Ganglion Cell Receptive Fields Research Articles

Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina.

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings.

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.

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.

Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks

SummaryTraditional models of retinal system identification analyze the neural response to artificial stimuli using models consisting of predefined components. The model design is limited to prior knowledge, and the artificial stimuli are too simple to be compared with stimuli processed by the retina. To fill in this gap with an explainable model that reveals how a population of neurons work together to encode the larger field of natural scenes, here we used a deep-learning model for identifying the computational elements of the retinal circuit that contribute to learning the dynamics of natural scenes. Experimental results verify that the recurrent connection plays a key role in encoding complex dynamic visual scenes while learning biological computational underpinnings of the retinal circuit. In addition, the proposed models reveal both the shapes and the locations of the spatiotemporal receptive fields of ganglion cells.

Fine Structure of the Receptive Fields of Orientation-Selective Ganglion Cells in the Fish Retina

Fine Structure of the Receptive Fields of Orientation-Selective Ganglion Cells in the Fish Retina

Unravelling Neural Coding of Dynamic Natural Visual Scenes via Convolutional Recurrent Neural Networks

Retina, providing and preprocessing almost all the visual information for brain, is a much sophisticated neural system than we think. In neural coding, the central goal is to finding the relationship between a cause (e.g. a visual stimulus) and the effect (i.e., the neural response). Neural system identification aims to reveal the computational black boxes by learning the stimulus-response relationship. Traditional models of retinal system identification analysis the neural respond to artificial stimulus by models consisted of predefined components. The design of the model is limited by prior knowledge, and the artificial stimulus is too simple to be compared with the stimulus actually processed by the retina. As the most successful prediction models, deep neural networks, have demonstrated powerful computational ability in neural coding. In this study, to fill in the gap of explainable model that reveals how population of neurons work together to encode the larger field of dynamic natural scenes, we used a deep learning model to identify the computational elements of the retinal neural system that contribute to learning of the dynamics of natural visual scenes. Specifically, the proposed model can separate intricate spatiotemporal patterns by leveraging building blocks of the neural network model. By using physiological data with sequential natural scene inputs, we verify that the recurrent connection plays a key role in encoding complex dynamic visual scenes while learning biological computational underpinnings of the retina circuit. Our model subsequently learns both the shapes and location of the spatiotemporal receptive fields of ganglion cells. Moreover, we propose a method for evaluating the importance of the kernels learned by the network model in encoding dynamic visual scenes, which allows us to disentangle the dynamic computational structure of the retina. These results provide new insights into understanding the encoding mechanisms of retinal neurons and promote model design in machine learning for computational vision involving complex dynamic visual scenes.

Glycinergic and GABAergic interneurons shift the location and differentially alter the size of ganglion cell receptive field centers in the mammalian retina

By using the multi-electrode array (MEA) recording technique in conjunction with white-noise checkerboard stimuli and reverse correlation methods, we studied modulatory actions of glycinergic and GABAergic interneurons on spatiotemporal profiles of ganglion cells (GCs) in dark-adapted mouse retinas. We found that application of 2 µM strychnine decreased receptive field center radii of GCs by a mean value of 11%, and shifted the GC receptive field (RF) centers by a mean distance of 28.3 µm. On the other hand, 200 µM picrotoxin + 100 µM bicuculline + 50 µM TPMPA increased GC receptive field center radii by a mean value of 19%, and shifted the GC RF centers by a mean distance of 53.7 µm. Glycinergic neurons in the mouse retina are narrow-field amacrine cells that have been shown to mediate ON-OFF crossover inhibitory synapses within the RGs’ RF center, therefore they may increase the size and shift the location of GC RF center by synergistic addition to bipolar cell inputs to GCs. GABAergic neurons are wide-field amacrine cells and horizontal cells that are known to mediate antagonistic surround responses of GCs, and thus they decrease the GCs’ RF center size. Our results suggest that a major global function of glycinergic and GABAergic interneurons in the mammalian retina is to provide the flexibility for adjusting the size and location of GCs’ RF centers. The apparent shifts of GC RF centers suggest that the synergistic addition by GlyACs and the surround inhibition by GABAergic interneurons are not spatially symmetrical within GC RFs.

Genetic dissection of rod and cone pathways mediating light responses and receptive fields of ganglion cells in the mouse retina

Retinal ganglion cells (GCs) are important visual neurons which carry complex spatiotemporal information from the retina to higher visual centers in the brain. By taking advantage of pathway-specific knockout/mutant mice and multi-electrode array (MEA) recording techniques, we analyze contributions of rod and cone pathways to responsiveness, kinetics and receptive field profiles of GCs under scotopic and photopic conditions. Our data suggest: (1) Scotopic responses of some GCs require all three rod pathways, some require only the secondary and tertiary rod pathways, and others require only the tertiary rod pathway. (2) There are more responsive GCs in photopic conditions than responsive GCs in scotopic conditions. (3) Gap junctions slow down GCs’ scotopic light responses and increase GCs’ ratio of antagonistic to center inputs. (4) Cone pathways do not affect the kinetics but alter the ratio of antagonistic to center inputs of scotopic GC responses, and they speed up GCs photopic responses and alter the ratio of GCs’ antagonistic to center synaptic inputs and receptive field profiles. (5) Rod bipolar cells shorten response latency of ON GCs and increase the ratio of GCs’ antagonistic to center synaptic inputs. (6) Light adaptation speeds up GCs’ temporal processing and tunes GC photopic responses to higher frequencies, and the tertiary rod pathway plays a significant role in adaptation-induced TTP changes in some GCs. (7) GC RF center sizes are partially mediated by AIIACs and GC-GC coupling. (8) Connexin36 gap junctions and cone pathways alter synaptic circuits underlying antagonistic surround inputs to GCs in photopic conditions.

Bicycronic construct for optogenetic prosthesis of ganglion cell receptive field of degenerated retina

For the purpose of optogenetic prosthetics of the receptive field of the retinal ganglion cell, we have created a bicistronic genetic construct that carries genes of excitatory (channelorhodopsin2) and inhibitory (anionic channelorhodopsin) rhodopsins. A distinctive feature of this construct is the combination of two genes into one construct with the mutant IRES inserted between them, which ensures precise ratio of the expression levels of the first and second gene in each transfected cell. It was found that the illumination of the central part of transfected neuron with light with a wavelength of 470 nm causes the generation of action potentials in the cell. At the same time, light stimulation of the periphery of the neuron causes cessation of the generation of action potentials. Thus, we were able to simulate the ON-OFF interaction of the receptive field of the retinal ganglion cell using optogenetic methods. Theoretically, this construction can be used for optogenetic prosthetics of degenerative retina in case of its delivery to ganglion cells using lentiviral vectors.

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 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.

Artificial Shape Perception Retina Network Based on Tunable Memristive Neurons

Retina shows an extremely high signal processing efficiency because of its specific signal processing strategy which called computing in sensor. In retina, photoreceptor cells encode light signals into spikes and ganglion cells finish the shape perception process. In order to realize the neuromorphic vision sensor, the one-transistor-one-memristor (1T1M) structure which formed by one memristor and one MOSFET in serial is used to construct photoreceptor cell and ganglion cell. The voltage changes between two terminals of memristor and MOSFET can mimic the changes of membrane potential caused by spikes and illumination respectively. In this paper, the tunable memristive neurons with 1T1M structures are built. According to the concept of receptive field of ganglion cells (GCs) in the retina, the artificial shape perception retina network is constructed with these memristive neurons. The final results show that the artificial retina can extract shape information from the image and transfer it into spike frequency realizing the function of computing in sensor.

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.

Eliminating Glutamatergic Input onto Horizontal Cells Changes the Dynamic Range and Receptive Field Organization of Mouse Retinal Ganglion Cells.

In the mammalian retina, horizontal cells receive glutamatergic inputs from many rod and cone photoreceptors and return feedback signals to them, thereby changing photoreceptor glutamate release in a light-dependent manner. Horizontal cells also provide feedforward signals to bipolar cells. It is unclear, however, how horizontal cell signals also affect the temporal, spatial, and contrast tuning in retinal output neurons, the ganglion cells. To study this, we generated a genetically modified mouse line in which we eliminated the light dependency of feedback by deleting glutamate receptors from mouse horizontal cells. This genetic modification allowed us to investigate the impact of horizontal cells on ganglion cell signaling independent of the actual mode of feedback in the outer retina and without pharmacological manipulation of signal transmission. In control and genetically modified mice (both sexes), we recorded the light responses of transient OFF-α retinal ganglion cells in the intact retina. Excitatory postsynaptic currents (EPSCs) were reduced and the cells were tuned to lower temporal frequencies and higher contrasts, presumably because photoreceptor output was attenuated. Moreover, receptive fields of recorded cells showed a significantly altered surround structure. Our data thus suggest that horizontal cells are responsible for adjusting the dynamic range of retinal ganglion cells and, together with amacrine cells, contribute to the center/surround organization of ganglion cell receptive fields in the mouse.SIGNIFICANCE STATEMENT Horizontal cells represent a major neuronal class in the mammalian retina and provide lateral feedback and feedforward signals to photoreceptors and bipolar cells, respectively. The mode of signal transmission remains controversial and, moreover, the contribution of horizontal cells to visual processing is still elusive. To address the question of how horizontal cells affect retinal output signals, we recorded the light responses of transient OFF-α retinal ganglion cells in a newly generated mouse line. In this mouse line, horizontal cell signals were no longer modulated by light. With light response recordings, we show that horizontal cells increase the dynamic range of retinal ganglion cells for contrast and temporal changes and contribute to the center/surround organization of their receptive fields.

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.

Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells.

Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell's signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell's receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types.NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types.

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.

Functional properties of spontaneous excitatory currents and encoding of light/dark transitions in horizontal cells of the mouse retina.

As all visual information is represented in the spatio-temporal dynamics of transmitter release from photoreceptors and the combined postsynaptic responses of second-order neurons, appropriate synaptic transfer functions are fundamental for a meaningful perception of the visual world. The functional contribution of horizontal cells to gain control and organization of bipolar and ganglion cell receptive fields can only be evaluated with an in-depth understanding of signal processing in horizontal cells. Therefore, a horizontal slice preparation of the mouse retina was established to record from horizontal cell bodies with their dendritic fields intact and receiving functional synaptic input from cone photoreceptors. Horizontal cell bodies showed spontaneous excitatory currents (spEPSCs) of monophasic and more complex multi-peak waveforms. spEPSCs were induced by quantal release of glutamate from presynaptic cones with a unitary amplitude of 3 pA. Non-stationary noise analysis revealed that spEPSCs with a monoexponential decay were mediated by 7-8 glutamate receptors with a single-channel amplitude of 1.55 pA. Responses to photopic full-field illumination were characterized by reduction of a tonic inward current or hyperpolarization, inhibition of spEPSCs, followed by a fast and transient inward current at light offset. The response to periodic dark/light transitions of different frequencies was dependent on the adaptational status of the cell with a limiting frequency of 10 Hz. Both on and off components of the light response were mediated by AMPA and kainate receptors. Detailed analysis of horizontal cell synaptic physiology is a prerequisite for understanding signal coding and processing at the photoreceptor ribbon synapse.

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.