ABSTRACT
The vertebrate retina first evolved some 500 million years ago in ancestral marine chordates. Since then, the eyes of different species have been tuned to best support their unique visuoecological lifestyles. Visual specializations in eye designs, large-scale inhomogeneities across the retinal surface and local circuit motifs mean that all species' retinas are unique. Computational theories, such as the efficient coding hypothesis, have come a long way towards an explanation of the basic features of retinal organization and function; however, they cannot explain the full extent of retinal diversity within and across species. To build a truly general understanding of vertebrate vision and the retina's computational purpose, it is therefore important to more quantitatively relate different species' retinal functions to their specific natural environments and behavioural requirements. Ultimately, the goal of such efforts should be to build up to a more general theory of vision.
Subject(s)
Biological Evolution , Retina/physiology , Vision, Ocular/physiology , Animals , Behavior, Animal , Humans , Models, Neurological , Retinal Ganglion Cells/physiology , Retinal Neurons/physiology , Species SpecificityABSTRACT
Neural population responses in sensory systems are driven by external physical stimuli. This stimulus-response relationship is typically characterized by receptive fields, which have been estimated by neural system identification approaches. Such models usually require a large amount of training data, yet, the recording time for animal experiments is limited, giving rise to epistemic uncertainty for the learned neural transfer functions. While deep neural network models have demonstrated excellent power on neural prediction, they usually do not provide the uncertainty of the resulting neural representations and derived statistics, such as most exciting inputs (MEIs), from in silico experiments. Here, we present a Bayesian system identification approach to predict neural responses to visual stimuli, and explore whether explicitly modeling network weight variability can be beneficial for identifying neural response properties. To this end, we use variational inference to estimate the posterior distribution of each model weight given the training data. Tests with different neural datasets demonstrate that this method can achieve higher or comparable performance on neural prediction, with a much higher data efficiency compared to Monte Carlo dropout methods and traditional models using point estimates of the model parameters. At the same time, our variational method provides us with an effectively infinite ensemble, avoiding the idiosyncrasy of any single model, to generate MEIs. This allows us to estimate the uncertainty of stimulus-response function, which we have found to be negatively correlated with the predictive performance at model level and may serve to evaluate models. Furthermore, our approach enables us to identify response properties with credible intervals and to determine whether the inferred features are meaningful by performing statistical tests on MEIs. Finally, in silico experiments show that our model generates stimuli driving neuronal activity significantly better than traditional models in the limited-data regime.
Subject(s)
Bayes Theorem , Computational Biology , Models, Neurological , Animals , Computational Biology/methods , Neural Networks, Computer , Computer Simulation , Neurons/physiology , Monte Carlo Method , Algorithms , Photic Stimulation , Humans , Models, StatisticalABSTRACT
Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically plausible filters, meaning that they more closely resembled neural representation in early visual systems. We found these results applied to retinal responses to different artificial stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. The benefit of natural scene statistics became marginal, however, for predicting the responses to natural movies. In summary, our results indicate that efficiently encoding environmental inputs can improve system identification models, at least for noise stimuli, and point to the benefit of probing the visual system with naturalistic stimuli.
Subject(s)
Neurons , Noise , Neurons/physiology , Environment , Models, Neurological , Photic StimulationABSTRACT
The retina extracts visual features for transmission to the brain. Different types of bipolar cell split the photoreceptor input into parallel channels and provide the excitatory drive for downstream visual circuits. Mouse bipolar cell types have been described at great anatomical and genetic detail, but a similarly deep understanding of their functional diversity is lacking. Here, by imaging light-driven glutamate release from more than 13,000 bipolar cell axon terminals in the intact retina, we show that bipolar cell functional diversity is generated by the interplay of dendritic excitatory inputs and axonal inhibitory inputs. The resulting centre and surround components of bipolar cell receptive fields interact to decorrelate bipolar cell output in the spatial and temporal domains. Our findings highlight the importance of inhibitory circuits in generating functionally diverse excitatory pathways and suggest that decorrelation of parallel visual pathways begins as early as the second synapse of the mouse visual system.
Subject(s)
Neural Inhibition/physiology , Photic Stimulation , Retina/physiology , Amacrine Cells/physiology , Animals , Dendrites/physiology , Dendrites/radiation effects , Glutamic Acid/metabolism , Glycine/metabolism , Mice , Mice, Inbred C57BL , Neural Inhibition/radiation effects , Presynaptic Terminals/physiology , Presynaptic Terminals/radiation effects , Retina/cytology , Retina/radiation effects , Retinal Bipolar Cells/physiology , Retinal Bipolar Cells/radiation effects , Synapses/physiology , Synapses/radiation effects , Time Factors , Visual Pathways/physiology , Visual Pathways/radiation effects , gamma-Aminobutyric Acid/metabolismABSTRACT
In the vertebrate visual system, all output of the retina is carried by retinal ganglion cells. Each type encodes distinct visual features in parallel for transmission to the brain. How many such 'output channels' exist and what each encodes are areas of intense debate. In the mouse, anatomical estimates range from 15 to 20 channels, and only a handful are functionally understood. By combining two-photon calcium imaging to obtain dense retinal recordings and unsupervised clustering of the resulting sample of more than 11,000 cells, here we show that the mouse retina harbours substantially more than 30 functional output channels. These include all known and several new ganglion cell types, as verified by genetic and anatomical criteria. Therefore, information channels from the mouse eye to the mouse brain are considerably more diverse than shown thus far by anatomical studies, suggesting an encoding strategy resembling that used in state-of-the-art artificial vision systems.
Subject(s)
Retinal Ganglion Cells/classification , Retinal Ganglion Cells/physiology , Animals , Brain/cytology , Calcium Signaling , Cluster Analysis , Female , Male , Mice , Models, Genetic , Probability , Retinal Ganglion Cells/cytologyABSTRACT
Understanding how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source in silico implementation of a spiking neuron that costs £25 and mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, to dials controlling current injection and noise levels, to a photodiode that makes Spikeling light sensitive, and to a light-emitting diode (LED) and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks mimicking electrophysiological experiments. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the United Kingdom.
Subject(s)
Action Potentials/physiology , Models, Neurological , Neurons/physiology , Neurosciences/education , Neurosciences/instrumentation , Animals , Community-Institutional Relations , Computer Simulation , Equipment Design , Nerve Net/physiology , Neural Networks, Computer , Synapses/physiologyABSTRACT
Inherited retinal degeneration (RD) is a devastating and currently untreatable neurodegenerative condition that leads to loss of photoreceptor cells and blindness. The vast genetic heterogeneity of RD, the lack of "druggable" targets, and the access-limiting blood-retinal barrier (BRB) present major hurdles toward effective therapy development. Here, we address these challenges (i) by targeting cGMP (cyclic guanosine- 3',5'-monophosphate) signaling, a disease driver common to different types of RD, and (ii) by combining inhibitory cGMP analogs with a nanosized liposomal drug delivery system designed to facilitate transport across the BRB. Based on a screen of several cGMP analogs we identified an inhibitory cGMP analog that interferes with activation of photoreceptor cell death pathways. Moreover, we found liposomal encapsulation of the analog to achieve efficient drug targeting to the neuroretina. This pharmacological treatment markedly preserved in vivo retinal function and counteracted photoreceptor degeneration in three different in vivo RD models. Taken together, we show that a defined class of compounds for RD treatment in combination with an innovative drug delivery method may enable a single type of treatment to address genetically divergent RD-type diseases.
Subject(s)
Blood-Retinal Barrier/metabolism , Cyclic GMP/analogs & derivatives , Cyclic GMP/administration & dosage , Disease Models, Animal , Drug Delivery Systems , Retinal Degeneration/drug therapy , Animals , Blood-Retinal Barrier/drug effects , Cyclic GMP/pharmacology , Cyclic GMP-Dependent Protein Kinases/metabolism , Liposomes , Mice , Photoreceptor Cells/metabolism , Retina/drug effects , Retina/metabolism , Retinal Degeneration/metabolism , Signal Transduction/drug effectsABSTRACT
The ability to detect moving objects is an ethologically salient function. Direction-selective neurons have been identified in the retina, thalamus, and cortex of many species, but their homology has remained unclear. For instance, it is unknown whether direction-selective retinal ganglion cells (DSGCs) exist in primates and, if so, whether they are the equivalent to mouse and rabbit DSGCs. Here, we used a molecular/circuit approach in both sexes to address these issues. In mice, we identify the transcription factor Satb2 (special AT-rich sequence-binding protein 2) as a selective marker for three RGC types: On-Off DSGCs encoding motion in either the anterior or posterior direction, a newly identified type of Off-DSGC, and an Off-sustained RGC type. In rabbits, we find that expression of Satb2 is conserved in On-Off DSGCs; however, it has evolved to include On-Off DSGCs encoding upward and downward motion in addition to anterior and posterior motion. Next, we show that macaque RGCs express Satb2 most likely in a single type. We used rabies virus-based circuit-mapping tools to reveal the identity of macaque Satb2-RGCs and discovered that their dendritic arbors are relatively large and monostratified. Together, these data indicate Satb2-expressing On-Off DSGCs are likely not present in the primate retina. Moreover, if DSGCs are present in the primate retina, it is unlikely that they express Satb2.SIGNIFICANCE STATEMENT The ability to detect object motion is a fundamental feature of almost all visual systems. Here, we identify a novel marker for retinal ganglion cells encoding directional motion that is evolutionarily conserved in mice and rabbits, but not in primates. We show in macaque monkeys that retinal ganglion cells (RGCs) that express this marker comprise a single type and are morphologically distinct from mouse and rabbit direction-selective RGCs. Our findings indicate that On-Off direction-selective retinal neurons may have evolutionarily diverged in primates and more generally provide novel insight into the identity and organization of primate parallel visual pathways.
Subject(s)
DNA Fingerprinting , Retinal Ganglion Cells/physiology , Visual Pathways/physiology , Animals , Electrophysiological Phenomena/physiology , Female , Macaca , Male , Matrix Attachment Region Binding Proteins/genetics , Matrix Attachment Region Binding Proteins/physiology , Mice , Mice, Inbred C57BL , Motion Perception/physiology , Primates , Rabbits , Retina/physiology , Species Specificity , Transcription Factors/genetics , Transcription Factors/physiologyABSTRACT
Variability, stochastic or otherwise, is a central feature of neural activity. Yet the means by which estimates of variation and uncertainty are derived from noisy observations of neural activity is often heuristic, with more weight given to numerical convenience than statistical rigour. For two-photon imaging data, composed of fundamentally probabilistic streams of photon detections, the problem is particularly acute. Here, we present a statistical pipeline for the inference and analysis of neural activity using Gaussian Process regression, applied to two-photon recordings of light-driven activity in ex vivo mouse retina. We demonstrate the flexibility and extensibility of these models, considering cases with non-stationary statistics, driven by complex parametric stimuli, in signal discrimination, hierarchical clustering and other inference tasks. Sparse approximation methods allow these models to be fitted rapidly, permitting them to actively guide the design of light stimulation in the midst of ongoing two-photon experiments.
Subject(s)
Bayes Theorem , Microscopy, Fluorescence, Multiphoton/statistics & numerical data , Models, Neurological , Animals , Calcium Signaling , Computational Biology , Glutamic Acid/physiology , Heuristics , In Vitro Techniques , Mice , Mice, Inbred C57BL , Mice, Transgenic , Models, Statistical , Neurons/physiology , Normal Distribution , Photic Stimulation , Regression Analysis , Retina/physiology , Retina/radiation effects , Signal-To-Noise Ratio , UncertaintyABSTRACT
[This corrects the article DOI: 10.1371/journal.pcbi.1007205.].
ABSTRACT
Retinal bipolar cells are the first 'projection neurons' of the vertebrate visual systemall of the information needed for vision is relayed by this intraretinal connection. Each of the at least 13 distinct types of bipolar cells systematically transforms the photoreceptor input in a different way, thereby generating specific channels that encode stimulus properties, such as polarity, contrast, temporal profile and chromatic composition. As a result, bipolar cell output signals represent elementary 'building blocks' from which the microcircuits of the inner retina derive a feature-oriented description of the visual world.
Subject(s)
Retina/physiology , Retinal Bipolar Cells/physiology , Vision, Ocular/physiology , Visual Pathways/physiology , Animals , Humans , Retina/cytology , Retinal Bipolar Cells/cytology , Visual Pathways/cytologyABSTRACT
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.
Subject(s)
Action Potentials/physiology , Calcium/metabolism , Computational Biology/methods , Models, Neurological , Algorithms , Animals , Calcium/chemistry , Calcium/physiology , Databases, Factual , Mice , Molecular Imaging , Optical Imaging , Retina/cytology , Retinal Neurons/cytology , Retinal Neurons/metabolismABSTRACT
Cone photoreceptors (cones) are essential for high-resolution daylight vision and colour perception. Loss of cones in hereditary retinal diseases has a dramatic impact on human vision. The mechanisms underlying cone death are poorly understood, and consequently, there are no treatments available. Previous studies suggest a central role for calcium (Ca2+) homeostasis deficits in photoreceptor degeneration; however, direct evidence for this is scarce and physiological measurements of Ca2+ in degenerating mammalian cones are lacking.Here, we took advantage of the transgenic HR2.1:TN-XL mouse line that expresses a genetically encoded Ca2+ biosensor exclusively in cones. We cross-bred this line with mouse models for primary ("cone photoreceptor function loss-1", cpfl1) and secondary ("retinal degeneration-1", rd1) cone degeneration, respectively, and assessed resting Ca2+ levels and light-evoked Ca2+ responses in cones using two-photon imaging. We found that Ca2+ dynamics were altered in cpfl1 cones, showing higher noise and variable Ca2+ levels, with significantly wider distribution than for wild-type and rd1 cones. Unexpectedly, up to 21% of cpfl1 cones still displayed light-evoked Ca2+ responses, which were larger and slower than wild-type responses. In contrast, genetically intact rd1 cones were characterized by lower noise and complete lack of visual function.Our study demonstrates alterations in cone Ca2+ dynamics in both primary and secondary cone degeneration. Our results are consistent with the view that higher (fluctuating) cone Ca2+ levels are involved in photoreceptor cell death in primary (cpfl1) but not in secondary (rd1) cone degeneration. These findings may guide the future development of therapies targeting photoreceptor Ca2+ homeostasis.
Subject(s)
Calcium/metabolism , Retinal Cone Photoreceptor Cells/metabolism , Retinal Degeneration/metabolism , Animals , Biosensing Techniques/methods , Calcium Signaling , Mice , Mice, TransgenicABSTRACT
[This corrects the article DOI: 10.1371/journal.pbio.1002086.].
ABSTRACT
The introduction of affordable, consumer-oriented 3-D printers is a milestone in the current "maker movement," which has been heralded as the next industrial revolution. Combined with free and open sharing of detailed design blueprints and accessible development tools, rapid prototypes of complex products can now be assembled in one's own garage--a game-changer reminiscent of the early days of personal computing. At the same time, 3-D printing has also allowed the scientific and engineering community to build the "little things" that help a lab get up and running much faster and easier than ever before.
Subject(s)
Information Dissemination/ethics , Printing, Three-Dimensional/instrumentation , Software , Developing Countries , Female , Humans , Laboratories , Male , Printing, Three-Dimensional/economics , Printing, Three-Dimensional/supply & distributionABSTRACT
The first synapse of the retina plays a fundamental role in the visual system. Due to its importance, it is critical that it encodes information from the outside world with the greatest accuracy and precision possible. Cone photoreceptor axon terminals contain many individual synaptic sites, each represented by a presynaptic structure called a 'ribbon'. These synapses are both highly sophisticated and conserved. Each ribbon relays the light signal to one ON cone bipolar cell and several OFF cone bipolar cells, while two dendritic processes from a GABAergic interneuron, the horizontal cell, modulate the cone output via parallel feedback mechanisms. The presence of these three partners within a single synapse has raised numerous questions, and its anatomical and functional complexity is still only partially understood. However, the understanding of this synapse has recently evolved, as a consequence of progress in understanding dendritic signal processing and its role in facilitating global versus local signalling. Indeed, for the downstream retinal network, dendritic processing in horizontal cells may be essential, as they must support important functional operations such as contrast enhancement, which requires spatial averaging of the photoreceptor array, while at the same time preserving accurate spatial information. Here, we review recent progress made towards a better understanding of the cone synapse, with an emphasis on horizontal cell function, and discuss why such complexity might be necessary for early visual processing.
Subject(s)
Retinal Cone Photoreceptor Cells/physiology , Retinal Horizontal Cells/physiology , Synapses/physiology , Animals , Interneurons/physiologyABSTRACT
Photoreceptors form a sophisticated synaptic complex with bipolar and horizontal cells, transmitting the signals generated by the phototransduction cascade to downstream retinal circuitry. The cone photoreceptor synapse shows several characteristic anatomical connectivity motifs that shape signal transfer: typically, ON-cone bipolar cells receive photoreceptor input through invaginating synapses; OFF-cone bipolar cells form basal synapses with photoreceptors. Both ON- and OFF-cone bipolar cells are believed to sample from all cone photoreceptors within their dendritic span. Electron microscopy and immunolabelling studies have established the robustness of these motifs, but have been limited by trade-offs in sample size and spatial resolution, respectively, constraining precise quantitative investigation to a few individual cells. 3D-serial electron microscopy overcomes these limitations and has permitted complete sets of neurons to be reconstructed over a comparatively large section of retinal tissue. Although the published mouse dataset lacks labels for synaptic structures, the characteristic anatomical motifs at the photoreceptor synapse can be exploited to identify putative synaptic contacts, which has enabled the development of a quantitative description of outer retinal connectivity. This revealed unexpected exceptions to classical motifs, including substantial interaction between rod and cone pathways at the photoreceptor synapse, sparse photoreceptor sampling and atypical contacts. Here, we summarize what was learned from this study in a more general context: we consider both the implications and limitations of the study and identify promising avenues for future research.
Subject(s)
Retina/physiology , Synapses/physiology , Animals , ConnectomeABSTRACT
Controlling neurotransmitter release by modulating the presynaptic calcium level is a key mechanism to ensure reliable signal transmission from one neuron to the next. In this study, we investigated how the glutamatergic output of cone photoreceptors (cones) in the mouse retina is shaped by different feedback mechanisms from postsynaptic GABAergic horizontal cells (HCs) using a combination of two-photon calcium imaging and pharmacology at the level of individual cone axon terminals. We provide evidence that hemichannel-mediated (putative ephaptic) feedback sets the cone output gain by defining the basal calcium level, a mechanism that may be crucial for adapting cones to the ambient light level. In contrast, pH-mediated feedback did not modulate the cone basal calcium level but affected the size and shape of light-evoked cone calcium signals in a contrast-dependent way: low-contrast light responses were amplified, whereas high-contrast light responses were reduced. Finally, we provide functional evidence that GABA shapes light-evoked calcium signals in cones. Because we could not localize ionotropic GABA receptors on cone axon terminals using electron microscopy, we suggest that GABA may act through GABA autoreceptors on HCs, thereby possibly modulating hemichannel- and/or pH-mediated feedback. Together, our results suggest that at the cone synapse, hemichannel-mediated (ephaptic) and pH-mediated feedback fulfill distinct functions to adjust the output of cones to changing ambient light levels and stimulus contrasts and that the efficacy of these feedback mechanisms is likely modulated by GABA release in the outer retina.
Subject(s)
Calcium Signaling/physiology , Retinal Cone Photoreceptor Cells/physiology , Retinal Horizontal Cells/physiology , Synaptic Transmission/physiology , Visual Perception/physiology , Animals , Feedback, Physiological/physiology , Female , Male , Mice , Mice, Inbred C57BL , Mice, Transgenic , Microscopy, Immunoelectron , Patch-Clamp TechniquesABSTRACT
Fifteen years ago, the first mapping guidelines for the recording and evaluation of river physical habitat quality in Germany, closely following the Länder Arbeitsgemeinschaft Wasser (LAWA) field survey, have been published. In light of this experience, a revised version has now been developed for North Rhine-Westphalia (West Germany). For the assessment, the streams are divided into segments serving as survey units. The survey is performed primarily in the field from the mouth to the source by an on-site recording of data. Defined reference conditions of the relevant morphological stream types serve as basis of the evaluation. Two evaluation procedures are carried out independently to validate the quality of the data. The proven basic concept operates as follows: the local scale habitat variables are grouped into 31 single parameters, which are then aggregated into six main parameters. These can further be aggregated into three zones: streambed, banks and adjacent land. The main modifications of the presented version are the following: (1) a larger differentiation of morphological stream types and (2) a higher level of detail concerning the mapping of relevant habitat characteristics. The last point allows additional evaluation options related to the morphological needs of the instream biota and a differentiated survey of anthropogenic degradation. Despite all modifications, the comparability with previous surveys has been largely maintained. By qualitative comparison of this method with other European mapping guidelines, different concepts of hydromorphological mapping are finally discussed.