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Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or 'phosphenes') has limited resolution, and a great portion of the field's research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator's suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.

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The image fusion algorithm has great application value in the domain of computer vision, which makes the fused image have a more comprehensive and clearer description of the scene, and is beneficial to human eye recognition and automatic mechanical detection. In recent years, image fusion algorithms have achieved great success in different domains. However, it still has huge challenges in terms of the generalization of multi-modal image fusion. In reaction to this problem, this paper proposes a general image fusion framework based on an improved convolutional neural network. Firstly, the feature information of the input image is captured by the multiple feature extraction layers, and then multiple feature maps are stacked along the number of channels to acquire the feature fusion map. Finally, feature maps, which are derived from multiple feature extraction layers, are stacked in high dimensions by skip connection and convolution filtering for reconstruction to produce the final result. In this paper, multi-modal images are gained from multiple datasets to produce a large sample space to adequately train the network. Compared with the existing convolutional neural networks and traditional fusion algorithms, the proposed model not only has generality and stability but also has some strengths in subjective visualization and objective evaluation, while the average running time is at least 94% faster than the reference algorithm based on neural network.

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Loss of vision is a pressing medical and social problem leading to profound disability, loss of ability to work, serious alterations in the psycho-emotional state, and a decline of the quality of life. When conservative or surgical treatment can not help restore vision, the use of visual prosthesis - bionic eye - can be an effective solution. This review covers the main modern approaches to the development of visual prosthetic systems. Analysis of publications revealed that there are several main approaches to visual prosthesis differing primarily by the anatomical structure targeted for stimulation in order to activate visual sensations. The most significant among them are retinal prostheses, optic nerve stimulation, and cortical visual prostheses. Currently, retinal prostheses such as ARGUS II demonstrate the most successful results, since the stimulation of the surviving neural structures of the retina is a relatively easy task, but their field of application is limited to diseases associated with pathological changes in photoreceptors. The development of cortical visual prostheses is more difficult, but in the future they may allow using more stimulation channels to obtain a more detailed visual perception. In addition, cortical visual prostheses are universal, as they do not require preservation of any structures of the visual organ, only the primary visual cortex.

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With the development of bionic computer vision for images processing, researchers have easily obtained high-resolution zoom sensing images. The development of drones equipped with high-definition cameras has greatly increased the sample size and image segmentation and target detection are important links during the process of image information. As biomimetic remote sensing images are usually prone to blur distortion and distortion in the imaging, transmission and processing stages, this paper improves the vertical grid number of the YOLO algorithm. Firstly, the light and shade of a high-resolution zoom sensing image were abstracted, and the grey-level cooccurrence matrix extracted feature parameters to quantitatively describe the texture characteristics of the zoom sensing image. The Simple Linear Iterative Clustering (SLIC) superpixel segmentation method was used to achieve the segmentation of light/dark scenes, and the saliency area was obtained. Secondly, a high-resolution zoom sensing image model for segmenting light and dark scenes was established to made the dataset meet the recognition standard. Due to the refraction of the light passing through the lens and other factors, the difference of the contour boundary light and dark value between the target pixel and the background pixel would make it difficult to detect the target, and the pixels of the main part of the separated image would be sharper for edge detection. Thirdly, a YOLO algorithm with an improved vertical grid number was proposed to detect the target in real time on the processed superpixel image array. The adjusted aspect ratio of the target in the remote sensing image modified the number of vertical grids in the YOLO network structure by using 20 convolutional layers and five maximum aggregation layers, which was more accurately adapted to "short and coarse" of the identified object in the information density. Finally, through comparison with the improved algorithm and other mainstream algorithms in different environments, the test results on the aid dataset showed that in the target detection of high spatial resolution zoom sensing images, the algorithm in this paper showed higher accuracy than the YOLO algorithm and had real-time performance and detection accuracy.

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PURPOSE OF REVIEW: The goal is providing an update to the latest research surrounding optoelectronic devices, highlighting key studies and benefits and limitations of each device. RECENT FINDINGS: The Argus II demonstrated long-term safety after five-year follow-up. Due to lack of tack fixation, subretinal implants appear to displace over time. PRIMA's completed primate trial showed initial safety and potential for improved vision, resulting in ongoing clinical trials Bionic Vision Australia developed a new 44-electrode suprachoroidal device currently in a clinical trial. Orion (cortical stimulation) is currently undergoing a clinical trial to demonstrate safety. SUMMARY: Devices using external camera for images are unaffected by corneal or lens opacities but disconnect eye movements from image perception, while the opposite is true for implants directly detecting light. Visual acuity provided by devices is more complicated than implant electrode density and new devices aim to target this with innovative approaches.

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This article discusses bionic vision through the author's experiences as Australia's first research participant in an early prototype bionic eye trial. During her two-year participation, she drew on various theoretical perspectives, including critical and community development approaches that not only influence her professional social work perspective, but extend to her personal worldview. In a rapidly emerging biotechnological age, this article contributes a holistic perspective, bringing into focus theory and practice; issues of human experience, human rights, and oppressive relationships; tensions between agency and structure (particularly relating to disability from a social model of disability and the medical model); and practical applications of artificial vision. Beyond its practical applications, illuminated is the relevance of community development values and principles such as a sense of connectedness, participation, and empowerment, which are understood in terms of an antioppressive perspective. The article concludes by recognizing the potential benefit of bionic vision for vision-impaired and blind people in their everyday lives.

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Electrical stimulation of excitable cells provides therapeutic benefits for a variety of medical conditions, including restoration of partial vision to those blinded via some types of retinal degeneration. To improve visual percepts elicited by the current technology, researchers are conducting acute electrophysiology experiments, mainly in cats. However, the rat can provide a model of a range of retinal diseases and possesses a sufficiently large eye to be used in this field. This article presents a long-term anesthetic protocol to enable electrophysiology experiments to further the development of visual prostheses. Six Long-Evans rats (aged between 14 and 16 weeks) were included in this study. Surgical anesthesia was maintained for more than 15 h by combining constant intravenous infusion of ketamine (24.0-34.5 mg/kg/h), xylazine (0.9-1.2 mg/kg/h), and inhaled isoflurane in oxygen (<0.5%). Overall heart rate, respiratory rate, and body temperature remained between 187-233 beats/min, 45-58 breaths/min, and 36-38 °C, respectively. Neural responses to 200-ms light pulses were recorded from the superior colliculus using a 32-channel neural probe at the beginning and before termination of the experiment. Robust responses were recorded from distinct functional types of retinal pathways. In addition, a platinum electrode was implanted in the retrobulbar space. The retina was electrically stimulated, and the activation threshold was determined to be 5.24 ± 0.24 µC/cm2 . This protocol may be used not only in the field of visual prosthesis research, but in other research areas requiring longer term acute experiments.

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BACKGROUND/AIMS: Retinal prostheses use electrical stimulation to restore functional vision to patients blinded by retinitis pigmentosa. A key detail is the spatial pattern of ganglion cells activated by stimulation. Therefore, we characterized the spatial extent of network-mediated electrical activation of retinal ganglion cells (RGCs) in the epiretinal monopolar electrode configuration. METHODS: Healthy mouse RGC activities were recorded with a micro-electrode array (MEA). The stimuli consisted of monophasic rectangular cathodic voltage pulses and cycling full-field light flashes. RESULTS: Voltage tuning curves exhibited significant hysteresis, reflecting adaptation to electrical stimulation on the time scale of seconds. Responses decreased from 0 to 300 µm, and were also dependent on the strength of stimulation. Applying the Rayleigh criterion to the half-width at half-maximum of the electrical point spread function suggests a visual acuity limit of no better than 20/946. Threshold voltage showed only a modest increase across these distances. CONCLUSION: The existence of significant hysteresis requires that future investigations of electrical retinal stimulation control for such long-memory adaptation. The spread of electrical activation beyond 200 µm suggests that neighbouring electrodes in epiretinal implants based on indirect stimulation of RGCs may be indiscriminable at interelectrode spacings as large as 400 µm.

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After more than 40 years of research, visual prostheses are moving from the laboratory into the clinic. These devices are designed to provide prosthetic vision to the blind by stimulating localized neural populations in one of the retinotopically organized structures of the visual pathway - typically the retina or visual cortex. The long gestation of this research reflects the many significant technical challenges encountered including surgical access, mechanical stability, hardware miniaturization, hermetic encapsulation, high-density electrode arrays, and signal processing. This review provides an introduction to the pathophysiology of blindness; an overview of existing visual prostheses, their advantages and drawbacks; the perceptual effects evoked by electrical stimulation; as well as the role played by plasticity and training in clinical outcomes.

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Rapid, accurate reading is possible when isolated, single words from a sentence are sequentially presented at a fixed spatial location. We investigated if reading of words and sentences is possible when single letters are rapidly presented at the fovea under user-controlled or automatically controlled rates. When tested with complete sentences, trained participants achieved reading rates of over 60 wpm and accuracies of over 90% with the single letter reading (SLR) method and naive participants achieved average reading rates over 30 wpm with greater than 90% accuracy. Accuracy declined as individual letters were presented for shorter periods of time, even when the overall reading rate was maintained by increasing the duration of spaces between words. Words in the lexicon that occur more frequently were identified with higher accuracy and more quickly, demonstrating that trained participants have lexical access. In combination, our data strongly suggest that comprehension is possible and that SLR is a practicable form of reading under conditions in which normal scanning of text is not possible, or for scenarios with limited spatial and temporal resolution such as patients with low vision or prostheses.

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Altering the geometry of microelectrodes for use in a cortical neural prosthesis modifies the electric field generated in tissue, thereby affecting electrode efficacy and tissue damage. Commonly, electrodes with an active region located at the tip ("conical" electrodes) are used for stimulation of cortex but there is argument to believe this geometry may not be the best. Here we use finite element analysis to compare the electric fields generated by three types of electrodes, a conical electrode with exposed active tip, an annular electrode with active area located up away from the tip, and a striped annular electrode where the active annular region has bands of insulation interrupting the full active region. The results indicate that the current density on the surface of the conical electrodes can be up to 10 times greater than the current density on the annular electrodes of the same height, which may increase the propensity for tissue damage. However choosing the most efficient electrode geometry in order to reduce power consumption is dependent on the distance of the electrode to the target neurons. If neurons are located within 10 µm of the electrode, then a small conical electrode would be more power efficient. On the other hand if the target neuron is greater than 500 µm away-as happens normally when insertion of an array of electrodes into cortex results in a "kill zone" around each electrode due to insertion damage and inflammatory responses-then a large annular electrode would be more efficient.