Behavioral and neural mechanisms of visual short-term memory

描述（由申请人提供）：这项工作的目的是获得对健康的视觉短期记忆（VSTM）机制的基本定量理解。在许多疾病中都发现了VSTM缺陷，包括视觉忽视、顶叶和额叶损伤、注意缺陷/多动障碍和精神分裂症。对VSTM损失的更好描述可能会为帮助恢复部分损失的治疗任务指明方向。这项研究计划在很大程度上依赖于心理物理学和神经科学的结合。领先的VSTM模型断言VSTM是一种无噪声存储，具有大约4个项目的固定有限容量。额外的项目，如果有的话，将不会被记住。我们提出了另一种理论，从低水平视觉的神经机制的角度来看待VSTM的局限性。感官信息具有不确定性，部分原因是由于神经的可变性。在简单的感知任务中，如线索组合，众所周知，在这种不确定性下，人类会执行概率推理来优化性能。将相同的概念应用于VSTM，我们假设：1)由于神经约束，不确定性随着集合大小的增加而增加；2)大脑对不确定输入进行概率推理。我们称之为不确定性模型。目的1：检验不确定性模型或固定容量模型是否能更好地解释延迟估计性能。实验对象估计记忆物品的身份。我们将使用两个不同的任务来测量受试者的不确定性作为集合大小的函数。我们将检验VSTM不受固定容量限制的假设，而是受连续分布在项目之间的神经资源的约束。目的2：检验不确定性模型或固定容量模型是否能更好地解释变更检测性能。变化检测是研究VSTM的主要范式。我们将测试这样一个假设，即观察者通过计算给定噪声观测（概率推理）的变化概率来最佳地检测不确定性下的变化，类似于低级视觉任务。目的3：验证人类观察者在变化检测中最优地整合可能性和先验的假设。在下游计算中，最优观察者在逐个项目和逐个试验的基础上使用不确定性知识。为了测试人类是否在变化检测中这样做，我们将分别通过操纵对比和总体任务统计，在固定的集合大小上改变可能性或先验。目的4：建立视觉变化检测的神经基础模型。根据Aims 1-3的实验结果，我们将构建一个用于变化检测的行为约束神经网络。我们将使用概率总体编码的理论框架。所得的网络将完全基于不确定性模型，但表现出容量限制的外观。它将作为生理测试的基础。

DESCRIPTION (provided by applicant): The goal of this work is to gain a fundamental, quantitative understanding of the mechanisms of visual short- term memory (VSTM) in health. Deficits in VSTM are found in numerous disorders, including visual neglect, parietal and frontal lobe damage, attention deficit/hyperactivity disorder, and schizophrenia. A better characterization of VSTM loss may point the direction of therapy tasks to help restore some of the loss. This research proposal relies in an essential way on integrating psychophysics with neuroscience. The leading class of VSTM models asserts that VSTM is a noiseless storage with a fixed, limited capacity of about 4 items. Extra items, if any, will not be remembered. We propose an alternative theory that casts the limitations of VSTM in terms of the neural mechanisms of low-level vision. Sensory information comes with uncertainty, in part due to neural variability. In simple perceptual tasks like cue combination, it is well known that humans perform probabilistic inference to optimize performance under such uncertainty. Applying the same concepts to VSTM, we postulate that: 1) uncertainty increases with set size due to a neural constraint; 2) the brain performs probabilistic inference on uncertain inputs. We call this the uncertainty model. Aim 1: To test whether the uncertainty model or fixed-capacity models better explain delayed estimation performance. Subjects estimate the identity of a remembered item. We will use two distinct tasks to measure subjects' uncertainty as a function of set size. We will test the hypothesis that VSTM is limited not by a fixed capacity, but by a constraint on neural resources which are distributed continuously among items. Aim 2: To test whether the uncertainty model or fixed-capacity models better explain change detection performance. Change detection is a leading paradigm for studying VSTM. We will test the hypothesis that observers optimally detect changes under uncertainty by computing the probability of a change given the noisy observations (probabilistic inference), in analogy to low-level visual tasks. Aim 3: To test the hypothesis that human observers optimally integrate likelihoods and priors in change detection. An optimal observer uses knowledge of uncertainty on an item-to-item and trial-to-trial basis in downstream computation. To test whether humans do this in change detection, we will vary either the likelihood or a prior, at fixed set size, by manipulating contrast and overall task statistics, respectively. Aim 4: To model the neural basis of visual change detection. Informed by the experimental findings in Aims 1-3, we will construct a behaviorally constrained neural network for change detection. We will use the theoretical framework of probabilistic population coding. The resulting network will be entirely based on the uncertainty model but exhibit the appearance of a capacity limit. It will serve as a basis for physiological tests. PUBLIC HEALTH RELEVANCE: Deficits in visual short-term memory are found in many forms of brain damage and disease, including visual neglect, parietal and frontal lesions, attention deficit/hyperactivity disorder, and Alzheimer's disease. Here, we propose to better characterize, through experiment and theory, the behavioral and neural mechanisms underlying visual short-term memory, with the eventual goal of improving the diagnosis and treatment of these disorders.