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Sarkar R, Zanetti K, Reynaud A, Kingdom FAA. Surround masking reveals binocular adding and differencing channels. Vision Res 2024; 219:108396. [PMID: 38640684 DOI: 10.1016/j.visres.2024.108396] [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: 10/04/2023] [Revised: 03/20/2024] [Accepted: 03/20/2024] [Indexed: 04/21/2024]
Abstract
Recent studies suggest that binocular adding S+ and differencing S- channels play an important role in binocular vision. To test for such a role in the context of binocular contrast detection and binocular summation, we employed a surround masking paradigm consisting of a central target disk surrounded by a mask annulus. All stimuli were horizontally oriented 0.5c/d sinusoidal gratings. Correlated stimuli were identical in interocular spatial phase while anticorrelated stimuli were opposite in interocular spatial phase. There were four target conditions: monocular left eye, monocular right eye, binocular correlated and binocular anticorrelated, and three surround mask conditions: no surround, binocularly correlated and binocularly anticorrelated. We observed consistent elevation of detection thresholds for monocular and binocular targets across the two binocular surround mask conditions. In addition, we found an interaction between the type of surround and the type of binocular target: both detection and summation were relatively enhanced by surround masks and targets with opposite interocular phase relationships and reduced by surround masks and targets with the same interocular phase relationships. The data were reasonably well accounted for by a model of binocular combination termed MAX (S+S-), in which the decision variable is the probability summation of modeled S+ and S- channel responses, with a free parameter determining the relative gains of the two channels. Our results support the existence of two channels involved in binocular combination, S+ and S-, whose relative gains are adjustable by surround context.
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Affiliation(s)
- Rinku Sarkar
- McGill Vision Research, Department of Ophthalmology and Visual Sciences, Montréal General Hospital, Montréal, Quebec, Canada; Research Institute of McGill University Health Centre (RI-MUHC), Canada.
| | - Kiana Zanetti
- McGill Vision Research, Department of Ophthalmology and Visual Sciences, Montréal General Hospital, Montréal, Quebec, Canada
| | - Alexandre Reynaud
- McGill Vision Research, Department of Ophthalmology and Visual Sciences, Montréal General Hospital, Montréal, Quebec, Canada; Research Institute of McGill University Health Centre (RI-MUHC), Canada
| | - Frederick A A Kingdom
- McGill Vision Research, Department of Ophthalmology and Visual Sciences, Montréal General Hospital, Montréal, Quebec, Canada
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2
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Saeedi A, Wang K, Nikpourian G, Bartels A, Logothetis NK, Totah NK, Watanabe M. Brightness illusions drive a neuronal response in the primary visual cortex under top-down modulation. Nat Commun 2024; 15:3141. [PMID: 38653975 DOI: 10.1038/s41467-024-46885-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 03/13/2024] [Indexed: 04/25/2024] Open
Abstract
Brightness illusions are a powerful tool in studying vision, yet their neural correlates are poorly understood. Based on a human paradigm, we presented illusory drifting gratings to mice. Primary visual cortex (V1) neurons responded to illusory gratings, matching their direction selectivity for real gratings, and they tracked the spatial phase offset between illusory and real gratings. Illusion responses were delayed compared to real gratings, in line with the theory that processing illusions requires feedback from higher visual areas (HVAs). We provide support for this theory by showing a reduced V1 response to illusions, but not real gratings, following HVAs optogenetic inhibition. Finally, we used the pupil response (PR) as an indirect perceptual report and showed that the mouse PR matches the human PR to perceived luminance changes. Our findings resolve debates over whether V1 neurons are involved in processing illusions and highlight the involvement of feedback from HVAs.
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Affiliation(s)
- Alireza Saeedi
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany
- Research Group Neurobiology of Magnetoreception, Max Planck Institute for Neurobiology of Behavior - caesar, 53175, Bonn, Germany
| | - Kun Wang
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany
- Department of Physiology of Cognitive Processes, International Center for Primate Brain Research, Songjiang District, Shanghai, 201602, China
| | - Ghazaleh Nikpourian
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany
| | - Andreas Bartels
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany
- Department of Psychology, Vision and Cognition Lab, Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience, Tübingen, Germany
| | - Nikos K Logothetis
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany
- Department of Physiology of Cognitive Processes, International Center for Primate Brain Research, Songjiang District, Shanghai, 201602, China
- Centre for Imaging Sciences, University of Manchester, Manchester, M139PT, UK
| | - Nelson K Totah
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany.
- Helsinki Institute of Life Science (HILIFE), University of Helsinki, 00014, Helsinki, Finland.
- Faculty of Pharmacy, University of Helsinki, 00014, Helsinki, Finland.
- Neuroscience Center, University of Helsinki, 00014, Helsinki, Finland.
| | - Masataka Watanabe
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076, Tübingen, Germany.
- Department of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo, Japan.
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Zhu S, Oh YJ, Trepka E, Chen X, Moore T. Dependence of Contextual Modulation in Macaque V1 on Interlaminar Signal Flow. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590176. [PMID: 38659877 PMCID: PMC11042257 DOI: 10.1101/2024.04.18.590176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
In visual cortex, neural correlates of subjective perception can be generated by modulation of activity from beyond the classical receptive field (CRF). In macaque V1, activity generated by nonclassical receptive field (nCRF) stimulation involves different intracortical circuitry than activity generated by CRF stimulation, suggesting that interactions between neurons across V1 layers differ under CRF and nCRF stimulus conditions. We measured border ownership modulation within large populations of V1 neurons. We found that neurons in single columns preferred the same side of objects located outside of the CRF. In addition, we found that interactions between pairs of neurons situated across feedback/horizontal and input layers differed between CRF and nCRF stimulation. Furthermore, the magnitude of border ownership modulation was predicted by greater information flow from feedback/horizontal to input layers. These results demonstrate that the flow of signals between layers covaries with the degree to which neurons integrate information from beyond the CRF.
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Lewis CM, Wunderle T, Fries P. Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589006. [PMID: 38645050 PMCID: PMC11030389 DOI: 10.1101/2024.04.11.589006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.
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Chen SCY, Chen Y, Geisler WS, Seidemann E. Neural correlates of perceptual similarity masking in primate V1. eLife 2024; 12:RP89570. [PMID: 38592269 PMCID: PMC11003749 DOI: 10.7554/elife.89570] [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] [Indexed: 04/10/2024] Open
Abstract
Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed 'similarity masking'. To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.
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Affiliation(s)
- Spencer Chin-Yu Chen
- Center for Perceptual Systems, University of Texas at AustinAustinUnited States
- Department of Psychology, University of Texas at AustinAustinUnited States
- Center for Theoretical and Computational NeuroscienceAustinUnited States
- Department of Neuroscience, University of Texas at AustinAustinUnited States
- Department of Neurosurgery, Rutgers UniversityNew BrunswickUnited States
| | - Yuzhi Chen
- Center for Perceptual Systems, University of Texas at AustinAustinUnited States
- Department of Psychology, University of Texas at AustinAustinUnited States
- Center for Theoretical and Computational NeuroscienceAustinUnited States
- Department of Neuroscience, University of Texas at AustinAustinUnited States
| | - Wilson S Geisler
- Center for Perceptual Systems, University of Texas at AustinAustinUnited States
- Department of Psychology, University of Texas at AustinAustinUnited States
- Center for Theoretical and Computational NeuroscienceAustinUnited States
| | - Eyal Seidemann
- Center for Perceptual Systems, University of Texas at AustinAustinUnited States
- Department of Psychology, University of Texas at AustinAustinUnited States
- Center for Theoretical and Computational NeuroscienceAustinUnited States
- Department of Neuroscience, University of Texas at AustinAustinUnited States
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Burkhalter A, Ji W, Meier AM, D’Souza RD. Modular horizontal network within mouse primary visual cortex. Front Neuroanat 2024; 18:1364675. [PMID: 38650594 PMCID: PMC11033472 DOI: 10.3389/fnana.2024.1364675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/04/2024] [Indexed: 04/25/2024] Open
Abstract
Interactions between feedback connections from higher cortical areas and local horizontal connections within primary visual cortex (V1) were shown to play a role in contextual processing in different behavioral states. Layer 1 (L1) is an important part of the underlying network. This cell-sparse layer is a target of feedback and local inputs, and nexus for contacts onto apical dendrites of projection neurons in the layers below. Importantly, L1 is a site for coupling inputs from the outside world with internal information. To determine whether all of these circuit elements overlap in L1, we labeled the horizontal network within mouse V1 with anterograde and retrograde viral tracers. We found two types of local horizontal connections: short ones that were tangentially limited to the representation of the point image, and long ones which reached beyond the receptive field center, deep into its surround. The long connections were patchy and terminated preferentially in M2 muscarinic acetylcholine receptor-negative (M2-) interpatches. Anterogradely labeled inputs overlapped in M2-interpatches with apical dendrites of retrogradely labeled L2/3 and L5 cells, forming module-selective loops between topographically distant locations. Previous work showed that L1 of M2-interpatches receive inputs from the lateral posterior thalamic nucleus (LP) and from a feedback network from areas of the medial dorsal stream, including the secondary motor cortex. Together, these findings suggest that interactions in M2-interpatches play a role in processing visual inputs produced by object-and self-motion.
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Affiliation(s)
- Andreas Burkhalter
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
| | - Weiqing Ji
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
| | - Andrew M. Meier
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
- Department of Speech, Language and Hearing Sciences, College of Engineering, Boston University, Boston, MA, United States
| | - Rinaldo D. D’Souza
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
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Li Y, Dai W, Wang T, Wu Y, Dou F, Xing D. Visual surround suppression at the neural and perceptual levels. Cogn Neurodyn 2024; 18:741-756. [PMID: 38699623 PMCID: PMC11061091 DOI: 10.1007/s11571-023-10027-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 10/10/2023] [Accepted: 10/23/2023] [Indexed: 05/05/2024] Open
Abstract
Surround suppression was initially identified as a phenomenon at the neural level in which stimuli outside the neuron's receptive field alone cannot activate responses but can modulate neural responses to stimuli covered inside the receptive field. Subsequent studies showed that surround suppression is not only a critical property of neurons across species and brain areas but also has been found in visual perceptions. More importantly, surround suppression varies across individuals and shows significant differences between normal controls and patients with certain mental disorders. Here, we combined results from related literature and summarized the findings derived from physiological and psychophysical evidence. We first outline the basic properties of surround suppression in the visual system and perceptions. Then, we mainly summarize the differences in perceptual surround suppression among different human subjects. Our review suggests that there is no consensus regarding whether the strength of perceptual surround suppression could be used as an effective index to distinguish particular populations. Then, we summarized the similar mechanisms for surround suppression and cognitive impairments to further explore the potential clinical applications of surround suppression. A clearer understanding of the mechanisms of surround suppression in neural responses and perceptions is necessary for facilitating its clinical applications.
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Affiliation(s)
- Yang Li
- School of Criminology, People’s Public Security University of China, Beijing, 100038 China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
- College of Life Sciences, Beijing Normal University, Beijing, 100875 China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Fei Dou
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
- College of Life Sciences, Beijing Normal University, Beijing, 100875 China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
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Goris RLT, Coen-Cagli R, Miller KD, Priebe NJ, Lengyel M. Response sub-additivity and variability quenching in visual cortex. Nat Rev Neurosci 2024; 25:237-252. [PMID: 38374462 DOI: 10.1038/s41583-024-00795-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2024] [Indexed: 02/21/2024]
Abstract
Sub-additivity and variability are ubiquitous response motifs in the primary visual cortex (V1). Response sub-additivity enables the construction of useful interpretations of the visual environment, whereas response variability indicates the factors that limit the precision with which the brain can do this. There is increasing evidence that experimental manipulations that elicit response sub-additivity often also quench response variability. Here, we provide an overview of these phenomena and suggest that they may have common origins. We discuss empirical findings and recent model-based insights into the functional operations, computational objectives and circuit mechanisms underlying V1 activity. These different modelling approaches all predict that response sub-additivity and variability quenching often co-occur. The phenomenology of these two response motifs, as well as many of the insights obtained about them in V1, generalize to other cortical areas. Thus, the connection between response sub-additivity and variability quenching may be a canonical motif across the cortex.
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Affiliation(s)
- Robbe L T Goris
- Center for Perceptual Systems, University of Texas at Austin, Austin, TX, USA.
| | - Ruben Coen-Cagli
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA
- Dept. of Neuroscience, College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Swartz Program in Theoretical Neuroscience, Columbia University, New York, NY, USA
| | - Nicholas J Priebe
- Center for Learning and Memory, University of Texas at Austin, Austin, TX, USA
| | - Máté Lengyel
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK
- Center for Cognitive Computation, Department of Cognitive Science, Central European University, Budapest, Hungary
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Clark AM, Ingold A, Reiche CF, Cundy D, Balsor JL, Federer F, McAlinden N, Cheng Y, Rolston JD, Rieth L, Dawson MD, Mathieson K, Blair S, Angelucci A. An optrode array for spatiotemporally-precise large-scale optogenetic stimulation of deep cortical layers in non-human primates. Commun Biol 2024; 7:329. [PMID: 38485764 PMCID: PMC10940688 DOI: 10.1038/s42003-024-05984-2] [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: 12/20/2023] [Accepted: 02/27/2024] [Indexed: 03/18/2024] Open
Abstract
Optogenetics has transformed studies of neural circuit function, but remains challenging to apply to non-human primates (NHPs). A major challenge is delivering intense, spatiotemporally-precise, patterned photostimulation across large volumes in deep tissue. Such stimulation is critical, for example, to modulate selectively deep-layer corticocortical feedback circuits. To address this need, we have developed the Utah Optrode Array (UOA), a 10×10 glass needle waveguide array fabricated atop a novel opaque optical interposer, and bonded to an electrically addressable µLED array. In vivo experiments with the UOA demonstrated large-scale, spatiotemporally precise, activation of deep circuits in NHP cortex. Specifically, the UOA permitted both focal (confined to single layers/columns), and widespread (multiple layers/columns) optogenetic activation of deep layer neurons, as assessed with multi-channel laminar electrode arrays, simply by varying the number of activated µLEDs and/or the irradiance. Thus, the UOA represents a powerful optoelectronic device for targeted manipulation of deep-layer circuits in NHP models.
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Affiliation(s)
- Andrew M Clark
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Alexander Ingold
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Christopher F Reiche
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
| | - Donald Cundy
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Justin L Balsor
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Frederick Federer
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Niall McAlinden
- SUPA, Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow, UK
| | - Yunzhou Cheng
- SUPA, Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow, UK
| | - John D Rolston
- Departments of Neurosurgery and Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Loren Rieth
- Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, USA
- Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Martin D Dawson
- SUPA, Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow, UK
| | - Keith Mathieson
- SUPA, Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow, UK
| | - Steve Blair
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA.
| | - Alessandra Angelucci
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA.
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Morton MP, Denagamage S, Hudson NV, Nandy AS. Non-uniform contextual interactions in the visual cortex place fundamental limits on spatial vision. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.15.553380. [PMID: 37645826 PMCID: PMC10462024 DOI: 10.1101/2023.08.15.553380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
A prevailing assumption in our understanding of how neurons in the primary visual cortex (V1) integrate contextual information is that such processes are spatially uniform. Conversely, perceptual phenomena such as visual crowding, the impaired ability to accurately recognize a target stimulus among distractors, suggest that interactions among stimuli are distinctly non-uniform. Prior studies have shown flankers at specific spatial geometries exert differential effects on target perception. To resolve this discrepancy, we investigated how flanker geometry impacted the representation of a target stimulus in the laminar microcircuits of V1. Our study reveals flanker location differentially impairs stimulus representation in excitatory neurons in the superficial and input layers of V1 by tuned suppression and untuned facilitation of orientation responses. Mechanistically, this effect can be explained by asymmetrical spatial kernels in a normalization model of cortical activity. Strikingly, these non-uniform modulations of neural representation mirror perceptual anisotropies. These results establish the non-uniform spatial integration of information in the earliest stages of cortical processing as a fundamental limitation of spatial vision.
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Bi Z, Li H, Tian L. Top-down generation of low-resolution representations improves visual perception and imagination. Neural Netw 2024; 171:440-456. [PMID: 38150870 DOI: 10.1016/j.neunet.2023.12.030] [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: 03/25/2023] [Revised: 11/30/2023] [Accepted: 12/18/2023] [Indexed: 12/29/2023]
Abstract
Perception or imagination requires top-down signals from high-level cortex to primary visual cortex (V1) to reconstruct or simulate the representations bottom-up stimulated by the seen images. Interestingly, top-down signals in V1 have lower spatial resolution than bottom-up representations. It is unclear why the brain uses low-resolution signals to reconstruct or simulate high-resolution representations. By modeling the top-down pathway of the visual system using the decoder of a variational auto-encoder (VAE), we reveal that low-resolution top-down signals can better reconstruct or simulate the information contained in the sparse activities of V1 simple cells, which facilitates perception and imagination. This advantage of low-resolution generation is related to facilitating high-level cortex to form geometry-respecting representations observed in experiments. Furthermore, we present two findings regarding this phenomenon in the context of AI-generated sketches, a style of drawings made of lines. First, we found that the quality of the generated sketches critically depends on the thickness of the lines in the sketches: thin-line sketches are harder to generate than thick-line sketches. Second, we propose a technique to generate high-quality thin-line sketches: instead of directly using original thin-line sketches, we use blurred sketches to train VAE or GAN (generative adversarial network), and then infer the thin-line sketches from the VAE- or GAN-generated blurred sketches. Collectively, our work suggests that low-resolution top-down generation is a strategy the brain uses to improve visual perception and imagination, which inspires new sketch-generation AI techniques.
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Affiliation(s)
- Zedong Bi
- Lingang Laboratory, Shanghai 200031, China.
| | - Haoran Li
- Department of Physics, Hong Kong Baptist University, Hong Kong, China
| | - Liang Tian
- Department of Physics, Hong Kong Baptist University, Hong Kong, China; Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China; Institute of Systems Medicine and Health Sciences, Hong Kong Baptist University, Hong Kong, China; State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong, China.
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12
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Luo L, Wang X, Lu J, Chen G, Luan G, Li W, Wang Q, Fang F. Local field potentials, spiking activity, and receptive fields in human visual cortex. SCIENCE CHINA. LIFE SCIENCES 2024; 67:543-554. [PMID: 37957484 DOI: 10.1007/s11427-023-2436-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 08/21/2023] [Indexed: 11/15/2023]
Abstract
The concept of receptive field (RF) is central to sensory neuroscience. Neuronal RF properties have been substantially studied in animals, while those in humans remain nearly unexplored. Here, we measured neuronal RFs with intracranial local field potentials (LFPs) and spiking activity in human visual cortex (V1/V2/V3). We recorded LFPs via macro-contacts and discovered that RF sizes estimated from low-frequency activity (LFA, 0.5-30 Hz) were larger than those estimated from low-gamma activity (LGA, 30-60 Hz) and high-gamma activity (HGA, 60-150 Hz). We then took a rare opportunity to record LFPs and spiking activity via microwires in V1 simultaneously. We found that RF sizes and temporal profiles measured from LGA and HGA closely matched those from spiking activity. In sum, this study reveals that spiking activity of neurons in human visual cortex could be well approximated by LGA and HGA in RF estimation and temporal profile measurement, implying the pivotal functions of LGA and HGA in early visual information processing.
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Affiliation(s)
- Lu Luo
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China
- School of Psychology, Beijing Sport University, Beijing, 100084, China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China
- Beijing Key Laboratory of Epilepsy, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China
| | - Junshi Lu
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Guanpeng Chen
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Guoming Luan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China
- Beijing Key Laboratory of Epilepsy, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China
- Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Wu Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qian Wang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China.
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China.
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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13
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Nesse WH, Clark KL, Noudoost B. Information representation in an oscillating neural field model modulated by working memory signals. Front Comput Neurosci 2024; 17:1253234. [PMID: 38303900 PMCID: PMC10830742 DOI: 10.3389/fncom.2023.1253234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 11/27/2023] [Indexed: 02/03/2024] Open
Abstract
We study how stimulus information can be represented in the dynamical signatures of an oscillatory model of neural activity-a model whose activity can be modulated by input akin to signals involved in working memory (WM). We developed a neural field model, tuned near an oscillatory instability, in which the WM-like input can modulate the frequency and amplitude of the oscillation. Our neural field model has a spatial-like domain in which an input that preferentially targets a point-a stimulus feature-on the domain will induce feature-specific activity changes. These feature-specific activity changes affect both the mean rate of spikes and the relative timing of spiking activity to the global field oscillation-the phase of the spiking activity. From these two dynamical signatures, we define both a spike rate code and an oscillatory phase code. We assess the performance of these two codes to discriminate stimulus features using an information-theoretic analysis. We show that global WM input modulations can enhance phase code discrimination while simultaneously reducing rate code discrimination. Moreover, we find that the phase code performance is roughly two orders of magnitude larger than that of the rate code defined for the same model solutions. The results of our model have applications to sensory areas of the brain, to which prefrontal areas send inputs reflecting the content of WM. These WM inputs to sensory areas have been established to induce oscillatory changes similar to our model. Our model results suggest a mechanism by which WM signals may enhance sensory information represented in oscillatory activity beyond the comparatively weak representations based on the mean rate activity.
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Affiliation(s)
- William H. Nesse
- Department of Mathematics, University of Utah, Salt Lake City, UT, United States
| | - Kelsey L. Clark
- Department of Ophthalmology, University of Utah, Salt Lake City, UT, United States
| | - Behrad Noudoost
- Department of Ophthalmology, University of Utah, Salt Lake City, UT, United States
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14
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Huang S, Wu SJ, Sansone G, Ibrahim LA, Fishell G. Layer 1 neocortex: Gating and integrating multidimensional signals. Neuron 2024; 112:184-200. [PMID: 37913772 DOI: 10.1016/j.neuron.2023.09.041] [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: 07/24/2023] [Revised: 09/23/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.
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Affiliation(s)
- Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulia Sansone
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Leena Ali Ibrahim
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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15
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Aqil M, Knapen T, Dumoulin SO. Computational model links normalization to chemoarchitecture in the human visual system. SCIENCE ADVANCES 2024; 10:eadj6102. [PMID: 38170784 PMCID: PMC10776006 DOI: 10.1126/sciadv.adj6102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024]
Abstract
A goal of cognitive neuroscience is to provide computational accounts of brain function. Canonical computations-mathematical operations used by the brain in many contexts-fulfill broad information-processing needs by varying their algorithmic parameters. A key question concerns the identification of biological substrates for these computations and their algorithms. Chemoarchitecture-the spatial distribution of neurotransmitter receptor densities-shapes brain function. Here, we propose that local variations in specific receptor densities implement algorithmic modulations of canonical computations. To test this hypothesis, we combine mathematical modeling of brain responses with chemoarchitecture data. We compare parameters of divisive normalization obtained from 7-tesla functional magnetic resonance imaging with receptor density maps obtained from positron emission tomography. We find evidence that serotonin and γ-aminobutyric acid receptor densities are the biological substrate for algorithmic modulations of divisive normalization in the human visual system. Our model links computational and biological levels of vision, explaining how canonical computations allow the brain to fulfill broad information-processing needs.
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Affiliation(s)
- Marco Aqil
- Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
- Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Tomas Knapen
- Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
- Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Serge O. Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
- Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Experimental Psychology, Utrecht University, Utrecht, Netherlands
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16
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Fang Z, Bloem IM, Olsson C, Ma WJ, Winawer J. Normalization by orientation-tuned surround in human V1-V3. PLoS Comput Biol 2023; 19:e1011704. [PMID: 38150484 PMCID: PMC10793941 DOI: 10.1371/journal.pcbi.1011704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/17/2024] [Accepted: 11/20/2023] [Indexed: 12/29/2023] Open
Abstract
An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a multi-stage computation. The first stage is linear filtering. The second stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of the linear filters in quadrature phase. The third stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Motivated by these observations and others from the literature, we implement a divisive normalization model in which cells matched in orientation tuning ("tuned normalization") preferentially inhibit each other. We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.
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Affiliation(s)
- Zeming Fang
- Department of Psychology and Center for Neural Science, New York University, New York City, New York, United States of America
- Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America
| | - Ilona M. Bloem
- Department of Psychology and Center for Neural Science, New York University, New York City, New York, United States of America
| | - Catherine Olsson
- Department of Psychology and Center for Neural Science, New York University, New York City, New York, United States of America
| | - Wei Ji Ma
- Department of Psychology and Center for Neural Science, New York University, New York City, New York, United States of America
| | - Jonathan Winawer
- Department of Psychology and Center for Neural Science, New York University, New York City, New York, United States of America
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17
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Del Rosario J, Coletta S, Kim SH, Mobille Z, Peelman K, Williams B, Otsuki AJ, Del Castillo Valerio A, Worden K, Blanpain LT, Lovell L, Choi H, Haider B. Lateral inhibition in V1 controls neural & perceptual contrast sensitivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.10.566605. [PMID: 38014014 PMCID: PMC10680635 DOI: 10.1101/2023.11.10.566605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.
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18
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Li Z, Peng B, Huang JJ, Zhang Y, Seo MB, Fang Q, Zhang GW, Zhang X, Zhang LI, Tao HW. Enhancement and contextual modulation of visuospatial processing by thalamocollicular projections from ventral lateral geniculate nucleus. Nat Commun 2023; 14:7278. [PMID: 37949869 PMCID: PMC10638288 DOI: 10.1038/s41467-023-43147-9] [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: 03/05/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023] Open
Abstract
In the mammalian visual system, the ventral lateral geniculate nucleus (vLGN) of the thalamus receives salient visual input from the retina and sends prominent GABAergic axons to the superior colliculus (SC). However, whether and how vLGN contributes to fundamental visual information processing remains largely unclear. Here, we report in mice that vLGN facilitates visually-guided approaching behavior mediated by the lateral SC and enhances the sensitivity of visual object detection. This can be attributed to the extremely broad spatial integration of vLGN neurons, as reflected in their much lower preferred spatial frequencies and broader spatial receptive fields than SC neurons. Through GABAergic thalamocollicular projections, vLGN specifically exerts prominent surround suppression of visuospatial processing in SC, leading to a fine tuning of SC preferences to higher spatial frequencies and smaller objects in a context-dependent manner. Thus, as an essential component of the central visual processing pathway, vLGN serves to refine and contextually modulate visuospatial processing in SC-mediated visuomotor behaviors via visually-driven long-range feedforward inhibition.
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Affiliation(s)
- Zhong Li
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Bo Peng
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
- Graduate Program in Neuroscience, University of Southern California, Los Angeles, CA, 90033, USA
| | - Junxiang J Huang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
- Graduate Program in Biological and Biomedical Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Yuan Zhang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Michelle B Seo
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
- Graduate Program in Neuroscience, University of Southern California, Los Angeles, CA, 90033, USA
| | - Qi Fang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
- Graduate Program in Neuroscience, University of Southern California, Los Angeles, CA, 90033, USA
| | - Guang-Wei Zhang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Li I Zhang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
- Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
| | - Huizhong Whit Tao
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
- Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
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19
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Yu H, Chen S, Ye Z, Zhang Q, Tu Y, Hua T. Top-down influence of areas 21a and 7 differently affects the surround suppression of V1 neurons in cats. Cereb Cortex 2023; 33:11047-11059. [PMID: 37724432 DOI: 10.1093/cercor/bhad344] [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: 07/05/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/20/2023] Open
Abstract
Surround suppression (SS) is a phenomenon whereby a neuron's response to stimuli in its central receptive field (cRF) is suppressed by stimuli extending to its surround receptive field (sRF). Recent evidence show that top-down influence contributed to SS in the primary visual cortex (V1). However, how the top-down influence from different high-level cortical areas affects SS in V1 has not been comparatively observed. The present study applied transcranial direct current stimulation (tDCS) to modulate the neural activity in area 21a (A21a) and area 7 (A7) of cats and examined the changes in the cRF and sRF of V1 neurons. We found that anode-tDCS at A21a reduced V1 neurons' cRF size and increased their response to visual stimuli in cRF, causing an improved SS strength. By contrast, anode-tDCS at A7 increased V1 neurons' sRF size and response to stimuli in cRF, also enhancing the SS. Modeling analysis based on DoG function indicated that the increased SS of V1 neurons after anode-tDCS at A21a could be explained by a center-only mechanism, whereas the improved SS after anode-tDCS at A7 might be mediated through a combined center and surround mechanism. In conclusion, A21a and A7 may affect the SS of V1 neurons through different mechanisms.
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Affiliation(s)
- Hao Yu
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
- School of Basic Medical Sciences, Wannan Medical College, West Wenchang Road, Yijiang District, Wuhu, Anhui, China
| | - Shunshun Chen
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
| | - Zheng Ye
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
| | - Qiuyu Zhang
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
| | - Yanni Tu
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
| | - Tianmiao Hua
- College of Life Sciences, Anhui Normal University, Beijing East Road, Jinghu District, Wuhu, Anhui 241000, China
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20
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Chen SC, Chen Y, Geisler WS, Seidemann E. NEURAL CORRELATES OF PERCEPTUAL SIMILARITY MASKING IN PRIMATE V1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.06.547970. [PMID: 37503133 PMCID: PMC10369882 DOI: 10.1101/2023.07.06.547970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed "similarity masking". To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.
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Affiliation(s)
- Spencer C Chen
- Center for Perceptual Systems, University of Texas at Austin
- Center for Theoretical and Computational Neuroscience, University of Texas at Austin
- Department of Psychology, University of Texas at Austin
- Department of Neuroscience, University of Texas at Austin
- Department of Neurosurgery, Rutgers University
| | - Yuzhi Chen
- Center for Perceptual Systems, University of Texas at Austin
- Center for Theoretical and Computational Neuroscience, University of Texas at Austin
- Department of Psychology, University of Texas at Austin
- Department of Neuroscience, University of Texas at Austin
| | - Wilson S Geisler
- Center for Perceptual Systems, University of Texas at Austin
- Center for Theoretical and Computational Neuroscience, University of Texas at Austin
- Department of Psychology, University of Texas at Austin
| | - Eyal Seidemann
- Center for Perceptual Systems, University of Texas at Austin
- Center for Theoretical and Computational Neuroscience, University of Texas at Austin
- Department of Psychology, University of Texas at Austin
- Department of Neuroscience, University of Texas at Austin
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21
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LaFosse PK, Zhou Z, Scott VM, Deng Y, Histed MH. Single cell optogenetics reveals attenuation-by-suppression in visual cortical neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.13.557650. [PMID: 37745464 PMCID: PMC10515908 DOI: 10.1101/2023.09.13.557650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The relationship between neurons' input and spiking output is central to brain computation. Studies in vitro and in anesthetized animals suggest nonlinearities emerge in cells' input-output (activation) functions as network activity increases, yet how neurons transform inputs in vivo has been unclear. Here, we characterize cortical principal neurons' activation functions in awake mice using two-photon optogenetics and imaging. We find responses to fixed optogenetic input are nearly unchanged as neurons are excited, reflecting a linear response regime above neurons' resting point. In contrast, responses are dramatically attenuated by suppression. This attenuation is a powerful means to filter inputs arriving to suppressed cells, privileging other inputs arriving to excited neurons. These data have two major implications: first, neural activation functions in vivo accord with the activation functions used in recent machine learning systems, and second, neurons' IO functions can enhance sensory processing by attenuating some inputs while leaving others unchanged.
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Affiliation(s)
- Paul K LaFosse
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
- NIH-University of Maryland Graduate Partnerships Program, Bethesda, MD USA 20892
- Neuroscience and Cognitive Science Program, University of Maryland College Park, College Park, MD USA 20742
| | - Zhishang Zhou
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Victoria M Scott
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Yanting Deng
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Mark H Histed
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
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22
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Krishnakumaran R, Ray S. Temporal characteristics of gamma rhythm constrain properties of noise in an inhibition-stabilized network model. Cereb Cortex 2023; 33:10108-10121. [PMID: 37492002 PMCID: PMC10502791 DOI: 10.1093/cercor/bhad270] [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: 02/10/2023] [Revised: 07/07/2023] [Accepted: 07/08/2023] [Indexed: 07/27/2023] Open
Abstract
Gamma rhythm refers to oscillatory neural activity between 30 and 80 Hz, induced in visual cortex by stimuli such as iso-luminant hues or gratings. The power and peak frequency of gamma depend on the properties of the stimulus such as size and contrast. Gamma waveform is typically arch-shaped, with narrow troughs and broad peaks, and can be replicated in a self-oscillating Wilson-Cowan (WC) model operating in an appropriate regime. However, oscillations in this model are infinitely long, unlike physiological gamma that occurs in short bursts. Further, unlike the model, gamma is faster after stimulus onset and slows down over time. Here, we first characterized gamma burst duration in local field potential data recorded from two monkeys as they viewed full screen iso-luminant hues. We then added different types of noise in the inputs to the WC model and tested how that affected duration and temporal dynamics of gamma. While the model failed with the often-used Poisson noise, Ornstein-Uhlenbeck noise applied to both the excitatory and the inhibitory populations replicated the duration and slowing of gamma and replicated the shape and stimulus dependencies. Thus, the temporal dynamics of gamma oscillations put constraints on the type and properties of underlying neural noise.
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Affiliation(s)
- R Krishnakumaran
- IISc Mathematics Initiative, Department of Mathematics, Indian Institute of Science, C V Raman road, Bangalore 560012, Karnataka, India
| | - Supratim Ray
- IISc Mathematics Initiative, Department of Mathematics, Indian Institute of Science, C V Raman road, Bangalore 560012, Karnataka, India
- Centre for Neuroscience, Indian Institute of Science, C V Raman road, Bangalore 560012, Karnataka, India
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23
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Pan X, DeForge A, Schwartz O. Generalizing biological surround suppression based on center surround similarity via deep neural network models. PLoS Comput Biol 2023; 19:e1011486. [PMID: 37738258 PMCID: PMC10550176 DOI: 10.1371/journal.pcbi.1011486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 10/04/2023] [Accepted: 09/04/2023] [Indexed: 09/24/2023] Open
Abstract
Sensory perception is dramatically influenced by the context. Models of contextual neural surround effects in vision have mostly accounted for Primary Visual Cortex (V1) data, via nonlinear computations such as divisive normalization. However, surround effects are not well understood within a hierarchy, for neurons with more complex stimulus selectivity beyond V1. We utilized feedforward deep convolutional neural networks and developed a gradient-based technique to visualize the most suppressive and excitatory surround. We found that deep neural networks exhibited a key signature of surround effects in V1, highlighting center stimuli that visually stand out from the surround and suppressing responses when the surround stimulus is similar to the center. We found that in some neurons, especially in late layers, when the center stimulus was altered, the most suppressive surround surprisingly can follow the change. Through the visualization approach, we generalized previous understanding of surround effects to more complex stimuli, in ways that have not been revealed in visual cortices. In contrast, the suppression based on center surround similarity was not observed in an untrained network. We identified further successes and mismatches of the feedforward CNNs to the biology. Our results provide a testable hypothesis of surround effects in higher visual cortices, and the visualization approach could be adopted in future biological experimental designs.
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Affiliation(s)
- Xu Pan
- Department of Computer Science, University of Miami, Coral Gables, FL, United States of America
| | - Annie DeForge
- School of Information, University of California, Berkeley, CA, United States of America
- Bentley University, Waltham, MA, United States of America
| | - Odelia Schwartz
- Department of Computer Science, University of Miami, Coral Gables, FL, United States of America
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24
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Gurbuz BT, Boyaci H. Tilt aftereffect spreads across the visual field. Vision Res 2023; 205:108174. [PMID: 36630779 DOI: 10.1016/j.visres.2022.108174] [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: 09/06/2022] [Revised: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 01/11/2023]
Abstract
The tilt aftereffect (TAE) is observed when adaptation to a tilted contour alters the perceived tilt of a subsequently presented contour. Thus far, TAE has been treated as a local aftereffect observed only at the location of the adapter. Whether and how TAE spreads to other locations in the visual field has not been systematically studied. Here, we sought an answer to this question by measuring TAE magnitudes at locations including but not limited to the adapter location. The adapter was a tilted grating presented at the same peripheral location throughout an experimental session. In a single trial, participants indicated the perceived tilt of a test grating presented after the adapter at one of fifteen locations in the same visual hemifield as the adapter. We found non-zero TAE magnitudes in all locations tested, showing that the effect spreads across the tested visual hemifield. Next, to establish a link between neuronal activity and behavioral results and to predict the possible neuronal origins of the spread, we built a computational model based on known characteristics of the visual cortex. The simulation results showed that the model could successfully capture the pattern of the behavioral results. Furthermore, the pattern of the optimized receptive field sizes suggests that mid-level visual areas, such as V4, could be critically involved in TAE and its spread across the visual field.
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Affiliation(s)
- Busra Tugce Gurbuz
- Aysel Sabuncu Brain Research Center & National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey.
| | - Huseyin Boyaci
- Aysel Sabuncu Brain Research Center & National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey; Department of Psychology, Bilkent University, Ankara, Turkey; Department of Psychology, Justus Liebig University Giessen, Giessen, Germany.
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25
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Ping A, Pan L, Zhang J, Xu K, Schriver KE, Zhu J, Roe AW. Targeted Optical Neural Stimulation: A New Era for Personalized Medicine. Neuroscientist 2023; 29:202-220. [PMID: 34865559 DOI: 10.1177/10738584211057047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Targeted optical neural stimulation comprises infrared neural stimulation and optogenetics, which affect the nervous system through induced thermal transients and activation of light-sensitive proteins, respectively. The main advantage of this pair of optical tools is high functional selectivity, which conventional electrical stimulation lacks. Over the past 15 years, the mechanism, safety, and feasibility of optical stimulation techniques have undergone continuous investigation and development. When combined with other methods like optical imaging and high-field functional magnetic resonance imaging, the translation of optical stimulation to clinical practice adds high value. We review the theoretical foundations and current state of optical stimulation, with a particular focus on infrared neural stimulation as a potential bridge linking optical stimulation to personalized medicine.
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Affiliation(s)
- An Ping
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Li Pan
- Qiushi Academy for Advanced Studies (QAAS), Key Laboratory of Biomedical Engineering of Education Ministry & Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianmin Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kedi Xu
- Qiushi Academy for Advanced Studies (QAAS), Key Laboratory of Biomedical Engineering of Education Ministry & Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, Zhejiang, China.,Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Kenneth E Schriver
- Zhejiang University Interdisciplinary Institute of Neuroscience and Technology (ZIINT), School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Junming Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Anna Wang Roe
- Zhejiang University Interdisciplinary Institute of Neuroscience and Technology (ZIINT), School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China
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26
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Angelucci A, Clark A, Ingold A, Reiche C, Cundy D, Balsor J, Federer F, McAlinden N, Cheng Y, Rolston J, Rieth L, Dawson M, Mathieson K, Blair S. An Optrode Array for Spatiotemporally Precise Large-Scale Optogenetic Stimulation of Deep Cortical Layers in Non-human Primates. RESEARCH SQUARE 2023:rs.3.rs-2322768. [PMID: 36909489 PMCID: PMC10002840 DOI: 10.21203/rs.3.rs-2322768/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Optogenetics has transformed studies of neural circuit function, but remains challenging to apply in non-human primates (NHPs). A major challenge is delivering intense and spatially precise patterned photostimulation across large volumes in deep tissue. Here, we have developed and validated the Utah Optrode Array (UOA) to meet this critical need. The UOA is a 10×10 glass waveguide array bonded to an electrically-addressable μLED array. In vivo electrophysiology and immediate early gene (c-fos) immunohistochemistry demonstrated the UOA allows for large-scale spatiotemporally precise neuromodulation of deep tissue in macaque primary visual cortex. Specifically, the UOA permits both focal (single layers or columns), and large-scale (across multiple layers or columns) photostimulation of deep cortical layers, simply by varying the number of simultaneously activated μLEDs and/or the light irradiance. These results establish the UOA as a powerful tool for studying targeted neural populations within single or across multiple deep layers in complex NHP circuits.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - John Rolston
- Brigham & Women's Hospital and Harvard Medical School
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27
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Orekhova EV, Manyukhina VO, Galuta IA, Prokofyev AO, Goiaeva DE, Obukhova TS, Fadeev KA, Schneiderman JF, Stroganova TA. Gamma oscillations point to the role of primary visual cortex in atypical motion processing in autism. PLoS One 2023; 18:e0281531. [PMID: 36780507 PMCID: PMC9925089 DOI: 10.1371/journal.pone.0281531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/25/2023] [Indexed: 02/15/2023] Open
Abstract
Neurophysiological studies suggest that abnormal neural inhibition may explain a range of sensory processing differences in autism spectrum disorders (ASD). In particular, the impaired ability of people with ASD to visually discriminate the motion direction of small-size objects and their reduced perceptual suppression of background-like visual motion may stem from deficient surround inhibition within the primary visual cortex (V1) and/or its atypical top-down modulation by higher-tier cortical areas. In this study, we estimate the contribution of abnormal surround inhibition to the motion-processing deficit in ASD. For this purpose, we used a putative correlate of surround inhibition-suppression of the magnetoencephalographic (MEG) gamma response (GR) caused by an increase in the drift rate of a large annular high-contrast grating. The motion direction discrimination thresholds for the gratings of different angular sizes (1° and 12°) were assessed in a separate psychophysical paradigm. The MEG data were collected in 42 boys with ASD and 37 typically developing (TD) boys aged 7-15 years. Psychophysical data were available in 33 and 34 of these participants, respectively. The results showed that the GR suppression in V1 was reduced in boys with ASD, while their ability to detect the direction of motion was compromised only in the case of small stimuli. In TD boys, the GR suppression directly correlated with perceptual suppression caused by increasing stimulus size, thus suggesting the role of the top-down modulations of V1 in surround inhibition. In ASD, weaker GR suppression was associated with the poor directional sensitivity to small stimuli, but not with perceptual suppression. These results strongly suggest that a local inhibitory deficit in V1 plays an important role in the reduction of directional sensitivity in ASD and that this perceptual deficit cannot be explained exclusively by atypical top-down modulation of V1 by higher-tier cortical areas.
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Affiliation(s)
- Elena V. Orekhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
- * E-mail:
| | - Viktoriya O. Manyukhina
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
- National Research University Higher School of Economics, Moscow, Russian Federation
| | - Ilia A. Galuta
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Andrey O. Prokofyev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Dzerassa E. Goiaeva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Tatiana S. Obukhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Kirill A. Fadeev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Justin F. Schneiderman
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
| | - Tatiana A. Stroganova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
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28
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Nurminen L, Bijanzadeh M, Angelucci A. Size tuning of neural response variability in laminar circuits of macaque primary visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.17.524397. [PMID: 36711786 PMCID: PMC9882156 DOI: 10.1101/2023.01.17.524397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
A defining feature of the cortex is its laminar organization, which is likely critical for cortical information processing. For example, visual stimuli of different size evoke distinct patterns of laminar activity. Visual information processing is also influenced by the response variability of individual neurons and the degree to which this variability is correlated among neurons. To elucidate laminar processing, we studied how neural response variability across the layers of macaque primary visual cortex is modulated by visual stimulus size. Our laminar recordings revealed that single neuron response variability and the shared variability among neurons are tuned for stimulus size, and this size-tuning is layer-dependent. In all layers, stimulation of the receptive field (RF) reduced single neuron variability, and the shared variability among neurons, relative to their pre-stimulus values. As the stimulus was enlarged beyond the RF, both single neuron and shared variability increased in supragranular layers, but either did not change or decreased in other layers. Surprisingly, we also found that small visual stimuli could increase variability relative to baseline values. Our results suggest multiple circuits and mechanisms as the source of variability in different layers and call for the development of new models of neural response variability.
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Affiliation(s)
- Lauri Nurminen
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
- Present address: College of Optometry, University of Houston, 4401 Martin Luther King Boulevard, Houston, TX 77204-2020, USA
| | - Maryam Bijanzadeh
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
| | - Alessandra Angelucci
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
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29
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Gilday OD, Praegel B, Maor I, Cohen T, Nelken I, Mizrahi A. Surround suppression in mouse auditory cortex underlies auditory edge detection. PLoS Comput Biol 2023; 19:e1010861. [PMID: 36656876 PMCID: PMC9888713 DOI: 10.1371/journal.pcbi.1010861] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 01/31/2023] [Accepted: 01/09/2023] [Indexed: 01/20/2023] Open
Abstract
Surround suppression (SS) is a fundamental property of sensory processing throughout the brain. In the auditory system, the early processing stream encodes sounds using a one dimensional physical space-frequency. Previous studies in the auditory system have shown SS to manifest as bandwidth tuning around the preferred frequency. We asked whether bandwidth tuning can be found around frequencies away from the preferred frequency. We exploited the simplicity of spectral representation of sounds to study SS by manipulating both sound frequency and bandwidth. We recorded single unit spiking activity from the auditory cortex (ACx) of awake mice in response to an array of broadband stimuli with varying central frequencies and bandwidths. Our recordings revealed that a significant portion of neuronal response profiles had a preferred bandwidth that varied in a regular way with the sound's central frequency. To gain insight into the possible mechanism underlying these responses, we modelled neuronal activity using a variation of the "Mexican hat" function often used to model SS. The model accounted for response properties of single neurons with high accuracy. Our data and model show that these responses in ACx obey simple rules resulting from the presence of lateral inhibitory sidebands, mostly above the excitatory band of the neuron, that result in sensitivity to the location of top frequency edges, invariant to other spectral attributes. Our work offers a simple explanation for auditory edge detection and possibly other computations of spectral content in sounds.
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Affiliation(s)
- Omri David Gilday
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Benedikt Praegel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ido Maor
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tav Cohen
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Israel Nelken
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adi Mizrahi
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem, Israel
- * E-mail:
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30
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Orlandi JG, Abdolrahmani M, Aoki R, Lyamzin DR, Benucci A. Distributed context-dependent choice information in mouse posterior cortex. Nat Commun 2023; 14:192. [PMID: 36635318 PMCID: PMC9837177 DOI: 10.1038/s41467-023-35824-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 01/03/2023] [Indexed: 01/14/2023] Open
Abstract
Choice information appears in multi-area brain networks mixed with sensory, motor, and cognitive variables. In the posterior cortex-traditionally implicated in decision computations-the presence, strength, and area specificity of choice signals are highly variable, limiting a cohesive understanding of their computational significance. Examining the mesoscale activity in the mouse posterior cortex during a visual task, we found that choice signals defined a decision variable in a low-dimensional embedding space with a prominent contribution along the ventral visual stream. Their subspace was near-orthogonal to concurrently represented sensory and motor-related activations, with modulations by task difficulty and by the animals' attention state. A recurrent neural network trained with animals' choices revealed an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. Our results demonstrated an independent, multi-area decision variable in the posterior cortex, controlled by task features and cognitive demands, possibly linked to contextual inference computations in dynamic animal-environment interactions.
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Affiliation(s)
- Javier G Orlandi
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan.,Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
| | | | - Ryo Aoki
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
| | - Dmitry R Lyamzin
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
| | - Andrea Benucci
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan. .,University of Tokyo, Graduate School of Information Science and Technology, Department of Mathematical Informatics, 1-1-1 Yayoi, Bunkyo City, Tokyo, 113-0032, Japan.
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31
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Tan M, Yuan X, Liang B, Han S. DRFnet: Dynamic receptive field network for object detection and image recognition. Front Neurorobot 2023; 16:1100697. [PMID: 36704718 PMCID: PMC9871543 DOI: 10.3389/fnbot.2022.1100697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023] Open
Abstract
Biological experiments discovered that the receptive field of neurons in the primary visual cortex of an animal's visual system is dynamic and capable of being altered by the sensory context. However, in a typical convolution neural network (CNN), a unit's response only comes from a fixed receptive field, which is generally determined by the preset kernel size in each layer. In this work, we simulate the dynamic receptive field mechanism in the biological visual system (BVS) for application in object detection and image recognition. We proposed a Dynamic Receptive Field module (DRF), which can realize the global information-guided responses under the premise of a slight increase in parameters and computational cost. Specifically, we design a transformer-style DRF module, which defines the correlation coefficient between two feature points by their relative distance. For an input feature map, we first divide the relative distance corresponding to different receptive field regions between the target feature point and its surrounding feature points into N different discrete levels. Then, a vector containing N different weights is automatically learned from the dataset and assigned to each feature point, according to the calculated discrete level that this feature point belongs. In this way, we achieve a correlation matrix primarily measuring the relationship between the target feature point and its surrounding feature points. The DRF-processed responses of each feature point are computed by multiplying its corresponding correlation matrix with the input feature map, which computationally equals to accomplish a weighted sum of all feature points exploiting the global and long-range information as the weight. Finally, by superimposing the local responses calculated by a traditional convolution layer with DRF responses, our proposed approach can integrate the rich context information among neighbors and the long-range dependencies of background into the feature maps. With the proposed DRF module, we achieved significant performance improvement on four benchmark datasets for both tasks of object detection and image recognition. Furthermore, we also proposed a new matching strategy that can improve the detection results of small targets compared with the traditional IOU-max matching strategy.
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32
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Reynaert B, Morales C, Mpodozis J, Letelier JC, Marín GJ. A blinking focal pattern of re-entrant activity in the avian tectum. Curr Biol 2023; 33:1-14.e4. [PMID: 36446352 DOI: 10.1016/j.cub.2022.10.070] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 09/06/2022] [Accepted: 10/31/2022] [Indexed: 11/30/2022]
Abstract
Re-entrant connections are inherent to nervous system organization; however, a comprehensive understanding of their operation is still lacking. In birds, topographically organized re-entrant signals, carried by axons from the nucleus-isthmi-parvocellularis (Ipc), are distinctly recorded as bursting discharges across the optic tectum (TeO). Here, we used up to 48 microelectrodes regularly spaced on the superficial tectal layers of anesthetized pigeons to characterize the spatial-temporal pattern of this axonal re-entrant activity in response to different visual stimulation. We found that a brief luminous spot triggered repetitive waves of bursting discharges that, appearing from initial sources, propagated horizontally to areas representing up to 28° of visual space, widely exceeding the area activated by the retinal fibers. In response to visual motion, successive burst waves started along and around the stimulated tectal path, tracking the stimulus in discontinuous steps. When two stimuli were presented, the burst-wave sources alternated between the activated tectal loci, as if only one source could be active at any given time. Because these re-entrant signals boost the retinal input to higher visual areas, their peculiar dynamics mimic a blinking "spotlight," similar to the internal searching mechanism classically used to explain spatial attention. Tectal re-entry from Ipc is thus highly structured and intrinsically discontinuous, and higher tectofugal areas, which lack retinotopic organization, will thus receive incoming visual activity in a sequential and piecemeal fashion. We anticipate that analogous re-entrant patterns, perhaps hidden in less bi-dimensionally organized topographies, may organize the flow of neural activity in other parts of the brain as well.
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Affiliation(s)
- Bryan Reynaert
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile
| | - Cristian Morales
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile
| | - Jorge Mpodozis
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile
| | - Juan Carlos Letelier
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile
| | - Gonzalo J Marín
- Departamento de Biología, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile; Facultad de Medicina, Universidad Finis Terrae, Santiago 7501015, Chile.
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33
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Baranauskas G, Rysevaite-Kyguoliene K, Sabeckis I, Pauza DH. Saturation of visual responses explains size tuning in rat collicular neurons. Eur J Neurosci 2023; 57:285-309. [PMID: 36451583 DOI: 10.1111/ejn.15877] [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: 11/30/2021] [Revised: 08/03/2022] [Accepted: 11/21/2022] [Indexed: 12/02/2022]
Abstract
The receptive field of many visual neurons is composed of a central responsive area, the classical receptive field, and a non-classical receptive field, also called the "suppressive surround." A visual stimulus placed in the suppressive surround does not induce any response but modulates visual responses to stimuli within the classical receptive field, usually by suppressing them. Therefore, visual responses become smaller when stimuli exceed the classical receptive field size. The stimulus size inducing the maximal response is called the preferred stimulus size. In cortex, there is good correspondence between the sizes of the classical receptive field and the preferred stimulus. In contrast, in the rodent superior colliculus, the preferred size is often several fold smaller than the classical receptive field size. Here, we show that in the rat superior colliculus, the preferred stimulus size changes as a square root of the contrast inverse and the classical receptive field size is independent of contrast. In addition, responses to annulus were largely independent of the inner hole size. To explain these data, three models were tested: the divisive modulation of the gain by the suppressive surround (the "normalization" model), the difference of the Gaussians, and a divisive model that incorporates saturation to light flux. Despite the same number of free parameters, the model incorporating saturation to light performed the best. Thus, our data indicate that in rats, the saturation to light can be a dominant phenomenon even at relatively low illumination levels defining visual responses in the collicular neurons.
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Affiliation(s)
- Gytis Baranauskas
- Neurophysiology Laboratory, Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | | | - Ignas Sabeckis
- Anatomy Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Dainius H Pauza
- Anatomy Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania
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34
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Canoluk MU, Moors P, Goffaux V. Contributions of low- and high-level contextual mechanisms to human face perception. PLoS One 2023; 18:e0285255. [PMID: 37130144 PMCID: PMC10153715 DOI: 10.1371/journal.pone.0285255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 04/18/2023] [Indexed: 05/03/2023] Open
Abstract
Contextual modulations at primary stages of visual processing depend on the strength of local input. Contextual modulations at high-level stages of (face) processing show a similar dependence to local input strength. Namely, the discriminability of a facial feature determines the amount of influence of the face context on that feature. How high-level contextual modulations emerge from primary mechanisms is unclear due to the scarcity of empirical research systematically addressing the functional link between the two. We tested (62) young adults' ability to process local input independent of the context using contrast detection and (upright and inverted) morphed facial feature matching tasks. We first investigated contextual modulation magnitudes across tasks to address their shared variance. A second analysis focused on the profile of performance across contextual conditions. In upright eye matching and contrast detection tasks, contextual modulations only correlated at the level of their profile (averaged Fisher-Z transformed r = 1.18, BF10 > 100), but not magnitude (r = .15, BF10 = .61), suggesting the functional independence but similar working principles of the mechanisms involved. Both the profile (averaged Fisher-Z transformed r = .32, BF10 = 9.7) and magnitude (r = .28, BF10 = 4.58) of the contextual modulations correlated between inverted eye matching and contrast detection tasks. Our results suggest that non-face-specialized high-level contextual mechanisms (inverted faces) work in connection to primary contextual mechanisms, but that the engagement of face-specialized mechanisms for upright faces obscures this connection. Such combined study of low- and high-level contextual modulations sheds new light on the functional relationship between different levels of the visual processing hierarchy, and thus on its functional organization.
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Affiliation(s)
- Mehmet Umut Canoluk
- Research Institute for Psychological Science (IPSY), UCLouvain, Louvain-la-Neuve, Belgium
| | - Pieter Moors
- Department of Brain and Cognition, Laboratory of Experimental Psychology, KU Leuven, Leuven, Belgium
| | - Valerie Goffaux
- Research Institute for Psychological Science (IPSY), UCLouvain, Louvain-la-Neuve, Belgium
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Institute of Neuroscience (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
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35
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Altered visual cortex excitability in premenstrual dysphoric disorder: Evidence from magnetoencephalographic gamma oscillations and perceptual suppression. PLoS One 2022; 17:e0279868. [PMID: 36584199 PMCID: PMC9803314 DOI: 10.1371/journal.pone.0279868] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/15/2022] [Indexed: 12/31/2022] Open
Abstract
Premenstrual dysphoric disorder (PMDD) is a psychiatric condition characterized by extreme mood shifts during the luteal phase of the menstrual cycle (MC) due to abnormal sensitivity to neurosteroids and unbalanced neural excitation/inhibition (E/I) ratio. We hypothesized that in women with PMDD in the luteal phase, these factors would alter the frequency of magnetoencephalographic visual gamma oscillations, affect modulation of their power by excitatory drive, and decrease perceptual spatial suppression. Women with PMDD and control women were examined twice-during the follicular and luteal phases of their MC. We recorded visual gamma response (GR) while modulating the excitatory drive by increasing the drift rate of the high-contrast grating (static, 'slow', 'medium', and 'fast'). Contrary to our expectations, GR frequency was not affected in women with PMDD in either phase of the MC. GR power suppression, which is normally associated with a switch from the 'optimal' for GR slow drift rate to the medium drift rate, was reduced in women with PMDD and was the only GR parameter that distinguished them from control participants specifically in the luteal phase and predicted severity of their premenstrual symptoms. Over and above the atypical luteal GR suppression, in both phases of the MC women with PMDD had abnormally strong GR facilitation caused by a switch from the 'suboptimal' static to the 'optimal' slow drift rate. Perceptual spatial suppression did not differ between the groups but decreased from the follicular to the luteal phase only in PMDD women. The atypical modulation of GR power suggests that neuronal excitability in the visual cortex is constitutively elevated in PMDD and that this E/I imbalance is further exacerbated during the luteal phase. However, the unaltered GR frequency does not support the hypothesis of inhibitory neuron dysfunction in PMDD.
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36
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Williams N, Olson CR. Independent repetition suppression in macaque area V2 and inferotemporal cortex. J Neurophysiol 2022; 128:1421-1434. [PMID: 36350050 PMCID: PMC9678433 DOI: 10.1152/jn.00043.2022] [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: 02/08/2022] [Revised: 10/11/2022] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
Abstract
When a complexly structured natural image is presented twice in succession, first as adapter and then as test, neurons in area TE of macaque inferotemporal cortex exhibit repetition suppression, responding less strongly to the second presentation than to the first. This phenomenon, which has been studied primarily in TE, might plausibly be argued to arise in TE because TE neurons respond selectively to complex images and thus carry information adequate for determining whether an image is or is not a repeat. However, the idea has never been put to a direct test. To resolve this issue, we monitored neuronal responses to sequences of complex natural images under identical conditions in areas V2 and TE. We found that repetition suppression occurs in both areas. Moreover, in each area, suppression takes the form of a dynamic alteration whereby the initial peak of excitation is followed by a trough and then a rebound of firing rate. To assess whether repetition suppression in either area is transmitted from the other area, we analyzed the timing of the phenomenon and its degree of spatial generalization. Suppression occurs at shorter latency in V2 than in TE. Therefore it is not simply fed back from TE. Suppression occurs in TE but not in V2 under conditions in which the test and adapter are presented in different visual field quadrants. Therefore it is not simply fed forward from V2. We conclude that repetition suppression occurs independently in V2 and TE.NEW & NOTEWORTHY When a complexly structured natural image is presented twice in rapid succession, neurons in inferotemporal area TE exhibit repetition suppression, responding less strongly to the second than to the first presentation. We have explored whether this phenomenon is confined to high-order areas where neurons respond selectively to such images and thus carry information relevant to recognizing a repeat. We have found surprisingly that repetition suppression occurs even in low-order visual area V2.
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Affiliation(s)
- Nathaniel Williams
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Carl R Olson
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania
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Exercise does not enhance short-term deprivation-induced ocular dominance plasticity: evidence from dichoptic surround suppression. Vision Res 2022; 201:108123. [PMID: 36193605 DOI: 10.1016/j.visres.2022.108123] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/09/2022] [Accepted: 09/05/2022] [Indexed: 11/06/2022]
Abstract
The input from the two eyes is combined in the brain. In this combination, the relative strength of the input from each eye is determined by the ocular dominance. Recent work has shown that this dominance can be temporarily shifted. Covering one eye with an eye patch for a few hours makes its contribution stronger. It has been proposed that this shift can be enhanced by exercise. Here, we test this hypothesis using a dichoptic surround suppression task, and with exercise performed according to American College of Sport Medicine guidelines. We measured detection thresholds for patches of sinusoidal grating shown to one eye. When an annular mask grating was shown simultaneously to the other eye, thresholds were elevated. The difference in the elevation found in each eye is our measure of relative eye dominance. We made these measurements before and after 120 min of monocular deprivation (with an eye patch). In the control condition, subjects rested during this time. For the exercise condition, 30 min of exercise were performed at the beginning of the patching period. This was followed by 90 min of rest. We find that patching results in a shift in ocular dominance that can be measured using dichoptic surround suppression. However, we find no effect of exercise on the magnitude of this shift. We further performed a meta-analysis on the four studies that have examined the effects of exercise on the dominance shift. Looking across these studies, we find no evidence for such an effect.
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Phillips DJ, Edwin Dickinson J, Badcock DR. Eliminating brightness induction effects when measuring motion centre-surround suppression of contrast. Vision Res 2022; 201:108139. [PMID: 36319511 DOI: 10.1016/j.visres.2022.108139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 06/09/2022] [Accepted: 06/15/2022] [Indexed: 11/08/2022]
Abstract
The perceived contrast of a central stimulus is supressed when it is embedded in a higher contrast surround, centre-surround suppression of contrast. Local brightness induction effects between the two stimulus regions have been proposed to account for conflicting results when relative grating phases were different. Here, suppression and brightness induction effects are dissociated using a centre-surround arrangement with moving gratings. Four experienced observers were involved in experiments, utilising two-interval forced-choice contrast matching tasks. The stimuli were drifting sinusoidal grating patterns with surrounds (95% contrast) differing in direction of motion and orientation relative to the 40% contrast centre grating. First a 90°-phase-offset same direction surround condition was compared to both same direction (phase aligned) and opposing direction conditions. The reduction in the suppression for the phase-offset condition suggested a reduction in brightness induction influences. Then suppression was examined when surround directions varied and where phase was either fixed or randomised. For small changes in the motion direction between centre and surround (0° to 26.6°) the amount of brightness induction varied sinusoidally with the difference in phase introduced by the direction difference. Finally, the spatial separation between the centre and surround was varied to determine the reduction of suppression and brightness induction with increasing spatial distance. We found both fit an exponential decay function, with surround suppression producing the larger range of influence. Our findings quantify both brightness induction and suppression effects and validate the use of phase randomisation to remove effects of brightness induction when evaluating surround suppression.
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Affiliation(s)
- Daisy J Phillips
- School of Psychological Science, The University of Western Australia, Australia.
| | - J Edwin Dickinson
- School of Psychological Science, The University of Western Australia, Australia
| | - David R Badcock
- School of Psychological Science, The University of Western Australia, Australia
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Object Boundary Detection in Natural Images May Depend on "Incitatory" Cell-Cell Interactions. J Neurosci 2022; 42:8960-8979. [PMID: 36241385 PMCID: PMC9732833 DOI: 10.1523/jneurosci.2581-18.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 08/16/2022] [Accepted: 10/06/2022] [Indexed: 01/05/2023] Open
Abstract
Detecting object boundaries is crucial for recognition, but how the process unfolds in visual cortex remains unknown. To study the problem faced by a hypothetical boundary cell, and to predict how cortical circuitry could produce a boundary cell from a population of conventional "simple cells," we labeled 30,000 natural image patches and used Bayes' rule to help determine how a simple cell should influence a nearby boundary cell depending on its relative offset in receptive field position and orientation. We identified the following three basic types of cell-cell interactions: rising and falling interactions with a range of slopes and saturation rates, and nonmonotonic (bump-shaped) interactions with varying modes and amplitudes. Using simple models, we show that a ubiquitous cortical circuit motif consisting of direct excitation and indirect inhibition-a compound effect we call "incitation"-can produce the entire spectrum of simple cell-boundary cell interactions found in our dataset. Moreover, we show that the synaptic weights that parameterize an incitation circuit can be learned by a single-layer "delta" rule. We conclude that incitatory interconnections are a generally useful computing mechanism that the cortex may exploit to help solve difficult natural classification problems.SIGNIFICANCE STATEMENT Simple cells in primary visual cortex (V1) respond to oriented edges and have long been supposed to detect object boundaries, yet the prevailing model of a simple cell-a divisively normalized linear filter-is a surprisingly poor natural boundary detector. To understand why, we analyzed image statistics on and off object boundaries, allowing us to characterize the neural-style computations needed to perform well at this difficult natural classification task. We show that a simple circuit motif known to exist in V1 is capable of extracting high-quality boundary probability signals from local populations of simple cells. Our findings suggest a new, more general way of conceptualizing cell-cell interconnections in the cortex.
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Shen S, Jiang X, Scala F, Fu J, Fahey P, Kobak D, Tan Z, Zhou N, Reimer J, Sinz F, Tolias AS. Distinct organization of two cortico-cortical feedback pathways. Nat Commun 2022; 13:6389. [PMID: 36302912 PMCID: PMC9613627 DOI: 10.1038/s41467-022-33883-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 10/06/2022] [Indexed: 12/25/2022] Open
Abstract
Neocortical feedback is critical for attention, prediction, and learning. To mechanically understand its function requires deciphering its cell-type wiring. Recent studies revealed that feedback between primary motor to primary somatosensory areas in mice is disinhibitory, targeting vasoactive intestinal peptide-expressing interneurons, in addition to pyramidal cells. It is unknown whether this circuit motif represents a general cortico-cortical feedback organizing principle. Here we show that in contrast to this wiring rule, feedback between higher-order lateromedial visual area to primary visual cortex preferentially activates somatostatin-expressing interneurons. Functionally, both feedback circuits temporally sharpen feed-forward excitation eliciting a transient increase-followed by a prolonged decrease-in pyramidal cell activity under sustained feed-forward input. However, under feed-forward transient input, the primary motor to primary somatosensory cortex feedback facilitates bursting while lateromedial area to primary visual cortex feedback increases time precision. Our findings argue for multiple cortico-cortical feedback motifs implementing different dynamic non-linear operations.
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Affiliation(s)
- Shan Shen
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Xiaolong Jiang
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX, USA
| | - Federico Scala
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Jiakun Fu
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Paul Fahey
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Dmitry Kobak
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
| | - Zhenghuan Tan
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Na Zhou
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Reimer
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Fabian Sinz
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Bernstein Center for Computational Neuroscience, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Andreas S Tolias
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
- Department of Electrical and Computational Engineering, Rice University, Houston, TX, USA.
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Prakash SS, Mayo JP, Ray S. Decoding of attentional state using local field potentials. Curr Opin Neurobiol 2022; 76:102589. [PMID: 35751949 PMCID: PMC9840850 DOI: 10.1016/j.conb.2022.102589] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/17/2022] [Accepted: 05/18/2022] [Indexed: 01/18/2023]
Abstract
We review recent efforts to decode visual spatial attention from different types of brain signals, such as spikes and local field potentials (LFPs). Combining signals from more electrodes improves decoding, but the pattern of improvement varies considerably depending on the signal as well as the task (for example, decoding of sensory stimulus/motor intention versus location of attention). We argue that this pattern of results conveys important information not only about the usefulness of a particular brain signal for decoding attention, but also about the spatial scale over which attention operates in the brain. The spatial scale, in turn, likely depends on the extent of underlying mechanisms such as normalization, gain control via excitation-inhibition interactions, and neuromodulatory regulation of attention.
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Affiliation(s)
- Surya S. Prakash
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
| | - J. Patrick Mayo
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Supratim Ray
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
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Feng S, Cui Z, Han Z, Li H, Yu H. V1-Origin Bidirectional Plasticity in Visual Thalamo-Ventral Pathway and Its Contribution to Saliency Detection of Dynamic Visual Inputs. J Neurosci 2022; 42:6359-6379. [PMID: 35851327 PMCID: PMC9398546 DOI: 10.1523/jneurosci.0539-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/12/2022] [Accepted: 07/08/2022] [Indexed: 11/21/2022] Open
Abstract
Visual neural plasticity and V1 saliency detection are vital for efficient coding of dynamically changing visual inputs. However, how does neural plasticity contribute to saliency detection of temporal statistically distributed visual stream remains unclear. Therefore, we adopted randomly presented but unevenly distributed stimuli with multiple orientations and examined the single-unit responses evoked by this biased orientation-adaptation protocol by single-unit recordings in the visual thalamo-ventral pathway of cats (of either sex). We found neuronal responses potentiated when the probability of biased orientation was slightly higher than other nonbiased ones and suppressed when the probability became much higher. This single neuronal short-term bidirectional plasticity is selectively induced by optimal stimuli but is interocularly transferable. It is inducible in LGN, Area 17, and Area 21a with distinct and hierarchically progressive patterns. With the results of latency analysis, receptive field structural test, cortical lesion, and simulations, we suggest this bidirectional plasticity may principally originate from the adaptation competition between excitatory and inhibitory components of V1 neuronal receptive field. In our simulation, above bidirectional plasticity could achieve saliency detection of dynamic visual inputs. These findings demonstrate a rapid probability dependent plasticity on the neural coding of visual stream and suggest its functional role in the efficient coding and saliency detection of dynamic environment.SIGNIFICANCE STATEMENT Novel elements within a dynamic visual stream can pop up from the context, which is vital for rapid response to a dynamically changing world. Saliency detection is a promising bottom-up mechanism contributing to efficient selection of visual inputs, wherein visual adaptation also plays a significant role. However, the saliency detection of dynamic visual stream is poorly understood. Here, we found a novel form of visual short-term bidirectional plasticity in multistages of the visual system that contributes to saliency detection of dynamic visual inputs. This bidirectional plasticity may principally originate from the local balance of excitation inhibition in primary visual cortex and propagates to lower and higher visual areas with progressive pattern change. Our findings suggest the excitation-inhibition balance within the visual system contributes to visual efficient coding.
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Affiliation(s)
- Shang Feng
- School of Life Sciences, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Centre for Brain Science, Fudan University, Shanghai 200433, China
| | - Zhichang Cui
- School of Life Sciences, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Centre for Brain Science, Fudan University, Shanghai 200433, China
| | - Zhengqi Han
- School of Life Sciences, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Centre for Brain Science, Fudan University, Shanghai 200433, China
| | - Hongjian Li
- School of Life Sciences, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Centre for Brain Science, Fudan University, Shanghai 200433, China
| | - Hongbo Yu
- School of Life Sciences, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Centre for Brain Science, Fudan University, Shanghai 200433, China
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43
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Li Y, Wang T, Yang Y, Dai W, Wu Y, Li L, Han C, Zhong L, Li L, Wang G, Dou F, Xing D. Cascaded normalizations for spatial integration in the primary visual cortex of primates. Cell Rep 2022; 40:111221. [PMID: 35977486 DOI: 10.1016/j.celrep.2022.111221] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 04/19/2022] [Accepted: 07/25/2022] [Indexed: 11/03/2022] Open
Abstract
Spatial integration of visual information is an important function in the brain. However, neural computation for spatial integration in the visual cortex remains unclear. In this study, we recorded laminar responses in V1 of awake monkeys driven by visual stimuli with grating patches and annuli of different sizes. We find three important response properties related to spatial integration that are significantly different between input and output layers: neurons in output layers have stronger surround suppression, smaller receptive field (RF), and higher sensitivity to grating annuli partially covering their RFs. These interlaminar differences can be explained by a descriptive model composed of two global divisions (normalization) and a local subtraction. Our results suggest suppressions with cascaded normalizations (CNs) are essential for spatial integration and laminar processing in the visual cortex. Interestingly, the features of spatial integration in convolutional neural networks, especially in lower layers, are different from our findings in V1.
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Affiliation(s)
- Yang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, 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
| | - Yi Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lianfeng Li
- China Academy of Launch Vehicle Technology, Beijing 100076, China
| | - Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lvyan Zhong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Liang Li
- Beijing Institute of Basic Medical Sciences, Beijing 100005, China
| | - Gang Wang
- Beijing Institute of Basic Medical Sciences, Beijing 100005, China
| | - Fei Dou
- 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
| | - 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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Dual counterstream architecture may support separation between vision and predictions. Conscious Cogn 2022; 103:103375. [DOI: 10.1016/j.concog.2022.103375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 12/03/2021] [Accepted: 06/28/2022] [Indexed: 11/24/2022]
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Mir Y, Zalányi L, Pálfi E, Ashaber M, Roe AW, Friedman RM, Négyessy L. Modular Organization of Signal Transmission in Primate Somatosensory Cortex. Front Neuroanat 2022; 16:915238. [PMID: 35873660 PMCID: PMC9305200 DOI: 10.3389/fnana.2022.915238] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/03/2022] [Indexed: 12/30/2022] Open
Abstract
Axonal patches are known as the major sites of synaptic connections in the cerebral cortex of higher order mammals. However, the functional role of these patches is highly debated. Patches are formed by populations of nearby neurons in a topographic manner and are recognized as the termination fields of long-distance lateral connections within and between cortical areas. In addition, axons form numerous boutons that lie outside the patches, whose function is also unknown. To better understand the functional roles of these two distinct populations of boutons, we compared individual and collective morphological features of axons within and outside the patches of intra-areal, feedforward, and feedback pathways by way of tract tracing in the somatosensory cortex of New World monkeys. We found that, with the exception of tortuosity, which is an invariant property, bouton spacing and axonal convergence properties differ significantly between axons within patch and no-patch domains. Principal component analyses corroborated the clustering of axons according to patch formation without any additional effect by the type of pathway or laminar distribution. Stepwise logistic regression identified convergence and bouton density as the best predictors of patch formation. These findings support that patches are specific sites of axonal convergence that promote the synchronous activity of neuronal populations. On the other hand, no-patch domains could form a neuroanatomical substrate to diversify the responses of cortical neurons.
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Affiliation(s)
- Yaqub Mir
- Theoretical Neuroscience and Complex Systems Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
- *Correspondence: Yaqub Mir
| | - László Zalányi
- Theoretical Neuroscience and Complex Systems Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
| | - Emese Pálfi
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
| | - Mária Ashaber
- California Institute of Technology, Department of Biology and Biological Engineering, Pasadena, CA, United States
| | - Anna W. Roe
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
- Interdisciplinary Institute of Neuroscience and Technology, School of 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
| | - Robert M. Friedman
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | - László Négyessy
- Theoretical Neuroscience and Complex Systems Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
- László Négyessy
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Le Bec B, Troncoso XG, Desbois C, Passarelli Y, Baudot P, Monier C, Pananceau M, Frégnac Y. Horizontal connectivity in V1: Prediction of coherence in contour and motion integration. PLoS One 2022; 17:e0268351. [PMID: 35802625 PMCID: PMC9269411 DOI: 10.1371/journal.pone.0268351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 04/26/2022] [Indexed: 11/30/2022] Open
Abstract
This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150–250°/s when it matches the propagation speed of horizontal connectivity (0.15–0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal “prediction” wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.
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Affiliation(s)
- Benoit Le Bec
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Xoana G. Troncoso
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Christophe Desbois
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
- Ecole Nationale Vétérinaire d’Alfort, Maisons-Alfort, France
| | - Yannick Passarelli
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Pierre Baudot
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Cyril Monier
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Marc Pananceau
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Yves Frégnac
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
- * E-mail:
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Barthélemy FV, Fleuriet J, Perrinet LU, Masson GS. A behavioral receptive field for ocular following in monkeys: Spatial summation and its spatial frequency tuning. eNeuro 2022; 9:ENEURO.0374-21.2022. [PMID: 35760525 PMCID: PMC9275147 DOI: 10.1523/eneuro.0374-21.2022] [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: 09/14/2021] [Revised: 06/13/2022] [Accepted: 06/16/2022] [Indexed: 11/21/2022] Open
Abstract
In human and non-human primates, reflexive tracking eye movements can be initiated at very short latency in response to a rapid shift of the image. Previous studies in humans have shown that only a part of the central visual field is optimal for driving ocular following responses. Herein, we have investigated spatial summation of motion information across a wide range of spatial frequencies and speeds of drifting gratings by recording short-latency ocular following responses in macaque monkeys. We show that optimal stimulus size for driving ocular responses cover a small (<20° diameter), central part of the visual field that shrinks with higher spatial frequency. This signature of linear motion integration remains invariant with speed and temporal frequency. For low and medium spatial frequencies, we found a strong suppressive influence from surround motion, evidenced by a decrease of response amplitude for stimulus sizes larger than optimal. Such suppression disappears with gratings at high frequencies. The contribution of peripheral motion was investigated by presenting grating annuli of increasing eccentricity. We observed an exponential decay of response amplitude with grating eccentricity, the decrease being faster for higher spatial frequencies. Weaker surround suppression can thus be explained by sparser eccentric inputs at high frequencies. A Difference-of-Gaussians model best renders the antagonistic contributions of peripheral and central motions. Its best-fit parameters coincide with several, well-known spatial properties of area MT neuronal populations. These results describe the mechanism by which central motion information is automatically integrated in a context-dependent manner to drive ocular responses.Significance statementOcular following is driven by visual motion at ultra-short latency in both humans and monkeys. Its dynamics reflect the properties of low-level motion integration. Here, we show that a strong center-surround suppression mechanism modulates initial eye velocity. Its spatial properties are dependent upon visual inputs' spatial frequency but are insensitive to either its temporal frequency or speed. These properties are best described with a Difference-of-Gaussian model of spatial integration. The model parameters reflect many spatial characteristics of motion sensitive neuronal populations in monkey area MT. Our results further outline the computational properties of the behavioral receptive field underpinning automatic, context-dependent motion integration.
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Affiliation(s)
- Frédéric V Barthélemy
- Institut de Neurosciences de la Timone, UMR7289, CNRS & Aix-Marseille Université, 13385 Marseille, France
| | - Jérome Fleuriet
- Institut de Neurosciences de la Timone, UMR7289, CNRS & Aix-Marseille Université, 13385 Marseille, France
- Assistance Publique-Hôpitaux de Paris, Intensive Care Unit, Raymond Poincaré Hospital, Garches, France
| | - Laurent U Perrinet
- Institut de Neurosciences de la Timone, UMR7289, CNRS & Aix-Marseille Université, 13385 Marseille, France
| | - Guillaume S Masson
- Institut de Neurosciences de la Timone, UMR7289, CNRS & Aix-Marseille Université, 13385 Marseille, France
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48
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Accurate Fish Detection under Marine Background Noise Based on the Retinex Enhancement Algorithm and CNN. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10070878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Underwater detection equipment with fish detection technology has broad application prospects in marine fishery resources exploration and conservation. In this paper, we establish a multi-scale retinex enhancement algorithm and a multi-scale feature-based fish detection model to improve underwater detection accuracy and ensure real-time performance. During image preprocessing, the enhancement algorithm combines the bionic structure of the fish retina and classical retinex theory to filter out underwater environmental noise. The detection model focuses on improving the detection performance on small-size targets using a deep learning method based on a convolutional neural network. We compare our method to current mainstream detection models (Faster R-CNN, RetinaNet, YOLO, SSDetc.), and the proposed model achieves better performance, with a mean Average Precision (mAP) of 78.31% and a mean Miss Rate (mMR) of 54.11% in the open fish image data set. The test results for the data from the field experiment prove the feasibility and stability of our model.
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Kınıklıoğlu M, Boyaci H. Increasing the spatial extent of attention strengthens surround suppression. Vision Res 2022; 199:108074. [PMID: 35717748 DOI: 10.1016/j.visres.2022.108074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 04/20/2022] [Accepted: 04/27/2022] [Indexed: 10/18/2022]
Abstract
Here we investigate how the extent of spatial attention affects center-surround interaction in visual motion processing. To do so, we measured motion direction discrimination thresholds in humans using drifting gratings and two attention conditions. Participants were instructed to limit their attention to the central part of the stimulus under the narrow attention condition, and to both central and surround parts under the wide attention condition. We found stronger surround suppression under the wide attention condition. The magnitude of the attention effect increased with the size of the surround when the stimulus had low contrast, but did not change when it had high contrast. Results also showed that attention had a weaker effect when the center and surround gratings drifted in opposite directions. Next, to establish a link between the behavioral results and the neuronal response characteristics, we performed computer simulations using the divisive normalization model. Our simulations showed that using smaller versus larger multiplicative attentional gain and parameters derived from the medial temporal (MT) area of the cortex, the model can successfully predict the observed behavioral results. These findings reveal the critical role of spatial attention on surround suppression and establish a link between neuronal activity and behavior. Further, these results also suggest that the reduced surround suppression found in certain clinical disorders (e.g., schizophrenia and autism spectrum disorder) may be caused by abnormal attention mechanisms.
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Affiliation(s)
- Merve Kınıklıoğlu
- Interdisciplinary Neuroscience Program, Bilkent University, Ankara 06800, Turkey; Aysel Sabuncu Brain Research Center & National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara 06800, Turkey.
| | - Huseyin Boyaci
- Interdisciplinary Neuroscience Program, Bilkent University, Ankara 06800, Turkey; Aysel Sabuncu Brain Research Center & National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara 06800, Turkey; Department of Psychology, Bilkent University, Ankara 06800, Turkey; Department of Psychology, Justus Liebig University Giessen, Giessen, Germany.
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Shirhatti V, Ravishankar P, Ray S. Gamma oscillations in primate primary visual cortex are severely attenuated by small stimulus discontinuities. PLoS Biol 2022; 20:e3001666. [PMID: 35700175 PMCID: PMC9197048 DOI: 10.1371/journal.pbio.3001666] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/10/2022] [Indexed: 11/22/2022] Open
Abstract
Gamma oscillations (30 to 80 Hz) have been hypothesized to play an important role in feature binding, based on the observation that continuous long bars induce stronger gamma in the visual cortex than bars with a small gap. Recently, many studies have shown that natural images, which have discontinuities in several low-level features, do not induce strong gamma oscillations, questioning their role in feature binding. However, the effect of different discontinuities on gamma has not been well studied. To address this, we recorded spikes and local field potential from 2 monkeys while they were shown gratings with discontinuities in 4 attributes: space, orientation, phase, or contrast. We found that while these discontinuities only had a modest effect on spiking activity, gamma power drastically reduced in all cases, suggesting that gamma could be a resonant phenomenon. An excitatory–inhibitory population model with stimulus-tuned recurrent inputs showed such resonant properties. Therefore, gamma could be a signature of excitation–inhibition balance, which gets disrupted due to discontinuities. Gamma oscillations (30-80 Hz) in visual cortex have been hypothesized to play an important role in feature binding, but this role has recently been questioned. This study shows that visual stimulus-induced gamma oscillations are highly attenuated with even small discontinuities in the stimulus. This "resonant" behaviour can be explained by a simple excitatory-inhibitory model in which discontinuities lead to a small reduction in lateral inputs.
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Affiliation(s)
- Vinay Shirhatti
- Centre for Neuroscience, Indian Institute of Science, Bengaluru, India
- IISc Mathematics Initiative, Indian Institute of Science, Bengaluru, India
| | | | - Supratim Ray
- Centre for Neuroscience, Indian Institute of Science, Bengaluru, India
- IISc Mathematics Initiative, Indian Institute of Science, Bengaluru, India
- * E-mail:
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