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Wang T, Lee TS, Yao H, Hong J, Li Y, Jiang H, Andolina IM, Tang S. Large-scale calcium imaging reveals a systematic V4 map for encoding natural scenes. Nat Commun 2024; 15:6401. [PMID: 39080309 PMCID: PMC11289446 DOI: 10.1038/s41467-024-50821-z] [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: 11/15/2023] [Accepted: 07/22/2024] [Indexed: 08/02/2024] Open
Abstract
Biological visual systems have evolved to process natural scenes. A full understanding of visual cortical functions requires a comprehensive characterization of how neuronal populations in each visual area encode natural scenes. Here, we utilized widefield calcium imaging to record V4 cortical response to tens of thousands of natural images in male macaques. Using this large dataset, we developed a deep-learning digital twin of V4 that allowed us to map the natural image preferences of the neural population at 100-µm scale. This detailed map revealed a diverse set of functional domains in V4, each encoding distinct natural image features. We validated these model predictions using additional widefield imaging and single-cell resolution two-photon imaging. Feature attribution analysis revealed that these domains lie along a continuum from preferring spatially localized shape features to preferring spatially dispersed surface features. These results provide insights into the organizing principles that govern natural scene encoding in V4.
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Affiliation(s)
- Tianye Wang
- Peking University School of Life Sciences, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China
| | - Tai Sing Lee
- Computer Science Department and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Haoxuan Yao
- Peking University School of Life Sciences, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China
| | - Jiayi Hong
- Peking University School of Life Sciences, Beijing, 100871, China
| | - Yang Li
- Peking University School of Life Sciences, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China
| | - Hongfei Jiang
- Peking University School of Life Sciences, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China
| | - Ian Max Andolina
- The Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Shiming Tang
- Peking University School of Life Sciences, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.
- IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China.
- Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China.
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2
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Greene MJ, Boehm AE, Vanston JE, Pandiyan VP, Sabesan R, Tuten WS. Unique yellow shifts for small and brief stimuli in the central retina. J Vis 2024; 24:2. [PMID: 38833255 PMCID: PMC11156209 DOI: 10.1167/jov.24.6.2] [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: 10/31/2023] [Accepted: 05/01/2024] [Indexed: 06/06/2024] Open
Abstract
The spectral locus of unique yellow was determined for flashes of different sizes (<11 arcmin) and durations (<500 ms) presented in and near the fovea. An adaptive optics scanning laser ophthalmoscope was used to minimize the effects of higher-order aberrations during simultaneous stimulus delivery and retinal imaging. In certain subjects, parafoveal cones were classified as L, M, or S, which permitted the comparison of unique yellow measurements with variations in local L/M ratios within and between observers. Unique yellow shifted to longer wavelengths as stimulus size or duration was reduced. This effect is most pronounced for changes in size and more apparent in the fovea than in the parafovea. The observed variations in unique yellow are not entirely predicted from variations in L/M ratio and therefore implicate neural processes beyond photoreception.
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Affiliation(s)
- Maxwell J Greene
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, Berkeley, CA, USA
| | - Alexandra E Boehm
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, Berkeley, CA, USA
| | - John E Vanston
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, Berkeley, CA, USA
| | - Vimal P Pandiyan
- Department of Ophthalmology, University of Washington, Seattle, WA, USA
| | - Ramkumar Sabesan
- Department of Ophthalmology, University of Washington, Seattle, WA, USA
| | - William S Tuten
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, Berkeley, CA, USA
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3
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Wang J, Du X, Yao S, Li L, Tanigawa H, Zhang X, Roe AW. Mesoscale organization of ventral and dorsal visual pathways in macaque monkey revealed by 7T fMRI. Prog Neurobiol 2024; 234:102584. [PMID: 38309458 DOI: 10.1016/j.pneurobio.2024.102584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
In human and nonhuman primate brains, columnar (mesoscale) organization has been demonstrated to underlie both lower and higher order aspects of visual information processing. Previous studies have focused on identifying functional preferences of mesoscale domains in specific areas; but there has been little understanding of how mesoscale domains may cooperatively respond to single visual stimuli across dorsal and ventral pathways. Here, we have developed ultrahigh-field 7 T fMRI methods to enable simultaneous mapping, in individual macaque monkeys, of response in both dorsal and ventral pathways to single simple color and motion stimuli. We provide the first evidence that anatomical V2 cytochrome oxidase-stained stripes are well aligned with fMRI maps of V2 stripes, settling a long-standing controversy. In the ventral pathway, a systematic array of paired color and luminance processing domains across V4 was revealed, suggesting a novel organization for surface information processing. In the dorsal pathway, in addition to high quality motion direction maps of MT, MST and V3A, alternating color and motion direction domains in V3 are revealed. As well, submillimeter motion domains were observed in peripheral LIPd and LIPv. In sum, our study provides a novel global snapshot of how mesoscale networks in the ventral and dorsal visual pathways form the organizational basis of visual objection recognition and vision for action.
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Affiliation(s)
- Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital, 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
| | - Xiao Du
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Songping Yao
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Lihui Li
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Hisashi Tanigawa
- Department of Neurosurgery of the Second Affiliated Hospital, 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
| | - Xiaotong Zhang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China.
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4
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Karami B, Schwiedrzik CM. Visual perceptual learning of feature conjunctions leverages non-linear mixed selectivity. NPJ SCIENCE OF LEARNING 2024; 9:13. [PMID: 38429339 PMCID: PMC10907723 DOI: 10.1038/s41539-024-00226-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 02/16/2024] [Indexed: 03/03/2024]
Abstract
Visual objects are often defined by multiple features. Therefore, learning novel objects entails learning feature conjunctions. Visual cortex is organized into distinct anatomical compartments, each of which is devoted to processing a single feature. A prime example are neurons purely selective to color and orientation, respectively. However, neurons that jointly encode multiple features (mixed selectivity) also exist across the brain and play critical roles in a multitude of tasks. Here, we sought to uncover the optimal policy that our brain adapts to achieve conjunction learning using these available resources. 59 human subjects practiced orientation-color conjunction learning in four psychophysical experiments designed to nudge the visual system towards using one or the other resource. We find that conjunction learning is possible by linear mixing of pure color and orientation information, but that more and faster learning takes place when both pure and mixed selectivity representations are involved. We also find that learning with mixed selectivity confers advantages in performing an untrained "exclusive or" (XOR) task several months after learning the original conjunction task. This study sheds light on possible mechanisms underlying conjunction learning and highlights the importance of learning by mixed selectivity.
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Affiliation(s)
- Behnam Karami
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany
| | - Caspar M Schwiedrzik
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany.
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany.
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5
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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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6
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Conway BR, Malik-Moraleda S, Gibson E. Color appearance and the end of Hering's Opponent-Colors Theory. Trends Cogn Sci 2023; 27:791-804. [PMID: 37394292 PMCID: PMC10527909 DOI: 10.1016/j.tics.2023.06.003] [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: 06/14/2022] [Revised: 06/02/2023] [Accepted: 06/08/2023] [Indexed: 07/04/2023]
Abstract
Hering's Opponent-Colors Theory has been central to understanding color appearance for 150 years. It aims to explain the phenomenology of colors with two linked propositions. First, a psychological hypothesis stipulates that any color is described necessarily and sufficiently by the extent to which it appears reddish-versus-greenish, bluish-versus-yellowish, and blackish-versus-whitish. Second, a physiological hypothesis stipulates that these perceptual mechanisms are encoded by three innate brain mechanisms. We review the evidence and conclude that neither side of the linking proposition is accurate: the theory is wrong. We sketch out an alternative, Utility-Based Coding, by which the known retinal cone-opponent mechanisms represent optimal encoding of spectral information given competing selective pressure to extract high-acuity spatial information; and phenomenological color categories represent an adaptive, efficient, output of the brain governed by behavioral demands.
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Affiliation(s)
- Bevil R Conway
- Laboratory of Sensorimotor Research, National Eye Institute and National Institute of Mental Health, Bethesda, MD 20892, USA.
| | - Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, M.I.T., Cambridge, MA 02139, USA; Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02114, USA
| | - Edward Gibson
- Department of Brain and Cognitive Sciences, M.I.T., Cambridge, MA 02139, USA
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7
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Watakabe A, Skibbe H, Nakae K, Abe H, Ichinohe N, Rachmadi MF, Wang J, Takaji M, Mizukami H, Woodward A, Gong R, Hata J, Van Essen DC, Okano H, Ishii S, Yamamori T. Local and long-distance organization of prefrontal cortex circuits in the marmoset brain. Neuron 2023; 111:2258-2273.e10. [PMID: 37196659 PMCID: PMC10789578 DOI: 10.1016/j.neuron.2023.04.028] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/13/2023] [Accepted: 04/25/2023] [Indexed: 05/19/2023]
Abstract
The prefrontal cortex (PFC) has dramatically expanded in primates, but its organization and interactions with other brain regions are only partially understood. We performed high-resolution connectomic mapping of the marmoset PFC and found two contrasting corticocortical and corticostriatal projection patterns: "patchy" projections that formed many columns of submillimeter scale in nearby and distant regions and "diffuse" projections that spread widely across the cortex and striatum. Parcellation-free analyses revealed representations of PFC gradients in these projections' local and global distribution patterns. We also demonstrated column-scale precision of reciprocal corticocortical connectivity, suggesting that PFC contains a mosaic of discrete columns. Diffuse projections showed considerable diversity in the laminar patterns of axonal spread. Altogether, these fine-grained analyses reveal important principles of local and long-distance PFC circuits in marmosets and provide insights into the functional organization of the primate brain.
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Affiliation(s)
- Akiya Watakabe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan.
| | - Henrik Skibbe
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan.
| | - Ken Nakae
- Integrated Systems Biology Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Kyoto 606-8501, Japan; Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Aichi 444-8787, Japan
| | - Hiroshi Abe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Noritaka Ichinohe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Ultrastructural Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-0031, Japan
| | - Muhammad Febrian Rachmadi
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Faculty of Computer Science, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia
| | - Jian Wang
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Masafumi Takaji
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Hiroaki Mizukami
- Division of Genetic Therapeutics, Center for Molecular Medicine, Jichi Medical University, Shimotsuke, Tochigi 329-0498, Japan
| | - Alexander Woodward
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Rui Gong
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo 116-8551, Japan
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Physiology, Keio University School of Medicine, Tokyo 108-8345, Japan
| | - Shin Ishii
- Integrated Systems Biology Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Kyoto 606-8501, Japan
| | - Tetsuo Yamamori
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan.
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8
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Vanston JE, Boehm AE, Tuten WS, Roorda A. It's not easy seeing green: The veridical perception of small spots. J Vis 2023; 23:2. [PMID: 37133838 PMCID: PMC10166115 DOI: 10.1167/jov.23.5.2] [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: 11/16/2022] [Accepted: 03/26/2023] [Indexed: 05/04/2023] Open
Abstract
When single cones are stimulated with spots of 543-nm light presented against a white background, subjects report percepts that vary between predominately red, white, and green. However, light of the same spectral composition viewed over a large field under normal viewing conditions looks invariably green and highly saturated. It remains unknown what stimulus parameters are most important for governing the color appearance in the transition between these two extreme cases. The current study varied the size, intensity and retinal motion of stimuli presented in an adaptive optics scanning laser ophthalmoscope. Stimuli were either stabilized on target locations or allowed to drift across the retina with the eye's natural motion. Increasing both stimulus size and intensity led to higher likelihoods that monochromatic spots of light were perceived as green, whereas only higher intensities led to increases in perceived saturation. The data also show an interaction between size and intensity, suggesting that the balance between magnocellular and parvocellular activation may be critical factors for color perception. Surprisingly, under the range of conditions tested, color appearance did not depend on whether stimuli were stabilized. Sequential activation of many cones does not appear to drive hue and saturation perception as effectively as simultaneous activation of many cones.
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Affiliation(s)
- John Erik Vanston
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
| | - Alexandra E Boehm
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
| | - William S Tuten
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
| | - Austin Roorda
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
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9
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Cao P, Zhang M, Ni Z, Song XJ, Yang CL, Mao Y, Zhou W, Dong WY, Peng X, Zheng C, Zhang Z, Jin Y, Tao W. Green light induces antinociception via visual-somatosensory circuits. Cell Rep 2023; 42:112290. [PMID: 36947545 DOI: 10.1016/j.celrep.2023.112290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 12/19/2022] [Accepted: 03/03/2023] [Indexed: 03/23/2023] Open
Abstract
Light has been shown to relieve pain, but the underlying neural mechanisms remain unknown. Here, we show that low-intensity (200 lux) green light treatment exerts antinociceptive effects through a neural circuit from the visual cortex projecting to the anterior cingulate cortex (ACC) in mice. Specifically, viral tracing, in vivo two-photon calcium imaging, and fiber photometry recordings show that green light activated glutamatergic projections from the medial part of the secondary visual cortex (V2MGlu) to GABAergic neurons in the ACC, which drives inhibition of local glutamatergic neurons (V2MGlu→ACCGABA→Glu). Optogenetic or chemogenetic activation of the V2MGlu→ACCGABA→Glu circuit mimics green-light-induced antinociception in both neuropathic and inflammatory pain model mice. Artificial inhibition of ACC-projecting V2MGlu neurons abolishes the antinociception induced by green light. Taken together, our study shows the V2M-ACC circuit as a potential candidate mediating green-light-induced antinociceptive effects.
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Affiliation(s)
- Peng Cao
- Department of Anesthesiology, The First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Mingjun Zhang
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Ziyun Ni
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Xiang-Jie Song
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Chen-Ling Yang
- Department of Physiology, School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China
| | - Yu Mao
- Department of Anesthesiology, The First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; Department of Anesthesiology and Department of Pain Management, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, PR China
| | - Wenjie Zhou
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Wan-Ying Dong
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Xiaoqi Peng
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Changjian Zheng
- Department of Anesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu 241002, China
| | - Zhi Zhang
- Department of Anesthesiology, The First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China.
| | - Yan Jin
- Department of Biophysics and Neurobiology, Key Laboratory of Brain Function and Disease of Chinese Academy of Sciences, University of Science and Technology of China, Hefei 230027, China; Stroke Center and Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230036, China.
| | - Wenjuan Tao
- Department of Physiology, School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China; College & Hospital of Stomatology, Key Laboratory of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei 230032, China.
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10
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Aseyev N. Perception of color in primates: A conceptual color neurons hypothesis. Biosystems 2023; 225:104867. [PMID: 36792004 DOI: 10.1016/j.biosystems.2023.104867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/12/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.
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Affiliation(s)
- Nikolay Aseyev
- Institute Higher Nervous Activity and Neurophysiology, RAS, Moscow, 117485, Butlerova, 5A, Russian Federation.
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11
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Zhang Y, Schriver KE, Hu JM, Roe AW. Spatial frequency representation in V2 and V4 of macaque monkey. eLife 2023; 12:81794. [PMID: 36607323 PMCID: PMC9848390 DOI: 10.7554/elife.81794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 01/05/2023] [Indexed: 01/07/2023] Open
Abstract
Spatial frequency (SF) is an important attribute in the visual scene and is a defining feature of visual processing channels. However, there remain many unsolved questions about how extrastriate areas in primate visual cortex code this fundamental information. Here, using intrinsic signal optical imaging in visual areas of V2 and V4 of macaque monkeys, we quantify the relationship between SF maps and (1) visual topography and (2) color and orientation maps. We find that in orientation regions, low to high SF is mapped orthogonally to orientation; in color regions, which are reported to contain orthogonal axes of color and lightness, low SFs tend to be represented more frequently than high SFs. This supports a population-based SF fluctuation related to the 'color/orientation' organizations. We propose a generalized hypercolumn model across cortical areas, comprised of two orthogonal parameters with additional parameters.
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Affiliation(s)
- Ying Zhang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang UniversityHangzhouChina
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang UniversityHangzhouChina
| | - Kenneth E Schriver
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang UniversityHangzhouChina
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang UniversityHangzhouChina
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang UniversityHangzhouChina
| | - Jia Ming Hu
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang UniversityHangzhouChina
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang UniversityHangzhouChina
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang UniversityHangzhouChina
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang UniversityHangzhouChina
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang UniversityHangzhouChina
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang UniversityHangzhouChina
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12
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Li P, Garg AK, Zhang LA, Rashid MS, Callaway EM. Cone opponent functional domains in primary visual cortex combine signals for color appearance mechanisms. Nat Commun 2022; 13:6344. [PMID: 36284139 PMCID: PMC9596481 DOI: 10.1038/s41467-022-34020-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 10/11/2022] [Indexed: 12/25/2022] Open
Abstract
Studies of color perception have led to mechanistic models of how cone-opponent signals from retinal ganglion cells are integrated to generate color appearance. But it is unknown how this hypothesized integration occurs in the brain. Here we show that cone-opponent signals transmitted from retina to primary visual cortex (V1) are integrated through highly organized circuits within V1 to implement the color opponent interactions required for color appearance. Combining intrinsic signal optical imaging (ISI) and 2-photon calcium imaging (2PCI) at single cell resolution, we demonstrate cone-opponent functional domains (COFDs) that combine L/M cone-opponent and S/L + M cone-opponent signals following the rules predicted from psychophysical studies of color perception. These give rise to an orderly organization of hue preferences of the neurons within the COFDs and the generation of hue "pinwheels". Thus, spatially organized neural circuits mediate an orderly transition from cone-opponency to color appearance that begins in V1.
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Affiliation(s)
- Peichao Li
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, 1369 West Wenyi Road, 311121, Hangzhou, China
| | - Anupam K Garg
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Wilmer Eye Institute, Johns Hopkins University, 600N Wolfe Street, Baltimore, MD, 21287, USA
| | - Li A Zhang
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | | | - Edward M Callaway
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA.
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13
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Li M, Chen X, Yuan N, Lu Y, Liu Y, Gong H, Qian L, Andolina IM, Wu J, Zhang S, McLoughlin N, Sun X, Wang W. Effects of acute high intraocular pressure on red-green and blue-yellow cortical color responses in non-human primates. Neuroimage Clin 2022; 35:103092. [PMID: 35753237 PMCID: PMC9249948 DOI: 10.1016/j.nicl.2022.103092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/17/2022] [Accepted: 06/18/2022] [Indexed: 11/24/2022]
Abstract
Glaucoma is a leading cause of irreversible blindness worldwide, and intraocular pressure (IOP) is an established and modifiable risk factor for both chronic and acute glaucoma. The relationship between color vision deficits and chronic glaucoma has been described previously. However, the effects of acute glaucoma or acute primary angle closure, which has high prevalence in China, on color vision remains unclear. To address the above question, red-green or blue-yellow color responses in V1, V2, and V4 of seven rhesus macaques were monitored using intrinsic-signal optical imaging while monocular anterior chamber perfusions were performed to reversibly elevate IOP acutely over a clinically observed range of 30 to 90 mmHg. We found that the cortical population responses to both red-green and blue-yellow grating stimuli, systematically decreased as IOP increased from 30 to 90 mmHg. Although a similar decrement in magnitude was noted in V1, V2, and V4, blue-yellow responses were consistently more impaired than red-green responses at all levels of acute IOP elevation and in all monitored visual areas. This physiological study in non-human primates demonstrates that acute IOP elevations substantially depress the ability of the visual cortex to register color information. This effect is more severe for blue-yellow responses than for red-green responses, suggesting selective impairment of the koniocellular pathways compared with the parvocellular pathways. Together, we infer that blue-yellow color vision might be the most vulnerable visual function in acute glaucoma patients.
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Affiliation(s)
- Mengwei Li
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Xiaoxiao Chen
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Nini Yuan
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China; Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
| | - Yiliang Lu
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Ye Liu
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Hongliang Gong
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Liling Qian
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Ian Max Andolina
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Jihong Wu
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China; NHC Key Laboratory of Myopia (Fudan University), Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, China; Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, China
| | - Shenghai Zhang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China; NHC Key Laboratory of Myopia (Fudan University), Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, China; Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, China
| | - Niall McLoughlin
- School of Optometry and Vision Science, University of Bradford, UK
| | - Xinghuai Sun
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China; State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China; NHC Key Laboratory of Myopia (Fudan University), Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, China; Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, China.
| | - Wei Wang
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, Beijing, China.
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14
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Du X, Jiang X, Kuriki I, Takahata T, Zhou T, Roe AW, Tanigawa H. Representation of Cone-Opponent Color Space in Macaque Early Visual Cortices. Front Neurosci 2022; 16:891247. [PMID: 35794953 PMCID: PMC9251113 DOI: 10.3389/fnins.2022.891247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/20/2022] [Indexed: 11/13/2022] Open
Abstract
In primate vision, the encoding of color perception arises from three types of retinal cone cells (L, M, and S cones). The inputs from these cones are linearly integrated into two cone-opponent channels (cardinal axes) before the lateral geniculate nucleus. In subsequent visual cortical stages, color-preferring neurons cluster into functional domains within "blobs" in V1, "thin/color stripes" in V2, and "color bands" in V4. Here, we hypothesize that, with increasing cortical hierarchy, the functional organization of hue representation becomes more balanced and less dependent on cone opponency. To address this question, we used intrinsic signal optical imaging in macaque V1, V2, and V4 cortices to examine the domain-based representation of specific hues (here referred to as "hue domains") in cone-opponent color space (4 cardinal and 4 intermediate hues). Interestingly, we found that in V1, the relative size of S-cone hue preference domain was significantly smaller than that for other hues. This notable difference was less prominent in V2, and, in V4 was virtually absent, resulting in a more balanced representation of hues. In V2, hue clusters contained sequences of shifting preference, while in V4 the organization of hue clusters was more complex. Pattern classification analysis of these hue maps showed that accuracy of hue classification improved from V1 to V2 to V4. These results suggest that hue representation by domains in the early cortical hierarchy reflects a transformation away from cone-opponency and toward a full-coverage representation of hue.
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Affiliation(s)
- Xiao Du
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Xinrui Jiang
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ichiro Kuriki
- Department of Information and Computer Sciences, Graduate School of Science and Engineering, Saitama University, Saitama, Japan
| | - Toru Takahata
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Tao Zhou
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Hisashi Tanigawa
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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15
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Functionally specific and sparse domain-based micro-networks in monkey V1 and V2. Curr Biol 2022; 32:2797-2809.e3. [PMID: 35623347 DOI: 10.1016/j.cub.2022.04.095] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/05/2022] [Accepted: 04/28/2022] [Indexed: 11/23/2022]
Abstract
The cerebral cortices of human and nonhuman primate brains are characterized by submillimeter functional domains. However, little is known about the connections of single functional domains. Here, in macaque monkey visual cortex, we have developed a targeted focal electrical stimulation method, coupled with functional optical imaging, to map cortical networks with submillimeter precision in vivo. We find that single functional domains are a part of highly specific and sparse intra-areal and inter-areal micro-networks. Across color-related and orientation-related functionalities, these micro-networks exhibit parallel connection patterns, suggesting a common domain-based architecture. Moreover, these micro-networks shift topographically at a submillimeter scale, suggesting that they serve as a fundamental unit for cortical information processing. Our findings establish a domain-based connectional architecture in the primate brain and present new constraints for cortical map representation.
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16
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Stauch BJ, Peter A, Ehrlich I, Nolte Z, Fries P. Human visual gamma for color stimuli. eLife 2022; 11:75897. [PMID: 35532123 PMCID: PMC9122493 DOI: 10.7554/elife.75897] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Strong gamma-band oscillations in primate early visual cortex can be induced by homogeneous color surfaces (Peter et al., 2019; Shirhatti and Ray, 2018). Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 have often not been fully controlled for. Therefore, stronger responses to red might be due to differences in V1 input strength. We presented stimuli that had equal luminance and cone contrast levels in a color coordinate system based on responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human participants. We found gamma oscillations in early visual cortex which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change-detection performance. The strength of human color gamma responses for stimuli on the L-M axis could be well explained by L-M cone contrast and did not show a clear red bias when L-M cone contrast was properly equalized.
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Affiliation(s)
| | - Alina Peter
- Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany
| | - Isabelle Ehrlich
- Department of Psychology, Goethe University Frankfurt, Frankfurt, Germany
| | - Zora Nolte
- Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany
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17
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Lin B, Chen Y, Pan L, Du G, Huang X. Color Sensitivity of the Duration Aftereffect Depends on Sub- and Supra-second Durations. Front Psychol 2022; 13:858457. [PMID: 35391952 PMCID: PMC8980474 DOI: 10.3389/fpsyg.2022.858457] [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: 01/20/2022] [Accepted: 03/03/2022] [Indexed: 11/13/2022] Open
Abstract
The perception of duration becomes biased after repetitive duration adaptation; this is known as the duration aftereffect. The duration aftereffect exists in both the sub-second and supra-second ranges. However, it is unknown whether the properties and mechanisms of the adaptation aftereffect differ between sub-second and supra-second durations. In the present study, we addressed this question by investigating the color sensitivity of the duration aftereffect in the sub-second (Experiment 1) and supra-second (Experiment 2) ranges separately. We found that the duration aftereffect in the sub-second range could only partly transfer across different visual colors, whereas the duration aftereffect in the supra-second range could completely transfer across different visual colors. That is, the color-sensitivity of the duration aftereffect in the sub-second duration was stronger than that in the supra-second duration. These results imply that the mechanisms underlying the adaptation aftereffects of the sub-second and supra-second ranges are distinct.
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Affiliation(s)
- Bingxin Lin
- Faculty of Psychology, Southwest University, Chongqing, China.,Center of Studies for Psychology and Social Development, Southwest University, Chongqing, China.,Time Psychology Research Center, Southwest University, Chongqing, China
| | - Youguo Chen
- Faculty of Psychology, Southwest University, Chongqing, China.,Center of Studies for Psychology and Social Development, Southwest University, Chongqing, China.,Time Psychology Research Center, Southwest University, Chongqing, China
| | - Li Pan
- Faculty of Psychology, Southwest University, Chongqing, China.,Center of Studies for Psychology and Social Development, Southwest University, Chongqing, China.,Time Psychology Research Center, Southwest University, Chongqing, China
| | - Gang Du
- Faculty of Psychology, Southwest University, Chongqing, China.,Center of Studies for Psychology and Social Development, Southwest University, Chongqing, China.,Time Psychology Research Center, Southwest University, Chongqing, China
| | - Xiting Huang
- Faculty of Psychology, Southwest University, Chongqing, China.,Center of Studies for Psychology and Social Development, Southwest University, Chongqing, China.,Time Psychology Research Center, Southwest University, Chongqing, China
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18
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Hermann KL, Singh SR, Rosenthal IA, Pantazis D, Conway BR. Temporal dynamics of the neural representation of hue and luminance polarity. Nat Commun 2022; 13:661. [PMID: 35115511 PMCID: PMC8814185 DOI: 10.1038/s41467-022-28249-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 01/12/2022] [Indexed: 11/09/2022] Open
Abstract
Hue and luminance contrast are basic visual features. Here we use multivariate analyses of magnetoencephalography data to investigate the timing of the neural computations that extract them, and whether they depend on common neural circuits. We show that hue and luminance-contrast polarity can be decoded from MEG data and, with lower accuracy, both features can be decoded across changes in the other feature. These results are consistent with the existence of both common and separable neural mechanisms. The decoding time course is earlier and more temporally precise for luminance polarity than hue, a result that does not depend on task, suggesting that luminance contrast is an updating signal that separates visual events. Meanwhile, cross-temporal generalization is slightly greater for representations of hue compared to luminance polarity, providing a neural correlate of the preeminence of hue in perceptual grouping and memory. Finally, decoding of luminance polarity varies depending on the hues used to obtain training and testing data. The pattern of results is consistent with observations that luminance contrast is mediated by both L-M and S cone sub-cortical mechanisms.
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Affiliation(s)
- Katherine L Hermann
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, 20892, USA
- Department of Psychology, Stanford University, Stanford, CA, 94305, USA
| | - Shridhar R Singh
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, 20892, USA
| | - Isabelle A Rosenthal
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, 20892, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Bevil R Conway
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, 20892, USA.
- National Institute of Mental Health, Bethesda, MD, 20892, USA.
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19
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Ding J, Ye Z, Xu F, Hu X, Yu H, Zhang S, Tu Y, Zhang Q, Sun Q, Hua T, Lu ZL. Effects of top-down influence suppression on behavioral and V1 neuronal contrast sensitivity functions in cats. iScience 2022; 25:103683. [PMID: 35059603 PMCID: PMC8760559 DOI: 10.1016/j.isci.2021.103683] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/16/2021] [Accepted: 12/20/2021] [Indexed: 02/09/2023] Open
Abstract
To explore the relative contributions of higher-order and primary visual cortex (V1) to visual perception, we compared cats' behavioral and V1 neuronal contrast sensitivity functions (CSF) and threshold versus external noise contrast (TvC) functions before and after top-down influence of area 7 (A7) was modulated with transcranial direct current stimulation (tDCS). We found that suppressing top-down influence of A7 with cathode-tDCS, but not sham-tDCS, reduced behavioral and neuronal contrast sensitivity in the same range of spatial frequencies and increased behavioral and neuronal contrast thresholds in the same range of external noise levels. The neuronal CSF and TvC functions were highly correlated with their behavioral counterparts both before and after the top-down suppression. Analysis of TvC functions using the Perceptual Template Model (PTM) indicated that top-down influence of A7 increased both behavioral and V1 neuronal contrast sensitivity by reducing internal additive noise and the impact of external noise. Top-down suppression lowers both behavioral and V1 neuronal CSF functions Top-down suppression raises both behavioral and V1 neuronal TvC functions The neuronal CSFs and TvCs are highly correlated with their behavioral counterparts Top-down influence lowers internal additive noise and impact of external noise in V1
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Affiliation(s)
- Jian Ding
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Zheng Ye
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Fei Xu
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Xiangmei Hu
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Hao Yu
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Shen Zhang
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Yanni Tu
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Qiuyu Zhang
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Qingyan Sun
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Tianmiao Hua
- College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Zhong-Lin Lu
- Divison of Arts and Sciences, NYU Shanghai, Shanghai 200122, China.,Center for Neural Science and Department of Psychology, New York University, New York, NY 10003, USA.,NYU-ECNU Institute of Brain and Cognitive Science, NYU Shanghai, Shanghai 200062, China
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20
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Franken TP, Reynolds JH. Columnar processing of border ownership in primate visual cortex. eLife 2021; 10:72573. [PMID: 34845986 PMCID: PMC8631947 DOI: 10.7554/elife.72573] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 10/28/2021] [Indexed: 11/26/2022] Open
Abstract
To understand a visual scene, the brain segregates figures from background by assigning borders to foreground objects. Neurons in primate visual cortex encode which object owns a border (border ownership), but the underlying circuitry is not understood. Here, we used multielectrode probes to record from border ownership-selective units in different layers in macaque visual area V4 to study the laminar organization and timing of border ownership selectivity. We find that border ownership selectivity occurs first in deep layer units, in contrast to spike latency for small stimuli in the classical receptive field. Units on the same penetration typically share the preferred side of border ownership, also across layers, similar to orientation preference. Units are often border ownership-selective for a range of border orientations, where the preferred sides of border ownership are systematically organized in visual space. Together our data reveal a columnar organization of border ownership in V4 where the earliest border ownership signals are not simply inherited from upstream areas, but computed by neurons in deep layers, and may thus be part of signals fed back to upstream cortical areas or the oculomotor system early after stimulus onset. The finding that preferred border ownership is clustered and can cover a wide range of spatially contiguous locations suggests that the asymmetric context integrated by these neurons is provided in a systematically clustered manner, possibly through corticocortical feedback and horizontal connections. To understand a visual scene, the brain needs to identify objects and distinguish them from background. A border marks the transition from object to background, but to differentiate which side of the border belongs to the object and which to background, the brain must integrate information across space. An early signature of this computation is that brain cells signal which side of a border is ‘owned’ by an object, also known as border ownership. But how the brain computes border ownership remains unknown. The optic nerve is a cable-like group of nerve cells that transmits information from the eye to the brain’s visual processing areas and into the visual cortex. This flow of information is often described as traveling in a feedforward direction, away from the eyes to progressively more specialized areas in the visual cortex. However, there are also numerous feedback connections in the brain, running backward from more specialized to less specialized cortical areas. To better understand the role of these feedforward and feedback circuits in the visual processing of object borders, Franken and Reynolds made use of their stereotyped projection patterns across the cortex layers. Feedforward connections terminate in the middle layers of a cortical area, whereas feedback connections terminate in upper and lower layers. Since time is required for information to traverse the cortical layers, dissecting the timing of border ownership signals may reveal if border ownership is computed in a feedforward or feedback manner. To find out more, electrodes were used to record neural activity in the upper, middle and lower layers of the visual cortex of two rhesus monkeys as they were presented with a set of abstract scenes composed of simple shapes on a background. This revealed that cells signaling border ownership in deep layers of the cortex did so before the signals appeared in the middle layer. This suggests that feedback rather than feedforward is required to compute border ownership. Moreover, Franken and Reynolds found evidence that cells that prefer the same side of border ownership are clustered in columns, showing how these neural circuits are organized within the visual cortex. In summary, Franken and Reynolds found that the circuits of the primate brain that compute border ownership occur as columns, in which cells in deep layers signal border ownership first, suggesting that border ownership relies on feedback from more specialized areas. A better understanding of how feedback in the brain works to process visual information helps us appreciate what happens when these systems are impaired.
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Affiliation(s)
- Tom P Franken
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States
| | - John H Reynolds
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States
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21
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Meikle SJ, Wong YT. Neurophysiological considerations for visual implants. Brain Struct Funct 2021; 227:1523-1543. [PMID: 34773502 DOI: 10.1007/s00429-021-02417-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 10/17/2021] [Indexed: 11/26/2022]
Abstract
Neural implants have the potential to restore visual capabilities in blind individuals by electrically stimulating the neurons of the visual system. This stimulation can produce visual percepts known as phosphenes. The ideal location of electrical stimulation for achieving vision restoration is widely debated and dependent on the physiological properties of the targeted tissue. Here, the neurophysiology of several potential target structures within the visual system will be explored regarding their benefits and downfalls in producing phosphenes. These regions will include the lateral geniculate nucleus, primary visual cortex, visual area 2, visual area 3, visual area 4 and the middle temporal area. Based on the existing engineering limitations of neural prostheses, we anticipate that electrical stimulation of any singular brain region will be incapable of achieving high-resolution naturalistic perception including color, texture, shape and motion. As improvements in visual acuity facilitate improvements in quality of life, emulating naturalistic vision should be one of the ultimate goals of visual prostheses. To achieve this goal, we propose that multiple brain areas will need to be targeted in unison enabling different aspects of vision to be recreated.
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Affiliation(s)
- Sabrina J Meikle
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
- Department of Physiology and Biomedicine Discovery Institute, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
- Monash Vision Group, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
| | - Yan T Wong
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
- Department of Physiology and Biomedicine Discovery Institute, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
- Monash Vision Group, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
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22
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Oguchi M, Jiasen J, Yoshioka TW, Tanaka YR, Inoue K, Takada M, Kikusui T, Nomoto K, Sakagami M. Microendoscopic calcium imaging of the primary visual cortex of behaving macaques. Sci Rep 2021; 11:17021. [PMID: 34426639 PMCID: PMC8382832 DOI: 10.1038/s41598-021-96532-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/27/2021] [Indexed: 11/21/2022] Open
Abstract
In vivo calcium imaging with genetically encoded indicators has recently been applied to macaque brains to monitor neural activities from a large population of cells simultaneously. Microendoscopic calcium imaging combined with implantable gradient index lenses captures neural activities from deep brain areas with a compact and convenient setup; however, this has been limited to rodents and marmosets. Here, we developed miniature fluorescent microscopy to image neural activities from the primary visual cortex of behaving macaques. We found tens of clear fluorescent signals from three of the six brain hemispheres. A subset of these neurons showed clear retinotopy and orientation tuning. Moreover, we successfully decoded the stimulus orientation and tracked the cells across days. These results indicate that microendoscopic calcium imaging is feasible and reasonable for investigating neural circuits in the macaque brain by monitoring fluorescent signals from a large number of neurons.
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Affiliation(s)
- Mineki Oguchi
- Brain Science Institute, Tamagawa University, Machida, Tokyo, Japan
- School of Veterinary Medicine, Azabu University, Sagamihara, Kanagawa, Japan
| | - Jiang Jiasen
- Brain Science Institute, Tamagawa University, Machida, Tokyo, Japan
| | | | | | - Kenichi Inoue
- Department of Neuroscience, Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan
| | - Masahiko Takada
- Department of Neuroscience, Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan
| | - Takefumi Kikusui
- School of Veterinary Medicine, Azabu University, Sagamihara, Kanagawa, Japan
| | - Kensaku Nomoto
- School of Veterinary Medicine, Azabu University, Sagamihara, Kanagawa, Japan
- Department of Physiology, Dokkyo Medical University School of Medicine, Mibu, Tochigi, Japan
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23
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Chen J, Gegenfurtner KR. Electrophysiological evidence for higher-level chromatic mechanisms in humans. J Vis 2021; 21:12. [PMID: 34357373 PMCID: PMC8354086 DOI: 10.1167/jov.21.8.12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 07/13/2021] [Indexed: 11/24/2022] Open
Abstract
Color vision in humans starts with three types of cones (short [S], medium [M], and long [L] wavelengths) in the retina and three retinal and subcortical cardinal mechanisms, which linearly combine cone signals into the luminance channel (L + M), the red-green channel (L - M), and the yellow-blue channel (S-(L + M)). Chromatic mechanisms at the cortical level, however, are less well characterized. The present study investigated such higher-order chromatic mechanisms by recording electroencephalograms (EEGs) on human observers in a noise masking paradigm. Observers viewed colored stimuli that consisted of a target embedded in noise. Color directions of the target and noise varied independently and systematically in an isoluminant plane of color space. The target was flickering on-off at 3 Hz, eliciting steady-state visual evoked potential (SSVEP) responses. As a result, the masking strength could be estimated from the SSVEP amplitude in the presence of 6 Hz noise. Masking was strongest (i.e. target eliciting smallest SSVEPs) when the target and noise were along the same color direction, and was weakest (i.e. target eliciting highest SSVEPs) when the target and noise were along orthogonal directions. This pattern of results was observed both when the target color varied along the cardinal and intermediate directions, which is evidence for higher-order chromatic mechanisms tuned to intermediate axes. The SSVEP result can be well predicted by a model with multiple broadly tuned chromatic mechanisms. In contrast, a model with only cardinal mechanisms failed to account for the data. These results provide strong electrophysiological evidence for multiple chromatic mechanisms in the early visual cortex of humans.
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Affiliation(s)
- Jing Chen
- School of Psychology, Shanghai University of Sport, Shanghai, China
- https://orcid.org/0000-0002-3038-1786
| | - Karl R Gegenfurtner
- Abteilung Allgemeine Psychologie and Center for Mind, Brain & Behavior, Justus-Liebig-Universität Gießen, Gießen, Germany
- https://www.allpsych.uni-giessen.de/karl/
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24
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Ionta S. Visual Neuropsychology in Development: Anatomo-Functional Brain Mechanisms of Action/Perception Binding in Health and Disease. Front Hum Neurosci 2021; 15:689912. [PMID: 34135745 PMCID: PMC8203289 DOI: 10.3389/fnhum.2021.689912] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/06/2021] [Indexed: 12/16/2022] Open
Abstract
Vision is the main entrance for environmental input to the human brain. Even if vision is our most used sensory modality, its importance is not limited to environmental exploration. Rather it has strong links to motor competences, further extending to cognitive and social aspects of human life. These multifaceted relationships are particularly important in developmental age and become dramatically evident in presence of complex deficits originating from visual aberrancies. The present review summarizes the available neuropsychological evidence on the development of visual competences, with a particular focus on the associated visuo-motor integration skills in health and disease. With the aim of supporting future research and interventional settings, the goal of the present review is to constitute a solid base to help the translation of neuropsychological hypotheses into straightforward empirical investigations and rehabilitation/training protocols. This approach will further increase the impact, ameliorate the acceptance, and ease the use and implementation of lab-derived intervention protocols in real-life situations.
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Affiliation(s)
- Silvio Ionta
- Sensory-Motor Lab (SeMoLa), Department of Ophthalmology-University of Lausanne, Jules Gonin Eye Hospital-Fondation Asile des Aveugles, Lausanne, Switzerland
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25
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Color Tuning of Face-Selective Neurons in Macaque Inferior Temporal Cortex. eNeuro 2021; 8:ENEURO.0395-20.2020. [PMID: 33483324 PMCID: PMC8174038 DOI: 10.1523/eneuro.0395-20.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 12/08/2020] [Accepted: 12/12/2020] [Indexed: 11/21/2022] Open
Abstract
What role does color play in the neural representation of complex shapes? We approached the question by measuring color responses of face-selective neurons, using fMRI-guided microelectrode recording of the middle and anterior face patches of inferior temporal cortex (IT) in rhesus macaques. Face-selective cells responded weakly to pure color (equiluminant) photographs of faces. But many of the cells nonetheless showed a bias for warm colors when assessed using images that preserved the luminance contrast relationships of the original photographs. This bias was also found for non-face-selective neurons. Fourier analysis uncovered two components: the first harmonic, accounting for most of the tuning, was biased toward reddish colors, corresponding to the L>M pole of the L-M cardinal axis. The second harmonic showed a bias for modulation between blue and yellow colors axis, corresponding to the S-cone axis. To test what role face-selective cells play in behavior, we related the information content of the neural population with the distribution of face colors. The analyses show that face-selective cells are not optimally tuned to discriminate face colors, but are consistent with the idea that face-selective cells contribute selectively to processing the green-red contrast of faces. The research supports the hypothesis that color-specific information related to the discrimination of objects, including faces, is handled by neural circuits that are independent of shape-selective cortex, as captured by the multistage parallel processing framework of IT (Lafer-Sousa and Conway, 2013).
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26
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Guggiana Nilo DA, Riegler C, Hübener M, Engert F. Distributed chromatic processing at the interface between retina and brain in the larval zebrafish. Curr Biol 2021; 31:1945-1953.e5. [PMID: 33636122 DOI: 10.1016/j.cub.2021.01.088] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 12/30/2020] [Accepted: 01/25/2021] [Indexed: 02/07/2023]
Abstract
Larval zebrafish (Danio rerio) are an ideal organism for studying color vision, as their retina possesses four types of cone photoreceptors, covering most of the visible range and into the UV.1,2 Additionally, their eye and nervous systems are accessible to imaging, given that they are naturally transparent.3-5 Recent studies have found that, through a set of wavelength-range-specific horizontal, bipolar, and retinal ganglion cells (RGCs),6-9 the eye relays tetrachromatic information to several retinorecipient areas (RAs).10-13 The main RA is the optic tectum, receiving 97% of the RGC axons via the neuropil mass termed arborization field 10 (AF10).14,15 Here, we aim to understand the processing of chromatic signals at the interface between RGCs and their major brain targets. We used 2-photon calcium imaging to separately measure the responses of RGCs and neurons in the brain to four different chromatic stimuli in awake animals. We find that chromatic information is widespread throughout the brain, with a large variety of responses among RGCs, and an even greater diversity in their targets. Specific combinations of response types are enriched in specific nuclei, but there is no single color processing structure. In the main interface in this pathway, the connection between AF10 and tectum, we observe key elements of neural processing, such as enhanced signal decorrelation and improved chromatic decoding.16,17 A richer stimulus set revealed that these enhancements occur in the context of a more distributed code in tectum, facilitating chromatic signal association in this small vertebrate brain.
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Affiliation(s)
- Drago A Guggiana Nilo
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; Harvard Biophysics Graduate Program, Harvard University, Boston, MA 02115, USA; Department Synapses-Circuits-Plasticity, Max Planck Institute of Neurobiology, 81252 Martinsried, Germany.
| | - Clemens Riegler
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; Department of Neuroscience and Developmental Biology, University of Vienna, A-1090 Vienna, Austria
| | - Mark Hübener
- Department Synapses-Circuits-Plasticity, Max Planck Institute of Neurobiology, 81252 Martinsried, Germany
| | - Florian Engert
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
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27
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Rosenthal IA, Singh SR, Hermann KL, Pantazis D, Conway BR. Color Space Geometry Uncovered with Magnetoencephalography. Curr Biol 2021; 31:515-526.e5. [PMID: 33202253 PMCID: PMC7878424 DOI: 10.1016/j.cub.2020.10.062] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/21/2020] [Accepted: 10/21/2020] [Indexed: 02/07/2023]
Abstract
The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of measurements of brain activity obtained with magnetoencephalography to reverse-engineer a geometry of the neural representation of color space. The analyses depend upon determining similarity relationships among the spatial patterns of neural responses to different colors and assessing how these relationships change in time. We evaluate the approach by relating the results to universal patterns in color naming. Two prominent patterns of color naming could be accounted for by the decoding results: the greater precision in naming warm colors compared to cool colors evident by an interaction of hue and lightness, and the preeminence among colors of reddish hues. Additional experiments showed that classifiers trained on responses to color words could decode color from data obtained using colored stimuli, but only at relatively long delays after stimulus onset. These results provide evidence that perceptual representations can give rise to semantic representations, but not the reverse. Taken together, the results uncover a dynamic geometry that provides neural correlates for color appearance and generates new hypotheses about the structure of color space.
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Affiliation(s)
- Isabelle A Rosenthal
- Laboratory of Sensorimotor Research, National Eye Institute, Building 49, NIH Main Campus, Bethesda, MD 20892, USA
| | - Shridhar R Singh
- Laboratory of Sensorimotor Research, National Eye Institute, Building 49, NIH Main Campus, Bethesda, MD 20892, USA
| | - Katherine L Hermann
- Laboratory of Sensorimotor Research, National Eye Institute, Building 49, NIH Main Campus, Bethesda, MD 20892, USA
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 524 Main Street, Cambridge, MA 02139, USA
| | - Bevil R Conway
- Laboratory of Sensorimotor Research, National Eye Institute, Building 49, NIH Main Campus, Bethesda, MD 20892, USA; National Institute of Mental Health, Bethesda, MD 20892, USA.
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28
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Tang R, Song Q, Li Y, Zhang R, Cai X, Lu HD. Curvature-processing domains in primate V4. eLife 2020; 9:57502. [PMID: 33211007 PMCID: PMC7707829 DOI: 10.7554/elife.57502] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 11/18/2020] [Indexed: 11/13/2022] Open
Abstract
Neurons in primate V4 exhibit various types of selectivity for contour shapes, including curves, angles, and simple shapes. How are these neurons organized in V4 remains unclear. Using intrinsic signal optical imaging and two-photon calcium imaging, we observed submillimeter functional domains in V4 that contained neurons preferring curved contours over rectilinear ones. These curvature domains had similar sizes and response amplitudes as orientation domains but tended to separate from these regions. Within the curvature domains, neurons that preferred circles or curve orientations clustered further into finer scale subdomains. Nevertheless, individual neurons also had a wide range of contour selectivity, and neighboring neurons exhibited a substantial diversity in shape tuning besides their common shape preferences. In strong contrast to V4, V1 and V2 did not have such contour-shape-related domains. These findings highlight the importance and complexity of curvature processing in visual object recognition and the key functional role of V4 in this process.
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Affiliation(s)
- Rendong Tang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qianling Song
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ying Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Rui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xingya Cai
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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