Receptive Fields Of Retinal Ganglion Cells Research Articles

Photosynthetic Protein-Based Retinal Ganglion Cell Receptive Fields for Detecting Edges and Brightness Illusions.

Bacteriorhodopsin, isolated from a halophilic bacterium, is a photosynthetic protein with a structure and function similar to those of the visual pigment rhodopsin. A voltaic cell with bacteriorhodopsin sandwiched between two transparent electrodes exhibits a time-differential response akin to that observed in retinal ganglion cells. It is intriguing as a means to emulate excitation and inhibition in the neural response. Here, we present a neuromorphic device emulating the retinal ganglion cell receptive field fabricated by patterning bacteriorhodopsin onto two transparent electrodes and encapsulating them with an electrolyte solution. This protein-based artificial ganglion cell receptive field is characterized as a bandpass filter that simultaneously replicates excitatory and inhibitory responses within a single element, successfully detecting image edges and phenomena of brightness illusions. The device naturally emulates the highly interacting ganglion cell receptive fields by exploiting the inherent properties of proteins without the need for electronic components, bias power supply, or an external operating circuit.

Examining the concordance of retinal ganglion cell counts generated using measures of structure and function.

There are several indirect methods used to estimate retinal ganglion cell (RGC) count in an individual eye, but there is limited information as to the agreement between these methods. In this work, RGC receptive field (RGC-RF) count underlying a spot stimulus (0.43°, Goldmann III) was calculated and compared using three different methods. RGC-RF count was calculated at a retinal eccentricity of 2.32 mm for 44 healthy adult participants (aged 18-58 years, refractive error -9.75 DS to +1.75 DS) using: (i) functional measures of achromatic peripheral grating resolution acuity (PGRA), (ii) structural measures of RGC-layer thickness (OCT-model, based on the method outlined by Raza and Hood) and (iii) scaling published histology density data to simulate a global expansion in myopia (Histology-Balloon). Whilst average RGC-RF counts from the OCT-model (median 105.3, IQR 99.6-111.0) and the Histology-Balloon model (median 107.5, IQR 97.7-114.6) were similar, PGRA estimates were approximately 65% lower (median 37.7, IQR 33.8-46.0). However, there was poor agreement between all three methods (Bland-Altman 95% limits of agreement; PGRA/OCT: 55.4; PGRA/Histology-Balloon 59.3; OCT/Histology-Balloon: 52.4). High intersubject variability in RGC-RF count was evident using all three methods. The lower PGRA RGC-RF counts may be the result of targeting only a specific subset of functional RGCs, as opposed to the coarser approach of the OCT-model and Histology-Balloon, which include all RGCs, and also likely displaced amacrine cells. In the absence of a 'ground truth', direct measure of RGC-RF count, it is not possible to determine which method is most accurate, and each has limitations. However, what is clear is the poor agreement found between the methods prevents direct comparison of RGC-RF counts between studies utilising different methodologies and highlights the need to utilise the same method in longitudinal work.

Synchronous inhibitory pathways create both efficiency and diversity in the retina

Sensory receptive fields combine features that originate in different neural pathways. Retinal ganglion cell receptive fields compute intensity changes across space and time using a peripheral region known as the surround, a property that improves information transmission about natural scenes. The visual features that construct this fundamental property have not been quantitatively assigned to specific interneurons. Here, we describe a generalizable approach using simultaneous intracellular and multielectrode recording to directly measure and manipulate the sensory feature conveyed by a neural pathway to a downstream neuron. By directly controlling the gain of individual interneurons in the circuit, we show that rather than transmitting different temporal features, inhibitory horizontal cells and linear amacrine cells synchronously create the linear surround at different spatial scales and that these two components fully account for the surround. By analyzing a large population of ganglion cells, we observe substantial diversity in the relative contribution of amacrine and horizontal cell visual features while still allowing individual cells to increase information transmission under the statistics of natural scenes. Established theories of efficient coding have shown that optimal information transmission under natural scenes allows a diverse set of receptive fields. Our results give a mechanism for this theory, showing how distinct neural pathways synthesize a sensory computation and how this architecture both generates computational diversity and achieves the objective of high information transmission.

Retinal Processing: Insights from Mathematical Modelling.

The retina is the entrance of the visual system. Although based on common biophysical principles, the dynamics of retinal neurons are quite different from their cortical counterparts, raising interesting problems for modellers. In this paper, I address some mathematically stated questions in this spirit, discussing, in particular: (1) How could lateral amacrine cell connectivity shape the spatio-temporal spike response of retinal ganglion cells? (2) How could spatio-temporal stimuli correlations and retinal network dynamics shape the spike train correlations at the output of the retina? These questions are addressed, first, introducing a mathematically tractable model of the layered retina, integrating amacrine cells’ lateral connectivity and piecewise linear rectification, allowing for computing the retinal ganglion cells receptive field together with the voltage and spike correlations of retinal ganglion cells resulting from the amacrine cells networks. Then, I review some recent results showing how the concept of spatio-temporal Gibbs distributions and linear response theory can be used to characterize the collective spike response to a spatio-temporal stimulus of a set of retinal ganglion cells, coupled via effective interactions corresponding to the amacrine cells network. On these bases, I briefly discuss several potential consequences of these results at the cortical level.

Visual Deprivation Retards the Maturation of Dendritic Fields and Receptive Fields of Mouse Retinal Ganglion Cells.

It was well documented that both the size of the dendritic field and receptive field of retinal ganglion cells (RGCs) are developmentally regulated in the mammalian retina, and visual stimulation is required for the maturation of the dendritic and receptive fields of mouse RGCs. However, it is not clear whether the developmental changes of the RGC receptive field correlate with the dendritic field and whether visual stimulation regulates the maturation of the dendritic field and receptive field of RGCs in a correlated manner. The present work demonstrated that both the dendritic and receptive fields of RGCs continuously develop after eye opening. However, the correlation between the developmental changes in the receptive field size and the dendritic field varies among different RGC types. These results suggest a continuous change of synaptic converging of RGC synaptic inputs in an RGC type-dependent manner. Besides, light deprivation impairs both the development of dendritic and receptive fields.

Spike-triggered Clustering for Retinal Ganglion Cell Classification.

Retinal ganglion cells (RGCs), the retina’s output neurons, encode visual information through spiking. The RGC receptive field (RF) represents the basic unit of visual information processing in the retina. RFs are commonly estimated using the spike-triggered average (STA), which is the average of the stimulus patterns to which a given RGC is sensitive. Whereas STA, based on the concept of the average, is simple and intuitive, it leaves more complex structures in the RFs undetected. Alternatively, spike-triggered covariance (STC) analysis provides information on second-order RF statistics. However, STC is computationally cumbersome and difficult to interpret. Thus, the objective of this study was to propose and validate a new computational method, called spike-triggered clustering (STCL), specific for multimodal RFs. Specifically, RFs were fit with a Gaussian mixture model, which provides the means and covariances of multiple RF clusters. The proposed method recovered bipolar stimulus patterns in the RFs of ON-OFF cells, while the STA identified only ON and OFF RGCs, and the remaining RGCs were labeled as unknown types. In contrast, our new STCL analysis distinguished ON-OFF RGCs from the ON, OFF, and unknown RGC types classified by STA. Thus, the proposed method enables us to include ON-OFF RGCs prior to retinal information analysis.

Revisiting the Drasdo Model: Implications for Structure-Function Analysis of the Macular Region.

PurposeTo provide a consistent implementation of a retinal ganglion cell (RGC) displacement model proposed by Drasdo et al. for macular structure-function analysis, customizable by axial length (AL).MethodsThe effect of axial length on the shape of the inner retina was measured on 235 optical coherence tomography (OCT) scans from healthy eyes, to provide evidence for geometric scaling of structures with eye size. Following this assumption, we applied the Drasdo model to map perimetric stimuli on the radially displaced RGCs using two different methods: Method 1 only displaced the center of the stimuli; Method 2 applied the displacement to every point on the edge of the stimuli. We compared the accuracy of the two methods by calculating, for each stimulus, the number of expected RGC receptive fields and the number RGCs calculated from the histology map, expected to be equivalent. The same calculation was repeated on RGC density maps derived from 28 OCT scans from 28 young healthy subjects (age < 40 years) to confirm our results on clinically available measurements.ResultsThe size of the retinal structures significantly increased with AL (P < 0.001) and was well predicted by geometric scaling. Method 1 systematically underestimated the RGC counts by as much as 60%. No bias was observed with Method 2.ConclusionsThe Drasdo model can effectively account for AL assuming geometric scaling. Method 2 should be used for structure-function analyses.Translational RelevanceWe developed a free web App in Shiny R to make our results available for researchers.

Physiological constraints of visual pathway lead to more efficient coding of information in retina

Nowadays, numerous studies have investigated the modeling of efficient neural encoding processes in the retina of the eye to encode the sensory data. Retina, as the innermost coat of the eye, is the first and the most important area of the visual neural system of mammalians, which is responsible for neural processes. Retina encodes the information of light intensity into a sequence of spikes, and sends them to retinal ganglion cells (RGCs) for further processing. An appropriate retinal encoding model should be adapted to the real retina as much as possible by considering the physiological constraints of the visual pathway to transfer most of the information of the input signal to the brain without too much redundancy of the channel. In this paper, inspired from the existing linear models of retinal encoding process, which have employed input noise and the spatial locality of the RGCs receptive fields (RFs) in the calculation of the encoding matrix, two extra physiological constraints, adapted from the real retina are taken into account so as to achieve a more realistic model for themammalian retina. These new constraints that are the correlation between RGCs and the spatial locality of the photoreceptors’ projective fields (PFs), are modeled in a mathematical form and analyzed in detail. To quantify fidelity of the proposed encoding matrix and prove its superiority over existing models, various parameters of the models are calculated and presented in this paper: mean square error between the original and reconstructed image (MSE), the redundancy of the channel, the amount of information transferred through the channel, and the amount of wasted capacity for carrying input noise, to name a few. The results of these calculations show that the proposed model transfers input information with less redundancy of the channel. In other words, it reduces a portion of channel capacity which is wasted for carrying the input noise in comparison to the existing models. Also, due to considering extra physiological constraints in the proposed model, it is acceptable to have a slightly higher amount of MSE value in order to become similar to the real retina.

An S-cone circuit for edge detection in the primate retina

Midget retinal ganglion cells (RGCs) are the most common RGC type in the primate retina. Their responses have been proposed to mediate both color and spatial vision, yet the specific links between midget RGC responses and visual perception are unclear. Previous research on the dual roles of midget RGCs has focused on those comparing long (L) vs. middle (M) wavelength sensitive cones. However, there is evidence for several other rare midget RGC subtypes receiving S-cone input, but their role in color and spatial vision is uncertain. Here, we confirm the existence of the single S-cone center OFF midget RGC circuit in the central retina of macaque monkey both structurally and functionally. We investigated the receptive field properties of the S-OFF midget circuit with single cell electrophysiology and 3D electron microscopy reconstructions of the upstream circuitry. Like the well-studied L vs. M midget RGCs, the S-OFF midget RGCs have a center-surround receptive field consistent with a role in spatial vision. While spectral opponency in a primate RGC is classically assumed to contribute to hue perception, a role supporting edge detection is more consistent with the S-OFF midget RGC receptive field structure and studies of hue perception.

Functional characterization of retinal ganglion cells using tailored nonlinear modeling

The mammalian retina encodes the visual world in action potentials generated by 20–50 functionally and anatomically-distinct types of retinal ganglion cell (RGC). Individual RGC types receive synaptic input from distinct presynaptic circuits; therefore, their responsiveness to specific features in the visual scene arises from the information encoded in synaptic input and shaped by postsynaptic signal integration and spike generation. Unfortunately, there is a dearth of tools for characterizing the computations reflected in RGC spike output. Therefore, we developed a statistical model, the separable Nonlinear Input Model, to characterize the excitatory and suppressive components of RGC receptive fields. We recorded RGC responses to a correlated noise (“cloud”) stimulus in an in vitro preparation of mouse retina and found that our model accurately predicted RGC responses at high spatiotemporal resolution. It identified multiple receptive fields reflecting the main excitatory and suppressive components of the response of each neuron. Significantly, our model accurately identified ON-OFF cells and distinguished their distinct ON and OFF receptive fields, and it demonstrated a diversity of suppressive receptive fields in the RGC population. In total, our method offers a rich description of RGC computation and sets a foundation for relating it to retinal circuitry.

The Relationship Between the Photopic Negative Response and Retinal Ganglion Cell Topography.

To assess the topographic relationship between the photopic negative response (PhNR) and retinal ganglion cell distribution in healthy individuals. Data was recorded from 16 healthy participants. The amplitude of PhNRs obtained in response to focal long duration (250 ms) and brief flash (5 ms), red (660 nm) on blue (469 nm) stimuli of increasing size (5° - full field) were measured. The number of retinal ganglion cell receptive fields (RGCf) in each stimulus area was established from the literature and regression analysis used to determine the relationships between: PhNR amplitude and number of RGCfs stimulated, PhNR density and the RGCf density and response per RGCf as a function of eccentricity. The overall amplitude of the PhNR increased with stimulus size and the response density declined from ∼0.1 μV/deg in the macular region to ∼0.003 μV/deg approximately 45° from the fovea. Contrary to expectations, the relationship between the PhNR and number of RGCf was nonlinear, the response from more eccentric neurons being about three times greater than those in the macular region. Although the amplitude of the PhNR broadly maps on to the topographic distribution of RGCf the increase in PhNR amplitude with increasing eccentricity is only partly explained by RGCf numbers. Increases in the PhNR amplitude may be due to topographic variations in the contributions from other non-RGC neurons, as well as eccentricity-related morphologic and physiologic differences in RGCs.

Bicistronic Construct for Optogenetic Prosthesis of Ganglion Cell Receptive Field of Degenerative Retina.

To perform optogenetic prosthetics of the retinal ganglion cell receptive field, a bicistronic genetic construct carrying the genes encoding the excitatory (channelrhodopsin-2) and inhibitory (Guillardia thetaanion channelrhodopsin GtACR2) rhodopsins was created. A characteristic feature of this construct was the combination of these two genes with a mutant IRES insertion between them, which ensures the exact ratio of expression levels of the first and second genes in each transfected cell. Illumination of the central part of the neuron with light with a wavelength of 470 nm induced the action potential generation in the cell. Stimulation of the peripheral neuronal region with light induced the inhibition of action potential generation. Thus, using optogenetics methods, we simulated the ON-OFF interaction in the retinal ganglion cell receptive field. Theoretically, this construct can be used for optogenetic prosthetics of degenerative retina in the case of its delivery to the ganglion cells with lentiviral vectors.

The dynamic receptive fields of retinal ganglion cells.

Retinal ganglion cells (RGCs) were one of the first classes of sensory neurons to be described in terms of a receptive field (RF). Over the last six decades, our understanding of the diversity of RGC types and the nuances of their response properties has grown exponentially. We will review the current understanding of RGC RFs mostly from studies in mammals, but including work from other vertebrates as well. We will argue for a new paradigm that embraces the fluidity of RGC RFs with an eye toward the neuroethology of vision. Specifically, we will focus on (1) different methods for measuring RGC RFs, (2) RF models, (3) feature selectivity and the distinction between fluid and stable RF properties, and (4) ideas about the future of understanding RGC RFs.

Spatial summation across the visual field in strabismic and anisometropic amblyopia

Ricco’s area (the largest area of visual space in which stimulus area and intensity are inversely proportional at threshold) has previously been hypothesised to be a result of centre/surround antagonism in retinal ganglion cell receptive fields, but recent evidence suggests a sizeable cortical contribution. Here, Ricco’s area was measured in amblyopia, a condition in which retinal receptive fields are normal, to better understand its physiological basis. Spatial summation functions were determined at 12 visual field locations in both eyes of 14 amblyopic adults and 15 normal-sighted controls. Ricco’s area was significantly larger in amblyopic eyes than in fellow non-amblyopic eyes. Compared to the size of Ricco’s area in control eyes, Ricco’s area measured significantly larger in amblyopic eyes. Additionally, Ricco’s area in the fellow, non-amblyopic eye of amblyopic participants measured significantly smaller than in control eyes. Compared to controls, Ricco’s area was larger in amblyopic eyes and smaller in fellow non-amblyopic eyes. Amblyopia type, binocularity, and inter-ocular difference in visual acuity were significantly associated with inter-ocular differences in Ricco’s area in amblyopes. The physiological basis for Ricco’s area is unlikely to be confined to the retina, but more likely representative of spatial summation at multiple sites along the visual pathway.

Visual resolution and cone spacing in the nasal and inferior retina.

To determine the retinal eccentricity at which cones are no longer an observable substitute for ganglion cells on nasal and inferior parafoveal visual acuity. Visual acuities were measured on 12 healthy volunteers, under dynamic adaptive optic aberrations correction (crx1™) in white light, from 0° to 6°, every two degrees, along the nasal and inferior retinal meridians. Cone spacing was measured on images of the retina acquired using an adaptive optic flood illumination retina camera (rtx1™) at the same eccentricity, except at 0°. Cone spacing increased by around 0.13min of arc per degree of eccentricity and a difference of 7% between both meridians was observed (higher cone spacing in the inferior retinal meridian). Visual resolution was higher in the nasal retinal meridian (difference of around 28% or 0.15 logMAR at 6°). Cone spacing can predict minimum angle of resolution (MAR) at 2° in both semi retinal meridians. In the inferior retinal meridian, MAR measurements are fairly well predicted by Watson's 50% mathematical model based on the midget retinal ganglion cell density. Along the nasal retinal meridian, the measured MAR lies between Watson's 50% and 100% models. At 2° of eccentricity, cone density accurately predicts visual resolution in both the nasal and inferior retina, supporting the idea that only 50% of the foveal midget retinal ganglion cells determine VA. The 50% model can also predict VA in the inferior retinal meridian at 4° and 6° of eccentricity. However, the 50% model underestimated visual acuity in the nasal retinal meridian at 4° and 6° of eccentricity consistent with the partially overlapping ON and OFF midget retinal ganglion cell receptive fields.

Distinct subcomponents of mouse retinal ganglion cell receptive fields are differentially altered by light adaptation

The remarkable dynamic range of vision is facilitated by adaptation of retinal sensitivity to ambient lighting conditions. An important mechanism of sensitivity adaptation is control of the spatial and temporal window over which light is integrated. The retina accomplishes this by switching between parallel synaptic pathways with differing kinetics and degrees of synaptic convergence. However, the relative shifts in spatial and temporal integration are not well understood – particularly in the context of the antagonistic spatial surround. Here, we resolve these issues by characterizing the adaptation-induced changes to spatiotemporal integration in the linear receptive field center and surround of mouse retinal ganglion cells. While most ganglion cells lose their antagonistic spatial surround under scotopic conditions, a strong surround is maintained in a subset. We then applied a novel technique that allowed us to analyze the receptive field as a triphasic temporal filter in the center and a biphasic filter in the surround. The temporal tuning of the surround was relatively maintained across adaptation conditions compared to the center, which greatly increased its temporal integration. Though all phases of the center’s triphasic temporal response slowed, some shifted significantly less. Additionally, adaptation differentially shifted ON and OFF pathway temporal tuning, reducing their asymmetry under scotopic conditions. Finally, spatial integration was significantly increased by dark adaptation in some cells while it decreased it in others. These findings provide novel insight into how adaptation adjusts visual information processing by altering fundamental properties of ganglion cell receptive fields, such as center-surround antagonism and space-time integration.

Center-Surround Inhibition in Working Memory

Directing visual attention toward a particular feature or location in the environment suppresses processing of nearby stimuli [1-4]. Echoing the center-surround organization of retinal ganglion cell receptive fields [5], and biasing of competitive local neuronal dynamics in favor of task-relevant stimuli [6], this "inhibitory surround" attention mechanism accentuates the demarcation between task-relevant and irrelevant items. Here, we show that internally maintaining a color stimulus in working memory (WM), rather than visually attending the stimulus in the external environment, produces an analogous pattern of inhibition for stimuli that are nearby in color space. Replicating a well-known effect of attentional capture by stimuli that match WM content [7], visual attention was biased toward (task-irrelevant) stimuli that exactly matched a WM item. This bias was curtailed, however, for stimuli that were very similar to the WMcontent (i.e., within the inhibitory zone surrounding the focus of WM) and recovered for less similar stimuli (i.e., beyond the bounds of the inhibitory surround). Moreover, the expression of this inhibition effect was positively associated with WM performance across observers. In a second experiment, inhibition also occurred between two similar items simultaneously held in WM. This suggests that maintenance in WM is characterized by an excitatory peak centered on the focus of (internal) attention, surrounded by an inhibitory zone to limit interference by irrelevant and confusable representations. Here, thus, we show for the first time that the same center-surround selection mechanism that focuses visual attention on sensory stimuli also selectively maintains internally activated representations in WM.

Activation of Neuropeptide Y Receptors Modulates Retinal Ganglion Cell Physiology and Exerts Neuroprotective Actions In Vitro.

Neuropeptide Y (NPY) is expressed in mammalian retina but the location and potential modulatory effects of NPY receptor activation remain largely unknown. Retinal ganglion cell (RGC) death is a hallmark of several retinal degenerative diseases, particularly glaucoma. Using purified RGCs and ex vivo rat retinal preparations, we have measured RGC intracellular free calcium concentration ([Ca2+]i) and RGC spiking activity, respectively. We found that NPY attenuated the increase in the [Ca2+]i triggered by glutamate mainly via Y1 receptor activation. Moreover, (Leu31, Pro34)−NPY, a Y1/Y5 receptor agonist, increased the initial burst response of OFF-type RGCs, although no effect was observed on RGC spontaneous spiking activity. The Y1 receptor activation was also able to directly modulate RGC responses by attenuating the NMDA-induced increase in RGC spiking activity. These results suggest that Y1 receptor activation, at the level of inner or outer plexiform layers, leads to modulation of RGC receptive field properties. Using in vitro cultures of rat retinal explants exposed to NMDA, we found that NPY pretreatment prevented NMDA-induced cell death. However, in an animal model of retinal ischemia-reperfusion injury, pretreatment with NPY or (Leu31, Pro34)−NPY was not able to prevent apoptosis or rescue RGCs. In conclusion, we found modulatory effects of NPY application that for the first time were detected at the level of RGCs. However, further studies are needed to evaluate whether NPY neuroprotective actions detected in retinal explants can be translated into animal models of retinal degenerative diseases.

Letter identification and the neural image classifier.

Letter identification is an important visual task for both practical and theoretical reasons. To extend and test existing models, we have reviewed published data for contrast sensitivity for letter identification as a function of size and have also collected new data. Contrast sensitivity increases rapidly from the acuity limit but slows and asymptotes at a symbol size of about 1 degree. We recast these data in terms of contrast difference energy: the average of the squared distances between the letter images and the average letter image. In terms of sensitivity to contrast difference energy, and thus visual efficiency, there is a peak around ¼ degree, followed by a marked decline at larger sizes. These results are explained by a Neural Image Classifier model that includes optical filtering and retinal neural filtering, sampling, and noise, followed by an optimal classifier. As letters are enlarged, sensitivity declines because of the increasing size and spacing of the midget retinal ganglion cell receptive fields in the periphery.

Local density of human midget retinal ganglion cell receptive fields

Local density of human midget retinal ganglion cell receptive fields