Skerswetat Jan, Bex Peter J
Department of Ophthalmology, University of California-Irvine, 850 Health Sciences Road, Irvine, 9269, United States of America.
Department of Psychology, Northeastern University, 360 Huntington Ave, Boston, Massachusetts, 02115, United States of America.
bioRxiv. 2024 Sep 24:2024.09.24.614648. doi: 10.1101/2024.09.24.614648.
Multistable perceptual phenomena provide insights into the mind's dynamic states within a stable external environment and the neural underpinnings of these consciousness changes are often studied with binocular rivalry. Conventional methods to study binocular rivalry suffer from biases and assumptions that limit their ability to describe the continuous nature of this perceptual transitions and to discover what kind of percept was perceived across time. In this study, we propose a novel way to avoid those shortcomings by combining a continuous psychophysical method that estimates introspection during binocular rivalry with machine learning clustering and transition probability analysis. This combination of techniques reveals individual variability and complexity of perceptual experience in 28 normally sighted participants. Also, the analysis of transition probabilities between perceptual categories, i.e., exclusive and different kinds of mixed percepts, suggest that interocular perceptual competition, triggered by low-level stimuli, involves conflict between monocular and binocular neural processing sites rather than mutual inhibition of monocular sites.
多稳态知觉现象为洞察稳定外部环境中大脑的动态状态提供了线索,而这些意识变化的神经基础常通过双眼竞争来研究。研究双眼竞争的传统方法存在偏差和假设,限制了它们描述这种知觉转换的连续性以及发现随时间所感知到的是何种知觉的能力。在本研究中,我们提出了一种新颖的方法来避免这些缺点,即结合一种在双眼竞争期间估计内省的连续心理物理学方法与机器学习聚类和转换概率分析。这种技术组合揭示了28名正常视力参与者知觉体验的个体差异和复杂性。此外,对知觉类别(即排他性和不同类型的混合知觉)之间转换概率的分析表明,由低水平刺激引发的双眼间知觉竞争涉及单眼和双眼神经处理部位之间的冲突,而非单眼部位之间的相互抑制。