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Fish have highly developed vision that plays an important role in detecting and recognizing objects in different forms of visually guided behavior. All of these behaviors require high spatial resolution. The theoretical limit of spatial resolution is determined by the optics of the eye and the density of photoreceptors. However, further in the fish retina, each bipolar cell may collect signals from tens of photoreceptors, and each ganglion cell may collect signals from tens to hundreds of bipolar cells. If we assume that the input signals in this physiological funnel are simply summed, then fine gratings that are still distinguishable at the level of cones should not differ from the homogeneous surface for the ganglion cells. It is therefore generally considered that the resolution of the eye is determined not by the density of cones, but by the density of ganglion cells. Given the size of the receptive field of ganglion cells, one can conclude that the resolving power at the output of the fish retina should be ten times worse than at its input. But this contradicts the results of behavioral studies, for, as it is known, fish are able to distinguish periodic gratings at the limit of resolution of the cones. Our electrophysiological studies with extracellular recording of responses of individual ganglion cells to the motion of contrast gratings of different periods showed that the acuity of ganglion cells themselves is much higher and is close to the limit determined by the density of cones. The contradiction is explained by the fact that ganglion cells are not linear integrators of the input signals, their receptive fields being composed of subunits with significantly smaller zones of signal summation where nonlinear retinal processing takes place.

The output units of fish retina, i.e., the retinal ganglion cells (detectors), send highly processed information to the primary visual centers of the brain, settled in the midbrain formation tectum opticum (TO). Axons of different fish motion detectors terminate in different tectal levels. In the superficial layer of TO, axons of direction-selective ganglion cells (DS GCs) are terminated. Single unit responses of the DS GCs were recorded in intact fish from their axon terminals in TO. Goldfish DS GCs projecting to TO were shown to comprise six physiological types according to their selectivity to sign of stimulus contrast (ON and OFF units) and their preferred directions: three directions separated by 120${}^{\circ }$. These units, characterized by relatively small receptive fields and remarkable spatial resolution should be classified as local motion detectors. In addition to the retinal DS GCs, other kinds of DS units were extracellularly recorded in the superficial and deep sublaminae of tectum. Some features of their responses suggested that they originated from tectal neurons (TNs). Contrary to DS GCs which are characterized by small RFs and use separate ON and OFF channels, DS TNs have extra-large RFs and ON-OFF type responses. DS TNs were shown to select four preferred directions. Three of them are compatible with those already selected on the retinal level. Complementary to them, the fourth DS TN type with rostro-caudal preference (lacking in the retina) has been revealed. Possible functional interrelations between DS GCs and DS TNs are discussed.

Age-related macular degeneration and retinitis pigmentosa are two of the most common diseases that cause degeneration in the outer retina, which can lead to several visual impairments up to blindness. Vision restoration is an important goal for which several different research approaches are currently being pursued. We are concerned with restoration via retinal prosthetic devices. Prostheses can be implemented intraocularly and extraocularly, which leads to different categories of devices. Cortical Prostheses and Optic Nerve Prostheses are examples of extraocular solutions while Epiretinal Prostheses and Subretinal Prostheses are examples of intraocular solutions. Some of the prostheses that are successfully implanted and tested in animals as well as humans can restore basic visual functions but still have limitations. This paper will give an overview of the current state of art of Retinal Prostheses and compare the advantages and limitations of each type. The purpose of this review is thus to summarize the current technologies and approaches used in developing Retinal Prostheses and therefore to lay a foundation for future designs and research directions.

Color plays a key role in human vision but the neural machinery that underlies the transformation from stimulus to perception is not well understood. Here, we implemented a two-dimensional network model of the first stages in the primate parvocellular pathway (retina, lateral geniculate nucleus and layer 4C$\beta$ in V1) consisting of conductance-based point neurons. Model parameters were tuned based on physiological and anatomical data from the primate foveal and parafoveal vision, the most relevant visual field areas for color vision. We exhaustively benchmarked the model against well-established chromatic and achromatic visual stimuli, showing spatial and temporal responses of the model to disk- and ring-shaped light flashes, spatially uniform squares and sine-wave gratings of varying spatial frequency. The spatiotemporal patterns of parvocellular cells and cortical cells are consistent with their classification into chromatically single-opponent and double-opponent groups, and nonopponent cells selective for luminance stimuli. The model was implemented in the widely used neural simulation tool NEST and released as open source software. The aim of our modeling is to provide a biologically realistic framework within which a broad range of neuronal interactions can be examined at several different levels, with a focus on understanding how color information is processed.

The chronic and uncontrolled diabetes mellitus (DM) damages the retinal blood vessels leading to diabetic retinopathy (DR). The advanced stage of DR leads to loss of vision and subsequently blindness. The morphological changes during the progression of DR can be diagnosed using digital fundus images. The pathological changes in the retina influence the variations in pixel patterns which can be quantified using texture measures. In this paper, we have explored different texture measures namely statistical moments, gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), local binary pattern (LBP), laws mask energy (LME), fractal dimension (FD), fourier spectrum (FS) and Gabor wavelet to characterize and classify the normal and DR classes. We have tabulated 109 texture parameters for the normal and DR classes. Further, these features were subjected to empirical receiver operating characteristic (ROC) based ranking to select optimal feature set. The ranked nested features were fed to the support vector machine (SVM) classifier with different kernel functions to evaluate the highest performance measure using the least number of features to discriminate normal and DR classes. Our proposed system was evaluated using two different databases Kasturba Medical College Hospital (KMCH) and Tan Tock Seng Hospital (TTSH), each with 340 images (170 normal and 170 DR). We have also formulated an integrated index called as diabetic retinopathy risk index (DRRI) using selected texture features to discriminate normal and DR classes using single number. The proposed frame work can be used to help the clinicians and also for mass DR screening programs.

The present study investigated the neuroprotective effect of minocycline, a microglial inhibitor, against the retinal ischemia–reperfusion (IR) injury in the rat. The retinal IR injury was induced in Sprague–Dawley (SD) rats by infusing normal saline into anterior chamber of eye to create a higher intraocular pressure (IOP) than blood pressure for 45 min. Minocycline (45 and 90 mg/kg/day) was administered intraperitoneally to rats receiving IR injury. The neuroprotective effects were evaluated by morphometrical histology analysis 7 days after ischemia. The data was compared with the groups treated with saline and methylprenisolone (MP, 30 mg/kg, IV). The results showed that the retinal inner plexiform layer/outer nuclear layer (IPL/ONL) ratio was reduced following IR damage compared with that in the normal control. The IPL/ONL ratio was reduced to 43.5% in the IR-control group, 93.3% and 93.6% in the Mino-45 and Mino-90 group. The IPL/ONL ratio was preserved to 95.7% in the MP group. These results suggest that minocycline and methylprednisolone showed significantly good neuroprotective effects demonstrated in retinal histology of the rats under retinal IR injury.

Precise mathematical modeling of the primary visual cortex (V1) is still a challenging problem. Due to the high similarity of visual system of cat and human, in this paper, we present a hybrid model to track the electrical responses of neurons that are measured by a multi-electrode array implanted in cat V1. The proposed model combines a stochastic phenomenological model with a multilayer leaky integrate-and-fire (LIF) model to predict V1 responses. Since all the existing visual cortex models do not capture the stochastic properties of synaptic changes, the proposed phenomenological model provides input currents for V1 by utilizing continuous chaotic neural equations with a quantization rule. Then a multilayer LIF model is presented to mimic the functions of lateral geniculate nucleus (LGN) and V1 neurons by their corresponding differential equations. The input current in these models is from the presynaptic neurons, which are computed using the LIF model. The LGN-V1 neuronal connections are adopted from previous studies, where the receptive fields (RFs) of LGN neurons converge onto elongated spatial structures that denote RFs of V1 neurons. The main purpose of this paper is to develop a short-term plasticity model that is more consistent with the nature of the LGN and V1 responses compared to state-of-the-art models. Previous studies have not incorporated the stochastic and quantized behaviors of neurons that in the recorded data of implemented electrodes. The experimental results show the ability of the proposed model to accurately predict spikes recorded experimentally, indicating the model outperforms the state-of-the-art method.