Expectation and Attention in Visual Cognition

描述(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，视觉感知面临着两大制约。首先，视觉系统的计算限制使得它不可能同时高保真地分析我们周围环境的所有方面。为了迎接这一挑战，VISION依靠注意力机制，优先处理那些被认为与我们的福祉最相关的环境方面。其次，视觉信息本质上是模棱两可的，因为许多不同的物体可以投射出相同的视网膜图像，而一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规律来形成感知预期，提供关于最可能的视觉数据的上下文敏感的指导，从而应对这一挑战。尽管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调查，要么相互混淆，以至于人们对它们的关系仍然知之甚少。我们在这里认为，注意(刺激相关性)和预期(刺激概率)对知觉的双重影响的分离是我们对视觉认知理解的重大进步的关键，包括解决注意文献中长期存在的争论(注意是以相加的方式起作用还是以乘法的方式起作用？注意力的作用是早还是晚？)此外，这个问题与临床情况密切相关，在这些情况下，注意力和预测性过程似乎是不足的， 比如注意力缺陷多动障碍和精神分裂症。这个项目的总体目标是确定视觉认知中预期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，我们将通过检验预期和注意对信号检测和视觉神经反应的影响的时间性(早与晚)和性质(相加与相乘)来剖析期望和注意调节视觉知觉的计算机制。其次，我们将确定注意和期望是否以及如何在它们对视觉加工的调节中相互作用。最后，我们将利用在这项工作中开发的计算度量为翻译计算神经精神病学应用奠定基础，方法是将健康受试者的注意力和期望模型参数的个体差异与人格特征的差异联系起来，这些差异构成了临床疾病的已知风险因素，其病因涉及注意力和预测性加工缺陷。这些目标将通过计算模拟、心理物理测试、自我报告、功能磁共振成像(FMRI)、脑电和脑磁图(EEG，MEG)的组合来实现。这项拟议的工作在传统上将注意力和期望的研究分离开来，并促进了我们对人类如何理解和优先处理他们的视觉环境的了解。此外，它还直接关系到我们对视觉系统潜在的“故障模式”的理解 在控制注意力或准确预测和解释感觉信息方面有困难的患者群体的认知能力。

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.