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Song X, Guo T, Ma S, Zhou F, Tian J, Liu Z, Liu J, Li H, Chen Y, Chai X, Li L. Spatially Selective Retinal Ganglion Cell Activation Using Low Invasive Extraocular Temporal Interference Stimulation. Int J Neural Syst 2024:2450066. [PMID: 39318031 DOI: 10.1142/s0129065724500667] [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: 09/26/2024]
Abstract
Conventional retinal implants involve complex surgical procedures and require invasive implantation. Temporal Interference Stimulation (TIS) has achieved noninvasive and focused stimulation of deep brain regions by delivering high-frequency currents with small frequency differences on multiple electrodes. In this study, we conducted in silico investigations to evaluate extraocular TIS's potential as a novel visual restoration approach. Different from the previously published retinal TIS model, the new model of extraocular TIS incorporated a biophysically detailed retinal ganglion cell (RGC) population, enabling a more accurate simulation of retinal outputs under electrical stimulation. Using this improved model, we made the following major discoveries: (1) the maximum value of TIS envelope electric potential ([Formula: see text] showed a strong correlation with TIS-induced RGC activation; (2) the preferred stimulating/return electrode (SE/RE) locations to achieve focalized TIS were predicted; (3) the performance of extraocular TIS was better than same-frequency sinusoidal stimulation (SSS) in terms of lower RGC threshold and more focused RGC activation; (4) the optimal stimulation parameters to achieve lower threshold and focused activation were identified; and (5) spatial selectivity of TIS could be improved by integrating current steering strategy and reducing electrode size. This study provides insights into the feasibility and effectiveness of a low-invasive stimulation approach in enhancing vision restoration.
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Affiliation(s)
- Xiaoyu Song
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Saidong Ma
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Feng Zhou
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Jiaxin Tian
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Zhengyang Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Jiao Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Heng Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Yao Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Xinyu Chai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
| | - Liming Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
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2
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He L, Wang W, Ma L, Huang T. Optimization-Based Pairwise Interaction Point Process (O-PIPP): A Precise and Universal Retinal Mosaic Modeling Approach. Invest Ophthalmol Vis Sci 2024; 65:39. [PMID: 39042401 PMCID: PMC11268446 DOI: 10.1167/iovs.65.8.39] [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: 09/05/2023] [Accepted: 06/25/2024] [Indexed: 07/24/2024] Open
Abstract
Purpose A retinal mosaic, the spatial organization of a population of homotypic neurons, is thought to sample a specific visual feature into the feedforward visual pathway. The purpose of this study was to propose a universal modeling approach for precisely generating retinal mosaics and overcoming the limitations of previous models, especially in modeling abnormal mosaic patterns under disease conditions. Methods Here, we developed the optimization-based pairwise interaction point process (O-PIPP). It incorporates optimization techniques into previous simulation approaches, enabling directional control of the simulation process according to the user-designed optimization target. For the convenience of the community, we implemented the O-PIPP approach into a Python package and a website application. Results We showed that the O-PIPP can generate more precise neural spatial patterns of healthy and diseased mosaics compared to previous phenomenological approaches. Notably, through modeling the retinal neural circuitry with O-PIPP-simulated retinitis pigmentosa cone mosaics, we elucidated how the cone mosaic rearrangement impacted the information processing of ganglion cells. Conclusions The O-PIPP provides a precise and universal tool to simulate realistic mosaics, which could help to investigate the function of retinal mosaics in vision.
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Affiliation(s)
- Liuyuan He
- National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Wenyao Wang
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Lei Ma
- National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Tiejun Huang
- National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
- Beijing Academy of Artificial Intelligence, Beijing, China
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3
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Baden T. The vertebrate retina: a window into the evolution of computation in the brain. Curr Opin Behav Sci 2024; 57:None. [PMID: 38899158 PMCID: PMC11183302 DOI: 10.1016/j.cobeha.2024.101391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 03/14/2024] [Accepted: 03/24/2024] [Indexed: 06/21/2024]
Abstract
Animal brains are probably the most complex computational machines on our planet, and like everything in biology, they are the product of evolution. Advances in developmental and palaeobiology have been expanding our general understanding of how nervous systems can change at a molecular and structural level. However, how these changes translate into altered function - that is, into 'computation' - remains comparatively sparsely explored. What, concretely, does it mean for neuronal computation when neurons change their morphology and connectivity, when new neurons appear or old ones disappear, or when transmitter systems are slowly modified over many generations? And how does evolution use these many possible knobs and dials to constantly tune computation to give rise to the amazing diversity in animal behaviours we see today? Addressing these major gaps of understanding benefits from choosing a suitable model system. Here, I present the vertebrate retina as one perhaps unusually promising candidate. The retina is ancient and displays highly conserved core organisational principles across the entire vertebrate lineage, alongside a myriad of adjustments across extant species that were shaped by the history of their visual ecology. Moreover, the computational logic of the retina is readily interrogated experimentally, and our existing understanding of retinal circuits in a handful of species can serve as an anchor when exploring the visual circuit adaptations across the entire vertebrate tree of life, from fish deep in the aphotic zone of the oceans to eagles soaring high up in the sky.
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Seifert M, Roberts PA, Kafetzis G, Osorio D, Baden T. Birds multiplex spectral and temporal visual information via retinal On- and Off-channels. Nat Commun 2023; 14:5308. [PMID: 37652912 PMCID: PMC10471707 DOI: 10.1038/s41467-023-41032-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 08/18/2023] [Indexed: 09/02/2023] Open
Abstract
In vertebrate vision, early retinal circuits divide incoming visual information into functionally opposite elementary signals: On and Off, transient and sustained, chromatic and achromatic. Together these signals can yield an efficient representation of the scene for transmission to the brain via the optic nerve. However, this long-standing interpretation of retinal function is based on mammals, and it is unclear whether this functional arrangement is common to all vertebrates. Here we show that male poultry chicks use a fundamentally different strategy to communicate information from the eye to the brain. Rather than using functionally opposite pairs of retinal output channels, chicks encode the polarity, timing, and spectral composition of visual stimuli in a highly correlated manner: fast achromatic information is encoded by Off-circuits, and slow chromatic information overwhelmingly by On-circuits. Moreover, most retinal output channels combine On- and Off-circuits to simultaneously encode, or multiplex, both achromatic and chromatic information. Our results from birds conform to evidence from fish, amphibians, and reptiles which retain the full ancestral complement of four spectral types of cone photoreceptors.
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Affiliation(s)
- Marvin Seifert
- School of Life Sciences, University of Sussex, Brighton, UK.
| | - Paul A Roberts
- School of Life Sciences, University of Sussex, Brighton, UK
| | | | - Daniel Osorio
- School of Life Sciences, University of Sussex, Brighton, UK.
| | - Tom Baden
- School of Life Sciences, University of Sussex, Brighton, UK.
- Institute of Ophthalmic Research, University of Tübingen, Tübingen, Germany.
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5
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Qiu Y, Klindt DA, Szatko KP, Gonschorek D, Hoefling L, Schubert T, Busse L, Bethge M, Euler T. Efficient coding of natural scenes improves neural system identification. PLoS Comput Biol 2023; 19:e1011037. [PMID: 37093861 PMCID: PMC10159360 DOI: 10.1371/journal.pcbi.1011037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/04/2023] [Accepted: 03/20/2023] [Indexed: 04/25/2023] Open
Abstract
Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically plausible filters, meaning that they more closely resembled neural representation in early visual systems. We found these results applied to retinal responses to different artificial stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. The benefit of natural scene statistics became marginal, however, for predicting the responses to natural movies. In summary, our results indicate that efficiently encoding environmental inputs can improve system identification models, at least for noise stimuli, and point to the benefit of probing the visual system with naturalistic stimuli.
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Affiliation(s)
- Yongrong Qiu
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Graduate Training Centre of Neuroscience (GTC), International Max Planck Research School, U Tübingen, Tübingen, Germany
| | - David A Klindt
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Klaudia P Szatko
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Graduate Training Centre of Neuroscience (GTC), International Max Planck Research School, U Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience, Tübingen, Germany
| | - Dominic Gonschorek
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Research Training Group 2381, U Tübingen, Tübingen, Germany
| | - Larissa Hoefling
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience, Tübingen, Germany
| | - Timm Schubert
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
| | - Laura Busse
- Division of Neurobiology, Faculty of Biology, LMU Munich, Planegg-Martinsried, Germany
- Bernstein Center for Computational Neuroscience, Planegg-Martinsried, Germany
| | - Matthias Bethge
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience, Tübingen, Germany
- Institute for Theoretical Physics, U Tübingen, Tübingen, Germany
| | - Thomas Euler
- Institute for Ophthalmic Research, U Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), U Tübingen, Tübingen, Germany
- Bernstein Center for Computational Neuroscience, Tübingen, Germany
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6
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Roy S, Wang D, Rudzite AM, Perry B, Scalabrino ML, Thapa M, Gong Y, Sher A, Field GD. Large-scale interrogation of retinal cell functions by 1-photon light-sheet microscopy. CELL REPORTS METHODS 2023; 3:100453. [PMID: 37159670 PMCID: PMC10163030 DOI: 10.1016/j.crmeth.2023.100453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/05/2023] [Accepted: 03/24/2023] [Indexed: 05/11/2023]
Abstract
Visual processing in the retina depends on the collective activity of large ensembles of neurons organized in different layers. Current techniques for measuring activity of layer-specific neural ensembles rely on expensive pulsed infrared lasers to drive 2-photon activation of calcium-dependent fluorescent reporters. We present a 1-photon light-sheet imaging system that can measure the activity in hundreds of neurons in the ex vivo retina over a large field of view while presenting visual stimuli. This allows for a reliable functional classification of different retinal cell types. We also demonstrate that the system has sufficient resolution to image calcium entry at individual synaptic release sites across the axon terminals of dozens of simultaneously imaged bipolar cells. The simple design, large field of view, and fast image acquisition make this a powerful system for high-throughput and high-resolution measurements of retinal processing at a fraction of the cost of alternative approaches.
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Affiliation(s)
- Suva Roy
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Depeng Wang
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Andra M. Rudzite
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Benjamin Perry
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Miranda L. Scalabrino
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
- Stein Eye Institute, Department of Ophthalmology, University of California, Los Angeles, Los Angeles, CA 90024, USA
| | - Mishek Thapa
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
- Stein Eye Institute, Department of Ophthalmology, University of California, Los Angeles, Los Angeles, CA 90024, USA
| | - Yiyang Gong
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Greg D. Field
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
- Stein Eye Institute, Department of Ophthalmology, University of California, Los Angeles, Los Angeles, CA 90024, USA
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7
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de Montigny J, Sernagor E, Bauer R. Retinal self-organization: a model of retinal ganglion cells and starburst amacrine cells mosaic formation. Open Biol 2023; 13:220217. [PMID: 37015288 PMCID: PMC10072945 DOI: 10.1098/rsob.220217] [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: 04/06/2023] Open
Abstract
Individual retinal cell types exhibit semi-regular spatial patterns called retinal mosaics. Retinal ganglion cells (RGCs) and starburst amacrine cells (SACs) are known to exhibit such layouts. Mechanisms responsible for the formation of mosaics are not well understood but follow three main principles: (i) homotypic cells prevent nearby cells from adopting the same type, (ii) cell tangential migration and (iii) cell death. Alongside experiments in mouse, we use BioDynaMo, an agent-based simulation framework, to build a detailed and mechanistic model of mosaic formation. We investigate the implications of the three theories for RGC's mosaic formation. We report that the cell migration mechanism yields the most regular mosaics. In addition, we propose that low-density RGC type mosaics exhibit on average low regularities, and thus we question the relevance of regular spacing as a criterion for a group of RGCs to form a RGC type. We investigate SAC mosaics formation and interactions between the ganglion cell layer (GCL) and inner nuclear layer (INL) populations. We propose that homotypic interactions between the GCL and INL populations during mosaics creation are required to reproduce the observed SAC mosaics' characteristics. This suggests that the GCL and INL populations of SACs might not be independent during retinal development.
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Affiliation(s)
- Jean de Montigny
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Evelyne Sernagor
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Roman Bauer
- Department of Computer Science, University of Surrey, Guildford GU2 7XH, UK
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8
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Gupta D, Młynarski W, Sumser A, Symonova O, Svatoň J, Joesch M. Panoramic visual statistics shape retina-wide organization of receptive fields. Nat Neurosci 2023; 26:606-614. [PMID: 36959418 PMCID: PMC10076217 DOI: 10.1038/s41593-023-01280-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 02/14/2023] [Indexed: 03/25/2023]
Abstract
Statistics of natural scenes are not uniform-their structure varies dramatically from ground to sky. It remains unknown whether these nonuniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. Using the mouse (Mus musculus) as a model species, we show that receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon, in agreement with our predictions. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell types.
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Affiliation(s)
- Divyansh Gupta
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Wiktor Młynarski
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Anton Sumser
- Institute of Science and Technology Austria, Klosterneuburg, Austria
- Division of Neuroscience, Faculty of Biology, LMU, Munich, Germany
| | - Olga Symonova
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Jan Svatoň
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Maximilian Joesch
- Institute of Science and Technology Austria, Klosterneuburg, Austria.
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9
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Tring E, Ringach DL. Thalamocortical boutons cluster by ON/OFF responses in mouse primary visual cortex. J Neurophysiol 2023; 129:184-190. [PMID: 36515419 PMCID: PMC9844974 DOI: 10.1152/jn.00412.2022] [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: 09/27/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/15/2022] Open
Abstract
In higher mammals, the thalamic afferents to primary visual cortex cluster according to their responses to increases (ON) or decreases (OFF) in luminance. This feature of thalamocortical wiring is thought to create columnar, ON/OFF domains in V1. We have recently shown that mice also have ON/OFF cortical domains, but the organization of their thalamic afferents remains unknown. Here we measured the visual responses of thalamocortical boutons with two-photon imaging and found that they also cluster in space according to ON/OFF responses. Moreover, fluctuations in the relative density of ON/OFF boutons mirror fluctuations in the relative density of ON/OFF receptive field positions on the visual field. These findings indicate a segregation of ON/OFF signals already present in the thalamic input. We propose that ON/OFF clustering may reflect the spatial distribution of ON/OFF responses in retinal ganglion cell mosaics.NEW & NOTEWORTHY Neurons in primary visual cortex cluster into ON and OFF domains, which have been shown to be linked to the organization of receptive fields and cortical maps. Here we show that in the mouse such clustering is already present in the geniculate input, suggesting that the cortical architecture may be shaped by the representation of ON/OFF signals in the thalamus and the retina.
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Affiliation(s)
- Elaine Tring
- Department of Neurobiology, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Dario L Ringach
- Department of Neurobiology, David Geffen School of Medicine, UCLA, Los Angeles, California
- Department of Psychology, UCLA, Los Angeles, California
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10
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Sibille J, Gehr C, Benichov JI, Balasubramanian H, Teh KL, Lupashina T, Vallentin D, Kremkow J. High-density electrode recordings reveal strong and specific connections between retinal ganglion cells and midbrain neurons. Nat Commun 2022; 13:5218. [PMID: 36064789 PMCID: PMC9445019 DOI: 10.1038/s41467-022-32775-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 08/16/2022] [Indexed: 11/29/2022] Open
Abstract
The superior colliculus is a midbrain structure that plays important roles in visually guided behaviors in mammals. Neurons in the superior colliculus receive inputs from retinal ganglion cells but how these inputs are integrated in vivo is unknown. Here, we discovered that high-density electrodes simultaneously capture the activity of retinal axons and their postsynaptic target neurons in the superior colliculus, in vivo. We show that retinal ganglion cell axons in the mouse provide a single cell precise representation of the retina as input to superior colliculus. This isomorphic mapping builds the scaffold for precise retinotopic wiring and functionally specific connection strength. Our methods are broadly applicable, which we demonstrate by recording retinal inputs in the optic tectum in zebra finches. We find common wiring rules in mice and zebra finches that provide a precise representation of the visual world encoded in retinal ganglion cells connections to neurons in retinorecipient areas.
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Affiliation(s)
- Jérémie Sibille
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Carolin Gehr
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Jonathan I Benichov
- Max Planck Institute for Ornithology, Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
- Max Planck Institute for Biological Intelligence (in foundation), Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
| | - Hymavathy Balasubramanian
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Kai Lun Teh
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Tatiana Lupashina
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Daniela Vallentin
- Max Planck Institute for Ornithology, Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
- Max Planck Institute for Biological Intelligence (in foundation), Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
| | - Jens Kremkow
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany.
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany.
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany.
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11
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Abstract
An ultimate goal in retina science is to understand how the neural circuit of the retina processes natural visual scenes. Yet most studies in laboratories have long been performed with simple, artificial visual stimuli such as full-field illumination, spots of light, or gratings. The underlying assumption is that the features of the retina thus identified carry over to the more complex scenario of natural scenes. As the application of corresponding natural settings is becoming more commonplace in experimental investigations, this assumption is being put to the test and opportunities arise to discover processing features that are triggered by specific aspects of natural scenes. Here, we review how natural stimuli have been used to probe, refine, and complement knowledge accumulated under simplified stimuli, and we discuss challenges and opportunities along the way toward a comprehensive understanding of the encoding of natural scenes. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Dimokratis Karamanlis
- Department of Ophthalmology, University Medical Center Göttingen, Göttingen, Germany.,Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.,International Max Planck Research School for Neurosciences, Göttingen, Germany
| | - Helene Marianne Schreyer
- Department of Ophthalmology, University Medical Center Göttingen, Göttingen, Germany.,Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany
| | - Tim Gollisch
- Department of Ophthalmology, University Medical Center Göttingen, Göttingen, Germany.,Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.,Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), University of Göttingen, Göttingen, Germany
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12
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Westö J, Martyniuk N, Koskela S, Turunen T, Pentikäinen S, Ala-Laurila P. Retinal OFF ganglion cells allow detection of quantal shadows at starlight. Curr Biol 2022; 32:2848-2857.e6. [PMID: 35609606 DOI: 10.1016/j.cub.2022.04.092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 04/01/2022] [Accepted: 04/28/2022] [Indexed: 02/01/2023]
Abstract
Perception of light in darkness requires no more than a handful of photons, and this remarkable behavioral performance can be directly linked to a particular retinal circuit-the retinal ON pathway. However, the neural limits of shadow detection in very dim light have remained unresolved. Here, we unravel the neural mechanisms that determine the sensitivity of mice (CBA/CaJ) to light decrements at the lowest light levels by measuring signals from the most sensitive ON and OFF retinal ganglion cell types and by correlating their signals with visually guided behavior. We show that mice can detect shadows when only a few photon absorptions are missing among thousands of rods. Behavioral detection of such "quantal" shadows relies on the retinal OFF pathway and is limited by noise and loss of single-photon signals in retinal processing. Thus, in the dim-light regime, light increments and decrements are encoded separately via the ON and OFF retinal pathways, respectively.
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Affiliation(s)
- Johan Westö
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland
| | - Nataliia Martyniuk
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland
| | - Sanna Koskela
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Biosciences Research Programme, University of Helsinki, 00790 Helsinki, Finland
| | - Tuomas Turunen
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland
| | - Santtu Pentikäinen
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Biosciences Research Programme, University of Helsinki, 00790 Helsinki, Finland
| | - Petri Ala-Laurila
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland; Faculty of Biological and Environmental Sciences, Molecular and Integrative Biosciences Research Programme, University of Helsinki, 00790 Helsinki, Finland.
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13
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Najafian S, Koch E, Teh KL, Jin J, Rahimi-Nasrabadi H, Zaidi Q, Kremkow J, Alonso JM. A theory of cortical map formation in the visual brain. Nat Commun 2022; 13:2303. [PMID: 35484133 PMCID: PMC9050665 DOI: 10.1038/s41467-022-29433-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 03/16/2022] [Indexed: 11/11/2022] Open
Abstract
The cerebral cortex receives multiple afferents from the thalamus that segregate by stimulus modality forming cortical maps for each sense. In vision, the primary visual cortex maps the multiple dimensions of the visual stimulus in patterns that vary across species for reasons unknown. Here we introduce a general theory of cortical map formation, which proposes that map diversity emerges from species variations in the thalamic afferent density sampling sensory space. In the theory, increasing afferent sampling density enlarges the cortical domains representing the same visual point, allowing the segregation of afferents and cortical targets by multiple stimulus dimensions. We illustrate the theory with an afferent-density model that accurately replicates the maps of different species through afferent segregation followed by thalamocortical convergence pruned by visual experience. Because thalamocortical pathways use similar mechanisms for axon segregation and pruning, the theory may extend to other sensory areas of the mammalian brain.
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Affiliation(s)
- Sohrab Najafian
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States
| | - Erin Koch
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA, 91125, United States
| | - Kai Lun Teh
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
| | - Jianzhong Jin
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States
| | - Hamed Rahimi-Nasrabadi
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States
| | - Qasim Zaidi
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States
| | - Jens Kremkow
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
| | - Jose-Manuel Alonso
- Department of Biological and Visual Sciences, SUNY College of Optometry, New York, NY, 10036, United States.
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14
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Zhang LQ, Stocker AA. Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT. J Neurosci 2022; 42:2951-2962. [PMID: 35169018 PMCID: PMC8985856 DOI: 10.1523/jneurosci.1920-21.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 11/21/2022] Open
Abstract
Bayesian inference provides an elegant theoretical framework for understanding the characteristic biases and discrimination thresholds in visual speed perception. However, the framework is difficult to validate because of its flexibility and the fact that suitable constraints on the structure of the sensory uncertainty have been missing. Here, we demonstrate that a Bayesian observer model constrained by efficient coding not only well explains human visual speed perception but also provides an accurate quantitative account of the tuning characteristics of neurons known for representing visual speed. Specifically, we found that the population coding accuracy for visual speed in area MT ("neural prior") is precisely predicted by the power-law, slow-speed prior extracted from fitting the Bayesian observer model to psychophysical data ("behavioral prior") to the point that the two priors are indistinguishable in a cross-validation model comparison. Our results demonstrate a quantitative validation of the Bayesian observer model constrained by efficient coding at both the behavioral and neural levels.SIGNIFICANCE STATEMENT Statistical regularities of the environment play an important role in shaping both neural representations and perceptual behavior. Most previous work addressed these two aspects independently. Here we present a quantitative validation of a theoretical framework that makes joint predictions for neural coding and behavior, based on the assumption that neural representations of sensory information are efficient but also optimally used in generating a percept. Specifically, we demonstrate that the neural tuning characteristics for visual speed in brain area MT are precisely predicted by the statistical prior expectations extracted from psychophysical data. As such, our results provide a normative link between perceptual behavior and the neural representation of sensory information in the brain.
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15
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Skyberg R, Tanabe S, Chen H, Cang J. Coarse-to-fine processing drives the efficient coding of natural scenes in mouse visual cortex. Cell Rep 2022; 38:110606. [PMID: 35354030 PMCID: PMC9189856 DOI: 10.1016/j.celrep.2022.110606] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/07/2022] [Accepted: 03/10/2022] [Indexed: 12/01/2022] Open
Abstract
The visual system processes sensory inputs sequentially, perceiving coarse information before fine details. Here we study the neural basis of coarse-to-fine processing and its computational benefits in natural vision. We find that primary visual cortical neurons in awake mice respond to natural scenes in a coarse-to-fine manner, primarily driven by individual neurons rapidly shifting their spatial frequency preference from low to high over a brief response period. This shift transforms the population response in a way that counteracts the statistical regularities of natural scenes, thereby reducing redundancy and generating a more efficient neural representation. The increase in representational efficiency does not occur in either dark-reared or anesthetized mice, which show significantly attenuated coarse-to-fine spatial processing. Collectively, these results illustrate that coarse-to-fine processing is state dependent, develops postnatally via visual experience, and provides a computational advantage by generating more efficient representations of the complex spatial statistics of ethologically relevant natural scenes. Skyberg et al. show that the visual cortex of mice processes natural scenes in a coarse-to-fine manner, driven by individual neuron’s temporal dynamics. These response dynamics, which require visual experience to develop, reduce redundancy in the neural code and lead to more efficient representations of complex visual stimuli.
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Affiliation(s)
- Rolf Skyberg
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA
| | - Seiji Tanabe
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA
| | - Hui Chen
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA
| | - Jianhua Cang
- Department of Biology and Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA.
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16
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Song X, Qiu S, Shivdasani MN, Zhou F, Liu Z, Ma S, Chai X, Chen Y, Cai X, Guo T, Li L. An in-silico analysis of electrically-evoked responses of midget and parasol retinal ganglion cells in different retinal regions. J Neural Eng 2022; 19. [PMID: 35255486 DOI: 10.1088/1741-2552/ac5b18] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 03/07/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Visual outcomes provided by present retinal prostheses that primarily target retinal ganglion cells (RGCs) through epiretinal stimulation remain rudimentary, partly due to the limited knowledge of retinal responses under electrical stimulation. Better understanding of how different retinal regions can be quantitatively controlled with high spatial accuracy, will be beneficial to the design of micro-electrode arrays (MEAs) and stimulation strategies for next-generation wide-view, high-resolution epiretinal implants. METHODS A computational model was developed to assess neural activity at different eccentricities (2 mm and 5 mm) within the human retina. This model included midget and parasol RGCs with anatomically accurate cell distribution and cell-specific morphological information. We then performed in silico investigations of region-specific RGC responses to epiretinal electrical stimulation using varied electrode sizes (5 µm - 210 µm diameter), emulating both commercialized retinal implants and recently-developed prototype devices. RESULTS Our model of epiretinal stimulation predicted RGC population excitation analogous to the complex percepts reported in human subjects. Following this, our simulations suggest that midget and parasol RGCs have characteristic regional differences in excitation under preferred electrode sizes. Relatively central (2 mm) regions demonstrated higher number of excited RGCs but lower overall activated receptive field (RF) areas under the same stimulus amplitudes (two-way ANOVA, p < 0.05). Furthermore, the activated RGC numbers per unit active RF area (number-RF ratio) were significantly higher in central than in peripheral regions, and higher in the midget than in the parasol population under all tested electrode sizes (two-way ANOVA, p < 0.05). Our simulations also suggested that smaller electrodes exhibit a higher range of controllable stimulation parameters to achieve pre-defined performance of RGC excitation. ..
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Affiliation(s)
- Xiaoyu Song
- , Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
| | - Shirong Qiu
- Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
| | - Mohit N Shivdasani
- Graduate School of Biomedical Engineering, University of New South Wales, Lower Ground, Samuels Building (F25), Kensington, New South Wales, 2052, AUSTRALIA
| | - Feng Zhou
- Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
| | - Zhengyang Liu
- Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
| | - Saidong Ma
- Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
| | - Xinyu Chai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, Shanghai, 200240, CHINA
| | - Yao Chen
- Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200040, Shanghai, 200240, CHINA
| | - Xuan Cai
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, Shanghai, 200233, CHINA
| | - Tianruo Guo
- the University of New South Wales, Lower Ground, Samuels Building (F25), Sydney, 2052, AUSTRALIA
| | - Liming Li
- Shanghai Jiao Tong University, Dongchuan Road, Shanghai Minhang District No. 800, Shanghai, 200240, CHINA
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17
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Do MTH. Individual variations of visual information. Neuron 2022; 110:564-565. [PMID: 35176239 DOI: 10.1016/j.neuron.2022.01.024] [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] [Indexed: 01/12/2023]
Abstract
In this issue of Neuron, Shah et al. reveal that coding of visual space by the primate retina varies across individuals and sexes. A computational model provides insight into themes and variations of coding. Implications for sight restoration are explored.
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Affiliation(s)
- Michael Tri H Do
- F.M. Kirby Neurobiology Center, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, USA.
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18
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Dendro-somatic synaptic inputs to ganglion cells contradict receptive field and connectivity conventions in the mammalian retina. Curr Biol 2022; 32:315-328.e4. [PMID: 34822767 PMCID: PMC8792273 DOI: 10.1016/j.cub.2021.11.005] [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: 07/07/2021] [Revised: 10/08/2021] [Accepted: 11/02/2021] [Indexed: 01/26/2023]
Abstract
The morphology of retinal neurons strongly influences their physiological function. Ganglion cell (GC) dendrites ramify in distinct strata of the inner plexiform layer (IPL) so that GCs responding to light increments (ON) or decrements (OFF) receive appropriate excitatory inputs. This vertical stratification prescribes response polarity and ensures consistent connectivity between cell types, whereas the lateral extent of GC dendritic arbors typically dictates receptive field (RF) size. Here, we identify circuitry in mouse retina that contradicts these conventions. AII amacrine cells are interneurons understood to mediate "crossover" inhibition by relaying excitatory input from the ON layer to inhibitory outputs in the OFF layer. Ultrastructural and physiological analyses show, however, that some AIIs deliver powerful inhibition to OFF GC somas and proximal dendrites in the ON layer, rendering the inhibitory RFs of these GCs smaller than their dendritic arbors. This OFF pathway, avoiding entirely the OFF region of the IPL, challenges several tenets of retinal circuitry. These results also indicate that subcellular synaptic organization can vary within a single population of neurons according to their proximity to potential postsynaptic targets.
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19
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Differential susceptibility of retinal ganglion cell subtypes against neurodegenerative diseases. Graefes Arch Clin Exp Ophthalmol 2022; 260:1807-1821. [PMID: 35038014 DOI: 10.1007/s00417-022-05556-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 11/27/2021] [Accepted: 01/06/2022] [Indexed: 12/15/2022] Open
Abstract
Retinal ganglion cells (RGCs) are essential to propagate external visual information from the retina to the brain. Death of RGCs is speculated to be closely correlated with blinding retinal diseases, such as glaucoma and traumatic optic neuropathy (TON). Emerging innovative technologies have helped refine and standardize the classification of RGCs; at present, they are classified into more than 40 subpopulations in mammals. These RGC subtypes are identified by a combination of anatomical morphologies, electrophysiological functions, and genetic profiles. Increasing evidence suggests that neurodegenerative diseases do not collectively affect the RGCs. In fact, which RGC subtype exhibits the strongest or weakest susceptibility is hotly debated. Although a consensus has not yet been reached, it is certain that assorted RGCs display differential susceptibility against irreversible degeneration. Interestingly, a single RGC subtype can exhibit various vulnerabilities to optic nerve damage in diverse injury models. Thus, elucidating how susceptible RGC subtypes are to various injuries can protect vulnerable RGCs from damage and improve the possibility of preventing and treating visual impairment caused by neurodegenerative diseases. In this review, we summarize in detail the progress and status quo of research on the type-specific susceptibility of RGCs and point out current limitations and the possible directions for future research in this field.
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20
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Scene statistics and noise determine the relative arrangement of receptive field mosaics. Proc Natl Acad Sci U S A 2021; 118:2105115118. [PMID: 34556573 PMCID: PMC8488585 DOI: 10.1073/pnas.2105115118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 11/18/2022] Open
Abstract
Across a wide variety of species, cells in the retina specialized for signaling either increases (ON) or decreases (OFF) in light represent one of the most basic building blocks of visual computation. These cells coordinate to form mosaics, with each cell responsible for a small, minimally overlapping portion of visual space, but the ways in which these mosaics could be spatially coordinated with each other are relatively unknown. Here, we show how efficient coding theory, which hypothesizes that the nervous system minimizes the amount of redundant information it encodes, can predict the relative spatial arrangement of ON and OFF mosaics. The most information-efficient arrangements are determined both by levels of noise in the system and the statistics of natural images. Many sensory systems utilize parallel ON and OFF pathways that signal stimulus increments and decrements, respectively. These pathways consist of ensembles or grids of ON and OFF detectors spanning sensory space. Yet, encoding by opponent pathways raises a question: How should grids of ON and OFF detectors be arranged to optimally encode natural stimuli? We investigated this question using a model of the retina guided by efficient coding theory. Specifically, we optimized spatial receptive fields and contrast response functions to encode natural images given noise and constrained firing rates. We find that the optimal arrangement of ON and OFF receptive fields exhibits a transition between aligned and antialigned grids. The preferred phase depends on detector noise and the statistical structure of the natural stimuli. These results reveal that noise and stimulus statistics produce qualitative shifts in neural coding strategies and provide theoretical predictions for the configuration of opponent pathways in the nervous system.
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