Understanding the mechanisms that control the dynamics of perceptual switches

描述（由申请人提供）：即使在观看一个恒定的视觉场景时，不同的物体和组织也会自发地主导视觉意识。这些自发激活替代场景解释的“感知开关”很重要，因为它们可以检测到行为上的重要信息，这些信息可能是不可预测的，或者最初是显著的，可能存在于任何组织层面。双目竞争（一种通常用于研究感知开关的范式）的文献表明，感知开关是由涉及信号转导、适应、抑制相互作用、随机噪声、非线性（如阈值）和反应同步等组成过程的多阶段神经竞争介导的。这些过程的集体行动控制着感知开关，目前的动态模型为整合组成过程提供了一个合理的计算框架。然而，研究忽略了感知开关的一些关键方面。值得注意的是，没有人尝试通过实验来测量组成过程，以确定它们的实际（与假设相反）属性如何预测感知开关的动态。如果没有这些知识，就不可能确定在感知开关的动态中观察到的实质性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过程，但关于多个处理阶段的神经竞争如何交互控制感知开关的数据很少。我们的基本策略将是心理物理和电生理测量在不同处理阶段操作的组成过程，确定每个组成过程如何有助于感知转换，并使用这些信息来修改当前的模型。先进的模型将根据每个人测量的组成过程来预测感知开关的动态。研究结果还将详细说明感知转换动态中无法解释的变异性的来源，包括个体差异、可塑性、感知到感知的变异性和意图的影响。异常缓慢或快速的知觉转换可能与以持续或分心为特征的障碍有关。因此，我们的研究结果可以通过追踪不寻常的感知动态到特定成分过程的来源来促进有效治疗的发展。

DESCRIPTION (provided by applicant): Even while viewing a constant visual scene, different objects and organizations come to dominate visual awareness, often spontaneously. These "perceptual switches" that spontaneously activate alternative scene interpretations are important because they allow detection of behaviorally significant information which may not be predictable or initially salient and 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 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. Collective action of these processes controls perceptual switches, and the current dynamic models provide a plausible computational framework for integrating the component processes. However, research has overlooked some key aspects of perceptual switches. Prominently, no attempts have been made to experimentally measure the component processes to determine how their actual (as opposed to hypothesized) properties predict the dynamics of perceptual switches. Without this knowledge, it would be 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 models will predict the dynamics of perceptual switches for each individual on the basis of his or her measured component processes. The results will also specify the sources of the unexplained variability in the dynamics of perceptual switches, including individual differences, plasticity, percept-to-percept variability, and effects of intention. Unusually slow or fast perceptual switches may be associated with disorders characterized by perseveration or distractability. Our results may thus facilitate development of effective treatments by tracing the sources of unusual perceptual dynamics to specific component processes.