Biology subjects

Rieke, F.

Publications and source records attributed to Rieke, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Polyaxonal A1 amacrine cells form a spatially extended network in primate retina

Inhibitory networks shape information processing in the brain by integrating signals across space, regulating neuronal responses, and controlling the flow of signals through neural circuits. Understanding these computations requires linking the structure of individual inhibitory neuron types to their functional properties and network connectivity. The retina provides a tractable system for meeting this challenge, yet the organization of many retinal inhibitory circuits remains poorly understood. Here, we identify a population of polyaxonal amacrine cells recorded using multielectrode arrays as A1 amacrine cells, a morphologically defined interneuron type in primate retina. This identification is supported by a correspondence between properties of morphologically-identified A1 cells from single cell recordings and putative A1 amacrines in the array recordings. We then identified recursive bistratified ganglion cells in the array recordings based on their electrical coupling to A1 cells, linking this inhibitory network to retinal output pathways. A1 and recursive bistratified cells also share an asymmetry in receptive-field organization, with larger On than Off centers. Finally, A1 spike amplitudes decline during bursts, and analyses of their electrical images suggest that this change may cause some spikes to fail to propagate through their extensive axonal arbors. These findings establish the cellular identity and network organization of a long-range inhibitory circuit in the primate retina and reveal how neuronal architecture, connectivity, and spike dynamics may jointly shape the transmission of visual information.

neuroscience↗

bioRxiv2026

Designing stimuli for non-invasive, cell-type-specific manipulation of retinal ganglion cell activity

The retina encodes visual information through parallel pathways formed by distinct retinal ganglion (RGC) types. Current understanding of how each cell type contributes to downstream visual processing and perception is limited by a lack of tools for selectively manipulating the activities of individual RGC types. Here, we introduce a computational framework called STORM (SpatioTemporal Orthogonal Response Modulation) that creates visual stimuli that aim to selectively modulate the activities of specific RGC types while minimally affecting the activities of nearby RGCs of non-targeted types. To illustrate the approach, demonstrate its flexibility, and identify conditions under which each simulated RGC type could be selectively manipulated, we first applied this framework to simplified models of RGC function, such as Linear-Nonlinear-Poisson (LNP) and LN-LN cascade models. We also deployed this approach on more complex (and more accurate) models of RGC responses, based on convolutional neural networks. We demonstrate that differences in spatial receptive fields, temporal dynamics, response polarities, and nonlinearities can provide sufficient degrees of freedom for designing stimuli that selectively manipulate individual RGC types. We also generalize this approach to conditions where the receptive field locations are unknown for in vivo and clinical applications.

neuroscience↗

bioRxiv2026

Origin and functional impact of early nonlinearities in primate retina

Receptive fields provide a concise description of the stimulus selectivity of visual neurons. But this stimulus selectivity is neither static nor linear, and these nonlinear effects are not well captured by standard linear or pseudo-linear receptive field models. At the same time, receptive field models incorporating nonlinear effects are largely empirical, and are not easily interpreted in terms of underlying cellular and synaptic mechanisms. Here we show that two nonlinear mechanisms in the primate outer retina shape neural responses and that these contribute significantly to responses to natural stimuli and to the retinal output signals. Incorporating these outer retinal nonlinearities into models for visual function will improve our ability to identify the mechanistic origin of specific features of downstream visual responses.

neuroscience↗

bioRxiv2025

Rod-cone signal interference impairs mesopic motion discriminability in a model circuit

Under mesopic conditions, such as dawn or dusk, signals from both rod and cone photoreceptors contribute to perception. These parallel inputs are combined within the retina before being sent to subsequent visual areas. The integration of these kinetically-distinct parallel signals poses unique challenges for human vision. Though previous behavioral studies have found that dim lighting conditions specifically impair motion perception in human subjects, the origin of this dependence is unclear. In the present study, we create a model circuit that predicts ganglion cell responses to moving stimuli by incorporating electrophysiologically-derived circuit components into a Hassenstein-Reichardt correlator, a classical motion-detection model. The model circuit demonstrates that interactions between rod- and cone-derived signals negatively impact the encoding of a moving objects direction under mesopic conditions. Furthermore, we found that the model circuit could enhance its motion discriminability if it was only sensitive to the cone-activating components of the stimuli. We conclude that rod-cone signal interference occurring at the lowest level of vision has an impact on motion direction discrimination, a higher-level task with relevance for behavior.

neuroscience↗

bioRxiv2025

A data and task-constrained mechanistic model of the mouse outer retina shows robustness to contrast variations

Visual processing starts in the outer retina where photoreceptors transform light into electrochemical signals. These signals are modulated by inhibition from horizontal cells and sent to the inner retina via excitatory bipolar cells. The outer retina is thought to play an important role in contrast invariant coding of visual information, but how the different cell types implement this computation together remains incompletely understood. To understand the role of each cell type, we developed a fully-differentiable biophysical model of a circular patch of mouse outer retina. The model includes 200 cone photoreceptors with a realistic phototransduction cascade and ribbon synapses as well as horizontal and bipolar cells, all with cell-type specific ion channels. Going beyond decades of work constraining biophysical models of neurons only by experimental data, we used a dual approach, constraining some parameters of the model with available measurements and others by a visual task: (1) We fit the parameters of the cone models to whole cell patch-clamp measurements of photocurrents and two-photon glutamate imaging measurements of synaptic release. (2) We then trained the spatiotemporal outer retina model with photoreceptors and the other cell types to perform a visual classification task with varying contrast and luminance levels. We found that our outer retina model could learn to solve the classification task despite contrast and luminance variance in the stimuli. Testing different cell type compositions and connectivity patterns, we found that feedback from horizontal cells did not further improve task performance beyond that of excitatory photoreceptors and bipolar cells. This is surprising given that horizontal cells are positioned to mediate communication across cones and that they add to the models number of trainable parameters. Finally, we found that our model generalized better to out of distribution contrast levels than a linear classifier. Our work shows how the nonlinearities found in the outer retina can accomplish contrast invariant classification and teases apart the contributions of different cell types.

neuroscience↗

bioRxiv2025

Spatially-local inhibition and synaptic plasticity together enable dynamic, context-dependent integration of parallel sensory pathways

Retinal ganglion cells have traditionally been grouped into cells that are sensitive to luminance but not spatial structure and cells with responses that are enhanced by spatial structure. Neither category captures responses of mouse Off Transient alpha cells, which are largest for spatially homogeneous inputs and are suppressed by spatial structure. We identified two circuit mechanisms that together can explain this unusual spatial selectivity. First, inhibition to these cells is tuned to finer spatial structure than excitation, causing the balance of excitation and inhibition to depend on spatial scale. Second, the excitatory synapses onto these cells undergo strong synaptic depression and the modulation of that depression by presynaptic inhibition amplifies responses to the transition from spatially structured to homogeneous inputs. A spatiotemporal computational model incorporating these circuit features quantitatively recapitulates the observed dynamics. These findings reveal how localized inhibition and short-term plasticity jointly create the distinctive spatial selectivity of Off Transient cells.

neuroscience↗

bioRxiv2025

Dynamic expression of ASCL1 drives neurogenesis from infant and adult macaque Müller glia into immature retinal ganglion cells

Strategies to stimulate the regeneration of neurons in the adult central nervous system can offer universal solutions for neurodegenerative diseases. Taking lessons from naturally regenerating species, such as the zebrafish, we have previously shown that vector-mediated expression of proneural transcription factors can stimulate neurogenesis from the resident Muller glia (MG) population in the adult mouse retina, both in vitro and in vivo. To bring this closer to translation, we now show that vector-mediated expression of the proneural transcription factor ASCL1 can reprogram adult macaque MG into functional neurons. To this end, we established purified MG cultures and show they retain a mature transcriptomic profile that correlates with foveal and peripheral MG. Importantly, MG-derived neurons express retinal ganglion cell markers, can fire action potentials and have a transcriptome that overlaps with developing human and adult macaque retinal ganglion cells. To refine this approach for clinical application, we incorporated microRNA-124 target sites in the reprogramming cassette and show that this restricts expression to MG in mixed primary cultures and intact explant cultures of adult macaque retina. Regulating ASCL1 expression with microRNA-124 target sites maintained the reprogramming efficiency from adult MG cultures and improved the yield of RGC-like neurons from infant MG cultures. Most importantly, with this vector cassette we successfully reprogrammed macaque MG from both adult and infant retina into HuC/D+ neurons. Our findings demonstrate that ASCL1 can induce neurogenesis from macaque MG across ages and provide a targeted, effective strategy for potential clinical translation in retinal repair.

neuroscience↗

bioRxiv2024

Functional diversity in the output of the primate retina

The visual image transmitted by the retina to the brain has long been understood in terms of spatial filtering by the center-surround receptive fields of retinal ganglion cells (RGCs). Recently, this textbook view has been challenged by the stunning functional diversity and specificity observed in [~]40 distinct RGC types in the mouse retina. However, it is unclear whether the [~]20 morphologically and molecularly identified RGC types in primates exhibit similar functional diversity, or instead exhibit center-surround organization at different spatial scales. Here, we reveal striking and surprising functional diversity in macaque and human RGC types using large-scale multi-electrode recordings from isolated macaque and human retinas. In addition to the five well-known primate RGC types, 18-27 types were distinguished by their functional properties, likely revealing several previously unknown types. Surprisingly, many of these cell types exhibited striking non-classical receptive field structure, including irregular spatial and chromatic properties not previously reported in any species. Qualitatively similar results were observed in recordings from the human retina. The receptive fields of less-understood RGC types formed uniform mosaics covering visual space, confirming their classification, and the morphological counterparts of two types were established using single-cell recording. The striking receptive field diversity was paralleled by distinctive responses to natural movies and complexity of visual computation. These findings suggest that diverse RGC types, rather than merely filtering the scene at different spatial scales, instead play specialized roles in human vision.

neuroscience↗

bioRxiv2024

Stimulating the regenerative capacity of the human retina with proneural transcription factors in 3D cultures

Retinal diseases often lead to degeneration of specific retinal cell types with currently limited therapeutic options to replace the lost neurons. Previous studies have reported that overexpression of ASCL1 or combinations of proneural factors in Muller glia (MG) induces regeneration of functional neurons in the adult mouse retina. Recently, we applied the same strategy in dissociated cultures of fetal human MG and although we stimulated neurogenesis from MG, our effect in 2D cultures was modest and our analysis of newborn neurons was limited. In this study, we aimed to improve our MG reprogramming strategy in a more intact retinal environment. For this purpose, we used an in vitro culture system of human fetal retinal tissue and adult human postmortem retina. To stimulate reprogramming, we used lentiviral vectors to deliver constructs with a glial-specific promoter (HES1) driving ASCL1 alone or in combination with additional developmental transcription factors such as ATOH1 and NEUROD1. Combining IHC, scRNA-seq and electrophysiology, we show for the first time that human MG can generate new neurons even in adults. This work constitutes a key step towards a future clinical application of this regenerative medicine approach for retinal degenerative disorders.

developmental biology↗

bioRxiv2024

AAV-mediated expression of proneural factors stimulates neurogenesis from adult Müller glia in vivo.

The lack of regeneration in the human central nervous system (CNS) has major health implications. To address this, we previously used transgenic mouse models to show that neurogenesis can be stimulated in the adult mammalian retina by driving regeneration programs that other species activate following injury. Expression of specific proneural factors in adult Muller glia causes them to re-enter the cell cycle and give rise to new neurons following retinal injury. To bring this strategy closer to clinical application, we now show that neurogenesis can also be stimulated when delivering these transcription factors to Muller glia using adeno-associated viral (AAV) vectors. AAV-mediated neurogenesis phenocopies the neurogenesis we observed from transgenic animals, with different proneural factor combinations giving rise to distinct neuronal subtypes in vivo. Vector-borne neurons are morphologically, transcriptomically and physiologically similar to bipolar and amacrine/ganglion-like neurons. These results represent a key step forward in developing a cellular reprogramming approach to regenerative medicine in the CNS.

neuroscience↗

bioRxiv2024

Cone bipolar cell synapses generate transient versus sustained signals in parallel ON pathways of the mouse retina

Parallel processing is a fundamental organizing principle in the nervous system and understanding how parallel neural circuits generate distinct outputs from common inputs is a key goal of neuroscience. In the mammalian retina, divergence of cone signals into multiple feedforward bipolar cell pathways forms the initial basis for parallel retinal circuits dedicated to specific visual functions. Here, we used patch-clamp electrophysiology, electron microscopy and two photon imaging of a fluorescent glutamate sensor to examine how kinetically-distinct responses arise in transient versus sustained ON alpha RGCs (ON-T and ON-S RGCs) of the mouse retina. We directly compared the visual response properties of these RGCs with their presynaptic bipolar cell partners, which we identified using 3D electron microscopy reconstruction. Different ON bipolar cell subtypes (type 5i, type 6 and type 7) had indistinguishable light-driven responses whereas extracellular glutamate signals around RGC dendrites and postsynaptic excitatory currents measured in ON-T and ON-S RGCs in response to the identical stimuli used to probe bipolar cells were kinetically distinct. Anatomical examination of the bipolar cell axon terminals presynaptic to ON-T and ON-S RGCs suggests that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools may contribute to transient versus sustained kinetics. Our findings indicate that feedforward bipolar cell synapses are a primary point of divergence in kinetically distinct visual pathways.

neuroscience↗

bioRxiv2023

Light-adaptation clamp: a tool to predictably manipulate photoreceptor light responses

Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

neuroscience↗

bioRxiv2023

Ancient origin of the rod bipolar cell pathway in the vertebrate retina

Vertebrates rely on rod photoreceptors for vision in low-light conditions1. Mammals have a specialized downstream circuit for rod signaling called the primary rod pathway, which comprises specific cell types and wiring patterns that are thought to be unique to this lineage2-6. Thus, it has been long assumed that the primary rod pathway evolved in mammals3, 5-7. Here, we challenge this view by demonstrating that the mammalian primary rod pathway is conserved in zebrafish, which diverged from extant mammals [~]400 million years ago. Using single-cell RNA-sequencing, we identified two bipolar cell (BC) types in zebrafish that are related to mammalian rod BCs (RBCs) of the primary rod pathway. By combining electrophysiology, histology, and ultrastructural reconstruction of the zebrafish RBCs, we found that, like mammalian RBCs8, both zebrafish RBC types connect with all rods and red-cones in their dendritic territory, and provide output largely onto amacrine cells. The wiring pattern of the amacrine cells post-synaptic to one RBC type is strikingly similar to that of mammalian RBCs. This suggests that the cell types and circuit design of the primary rod pathway may have emerged before the divergence of teleost fish and amniotes (mammals, bird, reptiles). The second RBC type in zebrafish, which forms separate pathways from the first RBC type, is either lost in mammals or emerged in fish to serve yet unknown roles. Highlights- Zebrafish have two rod bipolar cell types (RBC1/2). - Synaptic connectivity of RBC1 resembles that of the mammalian RBCs. - The primary rod pathway therefore probably evolved more than 400 million years ago. - The second zebrafish RBC type, RBC2, forms a separate pathway from RBC1.

neuroscience↗

bioRxiv2023

Biophysical neural adaptation mechanisms enable deep learning models to capture dynamic retinal computation

Adaptation is a universal aspect of neural systems that changes circuit computations to match prevailing inputs. These changes facilitate efficient encoding of sensory inputs while avoiding saturation. Conventional artificial neural networks (ANNs) have limited adaptive capabilities, hindering their ability to reliably predict neural output under dynamic input conditions. Can embedding neural adaptive mechanisms in ANNs improve their performance? To answer this question, we develop a new deep learning model of the retina that incorporates the biophysics of photoreceptor adaptation at the front-end of conventional convolutional neural networks (CNNs). These conventional CNNs build on Deep Retina, a previously developed model of retinal ganglion cell (RGC) activity. CNNs that include this new photoreceptor layer outperform conventional CNN models at predicting primate and rat RGC responses to naturalistic stimuli that include dynamic local intensity changes and large changes in the ambient illumination. These improved predictions result directly from adaptation within the phototransduction cascade. This research underscores the potential of embedding models of neural adaptation in ANNs and using them to determine how neural circuits manage the complexities of encoding natural inputs that are dynamic and span a large range of light levels.

neuroscience↗

bioRxiv2022

Human retina trades single-photon detection for high-fidelity contrast encoding

We lack a fundamental understanding of how the spike output of the retina enables human visual perception. Here we show that human vision at its ultimate sensitivity limit depends on the spike output of ON but not OFF parasol (magnocellular) ganglion cells. Surprisingly, nonlinear signal processing in the retinal ON pathway precludes perceptual detection of single photons in darkness, but enables quantal-resolution discrimination of differences in light intensity.

neuroscience↗

bioRxiv2022

Vision-dependent and -independent molecular maturation of mouse retinal ganglion cells

The development and connectivity of retinal ganglion cells (RGCs), the retinas sole output neurons, are patterned by activity-independent transcriptional programs and activity-dependent remodeling. To inventory the molecular correlates of these influences, we applied high-throughput single-cell RNA sequencing (scRNA-seq) to mouse RGCs at six embryonic and postnatal ages. We identified temporally regulated modules of genes that correlate with, and likely regulate, multiple phases of RGC development, ranging from differentiation and axon guidance to synaptic recognition and refinement. Some of these genes are expressed broadly while others, including key transcription factors and recognition molecules, are selectively expressed by one or a few of the 45 transcriptomically distinct types defined previously in adult mice. Next, we used these results as a foundation to analyze the transcriptomes of RGCs in mice lacking visual experience due to dark rearing from birth or to mutations that ablate either bipolar or photoreceptor cells. 98.5% of visually deprived (VD) RGCs could be unequivocally assigned to a single RGC type based on their transcriptional profiles, demonstrating that visual activity is dispensable for acquisition and maintenance of RGC type identity. However, visual deprivation significantly reduced the transcriptomic distinctions among RGC types, implying that activity is required for complete RGC maturation or maintenance. Consistent with this notion, transcriptomic alternations in VD RGCs significantly overlapped with gene modules found in developing RGCs. Our results provide a resource for mechanistic analyses of RGC differentiation and maturation, and for investigating the role of activity in these processes.

neuroscience↗

bioRxiv2021

Contribution of linear and nonlinear mechanisms to predictive motion estimation

Successful behavior relies on the ability to use information obtained from past experience to predict what is likely to occur in the future. A salient example of predictive encoding comes from the vertebrate retina, where neural circuits encode information that can be used to estimate the trajectory of a moving object. Predictive computations should be a general property of sensory systems, but the features needed to identify these computations across neural systems are not well understood. Here, we identify several properties of predictive computations in the primate retina that likely generalize across sensory systems. These features include calculating the derivative of incoming signals, sparse signal integration, and delayed response suppression. These findings provide a deeper understanding of how the brain carries out predictive computations and identify features that can be used to recognize these computations throughout the brain.

neuroscience↗

bioRxiv2021

Systematic reduction of the dimensionality of natural scenes allows accurate predictions of retinal ganglion cell spike outputs.

The mammalian retina engages a broad array of linear and nonlinear circuit mechanisms to convert natural scenes into retinal ganglion cell (RGC) spike outputs. Although many individual integration mechanisms are well understood, predictive models of natural scene encoding perform poorly, likely due to interactions among the active mechanisms. Here, we identified spatial integration mechanisms relevant for natural scene encoding and used computational modeling to predict spike outputs in primate parasol RGCs. Our approach was to simplify the structure of natural scenes and empirically ask whether these changes were reflected in RGC spike responses. We observed that reducing natural movies to 16 linearly integrated regions described [~]80% of the structure of parasol RGC spike responses. We then used simplified stimuli to create high-dimensional metamers that recapitulated the spike response of full-field naturalistic movies. Finally, we identified the retinal computations that convert natural images in 16-dimensional space into 1-dimensional spike outputs.

neuroscience↗