Biology subjects

Benosman, R.

Publications and source records attributed to Benosman, R..

4 recordsLinked to original sources

bioRxiv2020

Optogenetic therapy: High spatiotemporal resolution and pattern recognition compatible with vision restoration in non-human primates

Restoring vision using optogenetics is an ideal medical application because the eye offers a direct window to access and stimulate the pathological area: the retina. Optogenetic therapy could be applied to diseases with photoreceptor degeneration such as retinitis pigmentosa. Here, we select the specific optogenetic construct that is now used in the clinical trial and assess the opsin functional efficacy on non-human primates retinal ganglion cells (RGCs). We chose the microbial opsin ChrimsonR and showed that the vector AAV2.7m8 produced greater transfection in RGCs compared to AAV2, and that ChrimsonR attached to tdTomato (ChR-tdT) is more efficiently expressed than ChrimsonR. The 600 nm light activates the RGCs transfected with the vector AAV2.7m8-ChR-tdT from an irradiance of 1015 photons.cm-2.s-1. Vector doses of 5.1010 and 5.1011 vg/eye transfect up to 7000 RGCs/mm2 in the perifovea, with no significant immune reaction. Furthermore, using a multielectrode array we recorded RGCs responses starting from 1ms stimulus duration. Using the recorded activity we were able to decode stimulus information and estimate a theoretical visual acuity of 20/249, above legal blindness. Altogether, our results pave the way for the ongoing clinical trial with the AAV2.7m8-ChrimsonR-tdT vector for vision restoration in patients affected by retinitis pigmentosa. One Sentence SummaryWe select here the vector and genetic construct best suited to provide vision restoration in patients suffering from retinopathies, we demonstrate temporal resolution compatible with high dynamic visual scenes and a visual acuity above legal blindness.

neuroscience↗

bioRxiv2019

Cortical visual prosthesis: a detailed large-scale simulation study

Recent advances in applying optogenetics in primates initiated the development of light based prosthetic implants for sensory restoration. Thanks to being the most well explored cortical area that is readily accessible at the surface of the brain, vision restoration via direct optogenetic activation of primary visual cortex is one of the most promising early targets for a optogenetics based prosthetic program. However, two fundamental elements of the cortical optogenetic prosthesis remain unclear. First, the exact mechanisms of neural dynamics under direct cortical stimulation, especially in the context of living, active and functionally specific intra-cortical neural circuitry, is poorly understood. Second, we lack protocols for transformation of arbitrary visual stimuli into light activation patterns that would induce perception of the said stimulus by the subject. In this study we address these issues using a large-scale spiking neural network modeling strategy of high biological fidelity. We examine the relationship between specific spatial configuration of light delivered to cortex and the resulting spatio-temporal pattern of activity evoked in the simulated cortical circuitry. Using such virtual experiments, we design a protocol for translation of a specific set of stimuli to activation pattern of a matrix of light emitting elements and provide a detailed assessment of the resulting cortical activations with respect to the natural vision control condition. In this study we restrict our focus to the grating stimulus class, which are an ideal starting point for exploration due to their thoroughly characterized representation in V1 and well-defined information content. However, we also provide an outline of a straight-forward road-map for transforming this grating centric stimulation protocol towards general strategy capable of transforming arbitrary spatio-temporal visual stimulus to a spatio-temporal pattern of light, thus enabling vision restoration via optogenetic V1 activation.

neuroscience↗

bioRxiv2018

Faster is better: Visual responses to motion are stronger for higher refresh rates

Although neural responses with a millisecond precision were reported in the retina, lateral geniculate nucleus and visual cortex of multiple species, the presence and role of such a fine temporal structure is still debated at the cortical level and the general belief remains that early visual system encodes information at slower timescales. In this study, we used a new stimulation platform to generate visual stimuli that were very precisely encoded in time and we characterized in human subjects the EEG responses to moving patterns that shared the same global motion but differed in their fine scale spatio-temporal properties. In two experiments, we manipulated the information within temporal windows that corresponded to the frame duration in conventional (1/60 = 16.7ms, experience 1) and more recent (1/120 = 8.3ms, experience 2) visual displays. Our results demonstrate that EEG responses to temporally dense and coherent trajectories are significantly stronger than those to control conditions without these properties. They extend previous results from our group that showed that accurate temporal information (<10ms) significantly improve perceptual judgments on spatial discrimination, digit recognition and sensitivity for speed [Kime et al., 2016]. Altogether, our results suggest that instead of low-pass filtering the temporal information it receives from its thalamic afferents, the visual cortex may actually exploit its richness to improve visual perception.\n\nSignificance statementMost visual experiments use frame-based stimulation screens which are synchronous and slow. This might not engage the full encoding capacity of the visual system, as in natural condition, visual information is asynchronously acquired by the retina with a very high temporal resolution. In the present study, we used an unconventional and highly configurable stimulation platform to determine the EEG responses to moving patterns that shared the same global motion but differed in their fine scale (<10ms) spatio-temporal properties. Our results demonstrate that brain responses in human are significantly stronger for motion patterns that are refreshed at very high frame rate (360Hz) and thereby provide a strong support for the use of very precise temporal stimulations in vision studies.

neuroscience↗

bioRxiv2018

Modeling the Electro-chemical Properties of Microbial Opsin ChrimsonR for Application to Optogenetics-based Vision Restoration

Optogenetic activation of neurons [1] have greatly contributed to our understanding of how neural circuits operate, and holds huge promise in the field of neural prosthetics, particularly in sensory restoration. The discovery of new channelrhodopsins, Chrimson -- which is 45 nm more red-shifted than any previously discovered or engineered channelrhodopsin -- and its mutant ChrimsonR with faster kinetics [2] made this technology available for medical applications. However, a detailed model that would be able to accurately reproduce the membrane potential dynamics in cells transfected with ChrimsonR under light stimulation is missing. We address this issue by developing the first model for the electrochemical behavior of ChrimsonR that predicts its conductance in response to arbitrary light stimulation. Our model captures ON and OFF dynamics of the protein for stimuli with frequencies up to 100 Hz and their relationship with the brightness, as well as its activation curve, the steady-state amplitude of the response as a function of light intensity. Additionally, we capture a slow adaptation mechanism at a timescale at the order of minutes. Our model holds for light intensities covering the whole dynamic range of the channel (from response onset to saturation) and for timescales in the order of up to several minutes. This model is a new step towards modeling the spiking activity of ChrimsonR-expressing neurons, required for the precise control of information transmission in optogenetics-based Brain-Computer Interfaces, and will inform future applications of ChrimsonR based optogenetics.

neuroscience↗