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The development of automatic methods for image and video quality assessment that correlate well with the perception of human observers is a very challenging open problem in vision science, with numerous practical applications in disciplines such as image processing and computer vision, as well as in the media industry. In the past two decades, the goal of image quality research has been to improve upon classical metrics by developing models that emulate some aspects of the visual system, and while the progress has been considerable, state-of-the-art quality assessment methods still share a number of shortcomings, like their performance dropping considerably when they are tested on a database that is quite different from the one used to train them, or their significant limitations in predicting observer scores for high framerate videos. In this work we propose a novel objective method for image and video quality assessment that is based on the recently introduced Intrinsically Non-linear Receptive Field (INRF) formulation, a neural summation model that has been shown to be better at predicting neural activity and visual perception phenomena than the classical linear receptive field. Here we start by optimizing, on a classic image quality database, the four parameters of a very simple INRF-based metric, and proceed to test this metric on three other databases, showing that its performance equals or surpasses that of the state-of-the-art methods, some of them having millions of parameters. Next, we extend to the temporal domain this INRF image quality metric, and test it on several popular video quality datasets; again, the results of our proposed INRF-based video quality metric are shown to be very competitive. [ABSTRACT FROM AUTHOR]

We showthat classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks as long as (i) the retina converts the input radiation into any tristimulus-like representation, and (ii) the post-retinal network solves the standard hue cancellation task, e.g. the network looks for the weights of the cancelling lights so that every monochromatic stimulus plus the weighted cancelling lights match a grey reference in the (arbitrary) color representation used by the network. In fact, the specific cancellation lights (and not the network architecture) are key to obtain human-like curves: results show that the classical choice of the lights is the one that leads to the best (more human-like) result, and any other choices lead to progressively different spectral sensitivities. We show this in two ways: through artificial psychophysics using a range of networks with different architectures and a range of cancellation lights, and through a change-of-basis theoretical analogy of the experiments. This suggests that the opponent curves of the classical experiment are just a by-product of the front-end photoreceptors and of a very specific experimental choice but they do not inform about the downstream color representation. In fact, the architecture of the post-retinal network (signal recombination or internal color space) seems irrelevant for the emergence of the curves in the classical experiment. This result in artificial networks questions the conventional interpretation of the classical result in humans by Jameson and Hurvich. [ABSTRACT FROM AUTHOR]

The development of automatic methods for image and video quality assessment that correlate well with the perception of human observers is a very challenging open problem in vision science, with numerous practical applications in disciplines such as image processing and computer vision, as well as in the media industry. In the past two decades, the goal of image quality research has been to improve upon classical metrics by developing models that emulate some aspects of the visual system, and while the progress has been considerable, state-of-the-art quality assessment methods still share a number of shortcomings, like their performance dropping considerably when they are tested on a database that is quite different from the one used to train them, or their significant limitations in predicting observer scores for high framerate videos. In this work we propose a novel objective method for image and video quality assessment that is based on the recently introduced Intrinsically Non-linear Receptive Field (INRF) formulation, a neural summation model that has been shown to be better at predicting neural activity and visual perception phenomena than the classical linear receptive field. Here we start by optimizing, on a classic image quality database, the four parameters of a very simple INRF-based metric, and proceed to test this metric on three other databases, showing that its performance equals or surpasses that of the state-of-the-art methods, some of them having millions of parameters. Next, we extend to the temporal domain this INRF image quality metric, and test it on several popular video quality datasets; again, the results of our proposed INRF-based video quality metric are shown to be very competitive.

We show that classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks as long as (i) the retina converts the input radiation into any tristimulus-like representation, and (ii) the post-retinal network solves the standard hue cancellation task, e.g. the network looks for the weights of the cancelling lights so that every monochromatic stimulus plus the weighted cancelling lights match a grey reference in the (arbitrary) color representation used by the network. In fact, the specific cancellation lights (and not the network architecture) are key to obtain human-like curves: results show that the classical choice of the lights is the one that leads to the best (more human-like) result, and any other choices lead to progressively different spectral sensitivities. We show this in two ways: through artificial psychophysics using a range of networks with different architectures and a range of cancellation lights, and through a change-of-basis theoretical analogy of the experiments. This suggests that the opponent curves of the classical experiment are just a by-product of the front-end photoreceptors and of a very specific experimental choice but they do not inform about the downstream color representation. In fact, the architecture of the post-retinal network (signal recombination or internal color space) seems irrelevant for the emergence of the curves in the classical experiment. This result in artificial networks questions the conventional interpretation of the classical result in humans by Jameson and Hurvich.

O'Malley et al. (2009) and Haufe (2013) suggest that the philosophical idea of science as hypothesis testing generates a pernicious bias towards hypothesis-driven research and against exploratory research in the review process of research proposals and the allocation of resources. This paper addresses a conceptual objection to the argument by O'Malley et al. (2009) and Haufe (2013). We argue that the funding agencies' concepts of good science do not belong to epistemological or philosophical contexts but to political and institutional contexts. This means that correcting (potential) biases in research funding does not entail correcting funding agencies' (supposed) philosophies of science. To illustrate this point, we provide an in-depth historical case study: the granting of funds to neuroscientist Pedro Maldonado by the Chilean funding programme FONDECYT. This is a relevant comparison as FONDECYT's guidelines explicitly promote hypothesis-driven research and endorse a view of "good science" as hypothesis testing. However, we will see that the overall influence of the philosophical idea of science as hypothesis testing over this funding programme, the research project, and the actual practice of hypothesis testing is somewhat limited. The concept of science as hypothesis testing seems to play a crucial institutional or political (not philosophical) role in allowing the conceptual articulation of social expectations and researchers' expectations. [ABSTRACT FROM AUTHOR]

The philosophical interest in experimental practice in neuroscience has brought renewed attention to the study of the development and use of techniques and tools for data production. John Bickle has argued that the construction and progression of theories in neuroscience are entirely dependent on the development and ingenious use of research tools. In Bickle's account, theory plays a tertiary role, as it depends on what the tools allow researchers to manipulate, and the tools, in turn, are developed not in order to test theories but as solutions to engineering problems. However, Bickle's account is not entirely precise in explaining what informs researchers' decision-making in their atheoretical laboratory tinkering. Identifying the sources that guide researchers in tool development and use is crucial if one wishes to contribute to the philosophical or meta-scientific understanding of experimental practice in neuroscience. In the following paper, I claim that decision-making in tools' development and use in neuroscience is doubly guided. Pre-existing theory and concepts determine information's relevance, whereas tools' functioning in controlled situations determines information's reliability. Accordingly, experimenters' decision-making is situated both in the context of analysing, modelling or interpreting information and in the context of producing information. I study the case of the tungsten microelectrode developed by David Hubel during the 1950s. First, I show that pre-existing theory and concepts (in particular, the "neuron doctrine" and the concepts of "receptive field" and "cortical column") determine in advance what information would be relevant to obtain from the microelectrode. Second, I show that Hubel's tinkering follows the guidelines derived from the very structure of what we recognise as reliable experimentally produced information. Finally, I suggest that data-production processes allow experimenters to assess what to expect from an experimental system in terms of concept- and theory-generation and confirmation, thereby endorsing Bickle's tenet on the tertiary role of theory in neuroscience. [ABSTRACT FROM AUTHOR]

This document is an editorial published in Frontiers in Neuroscience in 2024. It introduces the "Rising Stars in Visual Neuroscience 2022" Research Topic, which showcases the work of emerging leaders in the field. The research presented in this topic covers a wide range of areas in visual neuroscience, including retinal degeneration, decision strategies and performance, intermodal integration, and clinical applications. The editorial highlights specific studies that investigate retinal remodeling effects, decision-making in uncertain environments, crossmodal transfer of object information, compensatory mechanisms in visual processing, and a new digital tool for assessing hand-eye coordination in individuals with ultra low vision. The authors emphasize the importance of this research in advancing our understanding of visual neuroscience and identifying promising researchers in the field. [Extracted from the article]

The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning. Using bitmap images as inputs and by adjusting only a couple of learning-rate parameters, the new HMAX/COVIS model provides impressively good fits to human category-learning data from two qualitatively different experiments that used different types of category structures and different types of visual stimuli. Overall, the model provides a comprehensive neural and behavioral account of basal ganglia-mediated learning.

Summary: To explore the relative contributions of higher-order and primary visual cortex (V1) to visual perception, we compared cats' behavioral and V1 neuronal contrast sensitivity functions (CSF) and threshold versus external noise contrast (TvC) functions before and after top-down influence of area 7 (A7) was modulated with transcranial direct current stimulation (tDCS). We found that suppressing top-down influence of A7 with cathode-tDCS, but not sham-tDCS, reduced behavioral and neuronal contrast sensitivity in the same range of spatial frequencies and increased behavioral and neuronal contrast thresholds in the same range of external noise levels. The neuronal CSF and TvC functions were highly correlated with their behavioral counterparts both before and after the top-down suppression. Analysis of TvC functions using the Perceptual Template Model (PTM) indicated that top-down influence of A7 increased both behavioral and V1 neuronal contrast sensitivity by reducing internal additive noise and the impact of external noise.

Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental practice. Derrida's model relativises or dissolves the conceptual distinction between the moment of data production and a subsequent moment of data dissemination. It thus has consequences for understanding both data production (despite being intrinsically local, data production a priori generates transferrable and modellable information) and data dissemination (when modelling information, researchers needs to refer this information to the context of its production). We study a case of data production in a non-exploratory experimental system designed to test a pre-existing hypothesis in visual neuroscience. A case of theory-oriented experimental practice should allow us to identify the autonomous functioning of experimental systems in data production more clearly, insofar as it allows us to study the limits of pre-existing theory in the activities of these systems. We suggest that pre-existing concepts, hypotheses and theories condition the relevance but not the production of experimental data. [ABSTRACT FROM AUTHOR]

I focus on the concept of the receptive field of a sensory neuron, taking it as a prominent case to address conceptual change in the history of neuroscience. I argue for an interpretation of its role and evolution based on the idea, previously rehearsed in the philosophy of biology, of a problem agenda. I claim that the concept's main contribution to visual neuroscience was that of establishing a problem agenda for the early experimental research on visual processing, thus structuring the field's experimental practices and integration between converging scientific fields. I pay particular attention to the research programme led by Hubel and Wiesel, revolving their famous experiments on the cat's visual cortex during the 60s, when receptive field exploration blossomed. I additionally claim that the concept's more recent evolution, witnessing a loss in its definiteness and centrality, can be accommodated by my account. [ABSTRACT FROM AUTHOR]

The passing of Jack Pettigrew (University of Queensland) and Bogdan Dreher (University of Sydney) within 2 weeks of each other in May 2019 provided the catalyst for documenting the roles that they and their colleagues from the Peter Bishop School played in establishing vision research as a major strength in Australian neuroscience in the second half of the 20th century. [ABSTRACT FROM AUTHOR]

Two-photon (2P) microscopy is a cornerstone technique in neuroscience research. However, combining 2P imaging with spectrally arbitrary light stimulation can be challenging due to crosstalk between stimulation light and fluorescence detection. To overcome this limitation, we present a simple and low-cost electronic solution based on an ESP32 microcontroller and a TLC5947 LED driver to rapidly time-interleave stimulation and detection epochs during scans. Implemented for less than $100, our design can independently drive up to 24 arbitrary spectrum LEDs to meet user requirements. We demonstrate the utility of our stimulator for colour vision experiments on the in vivo tetrachromatic zebrafish retina and for optogenetic circuit mapping in Drosophila.

Reproducing the perception of a real-world scene on a display device is a very challenging task which requires the understanding of the camera processing pipeline, the display process, and the way the human visual system processes the light it captures. Mathematical models based on psychophysical and physiological laws on color vision, named Retinex, provide efficient tools to handle degradations produced during the camera processing pipeline like the reduction of the contrast. In particular, Batard and Bertalmío (in J Math Imaging Vis 60(6):849–881, 2018) described some psychophysical laws on brightness perception as covariant derivatives, included them into a variational model, and observed that the quality of the color image correction is correlated with the accuracy of the vision model it includes. Based on this observation, we postulate that this model can be improved by including more accurate data on vision with a special attention on visual neuroscience here. Then, inspired by the presence of neurons responding to different visual attributes in the area V1 of the visual cortex as orientation, color or movement, to name a few, and horizontal connections modeling the interactions between those neurons, we construct two variational models to process both local (edges, textures) and global (contrast) features. This is an improvement with respect to the model of Batard and Bertalmío as the latter cannot process local and global features independently and simultaneously. Finally, we conduct experiments on color images which corroborate the improvement provided by the new models. [ABSTRACT FROM AUTHOR]

Over 3 million people in the United States live with long-term disability because of a traumatic brain injury (TBI). The purpose of this study was to characterize and compare two different animal models of TBI (blunt head trauma and blast TBI) to determine common and divergent characteristics of these models. With recent literature reviews noting the prevalence of visual system injury in animal models of TBI, coupled with clinical estimates of 50–75% of all TBI cases, we decided to assess commonalities, if they existed, through visual system injury. A unilateral (left directed) blast and repeat blast model injury with coup-contra-coup injury patterns were compared to a midline blunt injury. Injuries were induced in adult male mice to observe and quantify visual deficits. Retinal ganglion cell loss and axonal degeneration in the optic tract, superior colliculus, and lateral geniculate nuclei were examined to trace injury outcomes throughout major vision-associated areas. Optokinetic response, immunohistochemistry, and western blots were analyzed. Where a single blunt injury produces significant visual deficits a single blast injury appears to have less severe visual consequences. Visual deficits after repeat blasts are similar to a single blast. Single blast injury induces contralateral damage to the right optic chiasm and tract whereas bilateral injury follows a single blunt TBI. Repeat blast injuries are required to see degeneration patterns in downstream regions similar to the damage seen in a single blunt injury. This finding is further supported by amyloid precursor protein (APP) staining in injured cohorts. Blunt injured groups present with staining 1.2 mm ahead of the optic nerve, indicating axonal breakage closer to the optic chiasm. In blast groups, APP was identifiable in a bilateral pattern only in the geniculate nucleus. Evidence for unilateral neuronal degeneration in brain tissue with bilateral axonal ruptures are pivotal discoveries in this model differentiation. Analysis of the two injury models suggests that there is a significant difference in the histological outcomes dependent on injury type, though visual system injury is likely present in more cases than are currently diagnosed clinically. • Brain injury modalities lead to overlapping and unique pathological outcomes. • Optic neuropathy may be a more common feature of TBI than previously thought. • Unilateral, coup-contra-coup blast TBI leads to contralateral optic tract injury. • Yet, a midline blunt TBI leads to bilateral optic nerve injury. • Identification of conserved pathology of TBI may lead to better treatments. [ABSTRACT FROM AUTHOR]

Technologies such as optical coherence tomography have facilitated the visualization of anatomical tissues such as that of the retina. The availability of in vivo retinal anatomical data has led to the hypothesis that it may be able to accurately predict visual function from anatomical information. However, accurate determination of the structure-function relationship has remained elusive in part due to contributions of non-retinal sources of variability, thus imposing potential limitations in the fidelity of the relationship. Furthermore, differences in manifestation of functional loss due to different retinal loci of change (inner retina or outer retinal elements) have also been the subject of debate. Here, we assessed the application of a novel, more objective psychophysical paradigm to better characterize the relationship between functional and structural characteristics in the eye. Using ocular diseases with known loci of anatomical change (glaucoma, inner retinal loss; and retinitis pigmentosa, outer retinal loss), we compared conventional more subjective psychophysical techniques that may be contaminated by the presence of non-retinal sources of variability with our more objective approach. We show that stronger correlations between underlying retinal structure and visual function can be achieved across a breadth of anatomical change by using a more objective psychophysical paradigm. This was independent of the locus of structural loss (at the ganglion cells for glaucoma or photoreceptors for retinitis pigmentosa), highlighting the role of downstream retinal elements to serve as anatomical limiting factors for studying the structure-function relationship. By reducing the contribution of non-retinal sources of variability in psychophysical measurements, we herein provide a structure-function model with higher fidelity. This reinforces the need to carefully consider the psychophysical protocol when examining the structure-function relationship in sensory systems.

Human visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation–a subject’s retinotopic measurements from small amounts of fMRI time–with a prior–a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.

Technologies such as optical coherence tomography have facilitated the visualization of anatomical tissues such as that of the retina. The availability of in vivo retinal anatomical data has led to the hypothesis that it may be able to accurately predict visual function from anatomical information. However, accurate determination of the structure-function relationship has remained elusive in part due to contributions of non-retinal sources of variability, thus imposing potential limitations in the fidelity of the relationship. Furthermore, differences in manifestation of functional loss due to different retinal loci of change (inner retina or outer retinal elements) have also been the subject of debate. Here, we assessed the application of a novel, more objective psychophysical paradigm to better characterize the relationship between functional and structural characteristics in the eye. Using ocular diseases with known loci of anatomical change (glaucoma, inner retinal loss; and retinitis pigmentosa, outer retinal loss), we compared conventional more subjective psychophysical techniques that may be contaminated by the presence of non-retinal sources of variability with our more objective approach. We show that stronger correlations between underlying retinal structure and visual function can be achieved across a breadth of anatomical change by using a more objective psychophysical paradigm. This was independent of the locus of structural loss (at the ganglion cells for glaucoma or photoreceptors for retinitis pigmentosa), highlighting the role of downstream retinal elements to serve as anatomical limiting factors for studying the structure-function relationship. By reducing the contribution of non-retinal sources of variability in psychophysical measurements, we herein provide a structure-function model with higher fidelity. This reinforces the need to carefully consider the psychophysical protocol when examining the structure-function relationship in sensory systems. [ABSTRACT FROM AUTHOR]

Our representation of the visual field is not homogenous. There are differences in resolution not only between the fovea and regions eccentric to it, but also between the nasal and temporal hemiretinae, that can be traced to asymmetric distributions of photoreceptors and ganglion cells. We review evidence for differences in visual and attentional processing and oculomotor behaviour that can be traced to asymmetries of the visual system, mainly emphasising nasal‐temporal asymmetries. Asymmetries in the visual system manifest in various measures, in basic psychophysical tests of visual performance, attentional processing, choice behaviour, saccadic peak velocity, and latencies. Nasal‐temporal asymmetries on saccadic latency seem primarily to occur for express saccades. Neural asymmetries between the upper and lower hemifields are strong and cause corresponding differences in performance between the hemifields. There are interesting individual differences in asymmetric processing which seem to be related to the strength of eye dominance. These neurophysiological asymmetries and the corresponding asymmetries in visual performance and oculomotor behaviour can strongly influence experimental results in vision and must be considered during experimental design and the interpretation of results. We review evidence for asymmetries in vision, attention, and oculomotor behaviour. We mainly focus on processing differences that can be traced to asymmetries of the visual system, in particular nasal‐temporal asymmetries. Biological asymmetries are found in the retina, the optic nerves and some brain areas involved in visual processing, and these asymmetries manifest in various measures, basic psychophysical tests of attentional processing, choice behaviour, and saccadic parameters. [ABSTRACT FROM AUTHOR]

Abstract Representations learned by deep convolutional neural networks (CNNs) for object recognition are a widely investigated model of the processing hierarchy in the human visual system. Using functional magnetic resonance imaging, CNN representations of visual stimuli have previously been shown to correspond to processing stages in the ventral and dorsal streams of the visual system. Whether this correspondence between models and brain signals also holds for activity acquired at high temporal resolution has been explored less exhaustively. Here, we addressed this question by combining CNN-based encoding models with magnetoencephalography (MEG). Human participants passively viewed 1,000 images of objects while MEG signals were acquired. We modelled their high temporal resolution source-reconstructed cortical activity with CNNs, and observed a feed-forward sweep across the visual hierarchy between 75 and 200 ms after stimulus onset. This spatiotemporal cascade was captured by the network layer representations, where the increasingly abstract stimulus representation in the hierarchical network model was reflected in different parts of the visual cortex, following the visual ventral stream. We further validated the accuracy of our encoding model by decoding stimulus identity in a left-out validation set of viewed objects, achieving state-of-the-art decoding accuracy. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

Partial visual deprivation from early monocular enucleation (the surgical removal of one eye within the first few years of life) results in a number of long-term morphological adaptations in adult cortical and subcortical visual, auditory, and multisensory brain regions. In this study, we investigated whether early monocular enucleation also results in the altered development of white matter structure. Diffusion tensor imaging and probabilistic tractography were performed to assess potential differences in visual system white matter in adult participants who had undergone early monocular enucleation compared to binocularly intact controls. To examine the microstructural properties of these tracts, mean diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were extracted bilaterally. Asymmetries opposite to those observed in controls were found for FA, MD, and RD in the optic radiations, the projections from primary visual cortex (V1) to the lateral geniculate nucleus (LGN), and the interhemispheric V1 projections of early monocular enucleation participants. Early monocular enucleation was also associated with significantly lower FA bidirectionally in the interhemispheric V1 projections. These differences were consistently greater for the tracts contralateral to the enucleated eye, and are consistent with the asymmetric LGN volumes and optic tract diameters previously demonstrated in this group of participants. Overall, these results indicate that early monocular enucleation has long-term effects on white matter structure in the visual pathway that results in reduced fiber organization in tracts contralateral to the enucleated eye. Hum Brain Mapp 39:133-144, 2018. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The center-surround organization of the receptive fields (RFs) of retinal ganglion cells highlights the presence of local contrast in visual stimuli. As RF of thalamic relay cells follow the same basic functional organization, it is often assumed that they contribute very little to alter the retinal output. However, in many species, thalamic relay cells largely outnumber their retinal inputs, which diverge to contact simultaneously several units at thalamic level. This gain in cell population as well as retinothalamic convergence opens the door to question how information about contrast is transformed at the thalamic stage. Here, we address this question using a realistic dynamic model of the retinothalamic circuit. Our results show that different components of the thalamic RF might implement filters that are analogous to two types of well-known image processing techniques to preserve the quality of a higher resolution version of the image on its way to the primary visual cortex. [ABSTRACT FROM AUTHOR]

Visual neuroscience is concerned with the neurobiological foundations of visual perception, that is, the morphological, physiological, and functional organization of the visual brain and its co-operative partners. One important approach for understanding the functional organization of the visual brain is the study of visual perception from the pathological perspective. The study of patients with focal injury to the visual brain allows conclusions about the representation of visual perceptual functions in the framework of association and dissociation of functions. Selective disorders have been reported for more 'elementary' visual capabilities, for example, color and movement vision, but also for visuo-cognitive capacities, such as visual agnosia or the visual field of attention. Because these visual disorders occur rather seldom as selective and specific dysfunctions, single cases have always played, and still play, a significant role in gaining insights into the functional organization of the visual brain. [ABSTRACT FROM AUTHOR]