Understanding the mechanisms that control the dynamics of perceptual switches

了解控制感知开关动态的机制

• 批准号: 7880336
• 负责人: SATORU SUZUKI
• 金额: $ 20.71万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7880336
• 关键词: Accounting; Address; Attention; Awareness; Behavioral; Binocular rivalry; Biological Neural Networks; Characteristics; Complex; Computer Simulation; Data; Detection; Development; Disease; Eye; Goals; Image; Individual; Individual Differences; Intention; Knowledge; Laboratories; Literature; Measurement; Measures; Mediating; Modeling; Noise; Pattern; Process; Property; Psychophysiology; Relative (related person); Research; Research Personnel; Role; Sensory; Signal Transduction; Simulate; Solutions; Source; Specific qualifier value; Speed; Staging; Stimulus; Stream; System; Techniques; Time; To specify; Variant; Visual; Visual evoked cortical potential; Weight; Work; base; computer framework; effective therapy; experience; feeding; improved; neuromechanism; programs; relating to nervous system; response

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.

描述（由申请人提供）：即使在观看恒定的视觉场景时，不同的物体和组织也会主导视觉意识，通常是自发的。这些自发激活替代场景解释的“感知开关”是重要的，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是显著的，并且可能存在于任何组织水平。关于双眼竞争的文献（通常用于研究感知开关的范例）表明，感知开关由多阶段神经竞争介导，所述多阶段神经竞争涉及诸如信号转导、适应、抑制相互作用、随机噪声、非线性（例如，阈值）和响应同步。这些过程的集体行动控制感知开关，目前的动态模型提供了一个合理的计算框架，整合组件的过程。然而，研究忽略了感知转换的一些关键方面。突出的是，没有尝试进行实验测量的组成过程，以确定其实际（而不是假设）的属性预测感知开关的动态。没有这些知识，就不可能具体说明在感知转换的动态中观察到的大量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，很少有数据存在关于神经竞争如何在多个处理阶段交互控制感知开关。我们的基本策略是从心理和电生理学的角度测量在不同处理阶段运行的组成过程，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。先进的模型将预测每个人的感知开关的动态基础上，他或她的测量组件的过程。研究结果还将说明感知开关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疾病有关。因此，我们的研究结果可能有助于发展有效的治疗方法，通过追踪不寻常的感知动态的来源，以特定的组件过程。