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Levinson M, Pack CC, Baillet S. Stimulus-dependent delay of perceptual filling-in by microsaccades. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.16.618545. [PMID: 39464089 PMCID: PMC11507861 DOI: 10.1101/2024.10.16.618545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Perception is a function of both stimulus features and active sensory sampling. The illusion of perceptual filling-in occurs when eye gaze is kept still: visual boundary perception may fail, causing adjacent visual features to remarkably merge into one uniform visual surface. Microsaccades-small, involuntary eye movements during gaze fixation-counteract perceptual filling-in, but the mechanisms underlying this process are not well understood. We investigated whether microsaccade efficacy for preventing filling-in depends on two boundary properties, color contrast and retinal eccentricity (distance from gaze center). Twenty-one human participants (male and female) fixated on a point until they experienced filling-in between two isoluminant colored surfaces. We found that increased color contrast independently extends the duration before filling-in but does not alter the impact of individual microsaccades. Conversely, lower eccentricity delayed filling-in only by increasing microsaccade efficacy. We propose that microsaccades facilitate stable boundary perception via a transient retinal motion signal that scales with eccentricity but is invariant to boundary contrast. These results shed light on how incessant eye movements integrate with ongoing stimulus processing to stabilize perceptual detail, with implications for visual rehabilitation and the optimization of visual presentations in virtual and augmented reality environments.
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Affiliation(s)
- Max Levinson
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada, H3A 2B4
| | - Christopher C. Pack
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada, H3A 2B4
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada, H3A 2B4
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Wu Y, Zhao M, Deng H, Wang T, Xin Y, Dai W, Huang J, Zhou T, Sun X, Liu N, Xing D. The neural origin for asymmetric coding of surface color in the primate visual cortex. Nat Commun 2024; 15:516. [PMID: 38225259 PMCID: PMC10789876 DOI: 10.1038/s41467-024-44809-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 01/03/2024] [Indexed: 01/17/2024] Open
Abstract
The coding privilege of end-spectral hues (red and blue) in the early visual cortex has been reported in primates. However, the origin of such bias remains unclear. Here, we provide a complete picture of the end-spectral bias in visual system by measuring fMRI signals and spiking activities in macaques. The correlated end-spectral biases between the LGN and V1 suggest a subcortical source for asymmetric coding. Along the ventral pathway from V1 to V4, red bias against green peaked in V1 and then declined, whereas blue bias against yellow showed an increasing trend. The feedforward and recurrent modifications of end-spectral bias were further revealed by dynamic causal modeling analysis. Moreover, we found that the strongest end-spectral bias in V1 was in layer 4C[Formula: see text]. Our results suggest that end-spectral bias already exists in the LGN and is transmitted to V1 mainly through the parvocellular pathway, then embellished by cortical processing.
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Affiliation(s)
- Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Minghui Zhao
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Haoyun Deng
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- College of Life Sciences, Beijing Normal University, Beijing, 100875, China
| | - Yumeng Xin
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Jiancao Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Tingting Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xiaowen Sun
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Ning Liu
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
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