Information processing in the primate retina: circuitry and coding

A method for electrophysiological characterization of hamster retinal ganglion cells using a high-density CMOS microelectrode array

Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 μm electrode pitch), we were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience, and latency. These properties were clustered to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density of 2780 cells/mm² at 2 mm (42°) from the optic nerve head. Using five parameters extracted from the responses to visual stimuli, we obtained seven ganglion cell types.

OFF bipolar cells in macaque retina: type-specific connectivity in the outer and inner synaptic layers

OFF bipolar cells in the macaque retina were recently classified into five types: flat midget bipolar (FMB) and diffuse bipolar (DB) 1, 2, 3a, and 3b. We examined all parallel pathways from cone photoreceptors via OFF bipolar cells to parasol and midget ganglion cells by serial section transmission electron microscopy. Basal contacts of OFF bipolar cells to cone pedicles were previously categorized as triad-associated (TA) and non-TA (NTA). The latter was further divided into two groups located in the middle and marginal areas of the pedicle at the present eccentricity of 15°. We then mapped the distributions of all three basal contacts of the five OFF bipolar cell types in the same area of cone pedicles. TA contacts were more numerous than NTA contacts in FMB (93%), DB1 (67%), and DB3a (81%) cells, but less in DB2 (30%) and DB3b (21%) cells. Cluster analysis of these contact parameters reconfirmed five distinct OFF bipolar cell types and showed these positional configurations of basal synapses to be cell type-specific. This architecture is thought to provide a spatial framework for the interstitial diffusion and local uptake of the neurotransmitter (glutamate) that spills over from ribbon synapses. All five OFF bipolar cell types formed ribbon-synaptic contacts to both parasol and midget ganglion cells. DB2 and 3a, DB1 and 3b, and FMB predominantly, moderately, and negligibly contacted parasol ganglion cells, respectively. FMB almost exclusively contacted midget ganglion cells, to which DB1 provided dominant output (58%), and DB2, 3a, and 3b provided between 3% and 10% of their output. Consequently, the cone signal sampling routes of a midget ganglion cell consisted of two substructures: the narrow (mainly 2-3 cones) FMB pathway and the wide (mainly 10 cones) DB pathway, where connection strength was four-fold greater in the FMB than DB pathway. The narrow and strong FMB pathway may confer the highest spatial resolution and sporadically may include blue cone signals.

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas.

Challenges in retinal circuit regeneration: linking neuronal connectivity to circuit function

Tremendous progress has been made in retinal regeneration, as exemplified by successful transplantation of retinal pigment epithelia and photoreceptor cells in the adult retina, as well as by generation of retinal tissue from embryonic stem cells and induced pluripotent cells. However, it remains unknown how new photoreceptors integrate within retinal circuits and contribute to vision restoration. There is a large gap in our understanding, at both the cellular and behavioral levels, of the functional roles of new neurons in the adult retina. This gap largely arises from the lack of appropriate methods for analyzing the organization and function of new neurons at the circuit level. To bridge this gap and understand the functional roles of new neurons in living animals, it will be necessary to identify newly formed connections, correlate them with function, manipulate their activity, and assess the behavioral outcome of these manipulations. Recombinant viral vectors are powerful tools not only for controlling gene expression and reprogramming cells, but also for tracing cell fates and neuronal connectivity, monitoring biological functions, and manipulating the physiological state of a specific cell population. These virus-based approaches, combined with electrophysiology and optical imaging, will provide circuit-level insight into neural regeneration and facilitate new strategies for achieving vision restoration in the adult retina. Herein, we discuss challenges and future directions in retinal regeneration research.

A synaptic signature for ON- and OFF-center parasol ganglion cells of the primate retina

In the primate retina, parasol ganglion cells contribute to the primary visual pathway via the magnocellular division of the lateral geniculate nucleus, display ON and OFF concentric receptive field structure, nonlinear spatial summation, and high achromatic temporal-contrast sensitivity. Parasol cells may be homologous to the alpha-Y cells of nonprimate mammals where evidence suggests that N-methyl-D-aspartate (NMDA) receptor-mediated synaptic excitation as well as glycinergic disinhibition play critical roles in contrast sensitivity, acting asymmetrically in OFF- but not ON-pathways. Here, light-evoked synaptic currents were recorded in the macaque monkey retina in vitro to examine the circuitry underlying parasol cell receptive field properties. Synaptic excitation in both ON and OFF types was mediated by NMDA as well as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)/kainate glutamate receptors. The NMDA-mediated current-voltage relationship suggested high Mg2+ affinity such that at physiological potentials, NMDA receptors contributed ∼20% of the total excitatory conductance evoked by moderate stimulus contrasts and temporal frequencies. Postsynaptic inhibition in both ON and OFF cells was dominated by a large glycinergic "crossover" conductance, with a relatively small contribution from GABAergic feedforward inhibition. However, crossover inhibition was largely rectified, greatly diminished at low stimulus contrasts, and did not contribute, via disinhibition, to contrast sensitivity. In addition, attenuation of GABAergic and glycinergic synaptic inhibition left center-surround and Y-type receptive field structure and high temporal sensitivity fundamentally intact and clearly derived from modulation of excitatory bipolar cell output. Thus, the characteristic spatial and temporal-contrast sensitivity of the primate parasol cell arises presynaptically and is governed primarily by modulation of the large AMPA/kainate receptor-mediated excitatory conductance. Moreover, the negative feedback responsible for the receptive field surround must derive from a nonGABAergic mechanism.

Calretinin and calbindin distribution patterns specify subpopulations of type I and type II spiral ganglion neurons in postnatal murine cochlea

As the first neural element in the auditory pathway, neurons in the spiral ganglion shape the initial coding of sound stimuli for subsequent processing. Within the ganglion, type I and type II neurons form divergent and convergent innervation patterns, respectively, with their hair cell sensory receptors, indicating that very different information is gathered and conveyed. Layered onto these basic innervation patterns are structural and electrophysiological features that provide additional levels of processing multifaceted sound stimuli. To understand the nature of this additional complexity of signal coding, we characterized the distribution of calretinin and calbindin, two regulators of intracellular calcium that serve as markers for neuronal subpopulations. We showed in acute preparations and in vitro that calretinin and calbindin staining levels were heterogeneous. Immunocytochemical analysis of colocalization further showed that high levels of staining for the two molecules rarely overlapped. Although varied amounts of calbindin and calretinin were found within each tonotopic location and neuronal type, some distinct subdistributions were noted. For example, calretinin levels were highest in neurons innervating the midcochlea region, whereas calbindin levels were similar across the entire ganglion. Furthermore, we noted that apical type II neurons, identified by antiperipherin labeling, had significantly lower levels of calretinin and higher levels of calbindin. We also established that the endogenous firing feature of onset tau of the subthreshold response showed a pattern related to quantified calretinin and calbindin staining levels. Taken together, our results suggest an additional dimension of complexity within the spiral ganglion beyond that currently categorized.

So many pieces, one puzzle: cell type specification and visual circuitry in flies and mice

The visual system is a powerful model for probing the development, connectivity, and function of neural circuits. Two genetically tractable species, mice and flies, are together providing a great deal of understanding of these processes. Current efforts focus on integrating knowledge gained from three cross-fostering fields of research: (1) understanding how the fates of different cell types are specified during development, (2) revealing the synaptic connections between identified cell types ("connectomics") by high-resolution three-dimensional circuit anatomy, and (3) causal testing of how identified circuit elements contribute to visual perception and behavior. Here we discuss representative examples from fly and mouse models to illustrate the ongoing success of this tripartite strategy, focusing on the ways it is enhancing our understanding of visual processing and other sensory systems.

Wiring patterns in the mouse retina: collecting evidence across the connectome, physiology and light microscopy

The visual system has often been thought of as a parallel processor because distinct regions of the brain process different features of visual information. However, increasing evidence for convergence and divergence of circuit connections, even at the level of the retina where visual information is first processed, chips away at a model of dedicated and distinct pathways for parallel information flow. Instead, our current understanding is that parallel channels may emerge, not from exclusive microcircuits for each channel, but from unique combinations of microcircuits. This review depicts diagrammatically the current knowledge and remaining puzzles about the retinal circuit with a focus on the mouse retina. Advances in techniques for labelling cells and genetic manipulations have popularized the use of transgenic mice. We summarize evidence gained from serial electron microscopy, electrophysiology and light microscopy to illustrate the wiring patterns in mouse retina. We emphasize the need to explore proposed retinal connectivity using multiple methods to verify circuits both structurally and functionally.

Sparsity and compressed coding in sensory systems

Considering that many natural stimuli are sparse, can a sensory system evolve to take advantage of this sparsity? We explore this question and show that significant downstream reductions in the numbers of neurons transmitting stimuli observed in early sensory pathways might be a consequence of this sparsity. First, we model an early sensory pathway using an idealized neuronal network comprised of receptors and downstream sensory neurons. Then, by revealing a linear structure intrinsic to neuronal network dynamics, our work points to a potential mechanism for transmitting sparse stimuli, related to compressed-sensing (CS) type data acquisition. Through simulation, we examine the characteristics of networks that are optimal in sparsity encoding, and the impact of localized receptive fields beyond conventional CS theory. The results of this work suggest a new network framework of signal sparsity, freeing the notion from any dependence on specific component-space representations. We expect our CS network mechanism to provide guidance for studying sparse stimulus transmission along realistic sensory pathways as well as engineering network designs that utilize sparsity encoding.

In forming a mental percept of the surrounding world, sensory information is processed and transmitted through a wide array of neuronal networks of various sizes and functionalities. Despite, and perhaps because of, this, sensory systems are able to render highly accurate representations of stimuli. In the retina, for example, photoreceptors transform light into electric signals, which are later processed by a significantly smaller network of ganglion cells before entering the optic nerve. How then is sensory information preserved along such a pathway? In this work, we put forth a possible answer to this question using compressed sensing, a recent advance in the field of signal processing that demonstrates how sparse signals can be reconstructed using very few samples. Through model simulation, we discover that stimuli can be recovered from ganglion-cell dynamics, and demonstrate how localized receptive fields improve stimulus encoding. We hypothesize that organisms have evolved to utilize the sparsity of stimuli, demonstrating that compressed sensing may be a universal information-processing framework underlying both information acquisition and retention in sensory systems.

Population activity changes during a trial-to-trial adaptation of bullfrog retinal ganglion cells

A 'trial-to-trial adaptation' of bullfrog retinal ganglion cells in response to a repetitive light stimulus was investigated in the present study. Using the multielectrode recording technique, we studied the trial-to-trial adaptive properties of ganglion cells and explored the activity of population neurons during this adaptation process. It was found that the ganglion cells adapted with different degrees: their firing rates were decreased in different extents from early-adaptation to late-adaptation stage, and this was accompanied by a decrease in cross-correlation strength. In addition, adaptation behavior was different for ON-response and OFF-response, which implied that the mechanism of the trial-to-trial adaptation might involve bipolar cells and/or their synapses with other neurons and the stronger adaptation in the ganglion cells' OFF-responses might reflect the requirement to avoid possible saturation in the OFF circuit.

Large pseudocounts and L2-norm penalties are necessary for the mean-field inference of Ising and Potts models

The mean-field (MF) approximation offers a simple, fast way to infer direct interactions between elements in a network of correlated variables, a common, computationally challenging problem with practical applications in fields ranging from physics and biology to the social sciences. However, MF methods achieve their best performance with strong regularization, well beyond Bayesian expectations, an empirical fact that is poorly understood. In this work, we study the influence of pseudocount and L(2)-norm regularization schemes on the quality of inferred Ising or Potts interaction networks from correlation data within the MF approximation. We argue, based on the analysis of small systems, that the optimal value of the regularization strength remains finite even if the sampling noise tends to zero, in order to correct for systematic biases introduced by the MF approximation. Our claim is corroborated by extensive numerical studies of diverse model systems and by the analytical study of the m-component spin model for large but finite m. Additionally, we find that pseudocount regularization is robust against sampling noise and often outperforms L(2)-norm regularization, particularly when the underlying network of interactions is strongly heterogeneous. Much better performances are generally obtained for the Ising model than for the Potts model, for which only couplings incoming onto medium-frequency symbols are reliably inferred.

Effects of dopamine on response properties of ON-OFF RGCs in encoding stimulus durations

Single retinal ganglion cell's (RGCs) response properties, such as spike count and response latency, are known to encode some features of visual stimuli. On the other hand, neuronal response can be modulated by dopamine (DA), an important endogenous neuromodulator in the retina. In the present study, we investigated the effects of DA on the spike count and the response latency of bullfrog ON-OFF RGCs during exposure to different stimulus durations. We found that neuronal spike count and response latency were both changed with stimulus durations, and exogenous DA (10 μM) obviously attenuated the stimulus-duration-dependent response latency change. Information analysis showed that the information about light ON duration was mainly carried by the OFF response and vice versa, and the stimulation information was carried by both spike count and response latency. However, during DA application, the information carried by the response latency was greatly decreased, which suggests that dopaminergic pathway is involved in modulating the role of response latency in encoding the information about stimulus durations.

Spatially patterned electrical stimulation to enhance resolution of retinal prostheses

Retinal prostheses electrically stimulate neurons to produce artificial vision in people blinded by photoreceptor degenerative diseases. The limited spatial resolution of current devices results in indiscriminate stimulation of interleaved cells of different types, precluding veridical reproduction of natural activity patterns in the retinal output. Here we investigate the use of spatial patterns of current injection to increase the spatial resolution of stimulation, using high-density multielectrode recording and stimulation of identified ganglion cells in isolated macaque retina. As previously shown, current passed through a single electrode typically induced a single retinal ganglion cell spike with submillisecond timing precision. Current passed simultaneously through pairs of neighboring electrodes modified the probability of activation relative to injection through a single electrode. This modification could be accurately summarized by a piecewise linear model of current summation, consistent with a simple biophysical model based on multiple sites of activation. The generalizability of the piecewise linear model was tested by using the measured responses to stimulation with two electrodes to predict responses to stimulation with three electrodes. Finally, the model provided an accurate prediction of which among a set of spatial stimulation patterns maximized selective activation of a cell while minimizing activation of a neighboring cell. The results demonstrate that tailored multielectrode stimulation patterns based on a piecewise linear model may be useful in increasing the spatial resolution of retinal prostheses.

A polyaxonal amacrine cell population in the primate retina

Amacrine cells are the most diverse and least understood cell class in the retina. Polyaxonal amacrine cells (PACs) are a unique subset identified by multiple long axonal processes. To explore their functional properties, populations of PACs were identified by their distinctive radially propagating spikes in large-scale high-density multielectrode recordings of isolated macaque retina. One group of PACs exhibited stereotyped functional properties and receptive field mosaic organization similar to that of parasol ganglion cells. These PACs had receptive fields coincident with their dendritic fields, but much larger axonal fields, and slow radial spike propagation. They also exhibited ON-OFF light responses, transient response kinetics, sparse and coordinated firing during image transitions, receptive fields with antagonistic surrounds and fine spatial structure, nonlinear spatial summation, and strong homotypic neighbor electrical coupling. These findings reveal the functional organization and collective visual signaling by a distinctive, high-density amacrine cell population.

Multiple redundant medulla projection neurons mediate color vision in Drosophila

The receptor mechanism for color vision has been extensively studied. In contrast, the circuit(s) that transform(s) photoreceptor signals into color percepts to guide behavior remain(s) poorly characterized. Using intersectional genetics to inactivate identified subsets of neurons, we have uncovered the first-order interneurons that are functionally required for hue discrimination in Drosophila. We developed a novel aversive operant conditioning assay for intensity-independent color discrimination (true color vision) in Drosophila. Single flying flies are magnetically tethered in an arena surrounded by blue and green LEDs (light-emitting diodes). The flies' optomotor response is used to determine the blue-green isoluminant intensity. Flies are then conditioned to discriminate between equiluminant blue or green stimuli. Wild-type flies are successfully trained in this paradigm when conditioned to avoid either blue or green. Functional color entrainment requires the function of the narrow-spectrum photoreceptors R8 and/or R7, and is within a limited range, intensity independent, suggesting that it is mediated by a color vision system. The medulla projection neurons, Tm5a/b/c and Tm20, receive direct inputs from R7 or R8 photoreceptors and indirect input from the broad-spectrum photoreceptors R1-R6 via the lamina neuron L3. Genetically inactivating these four classes of medulla projection neurons abolished color learning. However, inactivation of subsets of these neurons is insufficient to block color learning, suggesting that true color vision is mediated by multiple redundant pathways. We hypothesize that flies represent color along multiple axes at the first synapse in the fly visual system. The apparent redundancy in learned color discrimination sharply contrasts with innate ultraviolet (UV) spectral preference, which is dominated by a single pathway from the amacrine neuron Dm8 to the Tm5c projection neurons.

Scene analysis in the natural environment

The problem of scene analysis has been studied in a number of different fields over the past decades. These studies have led to important insights into problems of scene analysis, but not all of these insights are widely appreciated, and there remain critical shortcomings in current approaches that hinder further progress. Here we take the view that scene analysis is a universal problem solved by all animals, and that we can gain new insight by studying the problems that animals face in complex natural environments. In particular, the jumping spider, songbird, echolocating bat, and electric fish, all exhibit behaviors that require robust solutions to scene analysis problems encountered in the natural environment. By examining the behaviors of these seemingly disparate animals, we emerge with a framework for studying scene analysis comprising four essential properties: (1) the ability to solve ill-posed problems, (2) the ability to integrate and store information across time and modality, (3) efficient recovery and representation of 3D scene structure, and (4) the use of optimal motor actions for acquiring information to progress toward behavioral goals.

Wiring the retinal circuits activated by light during early development

Background

Light information is sorted by neuronal circuits to generate image-forming (IF) (interpretation and tracking of visual objects and patterns) and non-image-forming (NIF) tasks. Among the NIF tasks, photic entrainment of circadian rhythms, the pupillary light reflex, and sleep are all associated with physiological responses, mediated mainly by a small group of melanopsin-expressing retinal ganglion cells (mRGCs). Using Xenopus laevis as a model system, and analyzing the c-fos expression induced by light as a surrogate marker of neural activity, we aimed to establish the developmental time at which the cells participating in both systems come on-line in the retina.

Results

We found that the peripheral retina contains 80% of the two melanopsin-expressing cell types we identified in Xenopus: melanopsin-expressing horizontal cells (mHCs; opn4m+/opn4x+/Prox1+) and mRGCs (2.7% of the total RGCs; opn4m+/opn4x+/Pax6+/Isl1), in a ratio of 6:1. Only mRGCs induced c-fos expression in response to light. Dopaminergic (tyrosine hydroxylase-positive; TH+) amacrine cells (ACs) may be part of the melanopsin-mediated circuit, as shown by preferential c-fos induction by blue light. In the central retina, two cell types in the inner nuclear layer (INL) showed light-mediated induction of c-fos expression [(On-bipolar cells (Otx2+/Isl1+), and a sub-population of ACs (Pax6−/Isl1−)], as well as two RGC sub-populations (Isl1+/Pax6+ and Isl1+/Pax6−). Melanopsin and opsin expression turned on a day before the point at which c-fos expression could first be activated by light (Stage 37/38), in cells of both the classic vision circuit, and those that participate in the retinal component of the NIF circuit. Key to the classic vision circuit is that the component cells engage from the beginning as functional ‘unit circuits’ of two to three cells in the INL for every RGC, with subsequent growth of the vision circuit occurring by the wiring in of more units.

Conclusions

We identified melanopsin-expressing cells and specific cell types in the INL and the RGC layer which induce c-fos expression in response to light, and we determined the developmental time when they become active. We suggest an initial formulation of retinal circuits corresponding to the classic vision pathway and melanopsin-mediated circuits to which they may contribute.

Visual space is represented by nonmatching topographies of distinct mouse retinal ganglion cell types

The distributions of neurons in sensory circuits display ordered spatial patterns arranged to enhance or encode specific regions or features of the external environment. Indeed, visual space is not sampled uniformly across the vertebrate retina. Retinal ganglion cell (RGC) density increases and dendritic arbor size decreases toward retinal locations with higher sampling frequency, such as the fovea in primates and area centralis in carnivores [1]. In these locations, higher acuity at the level of individual cells is obtained because the receptive field center of a RGC corresponds approximately to the spatial extent of its dendritic arbor [2, 3]. For most species, structurally and functionally distinct RGC types appear to have similar topographies, collectively scaling their cell densities and arbor sizes toward the same retinal location [4]. Thus, visual space is represented across the retina in parallel by multiple distinct circuits [5]. In contrast, we find a population of mouse RGCs, known as alpha or alpha-like [6], that displays a nasal-to-temporal gradient in cell density, size, and receptive fields, which facilitates enhanced visual sampling in frontal visual fields. The distribution of alpha-like RGCs contrasts with other known mouse RGC types and suggests that, unlike most mammals, RGC topographies in mice are arranged to sample space differentially.

Genetic interactions between Brn3 transcription factors in retinal ganglion cell type specification

Background

Visual information is conveyed from the retina to the brain via 15–20 Retinal Ganglion Cell (RGC) types. The developmental mechanisms by which RGC types acquire their distinct molecular, morphological, physiological and circuit properties are essentially unknown, but may involve combinatorial transcriptional regulation. Brn3 transcription factors are expressed in RGCs from early developmental stages, and are restricted in adults to distinct, partially overlapping populations of RGC types. Previously, we described cell autonomous effects of Brn3b (Pou4f2) and Brn3a (Pou4f1) on RGC axon and dendrites development.

Methods and Findings

We now have investigated genetic interactions between Brn3 transcription factors with respect to RGC development, by crossing conventional knock-out alleles of each Brn3 gene with conditional knock-in reporter alleles of a second Brn3 gene, and analyzing the effects of single or double Brn3 knockouts on RGC survival and morphology. We find that Brn3b loss results in axon defects and dendritic arbor area and lamination defects in Brn3a positive RGCs, and selectively affects survival and morphology of specific Brn3c (Pou4f3) positive RGC types. Brn3a and Brn3b interact synergistically to control RGC numbers. Melanopsin positive ipRGCs are resistant to combined Brn3 loss but are under the transcriptional control of Isl1, expanding the combinatorial code of RGC specification.

Conclusions

Taken together these results complete our knowledge on the mechanisms of transcriptional control of RGC type specification. They demonstrate that Brn3b is required for the correct development of more RGC cell types than suggested by its expression pattern in the adult, but that several cell types, including some Brn3a, Brn3c or Melanopsin positive RGCs are Brn3b independent.

Two-photon imaging of nonlinear glutamate release dynamics at bipolar cell synapses in the mouse retina

Alpha/Y-type retinal ganglion cells encode visual information with a receptive field composed of nonlinear subunits. This nonlinear subunit structure enhances sensitivity to patterns composed of high spatial frequencies. The Y-cell's subunits are the presynaptic bipolar cells, but the mechanism for the nonlinearity remains incompletely understood. We investigated the synaptic basis of the subunit nonlinearity by combining whole-cell recording of mouse Y-type ganglion cells with two-photon fluorescence imaging of a glutamate sensor (iGluSnFR) expressed on their dendrites and throughout the inner plexiform layer. A control experiment designed to assess iGluSnFR's dynamic range showed that fluorescence responses from Y-cell dendrites increased proportionally with simultaneously recorded excitatory current. Spatial resolution was sufficient to readily resolve independent release at intermingled ON and OFF bipolar terminals. iGluSnFR responses at Y-cell dendrites showed strong surround inhibition, reflecting receptive field properties of presynaptic release sites. Responses to spatial patterns located the origin of the Y-cell nonlinearity to the bipolar cell output, after the stage of spatial integration. The underlying mechanism differed between OFF and ON pathways: OFF synapses showed transient release and strong rectification, whereas ON synapses showed relatively sustained release and weak rectification. At ON synapses, the combination of fast release onset with slower release offset explained the nonlinear response of the postsynaptic ganglion cell. Imaging throughout the inner plexiform layer, we found transient, rectified release at the central-most levels, with increasingly sustained release near the borders. By visualizing glutamate release in real time, iGluSnFR provides a powerful tool for characterizing glutamate synapses in intact neural circuits.

Processing of S-cone signals in the inner plexiform layer of the mammalian retina

Color information is encoded by two parallel pathways in the mammalian retina. One pathway compares signals from long- and middle-wavelength sensitive cones and generates red-green opponency. The other compares signals from short- and middle-/long-wavelength sensitive cones and generates blue-green (yellow) opponency. Whereas both pathways operate in trichromatic primates (including humans), the fundamental, phylogenetically ancient color mechanism shared among most mammals is blue-green opponency. In this review, we summarize the current understanding of how signals from short-wavelength sensitive cones are processed in the primate and nonprimate mammalian retina, with a focus on the inner plexiform layer where bipolar, amacrine, and ganglion cell processes interact to facilitate the generation of blue-green opponency.

Novel flicker-sensitive visual circuit neurons inhibited by stationary patterns

Many animals use visual motion cues for navigating within their surroundings. Both flies and vertebrates compute local motion by temporal correlation of neighboring photoreceptors, via so-called elementary motion detectors (EMDs). In the fly lobula plate and the vertebrate visual cortex the output from many EMDs is pooled in neurons sensitive to wide-field optic flow. Although the EMD has been the preferred model for more than 50 years, recent work has highlighted its limitations in describing some visual behaviors, such as responses to higher-order motion stimuli. Non-EMD motion processing may therefore serve an important function in vision. Here, we describe a novel neuron class in the fly lobula plate that clearly does not derive its input from classic EMDs. The centrifugal stationary inhibited flicker excited (cSIFE) neuron is strongly excited by flicker, up to very high temporal frequencies. The non-EMD driven flicker sensitivity leads to strong, nondirectional responses to high-speed, wide-field motion. Furthermore, cSIFE is strongly inhibited by stationary patterns, within a narrow wavelength band. cSIFE's outputs overlap with the inputs of well described optic flow-sensitive lobula plate tangential cells (LPTCs). Driving cSIFE affects the active dendrites of LPTCs, and cSIFE may therefore play a large role in motion vision.

Gap junctions are essential for generating the correlated spike activity of neighboring retinal ganglion cells

Neurons throughout the brain show spike activity that is temporally correlated to that expressed by their neighbors, yet the generating mechanism(s) remains unclear. In the retina, ganglion cells (GCs) show robust, concerted spiking that shapes the information transmitted to central targets. Here we report the synaptic circuits responsible for generating the different types of concerted spiking of GC neighbors in the mouse retina. The most precise concerted spiking was generated by reciprocal electrical coupling of GC neighbors via gap junctions, whereas indirect electrical coupling to a common cohort of amacrine cells generated the correlated activity with medium precision. In contrast, the correlated spiking with the lowest temporal precision was produced by shared synaptic inputs carrying photoreceptor noise. Overall, our results demonstrate that different synaptic circuits generate the discrete types of GC correlated activity. Moreover, our findings expand our understanding of the roles of gap junctions in the retina, showing that they are essential for generating all forms of concerted GC activity transmitted to central brain targets.

Temporal processing in the olfactory system: can we see a smell?

Sensory processing circuits in the visual and olfactory systems receive input from complex, rapidly changing environments. Although patterns of light and plumes of odor create different distributions of activity in the retina and olfactory bulb, both structures use what appears on the surface similar temporal coding strategies to convey information to higher areas in the brain. We compare temporal coding in the early stages of the olfactory and visual systems, highlighting recent progress in understanding the role of time in olfactory coding during active sensing by behaving animals. We also examine studies that address the divergent circuit mechanisms that generate temporal codes in the two systems, and find that they provide physiological information directly related to functional questions raised by neuroanatomical studies of Ramon y Cajal over a century ago. Consideration of differences in neural activity in sensory systems contributes to generating new approaches to understand signal processing.

Focal electrical stimulation of major ganglion cell types in the primate retina for the design of visual prostheses

Electrical stimulation of retinal neurons with an advanced retinal prosthesis may eventually provide high-resolution artificial vision to the blind. However, the success of future prostheses depends on the ability to activate the major parallel visual pathways of the human visual system. Electrical stimulation of the five numerically dominant retinal ganglion cell types was investigated by simultaneous stimulation and recording in isolated peripheral primate (Macaca sp.) retina using multi-electrode arrays. ON and OFF midget, ON and OFF parasol, and small bistratified ganglion cells could all be activated directly to fire a single spike with submillisecond latency using brief pulses of current within established safety limits. Thresholds for electrical stimulation were similar in all five cell types. In many cases, a single cell could be specifically activated without activating neighboring cells of the same type or other types. These findings support the feasibility of direct electrical stimulation of the major visual pathways at or near their native spatial and temporal resolution.

Gap junction permeability modulated by dopamine exerts effects on spatial and temporal correlation of retinal ganglion cells' firing activities

Synchronized activities among retinal ganglion cells (RGCs) via gap junctions can be increased by exogenous dopamine (DA). During DA application, single neurons' firing activities become more synchronized with its adjacent neighbors. One intriguing question is how the enhanced spatial synchronization alters the temporal firing structure of single neurons. In the present study, firing activities of bullfrog's dimming detectors in response to binary pseudo-random checker-board flickering were recorded via a multi-channel recording system. DA was applied in the retina to modulate synchronized activities between RGCs, and the effect of DA on firing activities of single neurons was examined. It was found that, during application of DA, synchronized activities between single neuron and its neighboring neurons was enhanced. At the meantime, the temporal structures of single neuron spike train changed significantly, and the temporal correlation in single neuron's response decreased. The pharmacological study results indicated that the activation of D1 receptor might have effects on gap junction permeability between RGCs. Our results suggested that the dopaminergic pathway participated in the modulation of spatial and temporal correlation of RGCs' firing activities, and may exert critical effects on visual information processing in the retina.

Regulation of spatial selectivity by crossover inhibition

Signals throughout the nervous system diverge into parallel excitatory and inhibitory pathways that later converge on downstream neurons to control their spike output. Converging excitatory and inhibitory synaptic inputs can exhibit a variety of temporal relationships. A common motif is feedforward inhibition, in which an increase (decrease) in excitatory input precedes a corresponding increase (decrease) in inhibitory input. The delay of inhibitory input relative to excitatory input originates from an extra synapse in the circuit shaping inhibitory input. Another common motif is push-pull or "crossover" inhibition, in which increases (decreases) in excitatory input occur together with decreases (increases) in inhibitory input. Primate On midget ganglion cells receive primarily feedforward inhibition and On parasol cells receive primarily crossover inhibition; this difference provides an opportunity to study how each motif shapes the light responses of cell types that play a key role in visual perception. For full-field stimuli, feedforward inhibition abbreviated and attenuated responses of On midget cells, while crossover inhibition, though plentiful, had surprisingly little impact on the responses of On parasol cells. Spatially structured stimuli, however, could cause excitatory and inhibitory inputs to On parasol cells to increase together, adopting a temporal relation very much like that for feedforward inhibition. In this case, inhibitory inputs substantially abbreviated a cell's spike output. Thus inhibitory input shapes the temporal stimulus selectivity of both midget and parasol ganglion cells, but its impact on responses of parasol cells depends strongly on the spatial structure of the light inputs.

Diverse visual features encoded in mouse lateral geniculate nucleus

The thalamus is crucial in determining the sensory information conveyed to cortex. In the visual system, the thalamic lateral geniculate nucleus (LGN) is generally thought to encode simple center-surround receptive fields, which are combined into more sophisticated features in cortex, such as orientation and direction selectivity. However, recent evidence suggests that a more diverse set of retinal ganglion cells projects to the LGN. We therefore used multisite extracellular recordings to define the repertoire of visual features represented in the LGN of mouse, an emerging model for visual processing. In addition to center-surround cells, we discovered a substantial population with more selective coding properties, including direction and orientation selectivity, as well as neurons that signal absence of contrast in a visual scene. The direction and orientation selective neurons were enriched in regions that match the termination zones of direction selective ganglion cells from the retina, suggesting a source for their tuning. Together, these data demonstrate that the mouse LGN contains a far more elaborate representation of the visual scene than current models posit. These findings should therefore have a significant impact on our understanding of the computations performed in mouse visual cortex.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

The power of connectivity: identity preserving transformations on visual streams in the spike domain

We investigate neural architectures for identity preserving transformations (IPTs) on visual stimuli in the spike domain. The stimuli are encoded with a population of spiking neurons; the resulting spikes are processed and finally decoded. A number of IPTs are demonstrated including faithful stimulus recovery, as well as simple transformations on the original visual stimulus such as translations, rotations and zoomings. We show that if the set of receptive fields satisfies certain symmetry properties, then IPTs can easily be realized and additionally, the same basic stimulus decoding algorithm can be employed to recover the transformed input stimulus. Using group theoretic methods we advance two different neural encoding architectures and discuss the realization of exact and approximate IPTs. These are realized in the spike domain processing block by a "switching matrix" that regulates the input/output connectivity between the stimulus encoding and decoding blocks. For example, for a particular connectivity setting of the switching matrix, the original stimulus is faithfully recovered. For other settings, translations, rotations and dilations (or combinations of these operations) of the original video stream are obtained. We evaluate our theoretical derivations through extensive simulations on natural video scenes, and discuss implications of our results on the problem of invariant object recognition in the spike domain.

Peptide regulators of peripheral taste function

The peripheral sensory organ of the gustatory system, the taste bud, contains a heterogeneous collection of sensory cells. These taste cells can differ in the stimuli to which they respond and the receptors and other signaling molecules they employ to transduce and encode those stimuli. This molecular diversity extends to the expression of a varied repertoire of bioactive peptides that appear to play important functional roles in signaling taste information between the taste cells and afferent sensory nerves and/or in processing sensory signals within the taste bud itself. Here, we review studies that examine the expression of bioactive peptides in the taste bud and the impact of those peptides on taste functions. Many of these peptides produced in taste buds are known to affect appetite, satiety or metabolism through their actions in the brain, pancreas and other organs, suggesting a functional link between the gustatory system and the neural and endocrine systems that regulate feeding and nutrient utilization.

A virtual retina for studying population coding

At every level of the visual system – from retina to cortex – information is encoded in the activity of large populations of cells. The populations are not uniform, but contain many different types of cells, each with its own sensitivities to visual stimuli. Understanding the roles of the cell types and how they work together to form collective representations has been a long-standing goal. This goal, though, has been difficult to advance, and, to a large extent, the reason is data limitation. Large numbers of stimulus/response relationships need to be explored, and obtaining enough data to examine even a fraction of them requires a great deal of experiments and animals. Here we describe a tool for addressing this, specifically, at the level of the retina. The tool is a data-driven model of retinal input/output relationships that is effective on a broad range of stimuli – essentially, a virtual retina. The results show that it is highly reliable: (1) the model cells carry the same amount of information as their real cell counterparts, (2) the quality of the information is the same – that is, the posterior stimulus distributions produced by the model cells closely match those of their real cell counterparts, and (3) the model cells are able to make very reliable predictions about the functions of the different retinal output cell types, as measured using Bayesian decoding (electrophysiology) and optomotor performance (behavior). In sum, we present a new tool for studying population coding and test it experimentally. It provides a way to rapidly probe the actions of different cell classes and develop testable predictions. The overall aim is to build constrained theories about population coding and keep the number of experiments and animals to a minimum.

Role of melatonin and its receptors in the vertebrate retina

Melatonin is a chemical signal of darkness that is produced by retinal photoreceptors and pinealocytes. In the retina, melatonin diffuses from the photoreceptors to bind to specific receptors on a variety of inner retinal neurons to modify their activity. Potential target cells for melatonin in the inner retina are amacrine cells, bipolar cells, horizontal cells, and ganglion cells. Melatonin inhibits the release of dopamine from amacrine cells and increases the light sensitivity of horizontal cells. Melatonin receptor subtypes show differential, cell-specific patterns of expression that are likely to underlie differential functional modulation of specific retinal pathways. Melatonin potentiates rod signals to ON-type bipolar cells, via activation of the melatonin MT2 (Mel1b) receptor, suggesting that melatonin modulates the function of specific retinal circuits based on the differential distribution of its receptors. The selective and differential expression of melatonin receptor subtypes in cone circuits suggest a conserved function for melatonin in enhancing transmission from rods to second-order neurons and thus promote dark adaptation.

Features and functions of nonlinear spatial integration by retinal ganglion cells

Ganglion cells in the vertebrate retina integrate visual information over their receptive fields. They do so by pooling presynaptic excitatory inputs from typically many bipolar cells, which themselves collect inputs from several photoreceptors. In addition, inhibitory interactions mediated by horizontal cells and amacrine cells modulate the structure of the receptive field. In many models, this spatial integration is assumed to occur in a linear fashion. Yet, it has long been known that spatial integration by retinal ganglion cells also incurs nonlinear phenomena. Moreover, several recent examples have shown that nonlinear spatial integration is tightly connected to specific visual functions performed by different types of retinal ganglion cells. This work discusses these advances in understanding the role of nonlinear spatial integration and reviews recent efforts to quantitatively study the nature and mechanisms underlying spatial nonlinearities. These new insights point towards a critical role of nonlinearities within ganglion cell receptive fields for capturing responses of the cells to natural and behaviorally relevant visual stimuli. In the long run, nonlinear phenomena of spatial integration may also prove important for implementing the actual neural code of retinal neurons when designing visual prostheses for the eye.

Human trichromacy revisited

The presence of a photopigment (melanopsin) within certain retinal ganglion cells was a surprising and significant discovery. This pigment is routinely described as "nonvisual" to highlight its signaling role in pupil dilation and circadian rhythms. Here we asked whether light absorbed by melanopsin can be seen by healthy human subjects. To answer this requires delivering intense (above rod saturation), well-controlled lights using four independent primaries. We collected detection thresholds to many four-primary stimuli. Threshold measurements in the fovea are explained by trichromatic theory, with no need to invoke a fourth photopigment. In the periphery, where melanopsin is present, threshold measurements deviate from trichromatic theory; at high photopic levels, sensitivity is explained by absorptions in four, not three, photopigment classes. We consider a series of hypotheses to explain the tetrasensitivity at high photopic levels in the human peripheral field. The most likely hypothesis is that in healthy human subjects melanopsin absorptions influence visibility.

Properties and application of a multichannel integrated circuit for low-artifact, patterned electrical stimulation of neural tissue

OBJECTIVE

Modern multielectrode array (MEA) systems can record the neuronal activity from thousands of electrodes, but their ability to provide spatio-temporal patterns of electrical stimulation is very limited. Furthermore, the stimulus-related artifacts significantly limit the ability to record the neuronal responses to the stimulation. To address these issues, we designed a multichannel integrated circuit for a patterned MEA-based electrical stimulation and evaluated its performance in experiments with isolated mouse and rat retina.

APPROACH

The Stimchip includes 64 independent stimulation channels. Each channel comprises an internal digital-to-analogue converter that can be configured as a current or voltage source. The shape of the stimulation waveform is defined independently for each channel by the real-time data stream. In addition, each channel is equipped with circuitry for reduction of the stimulus artifact.

MAIN RESULTS

Using a high-density MEA stimulation/recording system, we effectively stimulated individual retinal ganglion cells (RGCs) and recorded the neuronal responses with minimal distortion, even on the stimulating electrodes. We independently stimulated a population of RGCs in rat retina, and using a complex spatio-temporal pattern of electrical stimulation pulses, we replicated visually evoked spiking activity of a subset of these cells with high fidelity. Significance. Compared with current state-of-the-art MEA systems, the Stimchip is able to stimulate neuronal cells with much more complex sequences of electrical pulses and with significantly reduced artifacts. This opens up new possibilities for studies of neuronal responses to electrical stimulation, both in the context of neuroscience research and in the development of neuroprosthetic devices.

Neural stimulation for visual rehabilitation: advances and challenges

Blindness affects tens of million people worldwide and its prevalence constantly increases along with population aging. In some pathologies leading to vision loss, prosthetic approaches are currently the only hope for the patient to recover some visual perception. Here, we review the latest advances in visual prosthetic strategies with their respective strength and weakness. The principle is to electrically stimulate neurons along the visual pathway. Ocular approaches target the remaining retinal cells whereas brain stimulation aims at stimulating higher visual structures directly. Even though ocular approaches are less invasive and easier to implement, brain stimulation can be applied to diseases where the connection between the retina and the brain is lost such as in glaucoma and could therefore benefit to patients with different pathologies. Today, numbers of groups are investigating these strategies and the first devices start being commercialized. However, critical bottlenecks still impair our scientific efforts towards efficient visual implants. These challenges include electrode miniaturization, material optimization, multiplexing of stimulation channels and encoding of visual information into electrical stimuli.

Parasol cell mosaics are unlikely to drive the formation of structured orientation maps in primary visual cortex

The receptive fields of on- and off-center parasol cell mosaics independently tile the retina to ensure efficient sampling of visual space. A recent theoretical model represented the on- and off-center mosaics by noisy hexagonal lattices of slightly different density. When the two lattices are overlaid, long-range Moiré interference patterns are generated. These Moiré interference patterns have been suggested to drive the formation of highly structured orientation maps in visual cortex. Here, we show that noisy hexagonal lattices do not capture the spatial statistics of parasol cell mosaics. An alternative model based upon local exclusion zones, termed as the pairwise interaction point process (PIPP) model, generates patterns that are statistically indistinguishable from parasol cell mosaics. A key difference between the PIPP model and the hexagonal lattice model is that the PIPP model does not generate Moiré interference patterns, and hence stimulated orientation maps do not show any hexagonal structure. Finally, we estimate the spatial extent of spatial correlations in parasol cell mosaics to be only 200-350 μm, far less than that required to generate Moiré interference. We conclude that parasol cell mosaics are too disordered to drive the formation of highly structured orientation maps in visual cortex.

The slope of the psychometric function and non-stationarity of thresholds in spatiotemporal contrast vision

The slope of the two-interval, forced-choice psychometric function (e.g. the Weibull parameter, β) provides valuable information about the relationship between contrast sensitivity and signal strength. However, little is known about how or whether β varies with stimulus parameters such as spatiotemporal frequency and stimulus size and shape. A second unresolved issue concerns the best way to estimate the slope of the psychometric function. For example, if an observer is non-stationary (e.g. their threshold drifts between experimental sessions), β will be underestimated if curve fitting is performed after collapsing the data across experimental sessions. We measured psychometric functions for 2 experienced observers for 14 different spatiotemporal configurations of pulsed or flickering grating patches and bars on each of 8 days. We found β≈3 to be fairly constant across almost all conditions, consistent with a fixed nonlinear contrast transducer and/or a constant level of intrinsic stimulus uncertainty (e.g. a square law transducer and a low level of intrinsic uncertainty). Our analysis showed that estimating a single β from results averaged over several experimental sessions was slightly more accurate than averaging multiple estimates from several experimental sessions. However, the small levels of non-stationarity (SD≈0.8dB) meant that the difference between the estimates was, in practice, negligible.

Robust action recognition using multi-scale spatial-temporal concatenations of local features as natural action structures

Human and many other animals can detect, recognize, and classify natural actions in a very short time. How this is achieved by the visual system and how to make machines understand natural actions have been the focus of neurobiological studies and computational modeling in the last several decades. A key issue is what spatial-temporal features should be encoded and what the characteristics of their occurrences are in natural actions. Current global encoding schemes depend heavily on segmenting while local encoding schemes lack descriptive power. Here, we propose natural action structures, i.e., multi-size, multi-scale, spatial-temporal concatenations of local features, as the basic features for representing natural actions. In this concept, any action is a spatial-temporal concatenation of a set of natural action structures, which convey a full range of information about natural actions. We took several steps to extract these structures. First, we sampled a large number of sequences of patches at multiple spatial-temporal scales. Second, we performed independent component analysis on the patch sequences and classified the independent components into clusters. Finally, we compiled a large set of natural action structures, with each corresponding to a unique combination of the clusters at the selected spatial-temporal scales. To classify human actions, we used a set of informative natural action structures as inputs to two widely used models. We found that the natural action structures obtained here achieved a significantly better recognition performance than low-level features and that the performance was better than or comparable to the best current models. We also found that the classification performance with natural action structures as features was slightly affected by changes of scale and artificially added noise. We concluded that the natural action structures proposed here can be used as the basic encoding units of actions and may hold the key to natural action understanding.

Octopaminergic modulation of contrast sensitivity

Sensory systems adapt to prolonged stimulation by decreasing their response to continuous stimuli. Whereas visual motion adaptation has traditionally been studied in immobilized animals, recent work indicates that the animal's behavioral state influences the response properties of higher-order motion vision-sensitive neurons. During insect flight octopamine is released, and pharmacological octopaminergic activation can induce a fictive locomotor state. In the insect optic ganglia, lobula plate tangential cells (LPTCs) spatially pool input from local elementary motion detectors (EMDs) that correlate luminosity changes from two spatially discrete inputs after delaying the signal from one. The LPTC velocity optimum thereby depends on the spatial separation of the inputs and on the EMD's delay properties. Recently it was shown that behavioral activity increases the LPTC velocity optimum, with modeling suggesting this to originate in the EMD's temporal delay filters. However, behavior induces an additional post-EMD effect: the LPTC membrane conductance increases in flying flies. To physiologically investigate the degree to which activity causes presynaptic and postsynaptic effects, we conducted intracellular recordings of Eristalis horizontal system (HS) neurons. We constructed contrast response functions before and after adaptation at different temporal frequencies, with and without the octopamine receptor agonist chlordimeform (CDM). We extracted three motion adaptation components, where two are likely to be generated presynaptically of the LPTCs, and one within them. We found that CDM affected the early, EMD-associated contrast gain reduction, temporal frequency dependently. However, a CDM-induced change of the HS membrane conductance disappeared during and after visual stimulation. This suggests that physical activity mainly affects motion adaptation presynaptically of LPTCs, whereas post-EMD effects have a minimal effect.

Componentes sensoriais e atencionais do tempo de reação: efeitos do tamanho, excentricidade e previsibilidade de estímulos visuais

A percepção visual depende do arcabouço sensorial e do processamento atencional. Este trabalho estudou o efeito, sobre o tempo de reação manual (TR), do tamanho, excentricidade e previsibilidade de estímulos visuais. No experimento 1 (n=8), um alvo foi apresentado aleatoriamente em uma de quatro excentricidades diferentes, possuindo três possíveis tamanhos. O experimento 2 (n=12) apresentava configuração similar, porém uma pista indicava o quadrante de maior probabilidade (70%) de apresentação do alvo. Os resultados mostraram um aumento do TR em função da excentricidade do alvo, além de uma diminuição do TR com o aumento do tamanho do alvo e indicação correta da pista. Uma análise das interações sugere uma superposição de mecanismos atencionais e puramente sensoriais compartilhando um estágio comum do processamento visual.

Frequency and amplitude modulation have different effects on the percepts elicited by retinal stimulation

PURPOSE

In an effort to restore functional form vision, epiretinal prostheses that elicit percepts by directly stimulating remaining retinal circuitry were implanted in human subjects with advanced retinitis pigmentosa RP). In this study, manipulating pulse train frequency and amplitude had different effects on the size and brightness of phosphene appearance.

METHODS

Experiments were performed on a single subject with severe RP (implanted with a 16-channel epiretinal prosthesis in 2004) on nine individual electrodes. Psychophysical techniques were used to measure both the brightness and size of phosphenes when the biphasic pulse train was varied by either modulating the current amplitude (with constant frequency) or the stimulating frequency (with constant current amplitude).

RESULTS

Increasing stimulation frequency always increased brightness, while having a smaller effect on the size of elicited phosphenes. In contrast, increasing stimulation amplitude generally increased both the size and brightness of phosphenes. These experimental findings can be explained by using a simple computational model based on previous psychophysical work and the expected spatial spread of current from a disc electrode.

CONCLUSIONS

Given that amplitude and frequency have separable effects on percept size, these findings suggest that frequency modulation improves the encoding of a wide range of brightness levels without a loss of spatial resolution. Future retinal prosthesis designs could benefit from having the flexibility to manipulate pulse train amplitude and frequency independently (clinicaltrials.gov number, NCT00279500).

Light-evoked lateral GABAergic inhibition at single bipolar cell synaptic terminals is driven by distinct retinal microcircuits

Inhibitory amacrine cells (ACs) filter visual signals crossing the retina by modulating the excitatory, glutamatergic output of bipolar cells (BCs) on multiple temporal and spatial scales. Reciprocal feedback from ACs provides focal inhibition that is temporally locked to the activity of presynaptic BC activity, whereas lateral feedback originates from ACs excited by distant BCs. These distinct feedback mechanisms permit temporal and spatial computation at BC terminals. Here, we used a unique preparation to study light-evoked IPSCs recorded from axotomized terminals of ON-type mixed rod/cone BCs (Mb) in goldfish retinal slices. In this preparation, light-evoked IPSCs could only reach axotomized BC terminals via the lateral feedback pathway, allowing us to study lateral feedback in the absence of overlapping reciprocal feedback components. We found that light evokes ON and OFF lateral IPSCs (L-IPSCs) in Mb terminals having different temporal patterns and conveyed via distinct retinal pathways. The relative contribution of rods versus cones to ON and OFF L-IPSCs was light intensity dependent. ACs presynaptic to Mb BC terminals received inputs via AMPA/KA- and NMDA-type receptors in both the ON and OFF pathways, and used TTX-sensitive sodium channels to boost signal transfer along their processes. ON and OFF L-IPSCs, like reciprocal feedback IPSCs, were mediated by both GABA(A) and GABA(C) receptors. However, our results suggest that lateral and reciprocal feedback do not cross-depress each other, and are therefore mediated by distinct populations of ACs. These findings demonstrate that retinal inhibitory circuits are highly specialized to modulate BC output at different light intensities.

CNTF and retina

Ciliary neurotrophic factor (CNTF) is one of the most studied neurotrophic factors for neuroprotection of the retina. A large body of evidence demonstrates that CNTF promotes rod photoreceptor survival in almost all animal models. Recent studies indicate that CNTF also promotes cone photoreceptor survival and cone outer segment regeneration in the degenerating retina and improves cone function in dogs with congenital achromotopsia. In addition, CNTF is a neuroprotective factor and an axogenesis factor for retinal ganglion cells (RGCs). This review focuses on the effects of exogenous CNTF on photoreceptors and RGCs in the mammalian retina and the potential clinical application of CNTF for retinal degenerative diseases.

A processing platform for optoelectronic/optogenetic retinal prosthesis

The field of retinal prosthesis has been steadily developing over the last two decades. Despite the many obstacles, clinical trials for electronic approaches are in progress and already demonstrating some success. Optogenetic/optoelectronic retinal prosthesis may prove to have even greater capabilities. Although resolutions are now moving beyond recognition of simple shapes, it will nevertheless be poor compared to normal vision. If we define the aim to be to return mobility and natural scene recognition to the patient, it is important to maximize the useful visual information we attempt to transfer. In this paper, we highlight a method to simplify the scene, perform spatial image compression, and then apply spike coding. We then show the potential for translation on standard consumer processors. The algorithms are applicable to all forms of visual prosthesis, but we particularly focus on optogenetic approaches.