Direction selectivity in retinal bipolar cell axon terminals.
TL;DR: In this article, the authors used two-photon glutamate imaging to measure synaptic release and reveal that direction selectivity along all four directions arises earlier than expected at bipolar cell outputs.
About: This article is published in Neuron.The article was published on 2021-09-15 and is currently open access. It has received 14 citations till now. The article focuses on the topics: Axon terminal & Retina.
Citations
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TL;DR: In this article , the authors combined functional recordings of light-evoked responses and connectomic reconstruction to identify diverse direction-selective cell types in the macaque monkey retina with distinctive physiological properties and synaptic motifs.
Abstract: Abstract From mouse to primate, there is a striking discontinuity in our current understanding of the neural coding of motion direction. In non-primate mammals, directionally selective cell types and circuits are a signature feature of the retina, situated at the earliest stage of the visual process. In primates, by contrast, direction selectivity is a hallmark of motion processing areas in visual cortex, but has not been found in the retina, despite significant effort. Here we combined functional recordings of light-evoked responses and connectomic reconstruction to identify diverse direction-selective cell types in the macaque monkey retina with distinctive physiological properties and synaptic motifs. This circuitry includes an ON-OFF ganglion cell type, a spiking, ON-OFF polyaxonal amacrine cell and the starburst amacrine cell, all of which show direction selectivity. Moreover, we discovered that macaque starburst cells possess a strong, non-GABAergic, antagonistic surround mediated by input from excitatory bipolar cells that is critical for the generation of radial motion sensitivity in these cells. Our findings open a door to investigation of a precortical circuitry that computes motion direction in the primate visual system.
10 citations
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TL;DR: In this article , the authors studied the representation of motion in mouse retinal bipolar cells and found that some bipolar cells are radially direction selective, preferring the origin of small object motion trajectories.
Abstract: Motion sensing is a critical aspect of vision. We studied the representation of motion in mouse retinal bipolar cells and found that some bipolar cells are radially direction selective, preferring the origin of small object motion trajectories. Using a glutamate sensor, we directly observed bipolar cells synaptic output and found that there are radial direction selective and non-selective bipolar cell types, the majority being selective, and that radial direction selectivity relies on properties of the center-surround receptive field. We used these bipolar cell receptive fields along with connectomics to design biophysical models of downstream cells. The models and additional experiments demonstrated that bipolar cells pass radial direction selective excitation to starburst amacrine cells, which contributes to their directional tuning. As bipolar cells provide excitation to most amacrine and ganglion cells, their radial direction selectivity may contribute to motion processing throughout the visual system.
10 citations
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TL;DR: In this article , the authors investigated two circuits responsible for encoding different aspects of image motion: ON and ON-OFF direction-selective ganglion cells (DSGCs) and showed that distinct inhibitory pathways independently control tuning for motion velocity and motion direction in these two cell types.
8 citations
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TL;DR: In this paper , the authors found that bipolar glutamate release emphasizes objects that emerge in the receptive field (RF) during continuous motion, and that the alteration in signal dynamics induced by novel objects was more pronounced than edge enhancement.
Abstract: Abstract Antagonistic interactions between center and surround receptive field (RF) components lie at the heart of the computations performed in the visual system. Circularly symmetric center-surround RFs are thought to enhance responses to spatial contrasts (i.e., edges), but how visual edges affect motion processing is unclear. Here, we addressed this question in retinal bipolar cells, the first visual neuron with classic center-surround interactions. We found that bipolar glutamate release emphasizes objects that emerge in the RF; their responses to continuous motion are smaller, slower, and cannot be predicted by signals elicited by stationary stimuli. In our hands, the alteration in signal dynamics induced by novel objects was more pronounced than edge enhancement and could be explained by priming of RF surround during continuous motion. These findings echo the salience of human visual perception and demonstrate an unappreciated capacity of the center-surround architecture to facilitate novel object detection and dynamic signal representation.
8 citations
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TL;DR: In this paper , the authors investigated how neuromodulation alters the amount of information transmitted through the circuit and demonstrated that contrast sensitivity peaks in the afternoon accompanied by a four-fold increase in the average Shannon information transmitted from an active zone.
Abstract: Abstract Neuromodulators adapt sensory circuits to changes in the external world or the animal’s internal state and synapses are key control sites for such plasticity. Less clear is how neuromodulation alters the amount of information transmitted through the circuit. We investigated this question in the context of the diurnal regulation of visual processing in the retina of zebrafish, focusing on ribbon synapses of bipolar cells. We demonstrate that contrast-sensitivity peaks in the afternoon accompanied by a four-fold increase in the average Shannon information transmitted from an active zone. This increase reflects higher synaptic gain, lower spontaneous “noise” and reduced variability of evoked responses. Simultaneously, an increase in the probability of multivesicular events with larger information content increases the efficiency of transmission (bits per vesicle) by factors of 1.5-2.7. This study demonstrates the multiplicity of mechanisms by which a neuromodulator can adjust the synaptic transfer of sensory information.
5 citations
References
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TL;DR: This work reviews a general methodology for model-based clustering that provides a principled statistical approach to important practical questions that arise in cluster analysis, such as how many clusters are there, which clustering method should be used, and how should outliers be handled.
Abstract: Cluster analysis is the automated search for groups of related observations in a dataset. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures, and most clustering methods available in commercial software are also of this type. However, there is little systematic guidance associated with these methods for solving important practical questions that arise in cluster analysis, such as how many clusters are there, which clustering method should be used, and how should outliers be handled. We review a general methodology for model-based clustering that provides a principled statistical approach to these issues. We also show that this can be useful for other problems in multivariate analysis, such as discriminant analysis and multivariate density estimation. We give examples from medical diagnosis, minefield detection, cluster recovery from noisy data, and spatial density estimation. Finally, we mention limitations of the methodology and discuss recent development...
4,123 citations
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TL;DR: This work introduces a new method called sparse principal component analysis (SPCA) using the lasso (elastic net) to produce modified principal components with sparse loadings and shows that PCA can be formulated as a regression-type optimization problem.
Abstract: Principal component analysis (PCA) is widely used in data processing and dimensionality reduction. However, PCA suffers from the fact that each principal component is a linear combination of all the original variables, thus it is often difficult to interpret the results. We introduce a new method called sparse principal component analysis (SPCA) using the lasso (elastic net) to produce modified principal components with sparse loadings. We first show that PCA can be formulated as a regression-type optimization problem; sparse loadings are then obtained by imposing the lasso (elastic net) constraint on the regression coefficients. Efficient algorithms are proposed to fit our SPCA models for both regular multivariate data and gene expression arrays. We also give a new formula to compute the total variance of modified principal components. As illustrations, SPCA is applied to real and simulated data with encouraging results.
3,102 citations
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TL;DR: This work provides a systematic methodology for achieving comprehensive molecular classification of neurons, identifies novel neuronal types, and uncovers transcriptional differences that distinguish types within a class.
967 citations
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TL;DR: Circuit motifs that emerge from the data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglions cell is motion sensitive.
Abstract: Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer--the main computational neuropil region in the mammalian retina--the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.
929 citations
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TL;DR: An intensity-based glutamate-sensing fluorescent reporter with signal-to-noise ratio and kinetics appropriate for in vivo imaging is described and its utility for visualizing glutamate release by neurons and astrocytes in increasingly intact neurological systems is validated.
Abstract: We describe an intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) with signal-to-noise ratio and kinetics appropriate for in vivo imaging. We engineered iGluSnFR in vitro to maximize its fluorescence change, and we validated its utility for visualizing glutamate release by neurons and astrocytes in increasingly intact neurological systems. In hippocampal culture, iGluSnFR detected single field stimulus-evoked glutamate release events. In pyramidal neurons in acute brain slices, glutamate uncaging at single spines showed that iGluSnFR responds robustly and specifically to glutamate in situ, and responses correlate with voltage changes. In mouse retina, iGluSnFR-expressing neurons showed intact light-evoked excitatory currents, and the sensor revealed tonic glutamate signaling in response to light stimuli. In worms, glutamate signals preceded and predicted postsynaptic calcium transients. In zebrafish, iGluSnFR revealed spatial organization of direction-selective synaptic activity in the optic tectum. Finally, in mouse forelimb motor cortex, iGluSnFR expression in layer V pyramidal neurons revealed task-dependent single-spine activity during running.
824 citations