Expectation and Attention in Visual Cognition

描述（由申请人提供）：对视觉环境的准确解释对我们的生存至关重要。然而，视觉感知面临着两个主要的限制。首先，视觉系统的计算限制使得不可能同时以高保真度分析我们周围环境的所有方面。为了应对这一挑战，视觉依赖于注意力机制，优先处理那些被认为与我们的福祉最相关的环境方面。第二，视觉信息本质上是模糊的，因为许多不同的物体可以投射相同的视网膜图像，而单个物体可以投射许多不同的图像。大脑通过利用环境中的统计信息来形成感知预期，提供关于最可能的视觉数据的上下文敏感的指导来应对这一挑战。虽然期望和关注在日常生活中紧密交织在一起，但它们通常要么被孤立地研究，要么被混淆在一起，以至于它们的关系仍然知之甚少。我们在这里认为，解开的孪生影响的注意（刺激相关性）和预期（刺激概率）的感知是一个关键的重大进展，我们的理解视觉认知，包括解决长期存在的争论，在注意文学（注意行为的加法或乘法的方式？注意力是早还是晚？）。此外，这个问题与注意和预测过程似乎不足的临床条件密切相关， 例如注意力缺陷多动症和精神分裂症。本项目的总体目标是确定视觉认知中期望和注意的计算和神经机制。我们将这一目标分解为三个具体目标。首先，我们将剖析期望和注意调节视觉感知的计算机制，通过检查它们各自对信号检测和视觉神经反应的影响的时间（早期与晚期）和性质（加法与乘法）。其次，我们将确定注意和期望是否以及如何在视觉加工的调制中相互作用。最后，我们将利用这项工作中开发的计算指标，通过将健康受试者的注意力和期望模型参数的个体差异与构成临床疾病已知风险因素的人格特征差异联系起来，为翻译计算神经精神病学的应用奠定基础，这些疾病的病因涉及注意力和预测处理的缺陷。这些目标将通过计算模拟、心理物理测试、自我报告、功能性磁共振成像（fMRI）、脑电图和脑磁图（EEG、MEG）的组合来解决。拟议的工作桥梁传统上分离的研究注意力和期望，并推进我们的知识，人类如何理解，并优先考虑，他们的视觉环境。此外，它直接关系到提高我们对视觉系统潜在“故障模式”的理解。 在控制注意力或准确预测和解释感官信息方面有困难的患者群体的认知。

DESCRIPTION (provided by applicant): An accurate interpretation of the visual environment is crucial to our survival. However, visual perception is faced with two major constraints. First, computational limitations of the visual system render it impossible to simultaneously analyze all aspects of our surroundings with high fidelity. To meet this challenge, vision relies on mechanisms of attention, prioritizing the processing of those aspects of the environment deemed most relevant to our wellbeing. Second, visual information is inherently ambiguous, as many distinct objects can cast an identical retinal image, while a single object can cast many different images. The brain meets this challenge by exploiting statistical regularities in the environment to form perceptual expectations, providing context- sensitive guidance regarding the most probable visual data. Though expectation and attention are closely interwoven in everyday life, they have typically either been investigated in isolation or confounded with each other, such that their relation remains poorly understood. We here argue that the disentangling of the twin influences of attention (stimulus relevance) and expectation (stimulus probability) on perception is a key to major advances in our understanding of visual cognition, including the resolution of longstanding debates in the attention literature (does attention act in an additive o a multiplicative fashion? Does attention act early or late?). Moreover, this question is deeply relevant to clinical conditions in which attentive and predictive processes appear to be deficient, such as attention deficit hyperactivity disorder and schizophrenia. The overall goal of this projec is to determine the computational and neural mechanisms of expectation and attention in visual cognition. We break down this goal into three specific aims. Firstly, we will dissect the computational mechanisms by which expectation and attention modulate visual perception, by examining the timing (early vs. late) and nature (additive vs. multiplicative) of their respective influences on signal detection and visual neural responses. Secondly, we will determine whether and how attention and expectation interact in their modulation of visual processing. Finally, we will exploit the computational metrics developed in this work to lay the foundations for translational computational neuropsychiatry applications, by linking individual differences in attention and expectation model parameters in healthy subjects to variance in personality traits that constitute known risk-factors for clinical diseases whose etiology involves deficits in attentive and predictive processing. These aims will be addressed with a combination of computational simulations, psychophysical testing, self- report, functional magnetic resonance imaging (fMRI), electro-, and magneto-encephalography (EEG, MEG). The proposed work bridges traditionally segregated research on attention and expectation, and advances our knowledge of how humans make sense of, and prioritize, their visual environment. It is furthermore directly relevant to improving our understanding of potential 'failure modes' of visual cognition in patient populations who have difficulty with controlling attention or with accurately predicting and interpreting sensory information.