Biology subjects

Field, G. D.

Publications and source records attributed to Field, G. D..

At least 19 recordsLinked to original sources

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.

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bioRxiv2025

Projection Targeting with Phototagging to Study the Structure and Function of Retinal Ganglion Cells

Visual information from the retina is sent to diverse targets throughout the brain by different retinal ganglion cells (RGCs). Much of our knowledge about the different RGC types and how they are routed to these brain targets is based on mice, largely due to the extensive library of genetically modified mouse lines. To alleviate the need for using genetically modified animal models for studying retinal projections, we developed a high-throughput approach called projection targeting with phototagging that combines retrograde viral labeling, optogenetic identification, functional characterization using multi-electrode arrays, and morphological analysis. This method enables the simultaneous investigation of projections, physiology, and structure-function relationships across dozens to hundreds of cells in a single experiment. We validated this method in rats by targeting RGCs projecting to the superior colliculus, revealing multiple functionally defined cell types that align with prior studies in mice. By integrating established techniques into a scalable workflow, this framework enables comparative investigations of visual circuits across species, expanding beyond genetically tractable models. MotivationVisual information from the retina is distributed to diverse targets throughout the brain. Much of our knowledge about how visual information is processed and routed to these brain targets is based on mice because of the large library of genetically modified mouse lines. For most other species, such libraries are not available. Therefore, we were motivated to develop an approach for characterizing diverse retinal projections into the brain that can be applied to other species. We aimed to achieve projection targeting with retrograde viral vectors, followed by identification of circuit-specific retinal ganglion cells (RGCs) with optogenetics, functional characterization with multi-electrode array (MEA) recordings, and morphological description with in situ and confocal microscopy. The resulting high-throughput approach permits functional and morphological investigation of dozens to hundreds of cells in individual experiments. By replacing the need for genetically modified animals with a suite of standard techniques, this approach should improve cross-species comparisons of the initial stages of visual processing. SummaryUnderstanding the structure-function relationships across neurons is challenging, particularly when circuits are composed of dozens of distinct cell types. We refined an approach, called projection targeting with phototagging, that allows simultaneous elucidation of the projections, morphology, and visual response properties of diverse RGC types in the mammalian retina. The approach combines retrograde virally mediated phototagging of RGCs, microscopy, and large-scale MEA measurements. Importantly, the approach does not rely on transgenic animals and thus is generalizable across species. We validated this approach in rats by targeting retinal projections to the superior colliculus (SC). We showed that multiple RGC types project to the SC and that these results in rats align well with prior findings from transgenic mouse studies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=194 HEIGHT=200 SRC="FIGDIR/small/661576v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1003310org.highwire.dtl.DTLVardef@1881cdorg.highwire.dtl.DTLVardef@f1dba1org.highwire.dtl.DTLVardef@8a539f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe viral vector, AAV2retro, is effective for delivering opsins to retinal ganglion cells (RGCs) for phototagging and projection mapping. C_LIO_LIPhototagging allows matching RGC visual responses to morphology, while also identifying their central projections. C_LIO_LIThe approach does not rely on genetically modified animals and thus is generalizable across species. C_LI

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bioRxiv2024

Encoding manifolds constructed from grating responses organize responses to natural scenes in cortical visual areas

A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challenge, we have created ``encoding manifolds'' that reveal the overall responses of brain areas to diverse stimuli and organize individual neurons in stimulus-response coordinates according to their selectivity and response dynamics. Here we use encoding manifolds to compare the population-level encoding of primary visual cortex (VISp) with that of five higher visual areas (VISam, VISal, VISpm, VISlm, and VISrl), using data from the Allen Institute Visual Coding-Neuropixels dataset from the mouse. We show that the topology of the encoding manifold for VISp and for higher visual areas is continuous, with smooth coordinates along which stimulus selectivity and response dynamics are organized with layer and cell-type specificity. Surprisingly, the manifolds revealed novel relationships between how natural scenes are encoded relative to static gratings--a relationship conserved across visual areas. Namely, neurons preferring natural scenes preferred either low or high spatial frequency gratings, but not intermediate ones. Analyzing responses by cortical layer reveals a preference for gratings concentrated in layer 6, whereas preferences for natural scenes tended to be higher in layers 2/3 and 4. The results demonstrate how machine learning approaches can be used to organize and visualize the structure of sensory coding, thereby revealing novel relationships within and across brain areas and sensory stimuli.

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bioRxiv2023

Decomposition of retinal ganglion cell electrical images for cell type and functional inference

ObjectiveIdentifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and for the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. ApproachThe electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. ResultsThe decomposition was evaluated using large-scale multi-electrode recordings from the macaque retina. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells) substantially more accurately than previous approaches. SignificanceThese findings contribute to more accurate inference of RGC types and their original light responses based purely on their electrical features, with potential implications for vision restoration technology.

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bioRxiv2023

Population encoding of stimulus features along the visual hierarchy

The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to diverse visual features. Yet it remains unclear how neural populations in each area partition stimulus space to span these features. One possibility is that neural populations are organized into discrete groups of neurons, with each group signaling a particular constellation of features. Alternatively, neurons could be continuously distributed across feature-encoding space. To distinguish these possibilities, we presented a battery of visual stimuli to mouse retina and V1 while measuring neural responses with multi-electrode arrays. Using machine learning approaches, we developed a manifold embedding technique that captures how neural populations partition feature space and how visual responses correlate with physiological and anatomical properties of individual neurons. We show that retinal populations discretely encode features, while V1 populations provide a more continuous representation. Applying the same analysis approach to convolutional neural networks that model visual processing, we demonstrate that they partition features much more similarly to the retina, indicating they are more like big retinas than little brains.

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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.

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bioRxiv2023

Late gene therapy limits the restoration of retinal function in a mouse model of retinitis pigmentosa

Retinitis pigmentosa is an inherited photoreceptor degeneration that begins with rod loss followed by cone loss and eventual blindness. Gene therapies are being developed, but it is unknown how retinal function depends on the time of intervention. To uncover this dependence, we utilized a mouse model of retinitis pigmentosa capable of artificial genetic rescue. This model enables a benchmark of best-case gene therapy by removing the variables that complicate the ability to answer this vital question. Complete genetic rescue was performed at 25%, 50%, and 70% rod loss (early, mid and late, respectively). Early and mid treatment restored retinal function to near wild-type levels, specifically the sensitivity and signal fidelity of retinal ganglion cells (RGCs), the output neurons of the retina. However, some anatomical defects persisted. Late treatment retinas exhibited continued, albeit slowed, loss of sensitivity and signal fidelity among RGCs, as well as persistent gliosis. We conclude that gene replacement therapies delivered after 50% rod loss are unlikely to restore visual function to normal. This is critical information for administering gene therapies to rescue vision.

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bioRxiv2022

Thousandfold Cell-Specific Pharmacology of Neurotransmission

Cell-specific pharmaceutical technologies promise mechanistic insight into clinical drugs[-]those that treat, and often define, human disease. In particular, DART (drug acutely restricted by tethering) achieves genetically programmable control of drug concentration over cellular dimensions. The method is compatible with clinical pharmaceuticals and amenable to studies in behaving animals. Here, we describe DART.2, comprising three advances. First, we improve the efficiency of chemical capture, enabling cell-specific accumulation of drug to [~]3,000-times the ambient concentration in 15 min. Second, we develop tracer reagents, providing a behavior-independent measure of cellular target engagement in each animal. Third, we extend the method to positive allosteric modulators and outline design principles for this clinically significant class. We showcase the platform with four pharmaceuticals[-]two that weaken excitatory (AMPAR) or inhibitory (GABAAR) chemical neurotransmission, and two that strengthen these forms of synaptic communication. Across four labs, we tested reagents in the mouse cerebellum, basal ganglia, visual cortex, and retina. Collectively, we demonstrate robust, bidirectional editing of chemical neurotransmission. We provide for distribution of validated reagents, community design principles, and synthetic building blocks for application to diverse pharmaceuticals.

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bioRxiv2022

Large scale interrogation of retinal cell functions by 1-photon light-sheet microscopy

Visual processing in the retina depends on the collective activity of large ensembles of neurons organized in different layers. Current techniques for measuring activity of layer-specific neural ensembles rely on expensive pulsed infrared lasers to drive 2-photon activation of calcium-dependent fluorescent reporters. Here, we present a 1-photon light-sheet imaging system that can measure the activity in hundreds of ex vivo retinal neurons over a large field of view while simultaneously presenting visual stimuli. This allowed for a reliable functional classification of different retinal ganglion cell types. We also demonstrate that the system has sufficient resolution to image calcium entry at individual synaptic release sites across the axon terminals of dozens of simultaneously imaged bipolar cells. The simple design, a large field of view, and fast image acquisition, make this a powerful system for high-throughput and high-resolution measurements of retinal processing at a fraction of the cost of alternative approaches.

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bioRxiv2022

Cones and Cone Pathways Remain Functional in Advanced Retinal Degeneration

Most defects causing retinal degeneration in retinitis pigmentosa (RP) are rod-specific mutations, but the subsequent degeneration of cones, which produces loss of daylight vision and high-acuity perception, is the most debilitating feature of the disease. To understand better why cones degenerate and how cone vision might be restored, we have made the first single-cell recordings of light responses from degenerating cones and retinal interneurons after most rods have died and cones have lost their outer-segment disk membranes and synaptic pedicles. We show that degenerating cones have functional cyclic-nucleotide-gated channels and can continue to give light responses, apparently produced by opsin localized either to small areas of organized membrane near the ciliary axoneme or distributed throughout the inner segment. Light responses of second-order horizontal and bipolar cells are smaller and less sensitive but surprisingly similar to those of normal retina. Furthermore, retinal output as reflected in responses of ganglion cells is largely intact at cone-mediated light levels. Together, these findings show that cones and their retinal pathways can remain functional even as degeneration is progressing, an encouraging result for future research aimed at enhancing the light sensitivity of residual cones to restore vision in patients with genetically inherited retinal degeneration.

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bioRxiv2022

The functional organization of retinal ganglion cell receptive fields across light levels

Two major functions performed by the retina are to establish the parallel processing of visual information and to adapt visual encoding to the trillion-fold range of light intensities encountered in the environment. Previous work has highlighted many specialized cell types and circuits that instantiate parallel processing and light adaptation. However, fully understanding either process requires identifying how light adaptation and parallel processing interact. One possibility is that light adaptation causes uniform or proportional scaling to the receptive fields (RFs) of different retinal ganglion cell (RGC) types, the output neurons of the retina. Alternatively, light adaptation could cause a reorganization of RF structures across RGC types. To resolve these possibilities, we examined how the spatiotemporal RF structure of six simultaneously measured RGC types in the rat retina change from rod- to cone-mediated light levels. While light adaptation altered the RF properties of all six RGC types, we found that the relative structure across different RGC types was largely preserved across light levels. Surprisingly, most RGC types retained their center-surround RF structure even at low light levels, an observation that is at odds with prior efficient coding predictions. However, we show these predictions are incomplete and when RFs interact over a finite viewing area, efficient coding predicts the retention of surrounds under low signal-to-noise conditions.

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bioRxiv2022

Efficient coding, channel capacity and the emergence of retinal mosaics

Among the most striking features of retinal organization is the grouping of its output neurons, the retinal ganglion cells (RGCs), into a diversity of functional types. Each of these types exhibits a mosaic-like organization of receptive fields (RFs) that tiles the retina and visual space. Previous work has shown that many features of RGC organization, including the existence of ON and OFF cell types, the structure of spatial RFs, and their relative arrangement, can be predicted on the basis of efficient coding theory. This theory posits that the nervous system is organized to maximize information in its encoding of stimuli while minimizing metabolic costs. Here, we use efficient coding theory to present a comprehensive account of mosaic organization in the case of natural videos as the retinal channel capacity--the number of simulated RGCs available for encoding--is varied. We show that mosaic density increases with channel capacity up to a series of critical points at which, surprisingly, new cell types emerge. Each successive cell type focuses on increasingly high temporal frequencies and integrates signals over large spatial areas. In addition, we show theoretically and in simulation that a transition from mosaic alignment to anti-alignment across pairs of cell types is observed with increasing output noise and decreasing input noise. Together, these results offer a unified perspective on the relationship between retinal mosaics, efficient coding, and channel capacity that can help to explain the stunning functional diversity of retinal cell types.

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bioRxiv2022

Scalable variational inference for low-rank spatio-temporal receptive fields

An important problem in systems neuroscience is to characterize how a neuron integrates sensory inputs across space and time. The linear receptive field provides a mathematical characterization of this weighting function, and is commonly used to quantify neural response properties and classify cell types. However, estimating receptive fields is difficult in settings with limited data and correlated or high-dimensional stimuli. To overcome these difficulties, we propose a hierarchical model designed to flexibly parameterize low-rank receptive fields. The model includes Gaussian process priors over spatial and temporal components of the receptive field, encouraging smoothness in space and time. We also propose a new temporal prior called temporal relevance determination (TRD), which imposes a variable degree of smoothness as a function of time lag. We derive a scalable algorithm for variational Bayesian inference for both spatial and temporal receptive field components and hyperparameters. The resulting estimator scales to high-dimensional settings in which full-rank maximum likelihood or a posteriori estimates are intractable. We evaluate our approach on neural data from rat retina and primate cortex, and show that it substantially out-performs a variety of existing estimators. Our modeling approach will have useful extensions to a variety of other high-dimensional inference problems with smooth or low-rank structure.

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bioRxiv2022

Robust cone-mediated signaling persists late into rod photoreceptor degeneration

Rod photoreceptor degeneration causes deterioration in the morphology and physiology of cone photoreceptors along with changes in retinal circuits. These changes could diminish visual signaling at cone-mediated light levels, thereby limiting the efficacy of treatments such as gene therapy for rescuing normal, cone-mediated vision. However, the impact of progressive rod death on cone-mediated signaling remains unclear. A mouse model of rod degeneration was used to investigate the fidelity of retinal ganglion cell (RGC) signaling throughout disease progression. Despite clear deterioration of cone morphology with rod death, cone-mediated signaling among RGCs remained surprisingly robust: spatiotemporal receptive fields changed little and the mutual information between stimuli and spiking responses was relatively constant. This relative stability held until nearly all rods had died and cones had completely lost well-formed outer segments. Interestingly, RGC information rates were higher and more stable for natural movies than checkerboard noise as degeneration progressed. The main change in RGC responses with photoreceptor degeneration was a decrease in response gain. These results suggest that gene therapies for rod degenerative diseases are likely to successfully prolong cone-mediated vision even if there are changes to cone morphology and density.

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bioRxiv2021

The optimal spatial arrangement of ON and OFF receptive fields

Many sensory systems utilize parallel ON and OFF pathways that signal stimulus increments and decrements, respectively. These pathways consist of ensembles or grids of ON and OFF detectors spanning sensory space. Yet encoding by opponent pathways raises a question: How should grids of ON and OFF detectors be arranged to optimally encode natural stimuli? We investigated this question using a model of the retina guided by efficient coding theory. Specifically, we optimized spatial receptive fields and contrast response functions to encode natural images given noise and constrained firing rates. We find that the optimal arrangement of ON and OFF receptive fields exhibits a transition between aligned and anti-aligned grids. The preferred phase depends on detector noise and the statistical structure of the natural stimuli. These results reveal that noise and stimulus statistics produce qualitative shifts in neural coding strategies and provide novel theoretical predictions for the configuration of opponent pathways in the nervous system. Significance StatementAcross a wide variety of species, cells in the retina specialized for signaling either increases (ON) or decreases (OFF) in light represent one of the most basic building blocks of visual computation. These cells coordinate to form mosaics, with each cell responsible for a small, minimally-overlapping portion of visual space, but the ways in which these mosaics could be spatially coordinated with each other are relatively unknown. Here, we show how efficient coding theory, which hypothesizes that the nervous system minimizes the amount of redundant information it encodes, can predict the relative spatial arrangement of ON and OFF mosaics. The most information-efficient arrangements are determined both by levels of noise in the system and the statistics of natural images.

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bioRxiv2021

Properties of multi-vesicular release from rod photoreceptors support transmission of single photon responses

Vision under starlight requires rod photoreceptors to transduce and transmit single photon responses to the visual system. This remarkable sensitivity depends on a small voltage change reliably reducing glutamate release such that post-synaptic rod bipolar cells can robustly detect the signal. To transmit this small signal, we have found that rod vesicle release deviates strongly from a Poisson process under conditions that mimic darkness. Specifically, at their resting membrane potential in darkness, rods exhibit coordinated and regularly timed multivesicular release events. Each release event consisted of [~]17 vesicles and occurred 2-3 times more regularly than expected from a Poisson process. Hyperpolarizing rods to mimic the voltage change produced by a single photon response abruptly reduced the probability of multivesicular release nearly to zero with a rebound increase in release probability at stimulus offset. Simulations of these release dynamics indicate that this regularly timed, multivesicular release promotes transmission of single photon responses to post-synaptic neurons. Furthermore, the mechanism is efficient, requiring fewer vesicles to be released per second than uniquantal release governed by Poisson statistics.

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bioRxiv2019

Ignoring correlated activity causes a failure of retinal population codes under moonlight conditions

The retina encodes visual stimuli across light intensities spanning 10-12 orders of magnitude from starlight to sunlight. To accommodate this enormous range, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes in signal and noise impact decoding of retinal output. In particular, we consider the importance of accounting for noise correlations among RGCs to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminished decoding performance. In fact, assuming independence among a local population of RGCs produced worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine the signal and noise conditions under which this failure of population processing can occur. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.

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bioRxiv2019

Thrombospondin-1 Promotes Circuit-Specific Synapse Formation via β1-Integrin

Glial cells regulate synaptic connectivity during development, but whether they selectively instruct the formation of specific synaptic circuits is not known. Here we show that the major perisynaptic glia of the retina, the Muller glia (MG), control the proper establishment of the direction-selective (DS) circuit by a synaptogenic protein, Thrombospondin 1 (TSP1). We found that TSP1 promotes excitatory synapse formation specifically in on-off Direction-Selective retinal Ganglion Cells (ooDSGCs). Lack of TSP1 leads to reduced synapse formation within the inner plexiform sublayers containing DS-circuit, resulting in deficits of ooDSGC function. Even though pan-TSP receptor, 2{delta}-1, interaction is required for TSP1-induced synapse formation, the ooDSGC-subtype specificity of TSP1 is conferred by a second neuronal TSP1 receptor, {beta}1-Integrin. Furthermore, conditional deletion of {beta}1-Integrin in ooDSGCs results in diminished excitatory synapse formation without disturbing laminar organization showing that MG-secreted TSP1 controls circuit-specific synapse formation via {beta}1-Integrin.

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