大鼠和RNN的大脑。