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document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":96586633,"attachmentType":"pdf","workUrl":"https://www.academia.edu/94007172/Stochastic_Integrate_And_Fire_Model_For_The_Retina"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":96586633,"attachmentType":"pdf","workUrl":"https://www.academia.edu/94007172/Stochastic_Integrate_And_Fire_Model_For_The_Retina"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 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The spike generation mechanism of the models is typically performed by a Poisson process. Alternatively, a more realistic approach can be used by implementing an integrate and fire mechanism. In this paper we show that the Stochastic Leaky Integrate and Fire (SLIF) model is equivalent to a non-linear Poisson-based model. Furthermore, it proposes a dynamic model for the retina visual processing path, achieved through modulations. For estimating this model a two-step approach is proposed: i) an initial estimation is computed by using a spike-triggered analysis, and ii) the likelihood of the spike train is maximised by gradient ascent.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"TOWARDS A UNIFIED MODEL FOR THE RETINA - Static vs Dynamic Integrate and Fire Models","attachmentId":96586630,"attachmentType":"pdf","work_url":"https://www.academia.edu/94007170/TOWARDS_A_UNIFIED_MODEL_FOR_THE_RETINA_Static_vs_Dynamic_Integrate_and_Fire_Models","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/94007170/TOWARDS_A_UNIFIED_MODEL_FOR_THE_RETINA_Static_vs_Dynamic_Integrate_and_Fire_Models"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="17908935" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/17908935/Impulse_RETINA_model_comparison_between_biological_data_and_the_results_of_the_simulation">Impulse RETINA model: comparison between biological data and the results of the simulation</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37824259" href="https://independent.academia.edu/EmmanuelMarilly">Emmanuel Marilly</a></div><p class="ds-related-work--metadata ds2-5-body-xs">The Second International Symposium on Neuroinformatics and Neurocomputers, 1995</p><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT The model RETINA developed by the Laboratory LACOS (University of Le Havre, France) in collaboration with A.B. Kogan Research Institute for Neurocybernetics (Rostov State University, Russia) is a retinal neural network. It has been shown that the response given by this model allowed one to envisage a new approach in artifical vision. The implantation of the impulse neurons in RETINA allows us to get a frequency encoding of the informations. The main interest of the impulse RETINA is its reaction to the stimuli in movement or stationary with different shapes and velocities. The aim of this research is to develop a new artifical visual sensor. In this paper, the simulation results of the impulse RETINA are analyzed and compared with the biological results</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Impulse RETINA model: comparison between biological data and the results of the simulation","attachmentId":42218439,"attachmentType":"pdf","work_url":"https://www.academia.edu/17908935/Impulse_RETINA_model_comparison_between_biological_data_and_the_results_of_the_simulation","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/17908935/Impulse_RETINA_model_comparison_between_biological_data_and_the_results_of_the_simulation"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="17416327" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/17416327/Physiological_engineering_model_of_the_outer_retina">Physiological engineering model of the outer retina</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37143330" href="https://independent.academia.edu/ShiroUsui">Shiro Usui</a></div><p class="ds-related-work--abstract ds2-5-body-sm">In the vertebrate retina, the outer plexiform layer which consists of synaptic connections among photoreceptors, horizontal cells and bipolar cells, plays a fundamental role in color- and spatial-information processings. Developing a quantitative model of the outer retina is essential toward better understanding of the outer plexiform layer. Here we propose ionic current models of photoreceptor, horizontal cell and bipolar cells based on the published experimental data. The models provide a better understanding of the functional role of the ionic currents in outer retinal cells in generating the electrical responses. We also discuss how the function of the retinal outer plexiform layer may be studied by constructing a network model from the ionic current based single cell models</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Physiological engineering model of the outer retina","attachmentId":42261622,"attachmentType":"pdf","work_url":"https://www.academia.edu/17416327/Physiological_engineering_model_of_the_outer_retina","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/17416327/Physiological_engineering_model_of_the_outer_retina"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="108423672" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/108423672/Multiscale_modeling_of_ocular_physiology">Multiscale modeling of ocular physiology</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="5476151" href="https://independent.academia.edu/RiccardoSacco">Riccardo Sacco</a></div><p class="ds-related-work--metadata ds2-5-body-xs">HAL (Le Centre pour la Communication Scientifique Directe), 2018</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multiscale modeling of ocular physiology","attachmentId":106811800,"attachmentType":"pdf","work_url":"https://www.academia.edu/108423672/Multiscale_modeling_of_ocular_physiology","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/108423672/Multiscale_modeling_of_ocular_physiology"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="75679962" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/75679962/A_Computational_Model_Simulates_Light_Evoked_Responses_in_the_Retinal_Cone_Pathway">A Computational Model Simulates Light-Evoked Responses in the Retinal Cone Pathway</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33912975" href="https://usc.academia.edu/JeanmarieBouteiller">Jean-Marie C Bouteiller</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)</p><p class="ds-related-work--abstract ds2-5-body-sm">Partial vision restoration on degenerated retina can be achieved by electrically stimulating the surviving retinal ganglion cells via implanted electrodes to elicit a signal corresponding to the natural response of the cells. Realistic computational models of electrical stimulation of the retina can prove useful to test different stimulation strategies and improve the performance of retinal implants. Simulation of healthy retinal networks and their dynamical response to natural light stimulation may also help us understand how retinal processing takes place via a series of electrical signals flowing through different stages of retinal processing, ultimately giving rise to visual percepts. Such models may provide further insights on retinal network processing and thus guide the design of retinal prostheses and their stimulation protocols to generate more natural percepts. This work aims to characterize the photocurrent generated by healthy cone photoreceptors in response to a light flash stimulation and the resulting membrane potential for the photoreceptors and its postsynaptic cone bipolar cells. A simple network of ten cone photoreceptors synapsing with a cone bipolar cell is simulated using the NEURON environment and validated against patch-clamp recordings of cone photoreceptors and ON-type bipolar cells (ON-BC). The results presented will be valuable in modeling light-evoked or electrically stimulated retinal networks that comprise cone pathways. The computational models and methods developed in this work will serve as an integral building block in the development of large and realistic retinal networks. Clinical Relevance-Accurate computational model of a retinal neural network can help in predicting cell responses to electrical stimulation in vision restoration therapies using prostheses. It can be leveraged to optimize the stimulation parameters to match the natural light response of the network as closely as possible.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Computational Model Simulates Light-Evoked Responses in the Retinal Cone Pathway","attachmentId":83353966,"attachmentType":"pdf","work_url":"https://www.academia.edu/75679962/A_Computational_Model_Simulates_Light_Evoked_Responses_in_the_Retinal_Cone_Pathway","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/75679962/A_Computational_Model_Simulates_Light_Evoked_Responses_in_the_Retinal_Cone_Pathway"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="23634605" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/23634605/Stochastic_retinal_mechanisms_of_light_adaptation_and_gain_control">Stochastic retinal mechanisms of light adaptation and gain control</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11302330" href="https://washington.academia.edu/MichaelRudd">Michael Rudd</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Under appropriate experimental conditions, the threshold intensity of a visual stimulus varies as the square-root of the background illuminance. This square-root law has been observed in both psychophysical threshold experiments and in measurements of the thresholds of individual ganglion cells. A signal detection theory developed in the 1940s by H. L. de Vries and A. Rose, and since elaborated by H. B. Barlow and others, explains the square-root law on the basis of 'noise' due to fluctuations in the number of photon absorptions per unit area and unit time at the cornea. An alternative account of the square-root law - and also other threshold-vs-intensity slopes - is founded on the assumption of physiological gain control (W. A. H. Rushton, Proc. Roy. Soc. (London) B 162, 20-46, 1965; W. S. Geisler, J. Physiol. (London) 312, 165-179, 1979). In this paper, a neural model of light adaptation and gain control is described that shows how these two accounts of the square-root law can be reconciled by a stochastic gain control mechanism whose gain depends on the photon fluctuation level. The process by which spikes are generated in a ganglion cell is modeled in terms of a stochastic integrate-and-fire mechanism; this model is used to quantitatively fit toad retinal ganglion cell threshold data. A psychophysical model is then outlined showing how a statistical observer could analyze the ganglion cell spike trains generated by 'signal' and 'noise' trials in order to statistically discriminate the two conditions. The model is also shown to account for some dynamic aspects of ganglion cell responses, including ON- and OFF-responses. The neural light adaptation model predicts that - under the proper conditions - brightness matching judgments will also be subject to a square-root law. Experimental tests of the model under superthreshold conditions are proposed.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Stochastic retinal mechanisms of light adaptation and gain control","attachmentId":44045615,"attachmentType":"pdf","work_url":"https://www.academia.edu/23634605/Stochastic_retinal_mechanisms_of_light_adaptation_and_gain_control","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/23634605/Stochastic_retinal_mechanisms_of_light_adaptation_and_gain_control"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="17629027" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/17629027/_title_Computational_model_of_retinal_photocoagulation_and_rupture_title_"><title>Computational model of retinal photocoagulation and rupture</title></a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37492008" href="https://independent.academia.edu/PhilipHuie">Philip Huie</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Ophthalmic Technologies XIX, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">In patterned scanning laser photocoagulation, shorter duration (< 20 ms) pulses help reduce thermal damage beyond the photoreceptor layer, decrease treatment time and minimize pain. However, safe therapeutic window (defined as the ratio of rupture threshold power to that of light coagulation) decreases for shorter exposures. To quantify the extent of thermal damage in the retina, and maximize the therapeutic window, we developed a computational model of retinal photocoagulation and rupture. Model parameters were adjusted to match measured thresholds of vaporization, coagulation, and retinal pigment epithelial (RPE) damage. Computed lesion width agreed with histological measurements in a wide range of pulse durations and power. Application of ring-shaped beam profile was predicted to double the therapeutic window width for exposures in the range of 1 -10 ms.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"\u003ctitle\u003eComputational model of retinal photocoagulation and rupture\u003c/title\u003e","attachmentId":39623695,"attachmentType":"pdf","work_url":"https://www.academia.edu/17629027/_title_Computational_model_of_retinal_photocoagulation_and_rupture_title_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/17629027/_title_Computational_model_of_retinal_photocoagulation_and_rupture_title_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="91200401" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91200401/A_Nonlinear_Model_of_Spatiotemporal_Retinal_Processing_Simulations_of_X_and_Y_Retinal_Ganglion_Cell_Behavior">A Nonlinear Model of Spatiotemporal Retinal Processing: Simulations of X and Y Retinal Ganglion Cell Behavior</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="44686146" href="https://independent.academia.edu/PaoloGaudiano">Paolo Gaudiano</a></div><p class="ds-related-work--metadata ds2-5-body-xs">1993</p><p class="ds-related-work--abstract ds2-5-body-sm">Alfred P. Sloan Research Fellowship (BR-3122); Air Force Office of Scientific Research (F49620-92-J-0499)</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Nonlinear Model of Spatiotemporal Retinal Processing: Simulations of X and Y Retinal Ganglion Cell Behavior","attachmentId":94555057,"attachmentType":"pdf","work_url":"https://www.academia.edu/91200401/A_Nonlinear_Model_of_Spatiotemporal_Retinal_Processing_Simulations_of_X_and_Y_Retinal_Ganglion_Cell_Behavior","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91200401/A_Nonlinear_Model_of_Spatiotemporal_Retinal_Processing_Simulations_of_X_and_Y_Retinal_Ganglion_Cell_Behavior"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="108647764" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/108647764/Main_Retina_Information_Processing_Pathways_Modeling">Main Retina Information Processing Pathways Modeling</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="208787082" href="https://independent.academia.edu/XudongGuan">Xudong Guan</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Cognitive Informatics and Natural Intelligence, 2011</p><p class="ds-related-work--abstract ds2-5-body-sm">In many fields including digital image processing and artificial retina design, they always confront a balance issue among real-time, accuracy, computing load, power consumption, and other factors. It is difficult to achieve an optimal balance among these conflicting requirements. However, human retina can balance these conflicting requirements very well. It can efficiently and economically accomplish almost all the visual tasks. This paper presents a bio-inspired model of the retina, not only to simulate various types of retina cells but also to simulate complex structure of retina. The model covers main information processing pathways of retina so that it is much closer to the real retina. In this paper, the authors did some research on various characteristics of retina via large-scale statistical experiments, and further analyzed the relationship between retina’s structure and functions. The model can be used in bionic chip design, physiological assumptions verification, image pr...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Main Retina Information Processing Pathways Modeling","attachmentId":106975442,"attachmentType":"pdf","work_url":"https://www.academia.edu/108647764/Main_Retina_Information_Processing_Pathways_Modeling","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/108647764/Main_Retina_Information_Processing_Pathways_Modeling"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="108423617" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/108423617/Multiscale_nature_of_ocular_physiology">Multiscale nature of ocular physiology</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="5476151" href="https://independent.academia.edu/RiccardoSacco">Riccardo Sacco</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal for modeling in ophthalmology, 2018</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multiscale nature of ocular physiology","attachmentId":106811773,"attachmentType":"pdf","work_url":"https://www.academia.edu/108423617/Multiscale_nature_of_ocular_physiology","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/108423617/Multiscale_nature_of_ocular_physiology"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":96586633,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":96586633,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_96586633" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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