Understanding the mechanisms that control the dynamics of perceptual switches

描述(申请人提供)：当观看静态的视觉场景时，不同的对象和组织可以自发地来主导视觉感知。这些激活可供选择的场景解释的“感知开关”很重要，因为它们允许检测行为上重要的信息，这些信息可能是不可预测的或最初突出的，可能存在于组织的任何级别。关于双眼竞争(一种常用的研究知觉开关的范式)的文献表明，知觉开关是由多阶段神经竞争的集体作用所调节的，这些竞争涉及信号转导、适应、抑制相互作用、随机噪声、非线性(如阈值)和反应同步等组成部分。当代的动态模型为整合这些组件过程提供了一个可信的计算框架。然而，迄今为止的研究忽略了知觉转换的一些关键方面。值得注意的是，没有人试图测量组件过程来确定它们的实际(而不是假设的)属性如何预测感知开关的动态。如果没有这个知识，就不可能确定在感知开关的动态中观察到的显著的个体差异和可塑性的来源。此外，尽管越来越多的证据表明涉及多层次的过程，但关于多个处理阶段的神经竞争如何交互地控制知觉开关的数据很少。我们的基本策略将是从心理物理和电生理学上测量在不同加工阶段操作的组件过程，确定每个组件过程如何影响感知开关，并使用这些信息来修正当前的模型。先进的模型将根据每个人测量的组成部分过程来预测每个人的感知开关的动态。通过这种方式，我们将确定由于个体差异、可塑性、知觉到知觉的差异和有意控制而导致的感知开关实质性差异的不明来源。最后，为了开始将知觉转换的基础研究转化为对心理健康和视觉注意的更广泛的理解，我们将(1)使用该模型追踪与某些精神障碍相关的异常知觉动力学的来源到特定的成分过程，以及(2)确定潜在的知觉转换及其意向调节的成分过程如何与自愿注意能力相关联。与公共卫生相关：视觉场景往往会产生多种解释；当人们在单一解释的稳定性和看到不同解释的灵活性之间取得平衡时，他们的功能最有效。在许多神经和精神障碍中，知觉解释可能过于不稳定或过于僵化，包括注意力缺陷障碍和双相情感障碍。这些知觉变化的动态将使用双眼竞争范式结合心理物理、计算模型和电生理技术进行严格的研究，以揭示潜在的神经机制以及它们如何作为个人健康状况的函数而不同。

DESCRIPTION (provided by applicant): When a static visual scene is viewed, different objects and organizations can spontaneously come to dominate visual awareness. These "perceptual switches" that activate alternative scene interpretations are important because they allow detection of behaviorally significant information that may not be predictable or initially salient and that may exist at any level of organization. The literature on binocular rivalry (a paradigm commonly used to study perceptual switches) suggests that perceptual switches are mediated by collective action of multi-stage neural competition involving component processes such as signal transduction, adaptation, inhibitory interactions, stochastic noise, non-linearity (e.g., a threshold), and response synchronization. Contemporary dynamic models provide a plausible computational framework for integrating these component processes. However, research to date has overlooked some key aspects of perceptual switches. Prominently, no attempts have been made to measure the component processes to determine how their actual (as opposed to hypothesized) properties predict the dynamics of perceptual switches. Without this knowledge, it is impossible to specify the sources of the substantial individual differences and plasticity observed in the dynamics of perceptual switches. Further, in spite of growing evidence that multi-level processes are involved, little data exist regarding how neural competition at multiple processing stages interactively controls perceptual switches. Our basic strategy will be to psychophysically and electrophysiologically measure the component processes operating at different processing stages, determine how each component process contributes to perceptual switches, and use this information to revise the current models. The advanced model will predict the dynamics of perceptual switches for each individual on the basis of his or her measured component processes. In this way, we will determine the unexplained sources of substantial variability in perceptual switches due to individual differences, plasticity, percept-to-percept variability, and intentional control. Finally, to begin to translate the basic research on perceptual switching to a broader understanding of mental health and visual attention, we will (1) use the model to trace the sources of unusual perceptual dynamics associated with some psychiatric disorders to specific component processes, and (2) determine how the component processes underlying perceptual switches and their intentional modulations are associated with voluntary attention abilities. PUBLIC HEALTH RELEVANCE: Visual scenes often give rise to multiple interpretations; people function most effectively when they achieve a balance between the stability of a single interpretation and the flexibility to see alternative interpretations. Perceptual interpretations can be excessively unstable or excessively inflexible in a number of neurological and psychiatric disorders, including attention deficit disorder and bipolar disorder. The dynamics of these perceptual alternations will be rigorously examined using a binocular-rivalry paradigm together with psychophysical, computational modeling, and electrophysiological techniques to reveal the underlying neural mechanisms and how they differ as a function of the health status of the individual.