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Qian M, Wang J, Gao Y, Chen M, Liu Y, Zhou D, Lu HD, Zhang X, Hu JM, Roe AW. Multiple loci for foveolar vision in macaque monkey visual cortex. Nat Neurosci 2025; 28:137-149. [PMID: 39639181 PMCID: PMC11706779 DOI: 10.1038/s41593-024-01810-4] [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: 06/13/2023] [Accepted: 10/14/2024] [Indexed: 12/07/2024]
Abstract
In humans and nonhuman primates, the central 1° of vision is processed by the foveola, a retinal structure that comprises a high density of photoreceptors and is crucial for primate-specific high-acuity vision, color vision and gaze-directed visual attention. Here, we developed high-spatial-resolution ultrahigh-field 7T functional magnetic resonance imaging methods for functional mapping of the foveolar visual cortex in awake monkeys. In the ventral pathway (visual areas V1-V4 and the posterior inferior temporal cortex), viewing of a small foveolar spot elicits a ring of multiple (eight) foveolar representations per hemisphere. This ring surrounds an area called the 'foveolar core', which is populated by millimeter-scale functional domains sensitive to fine stimuli and high spatial frequencies, consistent with foveolar visual acuity, color and achromatic information and motion. Thus, this elaborate rerepresentation of central vision coupled with a previously unknown foveolar core area signifies a cortical specialization for primate foveation behaviors.
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Affiliation(s)
- Meizhen Qian
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China
| | - Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yang Gao
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- College of Electrical Engineering, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ming Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yin Liu
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Dengfeng Zhou
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaotong Zhang
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
- College of Electrical Engineering, Zhejiang University, Hangzhou, China.
| | - Jia Ming Hu
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital & Liangzhu Laboratory of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, China.
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China.
- Zhejiang Key Laboratory of Research and Transformation for Major Neurosurgical Diseases, Hangzhou, China.
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
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Tünçok E, Carrasco M, Winawer J. Spatial attention alters visual cortical representation during target anticipation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.02.583127. [PMID: 38496524 PMCID: PMC10942396 DOI: 10.1101/2024.03.02.583127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Attention enables us to efficiently and flexibly interact with the environment by prioritizing some image features in preparation for responding to a stimulus. Using a concurrent psychophysics- fMRI experiment, we investigated how covert spatial attention affects responses in human visual cortex prior to target onset, and how it affects subsequent behavioral performance. Performance improved at cued locations and worsened at uncued locations, relative to distributed attention, demonstrating a selective tradeoff in processing. Pre-target BOLD responses in cortical visual field maps changed in two ways: First, there was a stimulus-independent baseline shift, positive in map locations near the cued location and negative elsewhere, paralleling the behavioral results. Second, population receptive field centers shifted toward the attended location. Both effects increased in higher visual areas. Together, the results show that spatial attention has large effects on visual cortex prior to target appearance, altering neural response properties throughout and across multiple visual field maps.
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Tozzi A, Mariniello L. Unusual Mathematical Approaches Untangle Nervous Dynamics. Biomedicines 2022; 10:biomedicines10102581. [PMID: 36289843 PMCID: PMC9599563 DOI: 10.3390/biomedicines10102581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/16/2022] Open
Abstract
The massive amount of available neurodata suggests the existence of a mathematical backbone underlying neuronal oscillatory activities. For example, geometric constraints are powerful enough to define cellular distribution and drive the embryonal development of the central nervous system. We aim to elucidate whether underrated notions from geometry, topology, group theory and category theory can assess neuronal issues and provide experimentally testable hypotheses. The Monge’s theorem might contribute to our visual ability of depth perception and the brain connectome can be tackled in terms of tunnelling nanotubes. The multisynaptic ascending fibers connecting the peripheral receptors to the neocortical areas can be assessed in terms of knot theory/braid groups. Presheaves from category theory permit the tackling of nervous phase spaces in terms of the theory of infinity categories, highlighting an approach based on equivalence rather than equality. Further, the physical concepts of soft-matter polymers and nematic colloids might shed new light on neurulation in mammalian embryos. Hidden, unexpected multidisciplinary relationships can be found when mathematics copes with neural phenomena, leading to novel answers for everlasting neuroscientific questions. For instance, our framework leads to the conjecture that the development of the nervous system might be correlated with the occurrence of local thermal changes in embryo–fetal tissues.
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Affiliation(s)
- Arturo Tozzi
- Center for Nonlinear Science, University of North Texas, Denton, TX 76203-5017, USA
- Correspondence:
| | - Lucio Mariniello
- Department of Pediatrics, University Federico II, 80131 Naples, Italy
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