Fred Rieke

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.

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.

The receptive fields of retinal neurons are the foundation for all downstream computations in the visual system, shaping our understanding of information processing across the visual hierarchy. Here, we provide an updated view of how receptive field surrounds of major primate retinal output pathways contribute to texture processing. We show that spatial structure in the receptive field surround enhances responses of ON parasol and ON midget retinal ganglion cells, but suppresses responses of their OFF counterparts. This leads to distinct roles in spatial encoding, with ON pathways acting as spatial integrators for texture and OFF pathways functioning as differentiators. Surprisingly, this asymmetry originates from nonlinear spatial integration in horizontal cells—neurons traditionally thought to integrate inputs linearly. Instead, we show that spatial structure in natural images robustly engages horizontal cells, which differentially modulate ON and OFF bipolar cells and, in turn, ON and OFF retinal ganglion cells. This updated view of the spatial sensitivity of key retinal output pathways raises questions about what information is available to downstream cortical circuits and how it is used to guide visual behavior.

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.

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 retinal ganglion cells (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 (types 5i, 6, and 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.

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 model’s 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.

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.

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 Müller 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.

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.