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Muralidharan M, Guo T, Tsai D, Lee JI, Fried S, Dokos S, Morley JW, Lovell NH, Shivdasani MN. Neural activity of retinal ganglion cells under continuous, dynamically-modulated high frequency electrical stimulation. J Neural Eng 2024; 21:015001. [PMID: 38290151 DOI: 10.1088/1741-2552/ad2404] [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: 01/19/2023] [Accepted: 01/30/2024] [Indexed: 02/01/2024]
Abstract
Objective.Current retinal prosthetics are limited in their ability to precisely control firing patterns of functionally distinct retinal ganglion cell (RGC) types. The aim of this study was to characterise RGC responses to continuous, kilohertz-frequency-varying stimulation to assess its utility in controlling RGC activity.Approach.We usedin vitropatch-clamp experiments to assess electrically-evoked ON and OFF RGC responses to frequency-varying pulse train sequences. In each sequence, the stimulation amplitude was kept constant while the stimulation frequency (0.5-10 kHz) was changed every 40 ms, in either a linearly increasing, linearly decreasing or randomised manner. The stimulation amplitude across sequences was increased from 10 to 300µA.Main results.We found that continuous stimulation without rest periods caused complex and irreproducible stimulus-response relationships, primarily due to strong stimulus-induced response adaptation and influence of the preceding stimulus frequency on the response to a subsequent stimulus. In addition, ON and OFF populations showed different sensitivities to continuous, frequency-varying pulse trains, with OFF cells generally exhibiting more dependency on frequency changes within a sequence. Finally, the ability to maintain spiking behaviour to continuous stimulation in RGCs significantly reduced over longer stimulation durations irrespective of the frequency order.Significance.This study represents an important step in advancing and understanding the utility of continuous frequency modulation in controlling functionally distinct RGCs. Our results indicate that continuous, kHz-frequency-varying stimulation sequences provide very limited control of RGC firing patterns due to inter-dependency between adjacent frequencies and generally, different RGC types do not display different frequency preferences under such stimulation conditions. For future stimulation strategies using kHz frequencies, careful consideration must be given to design appropriate pauses in stimulation, stimulation frequency order and the length of continuous stimulation duration.
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Affiliation(s)
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
| | - David Tsai
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
- School of Electrical Engineering & Telecommunications, UNSW, Sydney, NSW 2052, Australia
| | - Jae-Ik Lee
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Shelley Fried
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Socrates Dokos
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
| | - John W Morley
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
- School of Medicine, Western Sydney University, Penrith, NSW 2751, Australia
| | - Nigel H Lovell
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
- Tyree Institute of Health Engineering (iHealthE), UNSW, Sydney, NSW 2052, Australia
| | - Mohit N Shivdasani
- Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
- Tyree Institute of Health Engineering (iHealthE), UNSW, Sydney, NSW 2052, Australia
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2
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Crosser JT, Brinkman BAW. Applications of information geometry to spiking neural network activity. Phys Rev E 2024; 109:024302. [PMID: 38491696 DOI: 10.1103/physreve.109.024302] [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: 05/18/2023] [Accepted: 01/10/2024] [Indexed: 03/18/2024]
Abstract
The space of possible behaviors that complex biological systems may exhibit is unimaginably vast, and these systems often appear to be stochastic, whether due to variable noisy environmental inputs or intrinsically generated chaos. The brain is a prominent example of a biological system with complex behaviors. The number of possible patterns of spikes emitted by a local brain circuit is combinatorially large, although the brain may not make use of all of them. Understanding which of these possible patterns are actually used by the brain, and how those sets of patterns change as properties of neural circuitry change is a major goal in neuroscience. Recently, tools from information geometry have been used to study embeddings of probabilistic models onto a hierarchy of model manifolds that encode how model outputs change as a function of their parameters, giving a quantitative notion of "distances" between outputs. We apply this method to a network model of excitatory and inhibitory neural populations to understand how the competition between membrane and synaptic response timescales shapes the network's information geometry. The hyperbolic embedding allows us to identify the statistical parameters to which the model behavior is most sensitive, and demonstrate how the ranking of these coordinates changes with the balance of excitation and inhibition in the network.
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Affiliation(s)
- Jacob T Crosser
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, USA and Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York 11794, USA
| | - Braden A W Brinkman
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, USA and Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York 11794, USA
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3
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Leong F, Rahmani B, Psaltis D, Moser C, Ghezzi D. An actor-model framework for visual sensory encoding. Nat Commun 2024; 15:808. [PMID: 38280912 PMCID: PMC10821921 DOI: 10.1038/s41467-024-45105-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/15/2024] [Indexed: 01/29/2024] Open
Abstract
A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For example, in visual prostheses, one key aspect of artificial image encoding is to downsample images captured by a camera to a size matching the number of inputs and resolution of the prosthesis. Here, we show that downsampling an image using the inherent computation of the retinal network yields better performance compared to learning-free downsampling methods. We have validated a learning-based approach (actor-model framework) that exploits the signal transformation from photoreceptors to retinal ganglion cells measured in explanted mouse retinas. The actor-model framework generates downsampled images eliciting a neuronal response in-silico and ex-vivo with higher neuronal reliability than the one produced by a learning-free approach. During the learning process, the actor network learns to optimize contrast and the kernel's weights. This methodological approach might guide future artificial image encoding strategies for visual prostheses. Ultimately, this framework could be applicable for encoding strategies in other sensory prostheses such as cochlear or limb.
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Affiliation(s)
- Franklin Leong
- Medtronic Chair in Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Babak Rahmani
- Laboratory of Applied Photonics Devices, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Microsoft Research, Cambridge, UK
| | - Demetri Psaltis
- Optics Laboratory, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Christophe Moser
- Laboratory of Applied Photonics Devices, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Diego Ghezzi
- Medtronic Chair in Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
- Ophthalmic and Neural Technologies Laboratory, Department of Ophthalmology, University of Lausanne, Hôpital ophtalmique Jules-Gonin, Fondation Asile des Aveugles, Lausanne, Switzerland.
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4
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Dyballa L, Rudzite AM, Hoseini MS, Thapa M, Stryker MP, Field GD, Zucker SW. Population encoding of stimulus features along the visual hierarchy. Proc Natl Acad Sci U S A 2024; 121:e2317773121. [PMID: 38227668 PMCID: PMC10823231 DOI: 10.1073/pnas.2317773121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/13/2023] [Indexed: 01/18/2024] Open
Abstract
The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to diverse visual features. Yet it remains unclear how neural populations in each area partition stimulus space to span these features. One possibility is that neural populations are organized into discrete groups of neurons, with each group signaling a particular constellation of features. Alternatively, neurons could be continuously distributed across feature-encoding space. To distinguish these possibilities, we presented a battery of visual stimuli to the mouse retina and V1 while measuring neural responses with multi-electrode arrays. Using machine learning approaches, we developed a manifold embedding technique that captures how neural populations partition feature space and how visual responses correlate with physiological and anatomical properties of individual neurons. We show that retinal populations discretely encode features, while V1 populations provide a more continuous representation. Applying the same analysis approach to convolutional neural networks that model visual processing, we demonstrate that they partition features much more similarly to the retina, indicating they are more like big retinas than little brains.
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Affiliation(s)
- Luciano Dyballa
- Department of Computer Science, Yale University, New Haven, CT06511
| | | | - Mahmood S. Hoseini
- Department of Physiology, University of California, San Francisco, CA94143
| | - Mishek Thapa
- Department of Neurobiology, Duke University, Durham, NC27708
- Department of Ophthalmology, David Geffen School of Medicine, Stein Eye Institute, University of California, Los Angeles, CA90095
| | - Michael P. Stryker
- Department of Physiology, University of California, San Francisco, CA94143
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA94143
| | - Greg D. Field
- Department of Neurobiology, Duke University, Durham, NC27708
- Department of Ophthalmology, David Geffen School of Medicine, Stein Eye Institute, University of California, Los Angeles, CA90095
| | - Steven W. Zucker
- Department of Computer Science, Yale University, New Haven, CT06511
- Department of Biomedical Engineering, Yale University, New Haven, CT06511
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5
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Patterson SS, Girresch RJ, Mazzaferri MA, Bordt AS, Piñon-Teal WL, Jesse BD, Perera DCW, Schlepphorst MA, Kuchenbecker JA, Chuang AZ, Neitz J, Marshak DW, Ogilvie JM. Synaptic Origins of the Complex Receptive Field Structure in Primate Smooth Monostratified Retinal Ganglion Cells. eNeuro 2024; 11:ENEURO.0280-23.2023. [PMID: 38290840 PMCID: PMC11078106 DOI: 10.1523/eneuro.0280-23.2023] [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: 08/04/2023] [Revised: 11/21/2023] [Accepted: 12/04/2023] [Indexed: 02/01/2024] Open
Abstract
Considerable progress has been made in studying the receptive fields of the most common primate retinal ganglion cell (RGC) types, such as parasol RGCs. Much less is known about the rarer primate RGC types and the circuitry that gives rise to noncanonical receptive field structures. The goal of this study was to analyze synaptic inputs to smooth monostratified RGCs to determine the origins of their complex spatial receptive fields, which contain isolated regions of high sensitivity called "hotspots." Interestingly, smooth monostratified RGCs co-stratify with the well-studied parasol RGCs and are thus constrained to receiving input from bipolar and amacrine cells with processes sharing the same layer, raising the question of how their functional differences originate. Through 3D reconstructions of circuitry and synapses onto ON smooth monostratified and ON parasol RGCs from central macaque retina, we identified four distinct sampling strategies employed by smooth and parasol RGCs to extract diverse response properties from co-stratifying bipolar and amacrine cells. The two RGC types differed in the proportion of amacrine cell input, relative contributions of co-stratifying bipolar cell types, amount of synaptic input per bipolar cell, and spatial distribution of bipolar cell synapses. Our results indicate that the smooth RGC's complex receptive field structure arises through spatial asymmetries in excitatory bipolar cell input which formed several discrete clusters comparable with physiologically measured hotspots. Taken together, our results demonstrate how the striking differences between ON parasol and ON smooth monostratified RGCs arise from distinct strategies for sampling a common set of synaptic inputs.
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Affiliation(s)
- Sara S Patterson
- Center for Visual Science, University of Rochester, Rochester, NewYork 14617
| | - Rebecca J Girresch
- Department of Biology, Saint Louis University, Saint Louis, Missouri 63103
| | - Marcus A Mazzaferri
- Department of Ophthalmology, University of Washington, Seattle, Washington 98104
| | - Andrea S Bordt
- Department of Ophthalmology, University of Washington, Seattle, Washington 98104
- Departments of Ophthalmology & Visual Science, McGovern Medical School, Houston, Texas 77030
| | - Wendy L Piñon-Teal
- Department of Biology, Saint Louis University, Saint Louis, Missouri 63103
| | - Brett D Jesse
- Department of Biology, Saint Louis University, Saint Louis, Missouri 63103
| | | | | | - James A Kuchenbecker
- Department of Ophthalmology, University of Washington, Seattle, Washington 98104
| | - Alice Z Chuang
- Departments of Ophthalmology & Visual Science, McGovern Medical School, Houston, Texas 77030
| | - Jay Neitz
- Department of Ophthalmology, University of Washington, Seattle, Washington 98104
| | - David W Marshak
- Neurobiology and Anatomy, McGovern Medical School, Houston, Texas 77030
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6
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Castillo García M, Urdapilleta E. A dynamical adaptation model of visual spatiotemporal processing in cones and horizontal cells. Math Biosci 2023; 366:109104. [PMID: 37918478 DOI: 10.1016/j.mbs.2023.109104] [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: 09/14/2023] [Revised: 10/26/2023] [Accepted: 10/29/2023] [Indexed: 11/04/2023]
Abstract
In this work, we introduce a phenomenological model for the cone-horizontal cell assembly, including spatial integration and formation of receptive field-like structures. The model extends our previous dynamical adaptation description with gain control accounting for processes in single cones, valid in severe nonlinear regimes. Here, a spatially extended feedback mechanism is introduced from horizontal cells to cones to account for experimental evidence, contributing thus to the development of a center-surround receptive field in cones and downstream bipolar cells. Feedback gain is defined on different spatial scales by weighting spatial filters: a short scale accounting for cone input to the feedback mechanism and a large scale driven by the syncytium characteristics of horizontal cells. A third spatial scale improves the description, mimicking neighboring cone-cone coupling. This overall spatial integration couples to temporal signal processing, thus obtaining a spatiotemporal model of outer retina responses capable of reproducing nonlinear features in both dimensions (space and time). The model was tested and validated using measurements on horizontal cells from different studies, with excellent performance. By its phenomenological nature, signal processing properties are inferred from model parameters. The model can be used in arrays of processing units with more complex incoming patterns of visual stimuli.
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Affiliation(s)
- Miguel Castillo García
- Centro Atómico Bariloche and Instituto Balseiro, Comisión Nacional de Energía Atómica (CNEA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Cuyo, Av. E. Bustillo 9500, R8402AGP San Carlos de Bariloche, Río Negro, Argentina
| | - Eugenio Urdapilleta
- Centro Atómico Bariloche and Instituto Balseiro, Comisión Nacional de Energía Atómica (CNEA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Cuyo, Av. E. Bustillo 9500, R8402AGP San Carlos de Bariloche, Río Negro, Argentina.
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7
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Wu EG, Rudzite AM, Bohlen MO, Li PH, Kling A, Cooler S, Rhoades C, Brackbill N, Gogliettino AR, Shah NP, Madugula SS, Sher A, Litke AM, Field GD, Chichilnisky E. Decomposition of retinal ganglion cell electrical images for cell type and functional inference. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565889. [PMID: 37986895 PMCID: PMC10659265 DOI: 10.1101/2023.11.06.565889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Identifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. The electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. Large-scale multi-electrode recordings from the macaque retina were used to test the effectiveness of the decomposition. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells), a substantial advance. Together, these findings may contribute to more accurate inference of RGC types and their original light responses in the degenerated retina, with possible implications for other electrical imaging applications.
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Affiliation(s)
- Eric G. Wu
- Department of Electrical Engineering, Stanford University
| | | | | | - Peter H. Li
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | - Alexandra Kling
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | - Sam Cooler
- Department of Neurosurgery, Stanford University
| | | | | | | | - Nishal P. Shah
- Department of Electrical Engineering, Stanford University
- Department of Neurosurgery, Stanford University
| | - Sasidhar S. Madugula
- Neurosciences PhD Program, Stanford University
- Stanford School of Medicine, Stanford University
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Alan M. Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Greg D. Field
- Department of Neurobiology, Duke University
- Stein Eye Institute, Department of Ophthalmology, University of California, Los Angeles
| | - E.J. Chichilnisky
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
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8
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Khadir A, Maghareh M, Sasani Ghamsari S, Beigzadeh B. Brain activity characteristics of RGB stimulus: an EEG study. Sci Rep 2023; 13:18988. [PMID: 37923926 PMCID: PMC10624840 DOI: 10.1038/s41598-023-46450-z] [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: 05/25/2023] [Accepted: 11/01/2023] [Indexed: 11/06/2023] Open
Abstract
The perception of color is a fundamental cognitive feature of our psychological experience, with an essential role in many aspects of human behavior. Several studies used magnetoencephalography, functional magnetic resonance imaging, and electroencephalography (EEG) approaches to investigate color perception. Their methods includes the event-related potential and spectral power activity of different color spaces, such as Derrington-Krauskopf-Lennie and red-green-blue (RGB), in addition to exploring the psychological and emotional effects of colors. However, we found insufficient studies in RGB space that considered combining all aspects of EEG signals. Thus, in the present study, focusing on RGB stimuli and using a data-driven approach, we investigated significant differences in the perception of colors. Our findings show that beta oscillation of green compared to red and blue colors occurs in early sensory periods with a latency shifting in the occipital region. Furthermore, in the occipital region, the theta power of the blue color decreases noticeably compared to the other colors. Concurrently, in the prefrontal area, we observed an increase in phase consistency in response to the green color, while the blue color showed a decrease. Therefore, our results can be used to interpret the brain activity mechanism of color perception in RGB color space and to choose suitable colors for more efficient performance in cognitive activities.
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Affiliation(s)
- Alireza Khadir
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Mohammad Maghareh
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Shamim Sasani Ghamsari
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Borhan Beigzadeh
- Biomechatronics and Cognitive Engineering Research Lab, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.
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9
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Wang AYM, Kulkarni MM, McLaughlin AJ, Gayet J, Smith BE, Hauptschein M, McHugh CF, Yao YY, Puthussery T. An ON-type direction-selective ganglion cell in primate retina. Nature 2023; 623:381-386. [PMID: 37880369 PMCID: PMC10632142 DOI: 10.1038/s41586-023-06659-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 09/20/2023] [Indexed: 10/27/2023]
Abstract
To maintain a stable and clear image of the world, our eyes reflexively follow the direction in which a visual scene is moving. Such gaze-stabilization mechanisms reduce image blur as we move in the environment. In non-primate mammals, this behaviour is initiated by retinal output neurons called ON-type direction-selective ganglion cells (ON-DSGCs), which detect the direction of image motion and transmit signals to brainstem nuclei that drive compensatory eye movements1. However, ON-DSGCs have not yet been identified in the retina of primates, raising the possibility that this reflex is mediated by cortical visual areas. Here we mined single-cell RNA transcriptomic data from primate retina to identify a candidate ON-DSGC. We then combined two-photon calcium imaging, molecular identification and morphological analysis to reveal a population of ON-DSGCs in the macaque retina. The morphology, molecular signature and GABA (γ-aminobutyric acid)-dependent mechanisms that underlie direction selectivity in primate ON-DSGCs are highly conserved with those in other mammals. We further identify a candidate ON-DSGC in human retina. The presence of ON-DSGCs in primates highlights the need to examine the contribution of subcortical retinal mechanisms to normal and aberrant gaze stabilization in the developing and mature visual system.
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Affiliation(s)
- Anna Y M Wang
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, Berkeley, CA, USA
| | - Manoj M Kulkarni
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, Berkeley, CA, USA
| | - Amanda J McLaughlin
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, Berkeley, CA, USA
| | - Jacqueline Gayet
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, Berkeley, CA, USA
| | - Benjamin E Smith
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Vision Science Graduate Program, University of California, Berkeley, Berkeley, CA, USA
| | - Max Hauptschein
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
| | - Cyrus F McHugh
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
- Vision Science Graduate Program, University of California, Berkeley, Berkeley, CA, USA
| | - Yvette Y Yao
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA
| | - Teresa Puthussery
- Herbert Wertheim School of Optometry and Vision Science, Berkeley, CA, USA.
- Helen Wills Neuroscience Institute, Berkeley, CA, USA.
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10
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Wu EG, Brackbill N, Rhoades C, Kling A, Gogliettino AR, Shah NP, Sher A, Litke AM, Simoncelli EP, Chichilnisky E. Fixational Eye Movements Enhance the Precision of Visual Information Transmitted by the Primate Retina. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.12.552902. [PMID: 37645934 PMCID: PMC10462030 DOI: 10.1101/2023.08.12.552902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the visual signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of macaque retinal ganglion cells (RGCs) of the major cell types, combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provided an interpretable framework for characterizing the retinal signal. Reconstructions were improved with artificial stimulus jitter that emulated fixational eye movements, even when the jitter trajectory was inferred from retinal spikes. Reconstructions were degraded by small artificial perturbations of spike times, revealing more precise temporal encoding than suggested by previous studies. Finally, reconstructions were substantially degraded when derived from a model that ignored cell-to-cell interactions, indicating the importance of stimulus-evoked correlations. Thus, fixational eye movements enhance the precision of the retinal representation.
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Affiliation(s)
- Eric G. Wu
- Department of Electrical Engineering, Stanford University
| | | | | | - Alexandra Kling
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | - Alex R. Gogliettino
- Hansen Experimental Physics Laboratory, Stanford University
- Neurosciences PhD Program, Stanford University
| | - Nishal P. Shah
- Department of Electrical Engineering, Stanford University
- Department of Neurosurgery, Stanford University
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Alan M. Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Eero P. Simoncelli
- Flatiron Institute, Simons Foundation
- Center for Neural Science, New York University
- Courant Institute of Mathematical Sciences, New York University
| | - E.J. Chichilnisky
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
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11
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Wang Q, So C, Zuo B, Banerjee S, Qiu C, Ting Z, Cheong AMY, Tse DYY, Pan F. Retinal ganglion cells encode differently in the myopic mouse retina? Exp Eye Res 2023; 234:109616. [PMID: 37580002 DOI: 10.1016/j.exer.2023.109616] [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: 03/07/2023] [Revised: 08/06/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023]
Abstract
The etiology of myopia remains unclear. This study investigated whether retinal ganglion cells (RGCs) in the myopic retina encode visual information differently from the normal retina and to determine the role of Connexin (Cx) 36 in this process. Generalized linear models (GLMs), which can capture stimulus-dependent changes in real neurons with spike timing precision and reliability, were used to predict RGCs responses to focused and defocused images in the retinas of wild-type (normal) and Lens-Induced Myopia (LIM) mice. As the predominant subunit of gap junctions in the mouse retina and a plausible modulator in myopia development, Cx36 knockout (KO) mice were used as a control for an intact retinal circuit. The kinetics of excitatory postsynaptic currents (EPSCs) of a single αRGC could reflect projection of both focused and defocused images in the retinas of normal and LIM, but not in the Cx36 knockout mice. Poisson GLMs revealed that RGC encoding of visual stimuli in the LIM retina was similar to that of the normal retina. In the LIM retinas, the linear-Gaussian GLM model with offset was a better fit for predicting the spike count under a focused image than the defocused image. Akaike information criterion (AIC) indicated that nonparametric GLM (np-GLM) model predicted focused/defocused images better in both LIM and normal retinas. However, the spike counts in 33% of αRGCs in LIM retinas were better fitted by exponential GLM (exp-GLM) under defocus, compared to only 13% αRGCs in normal retinas. The differences in encoding performance between LIM and normal retinas indicated the possible amendment and plasticity of the retinal circuit in myopic retinas. The absence of a similar response between Cx36 KO mice and normal/LIM mice might suggest that Cx36, which is associated with myopia development, plays a role in encoding focused and defocused images.
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Affiliation(s)
- Qin Wang
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong
| | - Chunghim So
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Bing Zuo
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Seema Banerjee
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - ChunTing Qiu
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Zhang Ting
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong; Hong Kong Polytechnic University Shenzhen Research Institute, Hong Kong
| | - Allen Ming-Yan Cheong
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong
| | - Dennis Yan-Yin Tse
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong
| | - Feng Pan
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong; Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Hong Kong; Hong Kong Polytechnic University Shenzhen Research Institute, Hong Kong.
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12
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Neuenschwander S, Rosso G, Branco N, Freitag F, Tehovnik EJ, Schmidt KE, Baron J. On the Functional Role of Gamma Synchronization in the Retinogeniculate System of the Cat. J Neurosci 2023; 43:5204-5220. [PMID: 37328291 PMCID: PMC10342227 DOI: 10.1523/jneurosci.1550-22.2023] [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: 08/12/2022] [Revised: 02/06/2023] [Accepted: 03/09/2023] [Indexed: 06/18/2023] Open
Abstract
Fast gamma oscillations, generated within the retina, and transmitted to the cortex via the lateral geniculate nucleus (LGN), are thought to carry information about stimulus size and continuity. This hypothesis relies mainly on studies conducted under anesthesia and the extent to which it holds under more naturalistic conditions remains unclear. Using multielectrode recordings of spiking activity in the retina and the LGN of both male and female cats, we show that visually driven gamma oscillations are absent for awake states and are highly dependent on halothane (or isoflurane). Under ketamine, responses were nonoscillatory, as in the awake condition. Response entrainment to the monitor refresh was commonly observed up to 120 Hz and was superseded by the gamma oscillatory responses induced by halothane. Given that retinal gamma oscillations are contingent on halothane anesthesia and absent in the awake cat, such oscillations should be considered artifactual, thus playing no functional role in vision.SIGNIFICANCE STATEMENT Gamma rhythms have been proposed to be a robust encoding mechanism critical for visual processing. In the retinogeniculate system of the cat, many studies have shown gamma oscillations associated with responses to static stimuli. Here, we extend these observations to dynamic stimuli. An unexpected finding was that retinal gamma responses strongly depend on halothane concentration levels and are absent in the awake cat. These results weaken the notion that gamma in the retina is relevant for vision. Notably, retinal gamma shares many of the properties of cortical gamma. In this respect, oscillations induced by halothane in the retina may serve as a valuable preparation, although artificial, for studying oscillatory dynamics.
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Affiliation(s)
- Sergio Neuenschwander
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Giovanne Rosso
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Natalia Branco
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Fabio Freitag
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Edward J Tehovnik
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Kerstin E Schmidt
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Jerome Baron
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais, 31270-901, Belo Horizonte, Brazil
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13
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Dyballa L, Rudzite AM, Hoseini MS, Thapa M, Stryker MP, Field GD, Zucker SW. Population encoding of stimulus features along the visual hierarchy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.545450. [PMID: 37425920 PMCID: PMC10327159 DOI: 10.1101/2023.06.27.545450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to diverse visual features. Yet it remains unclear how neural populations in each area partition stimulus space to span these features. One possibility is that neural populations are organized into discrete groups of neurons, with each group signaling a particular constellation of features. Alternatively, neurons could be continuously distributed across feature-encoding space. To distinguish these possibilities, we presented a battery of visual stimuli to mouse retina and V1 while measuring neural responses with multi-electrode arrays. Using machine learning approaches, we developed a manifold embedding technique that captures how neural populations partition feature space and how visual responses correlate with physiological and anatomical properties of individual neurons. We show that retinal populations discretely encode features, while V1 populations provide a more continuous representation. Applying the same analysis approach to convolutional neural networks that model visual processing, we demonstrate that they partition features much more similarly to the retina, indicating they are more like big retinas than little brains.
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Affiliation(s)
| | | | | | - Mishek Thapa
- Department of Neurobiology, Duke University
- Stein Eye Institute, Department of Ophthalmology, David Geffen School of Medicine, University of California, Los Angeles
| | - Michael P. Stryker
- Department of Physiology, University of California, San Francisco
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco
| | - Greg D. Field
- Department of Neurobiology, Duke University
- Stein Eye Institute, Department of Ophthalmology, David Geffen School of Medicine, University of California, Los Angeles
| | - Steven W. Zucker
- Department of Computer Science, Yale University
- Department of Biomedical Engineering, Yale University
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14
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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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15
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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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16
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Naudin L, Raison-Aubry L, Buhry L. A general pattern of non-spiking neuron dynamics under the effect of potassium and calcium channel modifications. J Comput Neurosci 2023; 51:173-186. [PMID: 36371576 DOI: 10.1007/s10827-022-00840-w] [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: 07/04/2022] [Revised: 10/08/2022] [Accepted: 11/02/2022] [Indexed: 11/13/2022]
Abstract
Electrical activity of excitable cells results from ion exchanges through cell membranes, so that genetic or epigenetic changes in genes encoding ion channels are likely to affect neuronal electrical signaling throughout the brain. There is a large literature on the effect of variations in ion channels on the dynamics of spiking neurons that represent the main type of neurons found in the vertebrate nervous systems. Nevertheless, non-spiking neurons are also ubiquitous in many nervous tissues and play a critical role in the processing of some sensory systems. To our knowledge, however, how conductance variations affect the dynamics of non-spiking neurons has never been assessed. Based on experimental observations reported in the biological literature and on mathematical considerations, we first propose a phenotypic classification of non-spiking neurons. Then, we determine a general pattern of the phenotypic evolution of non-spiking neurons as a function of changes in calcium and potassium conductances. Furthermore, we study the homeostatic compensatory mechanisms of ion channels in a well-posed non-spiking retinal cone model. We show that there is a restricted range of ion conductance values for which the behavior and phenotype of the neuron are maintained. Finally, we discuss the implications of the phenotypic changes of individual cells at the level of neuronal network functioning of the C. elegans worm and the retina, which are two non-spiking nervous tissues composed of neurons with various phenotypes.
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Affiliation(s)
- Loïs Naudin
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France.
| | - Laetitia Raison-Aubry
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France
| | - Laure Buhry
- Laboratoire Lorrain de Recherche en Informatique et ses Applications, CNRS, Université de Lorraine, Nancy, France.
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17
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Barkdoll K, Lu Y, Barranca VJ. New insights into binocular rivalry from the reconstruction of evolving percepts using model network dynamics. Front Comput Neurosci 2023; 17:1137015. [PMID: 37034441 PMCID: PMC10079880 DOI: 10.3389/fncom.2023.1137015] [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: 01/03/2023] [Accepted: 03/07/2023] [Indexed: 04/11/2023] Open
Abstract
When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.
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18
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Chen Y, Chen X, Baserdem B, Zhan H, Li Y, Davis MB, Kebschull JM, Zador AM, Koulakov AA, Albeanu DF. High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex. Cell 2022; 185:4117-4134.e28. [PMID: 36306734 PMCID: PMC9681627 DOI: 10.1016/j.cell.2022.09.038] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 07/22/2022] [Accepted: 09/28/2022] [Indexed: 11/07/2022]
Abstract
In most sensory modalities, neuronal connectivity reflects behaviorally relevant stimulus features, such as spatial location, orientation, and sound frequency. By contrast, the prevailing view in the olfactory cortex, based on the reconstruction of dozens of neurons, is that connectivity is random. Here, we used high-throughput sequencing-based neuroanatomical techniques to analyze the projections of 5,309 mouse olfactory bulb and 30,433 piriform cortex output neurons at single-cell resolution. Surprisingly, statistical analysis of this much larger dataset revealed that the olfactory cortex connectivity is spatially structured. Single olfactory bulb neurons targeting a particular location along the anterior-posterior axis of piriform cortex also project to matched, functionally distinct, extra-piriform targets. Moreover, single neurons from the targeted piriform locus also project to the same matched extra-piriform targets, forming triadic circuit motifs. Thus, as in other sensory modalities, olfactory information is routed at early stages of processing to functionally diverse targets in a coordinated manner.
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Affiliation(s)
- Yushu Chen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Xiaoyin Chen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Huiqing Zhan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yan Li
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Martin B Davis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Anthony M Zador
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
| | | | - Dinu F Albeanu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
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19
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Li Y, Wen Y, Liu X, Li Z, Lin B, Deng C, Yu Z, Zhu Y, Zhao L, Su W, Zhuo Y. Single-cell RNA sequencing reveals a landscape and targeted treatment of ferroptosis in retinal ischemia/reperfusion injury. J Neuroinflammation 2022; 19:261. [PMID: 36289494 PMCID: PMC9597965 DOI: 10.1186/s12974-022-02621-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 10/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The aim of this study was to establish a complete retinal cell atlas of ischemia-reperfusion injury by single-cell RNA sequencing, and to explore the underlying mechanism of retinal ischemia-reperfusion injury in mice. METHODS Single-cell RNA sequencing was used to evaluate changes in the mouse retinal ischemia reperfusion model. In vivo and in vitro experiments were performed to verify the protective effect of inhibiting ferroptosis in retinal ischemia-reperfusion injury. RESULTS After ischemia-reperfusion injury, retinal cells were significantly reduced, accompanied by the activation of myeloid and a large amount of blood-derived immune cell infiltration. The IFNG, MAPK and NFKB signaling pathways in retinal neuronal cells, together with the TNF signaling pathway in myeloid give rise to a strong inflammatory response in the I/R state. Besides, the expression of genes implicating iron metabolism, oxidative stress and multiple programed cell death pathways have changed in cell subtypes described above. Especially the ferroptosis-related genes and blocking this process could apparently alleviate the inflammatory immune responses and enhance retinal ganglion cells survival. CONCLUSIONS We established a comprehensive landscape of mouse retinal ischemia-reperfusion injury at the single-cell level, revealing the important role of ferroptosis during this injury, and targeted inhibition of ferroptosis can effectively protect retinal structure and function.
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Affiliation(s)
- Yangyang Li
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Yuwen Wen
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Xiuxing Liu
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Zhuang Li
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Bingying Lin
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Caibin Deng
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Ziyu Yu
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Yingting Zhu
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Ling Zhao
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Wenru Su
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
| | - Yehong Zhuo
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060 China
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20
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Caravaca-Rodriguez D, Gaytan SP, Suaning GJ, Barriga-Rivera A. Implications of Neural Plasticity in Retinal Prosthesis. Invest Ophthalmol Vis Sci 2022; 63:11. [PMID: 36251317 DOI: 10.1167/iovs.63.11.11] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Retinal degenerative diseases such as retinitis pigmentosa cause a progressive loss of photoreceptors that eventually prevents the affected person from perceiving visual sensations. The absence of a visual input produces a neural rewiring cascade that propagates along the visual system. This remodeling occurs first within the retina. Then, subsequent neuroplastic changes take place at higher visual centers in the brain, produced by either the abnormal neural encoding of the visual inputs delivered by the diseased retina or as the result of an adaptation to visual deprivation. While retinal implants can activate the surviving retinal neurons by delivering electric current, the unselective activation patterns of the different neural populations that exist in the retinal layers differ substantially from those in physiologic vision. Therefore, artificially induced neural patterns are being delivered to a brain that has already undergone important neural reconnections. Whether or not the modulation of this neural rewiring can improve the performance for retinal prostheses remains a critical question whose answer may be the enabler of improved functional artificial vision and more personalized neurorehabilitation strategies.
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Affiliation(s)
- Daniel Caravaca-Rodriguez
- Department of Applied Physics III, Technical School of Engineering, Universidad de Sevilla, Sevilla, Spain
| | - Susana P Gaytan
- Department of Physiology, Universidad de Sevilla, Sevilla, Spain
| | - Gregg J Suaning
- School of Biomedical Engineering, University of Sydney, Sydney, Australia
| | - Alejandro Barriga-Rivera
- Department of Applied Physics III, Technical School of Engineering, Universidad de Sevilla, Sevilla, Spain.,School of Biomedical Engineering, University of Sydney, Sydney, Australia
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21
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Arias A, Manubens-Gil L, Dierssen M. Fluorescent transgenic mouse models for whole-brain imaging in health and disease. Front Mol Neurosci 2022; 15:958222. [PMID: 36211979 PMCID: PMC9538927 DOI: 10.3389/fnmol.2022.958222] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/08/2022] [Indexed: 11/25/2022] Open
Abstract
A paradigm shift is occurring in neuroscience and in general in life sciences converting biomedical research from a descriptive discipline into a quantitative, predictive, actionable science. Living systems are becoming amenable to quantitative description, with profound consequences for our ability to predict biological phenomena. New experimental tools such as tissue clearing, whole-brain imaging, and genetic engineering technologies have opened the opportunity to embrace this new paradigm, allowing to extract anatomical features such as cell number, their full morphology, and even their structural connectivity. These tools will also allow the exploration of new features such as their geometrical arrangement, within and across brain regions. This would be especially important to better characterize brain function and pathological alterations in neurological, neurodevelopmental, and neurodegenerative disorders. New animal models for mapping fluorescent protein-expressing neurons and axon pathways in adult mice are key to this aim. As a result of both developments, relevant cell populations with endogenous fluorescence signals can be comprehensively and quantitatively mapped to whole-brain images acquired at submicron resolution. However, they present intrinsic limitations: weak fluorescent signals, unequal signal strength across the same cell type, lack of specificity of fluorescent labels, overlapping signals in cell types with dense labeling, or undetectable signal at distal parts of the neurons, among others. In this review, we discuss the recent advances in the development of fluorescent transgenic mouse models that overcome to some extent the technical and conceptual limitations and tradeoffs between different strategies. We also discuss the potential use of these strains for understanding disease.
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Affiliation(s)
- Adrian Arias
- Department of System Biology, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Linus Manubens-Gil
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Mara Dierssen
- Department of System Biology, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Experimental and Health Sciences, University Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain
- *Correspondence: Mara Dierssen,
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22
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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: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [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. The superior colliculus receives visual information from retinal ganglion cells, but it remains unclear how this information is organized and integrated in vivo. Here the authors describe how high-density electrodes can simultaneously capture the activity of incoming axons and target neurons in the superior colliculus, and demonstrate isomorphic mapping and strong and specific connections in mice and zebrafinches.
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Kim S, Roh H, Im M. Artificial Visual Information Produced by Retinal Prostheses. Front Cell Neurosci 2022; 16:911754. [PMID: 35734216 PMCID: PMC9208577 DOI: 10.3389/fncel.2022.911754] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 05/18/2022] [Indexed: 11/18/2022] Open
Abstract
Numerous retinal prosthetic systems have demonstrated somewhat useful vision can be restored to individuals who had lost their sight due to outer retinal degenerative diseases. Earlier prosthetic studies have mostly focused on the confinement of electrical stimulation for improved spatial resolution and/or the biased stimulation of specific retinal ganglion cell (RGC) types for selective activation of retinal ON/OFF pathway for enhanced visual percepts. To better replicate normal vision, it would be also crucial to consider information transmission by spiking activities arising in the RGC population since an incredible amount of visual information is transferred from the eye to the brain. In previous studies, however, it has not been well explored how much artificial visual information is created in response to electrical stimuli delivered by microelectrodes. In the present work, we discuss the importance of the neural information for high-quality artificial vision. First, we summarize the previous literatures which have computed information transmission rates from spiking activities of RGCs in response to visual stimuli. Second, we exemplify a couple of studies which computed the neural information from electrically evoked responses. Third, we briefly introduce how information rates can be computed in the representative two ways – direct method and reconstruction method. Fourth, we introduce in silico approaches modeling artificial retinal neural networks to explore the relationship between amount of information and the spiking patterns. Lastly, we conclude our review with clinical implications to emphasize the necessity of considering visual information transmission for further improvement of retinal prosthetics.
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Affiliation(s)
- Sein Kim
- Brain Science Institute, Korea Institute of Science and Technology, Seoul, South Korea
| | - Hyeonhee Roh
- Brain Science Institute, Korea Institute of Science and Technology, Seoul, South Korea
- School of Electrical Engineering, College of Engineering, Korea University, Seoul, South Korea
| | - Maesoon Im
- Brain Science Institute, Korea Institute of Science and Technology, Seoul, South Korea
- Division of Bio-Medical Science & Technology, KIST School, University of Science and Technology, Seoul, South Korea
- *Correspondence: Maesoon Im, ,
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24
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Italiano ML, Guo T, Lovell NH, Tsai D. Improving the spatial resolution of artificial vision using midget retinal ganglion cell populations modelled at the human fovea. J Neural Eng 2022; 19. [PMID: 35609556 DOI: 10.1088/1741-2552/ac72c2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/24/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Retinal prostheses seek to create artificial vision by stimulating surviving retinal neurons of patients with profound vision impairment. Notwithstanding tremendous research efforts, the performance of all implants tested to date has remained rudimentary, incapable of overcoming the threshold for legal blindness. To maximize the perceptual efficacy of retinal prostheses, a device must be capable of controlling retinal neurons with greater spatiotemporal precision. Most studies of retinal stimulation were derived from either non-primate species or the peripheral primate retina. We investigated if artificial stimulation could leverage the high spatial resolution afforded by the neural substrates at the primate fovea and surrounding regions to achieve improved percept qualities. APPROACH We began by developing a new computational model capable of generating anatomically accurate retinal ganglion cell (RGC) populations within the human central retina. Next, multiple RGC populations across the central retina were stimulated in-silico to compare clinical and recently proposed neurostimulation configurations based on their ability to improve perceptual efficacy and reduce activation thresholds. MAIN RESULTS Our model uniquely upholds eccentricity-dependent characteristics such as RGC density and dendritic field diameter, whilst incorporating anatomically accurate features such as axon projection and three-dimensional RGC layering, features often forgone in favor of reduced computational complexity. Following epiretinal stimulation, the RGCs in our model produced response patterns in shapes akin to the complex percepts reported in clinical trials. Our results also demonstrated that even within the neuron-dense central retina, epiretinal stimulation using a multi-return hexapolar electrode arrangement could reliably achieve spatially focused RGC activation and could achieve single-cell excitation in 74% of all tested locations. SIGNIFICANCE This study establishes an anatomically accurate three-dimensional model of the human central retina and demonstrates the potential for an epiretinal hexapolar configuration to achieve consistent, spatially confined retinal responses, even within the neuron-dense foveal region. Our results promote the prospect and optimization of higher spatial resolution in future epiretinal implants.
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Affiliation(s)
- Michael Lewis Italiano
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Sydney, New South Wales, 2052, AUSTRALIA
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Sydney, New South Wales, 2052, AUSTRALIA
| | - Nigel H Lovell
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Sydney, New South Wales, 2052, AUSTRALIA
| | - David Tsai
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Sydney, New South Wales, 2052, AUSTRALIA
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25
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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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26
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Patterson SS, Bembry BN, Mazzaferri MA, Neitz M, Rieke F, Soetedjo R, Neitz J. Conserved circuits for direction selectivity in the primate retina. Curr Biol 2022; 32:2529-2538.e4. [PMID: 35588744 DOI: 10.1016/j.cub.2022.04.056] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/25/2022] [Accepted: 04/20/2022] [Indexed: 02/06/2023]
Abstract
The detection of motion direction is a fundamental visual function and a classic model for neural computation. In the non-primate retina, direction selectivity arises in starburst amacrine cell (SAC) dendrites, which provide selective inhibition to direction-selective retinal ganglion cells (dsRGCs). Although SACs are present in primates, their connectivity and the existence of dsRGCs remain open questions. Here, we present a connectomic reconstruction of the primate ON SAC circuit from a serial electron microscopy volume of the macaque central retina. We show that the structural basis for the SACs' ability to confer directional selectivity on postsynaptic neurons is conserved. SACs selectively target a candidate homolog to the mammalian ON-sustained dsRGCs that project to the accessory optic system (AOS) and contribute to gaze-stabilizing reflexes. These results indicate that the capacity to compute motion direction is present in the retina, which is earlier in the primate visual system than classically thought.
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Affiliation(s)
- Sara S Patterson
- Center for Visual Science, University of Rochester, Rochester, NY 14620, USA; Department of Ophthalmology, University of Washington, Seattle, WA 98109, USA.
| | - Briyana N Bembry
- Department of Ophthalmology, University of Washington, Seattle, WA 98109, USA
| | - Marcus A Mazzaferri
- Department of Ophthalmology, University of Washington, Seattle, WA 98109, USA
| | - Maureen Neitz
- Department of Ophthalmology, University of Washington, Seattle, WA 98109, USA
| | - Fred Rieke
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Robijanto Soetedjo
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Jay Neitz
- Department of Ophthalmology, University of Washington, Seattle, WA 98109, USA.
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27
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Tangential high-density electrode insertions allow to simultaneously measure neuronal activity across an extended region of the visual field in mouse superior colliculus. J Neurosci Methods 2022; 376:109622. [PMID: 35525463 DOI: 10.1016/j.jneumeth.2022.109622] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 04/13/2022] [Accepted: 05/02/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND The superior colliculus (SC) is a midbrain structure that plays a central role in visual processing. Although we have learned a considerable amount about the function of single SC neurons, the way in which sensory information is represented and processed on the population level in awake behaving animals and across a large region of the retinotopic map is still largely unknown. Partially because the SC is anatomically located below the cortical sheet and the transverse sinus, which render the measure of neuronal activity from a large population of neurons in the SC technically difficult to perform. NEW METHOD To address this, we propose a tangential recording configuration using high-density electrode probes (Neuropixels) in mouse SC in vivo. This method permits a large number of recording sites (~200) inside the SC circuitry allowing to record from a large population of SC neurons along a vast area of retinotopic space. RESULTS This approach provides a unique opportunity to measure the activity of SC neuronal populations over up to ~2mm of SC tissue reporting for the first time the continuous receptive fields coverage of almost the entire SC retinotopy. Here we describe how to perform targeted tangential recordings along the anterior-posterior and the medio-lateral axis of the mouse SC in vivo in the upper visual layers. Furthermore, we describe how to combine this approach with optogenetic tools for cell-type identification on the population level. COMPARISON WITH EXISTING METHODS Vertical insertion has been a standard way to record visual responses in the SC. Inserting multi-shank probes vertically allows to cover a larger region of the SC but misses both the complete extent of the available retinotopy and the continuous measure allowed by the high density of recording sites on Neuropixels probes. CONCLUSION Altogether tangential insertions in the upper visual layers of the mouse SC using Neuropixels permit for the first time to access a majority of the retinotopically organized visual representation of the world at an unprecedented precision.
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28
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Pasmanter N, Occelli LM, Komáromy AM, Petersen-Jones SM. Use of extended protocols with nonstandard stimuli to characterize rod and cone contributions to the canine electroretinogram. Doc Ophthalmol 2022; 144:81-97. [PMID: 35247111 PMCID: PMC10426558 DOI: 10.1007/s10633-022-09866-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 02/08/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE In this study, we assessed several extended electroretinographic protocols using nonstandard stimuli. Our aim was to separate and quantify the contributions of different populations of retinal cells to the overall response, both to assess normal function and characterize dogs with inherited retinal disease. METHODS We investigated three different protocols for measuring the full-field flash electroretinogram-(1) chromatic dark-adapted red and blue flashes, (2) increasing luminance blue-background, (3) flicker with fixed frequency and increasing luminance, and flicker with increasing frequency at a fixed luminance-to assess rod and cone contributions to electroretinograms recorded in phenotypically normal control dogs and dogs lacking rod function. RESULTS Temporal separation of the rod- and cone-driven responses is possible in the fully dark-adapted eye using dim red flashes. A- and b-wave amplitudes decrease at different rates with increasing background luminance in control dogs. Flicker responses elicited with extended flicker protocols are well fit with mathematical models in control dogs. Dogs lacking rod function demonstrated larger amplitude dark-adapted compared to light-adapted flicker responses. CONCLUSIONS Using extended protocols of the full-field electroretinogram provides additional characterization of the health and function of different populations of cells in the normal retina and enables quantifiable comparison between phenotypically normal dogs and those with retinal disease.
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Affiliation(s)
- Nate Pasmanter
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 736 Wilson Road, D-208, East Lansing, MI, 48824, USA
| | - Laurence M Occelli
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 736 Wilson Road, D-208, East Lansing, MI, 48824, USA
| | - András M Komáromy
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 736 Wilson Road, D-208, East Lansing, MI, 48824, USA
| | - Simon M Petersen-Jones
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 736 Wilson Road, D-208, East Lansing, MI, 48824, USA.
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29
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Yu Z, Turner MH, Baudin J, Rieke F. Adaptation in cone photoreceptors contributes to an unexpected insensitivity of primate On parasol retinal ganglion cells to spatial structure in natural images. eLife 2022; 11:70611. [PMID: 35285798 PMCID: PMC8956286 DOI: 10.7554/elife.70611] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Accepted: 03/13/2022] [Indexed: 02/06/2023] Open
Abstract
Neural circuits are constructed from nonlinear building blocks, and not surprisingly overall circuit behavior is often strongly nonlinear. But neural circuits can also behave near linearly, and some circuits shift from linear to nonlinear behavior depending on stimulus conditions. Such control of nonlinear circuit behavior is fundamental to neural computation. Here, we study a surprising stimulus dependence of the responses of macaque On (but not Off) parasol retinal ganglion cells: these cells respond nonlinearly to spatial structure in some stimuli but near linearly to spatial structure in others, including natural inputs. We show that these differences in the linearity of the integration of spatial inputs can be explained by a shift in the balance of excitatory and inhibitory synaptic inputs that originates at least partially from adaptation in the cone photoreceptors. More generally, this highlights how subtle asymmetries in signaling - here in the cone signals - can qualitatively alter circuit computation.
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Affiliation(s)
- Zhou Yu
- Department of Physiology and Biophysics, University of Washington, Seattle, United States
| | - Maxwell H Turner
- Department of Physiology and Biophysics, University of Washington, Seattle, United States
| | - Jacob Baudin
- Department of Physiology and Biophysics, University of Washington, Seattle, United States
| | - Fred Rieke
- Department of Physiology and Biophysics, University of Washington, Seattle, United States
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30
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Shah NP, Brackbill N, Samarakoon R, Rhoades C, Kling A, Sher A, Litke A, Singer Y, Shlens J, Chichilnisky EJ. Individual variability of neural computations in the primate retina. Neuron 2022; 110:698-708.e5. [PMID: 34932942 PMCID: PMC8857061 DOI: 10.1016/j.neuron.2021.11.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 08/10/2021] [Accepted: 11/20/2021] [Indexed: 12/28/2022]
Abstract
Variation in the neural code contributes to making each individual unique. We probed neural code variation using ∼100 population recordings from major ganglion cell types in the macaque retina, combined with an interpretable computational representation of individual variability. This representation captured variation and covariation in properties such as nonlinearity, temporal dynamics, and spatial receptive field size and preserved invariances such as asymmetries between On and Off cells. The covariation of response properties in different cell types was associated with the proximity of lamination of their synaptic input. Surprisingly, male retinas exhibited higher firing rates and faster temporal integration than female retinas. Exploiting data from previously recorded retinas enabled efficient characterization of a new macaque retina, and of a human retina. Simulations indicated that combining a large dataset of retinal recordings with behavioral feedback could reveal the neural code in a living human and thus improve vision restoration with retinal implants.
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Affiliation(s)
- Nishal P Shah
- Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA; Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA.
| | - Nora Brackbill
- Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Physics, Stanford University, Stanford, CA 94305, USA
| | - Ryan Samarakoon
- Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
| | - Colleen Rhoades
- Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Alexandra Kling
- Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
| | - Alexander Sher
- University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Alan Litke
- University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Yoram Singer
- WorldQuant, LLC, 1700 E Putnam Ave., Old Greenwich, CT 06870, USA
| | - Jonathon Shlens
- Google Brain, 1600 Amphitheatre Pkwy., Mountain View, CA 94043, USA
| | - E J Chichilnisky
- Hansen Experimental Physics Lab, Stanford University, Stanford, CA 94305, USA; Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
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31
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Lee H, Cho SW, Kim SJ, Lee J, Kim KS, Kim I, Park JK, Kwak JY, Kim J, Park J, Jeong Y, Hwang GW, Lee KS, Ielmini D, Lee S. Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons. NANO LETTERS 2022; 22:733-739. [PMID: 35025519 DOI: 10.1021/acs.nanolett.1c04125] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (Vth). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.
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Affiliation(s)
- Hyejin Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
- Department of Physics, Yonsei University, Seoul 03722, Korea
| | - Seong Won Cho
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Korea
| | - Seon Jeong Kim
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
- Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Jaesang Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Korea
| | - Keun Su Kim
- Department of Physics, Yonsei University, Seoul 03722, Korea
| | - Inho Kim
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Jong-Keuk Park
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Joon Young Kwak
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Jaewook Kim
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Jongkil Park
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - YeonJoo Jeong
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Gyu Weon Hwang
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Kyeong-Seok Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
| | - Daniele Ielmini
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy
| | - Suyoun Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Korea
- Division of Nano & Information Technology, Korea University of Science and Technology, Daejeon 34316, Korea
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Huang C, Zeldenrust F, Celikel T. Cortical Representation of Touch in Silico. Neuroinformatics 2022; 20:1013-1039. [PMID: 35486347 PMCID: PMC9588483 DOI: 10.1007/s12021-022-09576-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2022] [Indexed: 12/31/2022]
Abstract
With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.
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Affiliation(s)
- Chao Huang
- grid.9647.c0000 0004 7669 9786Department of Biology, University of Leipzig, Leipzig, Germany
| | - Fleur Zeldenrust
- grid.5590.90000000122931605Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Tansu Celikel
- grid.5590.90000000122931605Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands ,grid.213917.f0000 0001 2097 4943School of Psychology, Georgia Institute of Technology, Atlanta, GA USA
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33
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Lukanov H, König P, Pipa G. Biologically Inspired Deep Learning Model for Efficient Foveal-Peripheral Vision. Front Comput Neurosci 2021; 15:746204. [PMID: 34880741 PMCID: PMC8645638 DOI: 10.3389/fncom.2021.746204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 10/27/2021] [Indexed: 11/13/2022] Open
Abstract
While abundant in biology, foveated vision is nearly absent from computational models and especially deep learning architectures. Despite considerable hardware improvements, training deep neural networks still presents a challenge and constraints complexity of models. Here we propose an end-to-end neural model for foveal-peripheral vision, inspired by retino-cortical mapping in primates and humans. Our model has an efficient sampling technique for compressing the visual signal such that a small portion of the scene is perceived in high resolution while a large field of view is maintained in low resolution. An attention mechanism for performing "eye-movements" assists the agent in collecting detailed information incrementally from the observed scene. Our model achieves comparable results to a similar neural architecture trained on full-resolution data for image classification and outperforms it at video classification tasks. At the same time, because of the smaller size of its input, it can reduce computational effort tenfold and uses several times less memory. Moreover, we present an easy to implement bottom-up and top-down attention mechanism which relies on task-relevant features and is therefore a convenient byproduct of the main architecture. Apart from its computational efficiency, the presented work provides means for exploring active vision for agent training in simulated environments and anthropomorphic robotics.
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Affiliation(s)
- Hristofor Lukanov
- Department of Neuroinformatics, Institute of Cognitive Science, Osnabrück University, Osnabrück, Germany
| | - Peter König
- Department of Neurobiopsychology, Institute of Cognitive Science, Osnabrück University, Osnabrück, Germany.,Department of Neurophysiology and Pathophysiology, Center of Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gordon Pipa
- Department of Neuroinformatics, Institute of Cognitive Science, Osnabrück University, Osnabrück, Germany
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34
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Williams B, Del Rosario J, Muzzu T, Peelman K, Coletta S, Bichler EK, Speed A, Meyer-Baese L, Saleem AB, Haider B. Spatial modulation of dark versus bright stimulus responses in the mouse visual system. Curr Biol 2021; 31:4172-4179.e6. [PMID: 34314675 PMCID: PMC8478832 DOI: 10.1016/j.cub.2021.06.094] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 05/20/2021] [Accepted: 06/30/2021] [Indexed: 01/06/2023]
Abstract
A fundamental task of the visual system is to respond to both increases and decreases of luminance with action potentials (ON and OFF responses1-4). OFF responses are stronger, faster, and more salient than ON responses in primary visual cortex (V1) of both cats5,6 and primates,7,8 but in ferrets9 and mice,10 ON responses can be stronger, weaker,11 or balanced12 in comparison to OFF responses. These discrepancies could arise from differences in species, experimental techniques, or stimulus properties, particularly retinotopic location in the visual field, as has been speculated;9 however, the role of retinotopy for ON/OFF dominance has not been systematically tested across multiple scales of neural activity within species. Here, we measured OFF versus ON responses across large portions of visual space with silicon probe and whole-cell patch-clamp recordings in mouse V1 and lateral geniculate nucleus (LGN). We found that OFF responses dominated in the central visual field, whereas ON and OFF responses were more balanced in the periphery. These findings were consistent across local field potential (LFP), spikes, and subthreshold membrane potential in V1, and were aligned with spatial biases in ON and OFF responses in LGN. Our findings reveal that retinotopy may provide a common organizing principle for spatial modulation of OFF versus ON processing in mammalian visual systems.
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Affiliation(s)
- Brice Williams
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Joseph Del Rosario
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Tomaso Muzzu
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Kayla Peelman
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Stefano Coletta
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Edyta K Bichler
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Lisa Meyer-Baese
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Aman B Saleem
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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Ahmed I, Johnston RJ, Singh MS. Pluripotent stem cell therapy for retinal diseases. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1279. [PMID: 34532416 PMCID: PMC8421932 DOI: 10.21037/atm-20-4747] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 12/04/2020] [Indexed: 12/20/2022]
Abstract
Pluripotent stem cells (PSCs), which include human embryonic stem cells (hESCs) and induced pluripotent stem cell (iPSC), have been used to study development of disease processes, and as potential therapies in multiple organ systems. In recent years, there has been increasing interest in the use of PSC-based transplantation to treat disorders of the retina in which retinal cells have been functionally damaged or lost through degeneration. The retina, which consists of neuronal tissue, provides an excellent system to test the therapeutic utility of PSC-based transplantation due to its accessibility and the availability of high-resolution imaging technology to evaluate effects. Preclinical trials in animal models of retinal diseases have shown improvement in visual outcomes following subretinal transplantation of PSC-derived photoreceptors or retinal pigment epithelium (RPE) cells. This review focuses on preclinical studies and clinical trials exploring the use of PSCs for retinal diseases. To date, several phase I/II clinical trials in patients with age-related macular degeneration (AMD) and Stargardt disease (STGD1) have demonstrated the safety and feasibility of PSC-derived RPE transplantation. Additional phase I/II clinical trials using PSC-derived RPE or photoreceptor cells for the treatment of AMD, STGD1, and also retinitis pigmentosa (RP) are currently in the pipeline. As this field continues to evolve, additional technologies may enhance PSC-derived cell transplantation through gene-editing of autologous cells, transplantation of more complex cellular structures such as organoids, and monitoring of transplanted cells through novel imaging technologies.
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Affiliation(s)
- Ishrat Ahmed
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Mandeep S Singh
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Abstract
Our sense of sight relies on photoreceptors, which transduce photons into the nervous system's electrochemical interpretation of the visual world. These precious photoreceptors can be disrupted by disease, injury, and aging. Once photoreceptors start to die, but before blindness occurs, the remaining retinal circuitry can withstand, mask, or exacerbate the photoreceptor deficit and potentially be receptive to newfound therapies for vision restoration. To maximize the retina's receptivity to therapy, one must understand the conditions that influence the state of the remaining retina. In this review, we provide an overview of the retina's structure and function in health and disease. We analyze a collection of observations on photoreceptor disruption and generate a predictive model to identify parameters that influence the retina's response. Finally, we speculate on whether the retina, with its remarkable capacity to function over light levels spanning nine orders of magnitude, uses these same adaptational mechanisms to withstand and perhaps mask photoreceptor loss.
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Affiliation(s)
- Joo Yeun Lee
- Department of Ophthalmology, University of California, San Francisco, California 94143, USA; , , ,
| | - Rachel A Care
- Department of Ophthalmology, University of California, San Francisco, California 94143, USA; , , ,
| | - Luca Della Santina
- Department of Ophthalmology, University of California, San Francisco, California 94143, USA; , , ,
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94143, USA
| | - Felice A Dunn
- Department of Ophthalmology, University of California, San Francisco, California 94143, USA; , , ,
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37
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Grünert U, Martin PR. Morphology, Molecular Characterization, and Connections of Ganglion Cells in Primate Retina. Annu Rev Vis Sci 2021; 7:73-103. [PMID: 34524877 DOI: 10.1146/annurev-vision-100419-115801] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The eye sends information about the visual world to the brain on over 20 parallel signal pathways, each specialized to signal features such as spectral reflection (color), edges, and motion of objects in the environment. Each pathway is formed by the axons of a separate type of retinal output neuron (retinal ganglion cell). In this review, we summarize what is known about the excitatory retinal inputs, brain targets, and gene expression patterns of ganglion cells in humans and nonhuman primates. We describe how most ganglion cell types receive their input from only one or two of the 11 types of cone bipolar cell and project selectively to only one or two target regions in the brain. We also highlight how genetic methods are providing tools to characterize ganglion cells and establish cross-species homologies.
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Affiliation(s)
- Ulrike Grünert
- Save Sight Institute, Faculty of Medicine and Health, The University of Sydney, Sydney NSW 2000, Australia; , .,Sydney Node, Australian Research Council Centre of Excellence for Integrative Brain Function, The University of Sydney, Sydney NSW 2000, Australia
| | - Paul R Martin
- Save Sight Institute, Faculty of Medicine and Health, The University of Sydney, Sydney NSW 2000, Australia; , .,Sydney Node, Australian Research Council Centre of Excellence for Integrative Brain Function, The University of Sydney, Sydney NSW 2000, Australia
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Kim YJ, Brackbill N, Batty E, Lee J, Mitelut C, Tong W, Chichilnisky EJ, Paninski L. Nonlinear Decoding of Natural Images From Large-Scale Primate Retinal Ganglion Recordings. Neural Comput 2021; 33:1719-1750. [PMID: 34411268 DOI: 10.1162/neco_a_01395] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/25/2021] [Indexed: 11/04/2022]
Abstract
Decoding sensory stimuli from neural activity can provide insight into how the nervous system might interpret the physical environment, and facilitates the development of brain-machine interfaces. Nevertheless, the neural decoding problem remains a significant open challenge. Here, we present an efficient nonlinear decoding approach for inferring natural scene stimuli from the spiking activities of retinal ganglion cells (RGCs). Our approach uses neural networks to improve on existing decoders in both accuracy and scalability. Trained and validated on real retinal spike data from more than 1000 simultaneously recorded macaque RGC units, the decoder demonstrates the necessity of nonlinear computations for accurate decoding of the fine structures of visual stimuli. Specifically, high-pass spatial features of natural images can only be decoded using nonlinear techniques, while low-pass features can be extracted equally well by linear and nonlinear methods. Together, these results advance the state of the art in decoding natural stimuli from large populations of neurons.
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Cowan CS, Renner M, De Gennaro M, Gross-Scherf B, Goldblum D, Hou Y, Munz M, Rodrigues TM, Krol J, Szikra T, Cuttat R, Waldt A, Papasaikas P, Diggelmann R, Patino-Alvarez CP, Galliker P, Spirig SE, Pavlinic D, Gerber-Hollbach N, Schuierer S, Srdanovic A, Balogh M, Panero R, Kusnyerik A, Szabo A, Stadler MB, Orgül S, Picelli S, Hasler PW, Hierlemann A, Scholl HPN, Roma G, Nigsch F, Roska B. Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution. Cell 2021; 182:1623-1640.e34. [PMID: 32946783 PMCID: PMC7505495 DOI: 10.1016/j.cell.2020.08.013] [Citation(s) in RCA: 301] [Impact Index Per Article: 100.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 06/14/2020] [Accepted: 08/06/2020] [Indexed: 01/05/2023]
Abstract
Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.
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Affiliation(s)
- Cameron S Cowan
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Magdalena Renner
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland
| | - Martina De Gennaro
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Brigitte Gross-Scherf
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - David Goldblum
- Department of Ophthalmology, University of Basel, 4031 Basel, Switzerland
| | - Yanyan Hou
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Martin Munz
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Tiago M Rodrigues
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Jacek Krol
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Tamas Szikra
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Rachel Cuttat
- Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland
| | - Annick Waldt
- Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland
| | - Panagiotis Papasaikas
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; Swiss Institute of Bioinformatics, 4058 Basel, Switzerland
| | - Roland Diggelmann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering of ETH Zurich, 4058 Basel, Switzerland
| | - Claudia P Patino-Alvarez
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Patricia Galliker
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Stefan E Spirig
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Dinko Pavlinic
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | | | - Sven Schuierer
- Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland
| | - Aldin Srdanovic
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Marton Balogh
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Riccardo Panero
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Akos Kusnyerik
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Department of Ophthalmology, Semmelweis University, 1085 Budapest, Hungary
| | - Arnold Szabo
- Department of Anatomy, Histology and Embryology, Semmelweis University, 1085 Budapest, Hungary
| | - Michael B Stadler
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; Swiss Institute of Bioinformatics, 4058 Basel, Switzerland
| | - Selim Orgül
- Department of Ophthalmology, University of Basel, 4031 Basel, Switzerland
| | - Simone Picelli
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Pascal W Hasler
- Department of Ophthalmology, University of Basel, 4031 Basel, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering of ETH Zurich, 4058 Basel, Switzerland
| | - Hendrik P N Scholl
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Department of Ophthalmology, University of Basel, 4031 Basel, Switzerland; Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Guglielmo Roma
- Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland.
| | - Florian Nigsch
- Novartis Institutes for Biomedical Research, 4056 Basel, Switzerland.
| | - Botond Roska
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; Department of Ophthalmology, University of Basel, 4031 Basel, Switzerland.
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40
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Hadjinicolaou AE, Meffin H, Maturana MI, Cloherty SL, Ibbotson MR. Prosthetic vision: devices, patient outcomes and retinal research. Clin Exp Optom 2021; 98:395-410. [DOI: 10.1111/cxo.12342] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Revised: 07/06/2015] [Accepted: 08/04/2015] [Indexed: 12/11/2022] Open
Affiliation(s)
- Alex E Hadjinicolaou
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia,
- ARC Centre of Excellence for Integrative Brain Function and Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia,
| | - Hamish Meffin
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia,
- ARC Centre of Excellence for Integrative Brain Function and Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia,
| | - Matias I Maturana
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia,
- Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Victoria, Australia,
| | - Shaun L Cloherty
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia,
- ARC Centre of Excellence for Integrative Brain Function and Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia,
- Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Victoria, Australia,
| | - Michael R Ibbotson
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia,
- ARC Centre of Excellence for Integrative Brain Function and Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia,
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Single-Cell Transcriptomic Comparison of Human Fetal Retina, hPSC-Derived Retinal Organoids, and Long-Term Retinal Cultures. Cell Rep 2021; 30:1644-1659.e4. [PMID: 32023475 PMCID: PMC7901645 DOI: 10.1016/j.celrep.2020.01.007] [Citation(s) in RCA: 152] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 09/11/2019] [Accepted: 12/31/2019] [Indexed: 12/18/2022] Open
Abstract
To study the development of the human retina, we use single-cell RNA sequencing (RNA-seq) at key fetal stages and follow the development of the major cell types as well as populations of transitional cells. We also analyze stem cell (hPSC)-derived retinal organoids; although organoids have a very similar cellular composition at equivalent ages as the fetal retina, there are some differences in gene expression of particular cell types. Moreover, the inner retinal lamination is disrupted at more advanced stages of organoids compared with fetal retina. To determine whether the disorganization in the inner retina is due to the culture conditions, we analyze retinal development in fetal retina maintained under similar conditions. These retinospheres develop for at least 6 months, displaying better inner retinal lamination than retinal organoids. Our single-cell RNA sequencing (scRNA-seq) comparisons of fetal retina, retinal organoids, and retinospheres provide a resource for developing better in vitro models for retinal disease.
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42
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Roy S, Jun NY, Davis EL, Pearson J, Field GD. Inter-mosaic coordination of retinal receptive fields. Nature 2021; 592:409-413. [PMID: 33692544 PMCID: PMC8049984 DOI: 10.1038/s41586-021-03317-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 02/01/2021] [Indexed: 11/09/2022]
Abstract
The output of the retina is organized into many detector grids, called ‘mosaics’ that signal different features of visual scenes to the brain1–4. Each mosaic comprises a single retinal ganglion cell (RGC) type, whose receptive fields (RFs) tile space. Many mosaics arise as pairs, signaling increments (ON) and decrements (OFF), respectively, of a particular visual feature5. Using a model of efficient coding6, we determine how such mosaic pairs should be arranged to optimize the encoding of natural scenes. We find that information is maximized when these mosaic pairs are anti-aligned, meaning the RF centers between mosaics are more distant than expected by chance. We test this prediction across multiple RF mosaics acquired with large-scale measurements of RGC light responses from rat and primate. We find that ON and OFF RGC pairs with similar feature selectivity exhibit anti-aligned RF mosaics, consistent with theory. ON and OFF types that encode distinct features exhibit independent mosaics. These results extend efficient coding theory (ECT) beyond individual cells to predict how populations of diverse RGC types are spatially arranged.
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Affiliation(s)
- Suva Roy
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Na Young Jun
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Emily L Davis
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - John Pearson
- Department of Neurobiology, Duke University, Durham, NC, USA.,Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Greg D Field
- Department of Neurobiology, Duke University, Durham, NC, USA.
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Abstract
The retinal output is the sole source of visual information for the brain. Studies in non-primate mammals estimate that this information is carried by several dozens of retinal ganglion cell types, each informing the brain about different aspects of a visual scene. Even though morphological studies of primate retina suggest a similar diversity of ganglion cell types, research has focused on the function of only a few cell types. In human retina, recordings from individual cells are anecdotal or focus on a small subset of identified types. Here, we present the first systematic ex-vivo recording of light responses from 342 ganglion cells in human retinas obtained from donors. We find a great variety in the human retinal output in terms of preferences for positive or negative contrast, spatio-temporal frequency encoding, contrast sensitivity, and speed tuning. Some human ganglion cells showed similar response behavior as known cell types in other primate retinas, while we also recorded light responses that have not been described previously. This first extensive description of the human retinal output should facilitate interpretation of primate data and comparison to other mammalian species, and it lays the basis for the use of ex-vivo human retina for in-vitro analysis of novel treatment approaches.
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44
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Kang JH, Jang YJ, Kim T, Lee BC, Lee SH, Im M. Electric Stimulation Elicits Heterogeneous Responses in ON but Not OFF Retinal Ganglion Cells to Transmit Rich Neural Information. IEEE Trans Neural Syst Rehabil Eng 2021; 29:300-309. [PMID: 33395394 DOI: 10.1109/tnsre.2020.3048973] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Retinal implants electrically stimulate surviving retinal neurons to restore vision in people blinded by outer retinal degeneration. Although the healthy retina is known to transmit a vast amount of visual information to the brain, it has not been studied whether prosthetic vision contains a similar amount of information. Here, we assessed the neural information transmitted by population responses arising in brisk transient (BT) and brisk sustained (BS) subtypes of ON and OFF retinal ganglion cells (RGCs) in the rabbit retina. To correlate the response heterogeneity and the information transmission, we first quantified the cell-to-cell heterogeneity by calculating the spike time tiling coefficient (STTC) across spiking patterns of RGCs in each type. Then, we computed the neural information encoded by the RGC population in a given type. In responses to light stimulation, spiking activities were more heterogeneous in OFF than ON RGCs (STTCAVG = 0.36, 0.45, 0.77 and 0.55 for OFF BT, OFF BS, ON BT, and ON BS, respectively). Interestingly, however, in responses to electric stimulation, both BT and BS subtypes of OFF RGCs showed remarkably homogeneous spiking patterns across cells (STTCAVG = 0.93 and 0.82 for BT and BS, respectively), whereas the two subtypes of ON RGCs showed slightly increased populational heterogeneity compared to light-evoked responses (STTCAVG = 0.71 and 0.63 for BT and BS, respectively). Consequently, the neural information encoded by the electrically-evoked responses of a population of 15 RGCs was substantially lower in the OFF than the ON pathway: OFF BT and BS cells transmit only ~23% and ~53% of the neural information transmitted by their ON counterparts. Together with previously-reported natural spiking activities in ON RGCs, the higher neural information may make ON responses more recognizable, eliciting the biased percepts of bright phosphenes.
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45
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Synthesis and properties of an AIE fluorescent probe for Cu2+ detection based on ESIPT system. CHEMICAL PAPERS 2021. [DOI: 10.1007/s11696-020-01447-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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46
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Ahn J, Yoo Y, Goo YS. Spike-triggered Clustering for Retinal Ganglion Cell Classification. Exp Neurobiol 2020; 29:433-452. [PMID: 33321473 PMCID: PMC7788309 DOI: 10.5607/en20029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 11/19/2022] Open
Abstract
Retinal ganglion cells (RGCs), the retina's output neurons, encode visual information through spiking. The RGC receptive field (RF) represents the basic unit of visual information processing in the retina. RFs are commonly estimated using the spike-triggered average (STA), which is the average of the stimulus patterns to which a given RGC is sensitive. Whereas STA, based on the concept of the average, is simple and intuitive, it leaves more complex structures in the RFs undetected. Alternatively, spike-triggered covariance (STC) analysis provides information on second-order RF statistics. However, STC is computationally cumbersome and difficult to interpret. Thus, the objective of this study was to propose and validate a new computational method, called spike-triggered clustering (STCL), specific for multimodal RFs. Specifically, RFs were fit with a Gaussian mixture model, which provides the means and covariances of multiple RF clusters. The proposed method recovered bipolar stimulus patterns in the RFs of ON-OFF cells, while the STA identified only ON and OFF RGCs, and the remaining RGCs were labeled as unknown types. In contrast, our new STCL analysis distinguished ON-OFF RGCs from the ON, OFF, and unknown RGC types classified by STA. Thus, the proposed method enables us to include ON-OFF RGCs prior to retinal information analysis.
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Affiliation(s)
- Jungryul Ahn
- Department of Physiology, Chungbuk National University School of Medicine, Cheongju 28644, Korea
| | - Yongseok Yoo
- Department of Electronics Engineering, Incheon National University, Incheon 22012, Korea
| | - Yong Sook Goo
- Department of Physiology, Chungbuk National University School of Medicine, Cheongju 28644, Korea
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47
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Abstract
Detection of target objects in the surrounding environment is a common visual task. There is a vast psychophysical and modeling literature concerning the detection of targets in artificial and natural backgrounds. Most studies involve detection of additive targets or of some form of image distortion. Although much has been learned from these studies, the targets that most often occur under natural conditions are neither additive nor distorting; rather, they are opaque targets that occlude the backgrounds behind them. Here, we describe our efforts to measure and model detection of occluding targets in natural backgrounds. To systematically vary the properties of the backgrounds, we used the constrained sampling approach of Sebastian, Abrams, and Geisler (2017). Specifically, millions of calibrated gray-scale natural-image patches were sorted into a 3D histogram along the dimensions of luminance, contrast, and phase-invariant similarity to the target. Eccentricity psychometric functions (accuracy as a function of retinal eccentricity) were measured for four different occluding targets and 15 different combinations of background luminance, contrast, and similarity, with a different randomly sampled background on each trial. The complex pattern of results was consistent across the three subjects, and was largely explained by a principled model observer (with only a single efficiency parameter) that combines three image cues (pattern, silhouette, and edge) and four well-known properties of the human visual system (optical blur, blurring and downsampling by the ganglion cells, divisive normalization, intrinsic position uncertainty). The model also explains the thresholds for additive foveal targets in natural backgrounds reported in Sebastian et al. (2017).
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48
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Abstract
The physiological response properties of neurons in the visual system are inherited mainly from feedforward inputs. Interestingly, feedback inputs often outnumber feedforward inputs. Although they are numerous, feedback connections are weaker, slower, and considered to be modulatory, in contrast to fast, high-efficacy feedforward connections. Accordingly, the functional role of feedback in visual processing has remained a fundamental mystery in vision science. At the core of this mystery are questions about whether feedback circuits regulate spatial receptive field properties versus temporal responses among target neurons, or whether feedback serves a more global role in arousal or attention. These proposed functions are not mutually exclusive, and there is compelling evidence to support multiple functional roles for feedback. In this review, the role of feedback in vision will be explored mainly from the perspective of corticothalamic feedback. Further generalized principles of feedback applicable to corticocortical connections will also be considered.
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Affiliation(s)
- Farran Briggs
- Departments of Neuroscience and Brain and Cognitive Sciences, Del Monte Institute for Neuroscience, and Center for Visual Science, University of Rochester, Rochester, New York 14642, USA;
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Muralidharan M, Guo T, Shivdasani MN, Tsai D, Fried S, Li L, Dokos S, Morley JW, Lovell NH. Neural activity of functionally different retinal ganglion cells can be robustly modulated by high-rate electrical pulse trains. J Neural Eng 2020; 17:045013. [DOI: 10.1088/1741-2552/ab9a97] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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Murphy AJ, Hasse JM, Briggs F. Physiological characterization of a rare subpopulation of doublet-spiking neurons in the ferret lateral geniculate nucleus. J Neurophysiol 2020; 124:432-442. [PMID: 32667229 DOI: 10.1152/jn.00191.2020] [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: 11/22/2022] Open
Abstract
Interest in exploring homologies in the early visual pathways of rodents, carnivores, and primates has recently grown. Retinas of these species contain morphologically and physiologically heterogeneous retinal ganglion cells that form the basis for parallel visual information processing streams. Whether rare retinal ganglion cells with unusual visual response properties in carnivores and primates project to the visual thalamus and drive unusual visual responses among thalamic relay neurons is poorly understood. We surveyed neurophysiological responses among hundreds of lateral geniculate nucleus (LGN) neurons in ferrets and observed a novel subpopulation of LGN neurons displaying doublet-spiking waveforms. Some visual response properties of doublet-spiking LGN neurons, like contrast and temporal frequency tuning, were intermediate to those of X and Y LGN neurons. Interestingly, most doublet-spiking LGN neurons were tuned for orientation and displayed direction selectivity for horizontal motion. Spatiotemporal receptive fields of doublet-spiking neurons were diverse and included center/surround organization, On/Off responses, and elongated separate On and Off subregions. Optogenetic activation of corticogeniculate feedback did not alter the tuning or spatiotemporal receptive fields of doublet-spiking neurons, suggesting that their unusual tuning properties were inherited from retinal inputs. The doublet-spiking LGN neurons were found throughout the depth of LGN recording penetrations. Together these findings suggest that while extremely rare (<2% of recorded LGN neurons), unique subpopulations of LGN neurons in carnivores receive retinal inputs that confer them with nonstandard visual response properties like direction selectivity. These results suggest that neuronal circuits for nonstandard visual computations are common across a variety of species, even though their proportions vary.NEW & NOTEWORTHY Interest in visual system homologies across species has recently increased. Across species, retinas contain diverse retinal ganglion cells including cells with unusual visual response properties. It is unclear whether rare retinal ganglion cells in carnivores project to and drive similarly unique visual responses in the visual thalamus. We discovered a rare subpopulation of thalamic neurons defined by unique spike shape and visual response properties, suggesting that nonstandard visual computations are common to many species.
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Affiliation(s)
- Allison J Murphy
- Neuroscience Graduate Program, University of Rochester, Rochester, New York.,Center for Visual Science, University of Rochester, Rochester, New York
| | - J Michael Hasse
- Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine, Rochester, New York.,Center for Neural Science, New York University, New York, New York
| | - Farran Briggs
- Neuroscience Graduate Program, University of Rochester, Rochester, New York.,Center for Visual Science, University of Rochester, Rochester, New York.,Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine, Rochester, New York.,Department of Neuroscience, University of Rochester School of Medicine, Rochester, New York.,Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York
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