140217045
A Retinal Circuit Generating a Dynamic Predictive Code for Oriented Features
Summary Sensory systems must reduce the transmission of redundant information to function efficiently. One strategy is to continuously adjust the sensitivity of neurons to suppress responses to common features of the input while enhancing responses to new ones. Here we image the excitatory synaptic inputs and outputs of retinal ganglion cells to understand how such dynamic predictive coding is implemented in the analysis of spatial patterns. Synapses of bipolar cells become tuned to orientation through presynaptic inhibition, generating lateral antagonism in the orientation domain. Individual ganglion cells receive excitatory synapses tuned to different orientations, but feedforward inhibition generates a high-pass filter that only transmits the initial activation of these inputs, removing redundancy. These results demonstrate how a dynamic predictive code can be implemented by circuit motifs common to many parts of the brain.
59790818
Possible Principles Underlying the Transformations of Sensory Messages
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4354013
Efficiency and ambiguity in an adaptive neural code
We examine the dynamics of a neural code in the context of stimuli whose statistical properties are themselves evolving dynamically. Adaptation to these statistics occurs over a wide range of timescales—from tens of milliseconds to minutes. Rapid components of adaptation serve to optimize the information that action potentials carry about rapid stimulus variations within the local statistical ensemble, while changes in the rate and statistics of action-potential firing encode information about the ensemble itself, thus resolving potential ambiguities. The speed with which information is optimized and ambiguities are resolved approaches the physical limit imposed by statistical sampling and noise.
24698209
Predictive coding: a fresh view of inhibition in the retina
Interneurons exhibiting centre-surround antagonism within their receptive fields are commonly found in peripheral visual pathways. We propose that this organization enables the visual system to encode spatial detail in a manner that minimizes the deleterious effects of intrinsic noise, by exploiting the spatial correlation that exists within natural scenes. The antagonistic surround takes a weighted mean of the signals in neighbouring receptors to generate a statistical prediction of the signal at the centre. The predicted value is subtracted from the actual centre signal, thus minimizing the range of outputs transmitted by the centre. In this way the entire dynamic range of the interneuron can be devoted to encoding a small range of intensities, thus rendering fine detail detectable against intrinsic noise injected at later stages in processing. This predictive encoding scheme also reduces spatial redundancy, thereby enabling the array of interneurons to transmit a larger number of distinguishable images, taking into account the expected structure of the visual world. The profile of the required inhibitory field is derived from statistical estimation theory. This profile depends strongly upon the signal: noise ratio and weakly upon the extent of lateral spatial correlation. The receptive fields that are quantitatively predicted by the theory resemble those of X-type retinal ganglion cells and show that the inhibitory surround should become weaker and more diffuse at low intensities. The latter property is unequivocally demonstrated in the first-order interneurons of the fly’s compound eye. The theory is extended to the time domain to account for the phasic responses of fly interneurons. These comparisons suggest that, in the early stages of processing, the visual system is concerned primarily with coding the visual image to protect against subsequent intrinsic noise, rather than with reconstructing the scene or extracting specific features from it. The treatment emphasizes that a neuron’s dynamic range should be matched to both its receptive field and the statistical properties of the visual pattern expected within this field. Finally, the analysis is synthetic because it is an extension of the background suppression hypothesis (Barlow & Levick 1976), satisfies the redundancy reduction hypothesis (Barlow 1961 a, b) and is equivalent to deblurring under certain conditions (Ratliff 1965).
17515861
What Does the Retina Know about Natural Scenes?
By examining the experimental data on the statistical properties of natural scenes together with (retinal) contrast sensitivity data, we arrive at a first principle, theoretical hypothesis for the purpose of retinal processing and its relationship to an animal's environment. We argue that the retinal goal is to transform the visual input as much as possible into a statistically independent basis as the first step in creating a redundancy reduced representation in the cortex, as suggested by Barlow. The extent of this whitening of the input is limited, however, by the need to suppress input noise. Our explicit theoretical solutions for the retinal filters also show a simple dependence on mean stimulus luminance: they predict an approximate Weber law at low spatial frequencies and a De Vries-Rose law at high frequencies. Assuming that the dominant source of noise is quantum, we generate a family of contrast sensitivity curves as a function of mean luminance. This family is compared to psychophysical data.
13438461
The Neuronal Organization of the Retina
The mammalian retina consists of neurons of >60 distinct types, each playing a specific role in processing visual images. They are arranged in three main stages. The first decomposes the outputs of the rod and cone photoreceptors into ∼12 parallel information streams. The second connects these streams to specific types of retinal ganglion cells. The third combines bipolar and amacrine cell activity to create the diverse encodings of the visual world--roughly 20 of them--that the retina transmits to the brain. New transformations of the visual input continue to be found: at least half of the encodings sent to the brain (ganglion cell response selectivities) remain to be discovered. This diversity of the retina's outputs has yet to be incorporated into our understanding of higher visual function.
26113779
Real and optimal neural images in early vision
IT has been suggested1–3 that the first steps in visual processing strive to compress as much information as possible about the outside world into the limited dynamic range of the visual channels. Here I compare measured neural images with theoretical calculations based on maximizing information, taking into account the statistical structure of natural images. Neural images were obtained by scanning an image while recording from a second-order neuron in the fly visual system. Over a 5.5-log-units-wide range of mean intensities, experiment and theory correspond well. At high mean intensities, redundancy in the image is reduced by spatial and temporal antagonism. At low mean intensities, spatial and temporal low-pass filtering combat noise and increase signal reliability.
10979040
Time-compressed preplay of anticipated events in human primary visual cortex
Perception is guided by the anticipation of future events. It has been hypothesized that this process may be implemented by pattern completion in early visual cortex, in which a stimulus sequence is recreated after only a subset of the visual input is provided. Here we test this hypothesis using ultra-fast functional magnetic resonance imaging to measure BOLD activity at precisely defined receptive field locations in visual cortex (V1) of human volunteers. We find that after familiarizing subjects with a spatial sequence, flashing only the starting point of the sequence triggers an activity wave in V1 that resembles the full stimulus sequence. This preplay activity is temporally compressed compared to the actual stimulus sequence and remains present even when attention is diverted from the stimulus sequence. Preplay might therefore constitute an automatic prediction mechanism for temporal sequences in V1.
486803
Dynamic predictive coding by the retina
Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode local differences in space and changes in time rather than the raw image intensity. This can be seen as a strategy of predictive coding, adapted through evolution to the average image statistics of the natural environment. Yet animals encounter many environments with visual statistics different from the average scene. Here we show that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new image statistics. We show that a network model with plastic synapses can account for the large variety of observed adaptations.
4361559
Adaptive filtering enhances information transmission in visual cortex
Sensory neuroscience seeks to understand how the brain encodes natural environments. However, neural coding has largely been studied using simplified stimuli. In order to assess whether the brain's coding strategy depends on the stimulus ensemble, we apply a new information-theoretic method that allows unbiased calculation of neural filters (receptive fields) from responses to natural scenes or other complex signals with strong multipoint correlations. In the cat primary visual cortex we compare responses to natural inputs with those to noise inputs matched for luminance and contrast. We find that neural filters adaptively change with the input ensemble so as to increase the information carried by the neural response about the filtered stimulus. Adaptation affects the spatial frequency composition of the filter, enhancing sensitivity to under-represented frequencies in agreement with optimal encoding arguments. Adaptation occurs over 40 s to many minutes, longer than most previously reported forms of adaptation.
4357826
Efficient auditory coding
The auditory neural code must serve a wide range of auditory tasks that require great sensitivity in time and frequency and be effective over the diverse array of sounds present in natural acoustic environments. It has been suggested that sensory systems might have evolved highly efficient coding strategies to maximize the information conveyed to the brain while minimizing the required energy and neural resources. Here we show that, for natural sounds, the complete acoustic waveform can be represented efficiently with a nonlinear model based on a population spike code. In this model, idealized spikes encode the precise temporal positions and magnitudes of underlying acoustic features. We find that when the features are optimized for coding either natural sounds or speech, they show striking similarities to time-domain cochlear filter estimates, have a frequency-bandwidth dependence similar to that of auditory nerve fibres, and yield significantly greater coding efficiency than conventional signal representations. These results indicate that the auditory code might approach an information theoretic optimum and that the acoustic structure of speech might be adapted to the coding capacity of the mammalian auditory system.
7597712
Detecting and representing predictable structure during auditory scene analysis
We use psychophysics and MEG to test how sensitivity to input statistics facilitates auditory-scene-analysis (ASA). Human subjects listened to ‘scenes’ comprised of concurrent tone-pip streams (sources). On occasional trials a new source appeared partway. Listeners were more accurate and quicker to detect source appearance in scenes comprised of temporally-regular (REG), rather than random (RAND), sources. MEG in passive listeners and those actively detecting appearance events revealed increased sustained activity in auditory and parietal cortex in REG relative to RAND scenes, emerging ~400 ms of scene-onset. Over and above this, appearance in REG scenes was associated with increased responses relative to RAND scenes. The effect of temporal structure on appearance-evoked responses was delayed when listeners were focused on the scenes relative to when listening passively, consistent with the notion that attention reduces ‘surprise’. Overall, the results implicate a mechanism that tracks predictability of multiple concurrent sources to facilitate active and passive ASA. DOI: http://dx.doi.org/10.7554/eLife.19113.001
6692266
Internally-organized mechanisms of the head direction sense
The head-direction (HD) system functions as a compass, with member neurons robustly increasing their firing rates when the animal's head points in a specific direction. HD neurons may be driven by peripheral sensors or, as computational models postulate, internally generated (attractor) mechanisms. We addressed the contributions of stimulus-driven and internally generated activity by recording ensembles of HD neurons in the antero-dorsal thalamic nucleus and the post-subiculum of mice by comparing their activity in various brain states. The temporal correlation structure of HD neurons was preserved during sleep, characterized by a 60°-wide correlated neuronal firing (activity packet), both within and across these two brain structures. During rapid eye movement sleep, the spontaneous drift of the activity packet was similar to that observed during waking and accelerated tenfold during slow-wave sleep. These findings demonstrate that peripheral inputs impinge on an internally organized network, which provides amplification and enhanced precision of the HD signal.
8583139
Reward and choice encoding in terminals of midbrain dopamine neurons depends on striatal target
Dopaminergic (DA) neurons in the midbrain provide rich topographic innervation of the striatum and are central to learning and to generating actions. Despite the importance of this DA innervation, it remains unclear whether and how DA neurons are specialized on the basis of the location of their striatal target. Thus, we sought to compare the function of subpopulations of DA neurons that target distinct striatal subregions in the context of an instrumental reversal learning task. We identified key differences in the encoding of reward and choice in dopamine terminals in dorsal versus ventral striatum: DA terminals in ventral striatum responded more strongly to reward consumption and reward-predicting cues, whereas DA terminals in dorsomedial striatum responded more strongly to contralateral choices. In both cases the terminals encoded a reward prediction error. Our results suggest that the DA modulation of the striatum is spatially organized to support the specialized function of the targeted subregion.
2727848
Dopamine reward prediction-error signalling: a two-component response
Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy.
185706
Linking pattern completion in the hippocampus to predictive coding in visual cortex
Models of predictive coding frame perception as a generative process in which expectations constrain sensory representations. These models account for expectations about how a stimulus will move or change from moment to moment, but do not address expectations about what other, distinct stimuli are likely to appear based on prior experience. We show that such memory-based expectations in human visual cortex are related to the hippocampal mechanism of pattern completion.
197685967
The hippocampus as a predictive map
A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity, and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. Furthermore, we argue that entorhinal grid cells encode a low-dimensional basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.
2024772
Canonical Microcircuits for Predictive Coding
This Perspective considers the influential notion of a canonical (cortical) microcircuit in light of recent theories about neuronal processing. Specifically, we conciliate quantitative studies of microcircuitry and the functional logic of neuronal computations. We revisit the established idea that message passing among hierarchical cortical areas implements a form of Bayesian inference-paying careful attention to the implications for intrinsic connections among neuronal populations. By deriving canonical forms for these computations, one can associate specific neuronal populations with specific computational roles. This analysis discloses a remarkable correspondence between the microcircuitry of the cortical column and the connectivity implied by predictive coding. Furthermore, it provides some intuitive insights into the functional asymmetries between feedforward and feedback connections and the characteristic frequencies over which they operate.
205044463
Seeing smells: imaging olfactory learning in bees
Using calcium imaging as bees learn to associate odors with a reward, Faber and colleagues show that learning changes activity patterns at the earliest olfactory site in the brain.
12304596
Coordinated dynamic encoding in the retina using opposing forms of plasticity
The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This newly observed dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails.
9265077
Synaptic mechanisms of adaptation and sensitization in the retina
Sensory systems continually adjust the way stimuli are processed. What are the circuit mechanisms underlying this plasticity? We investigated how synapses in the retina of zebrafish adjust to changes in the temporal contrast of a visual stimulus by imaging activity in vivo. Following an increase in contrast, bipolar cell synapses with strong initial responses depressed, whereas synapses with weak initial responses facilitated. Depression and facilitation predominated in different strata of the inner retina, where bipolar cell output was anticorrelated with the activity of amacrine cell synapses providing inhibitory feedback. Pharmacological block of GABAergic feedback converted facilitating bipolar cell synapses into depressing ones. These results indicate that depression intrinsic to bipolar cell synapses causes adaptation of the ganglion cell response to contrast, whereas depression in amacrine cell synapses causes sensitization. Distinct microcircuits segregating to different layers of the retina can cause simultaneous increases or decreases in the gain of neural responses.
24714443
Insights from the retina into the diverse and general computations of adaptation, detection, and prediction
The retina performs a diverse set of complex, nonlinear, computations, beyond the simple linear photoreceptor weighting assumed in the classical understanding of ganglion cell receptive fields. Here we attempt to organize these computations and extract rules that correspond to three distinct goals of early sensory systems. First, the retina acts efficiently to transmit information to the higher brain for further processing. We observe that although the retina adapts to a number of complex statistics, many of these may be explained by local adaptation to the mean signal strength at that stage. Second, ganglion cells signal the detection of a diverse set of features. Recent results indicate that feature selectivity arises through the action of specific inhibition, rather than through the convergence of excitation as in classical cortical models. Finally, the retina conveys predictions about the stimulus, a function usually attributed only to the higher brain. We expect that computational and mechanistic rules associated with these classes of functions will be an important guide in the study of other neural circuits.
1583895
Adaptation maintains population homeostasis in primary visual cortex
Sensory systems exhibit mechanisms of neural adaptation, which adjust neuronal activity on the basis of recent stimulus history. In primary visual cortex (V1) in particular, adaptation controls the responsiveness of individual neurons and shifts their visual selectivity. What benefits does adaptation confer on a neuronal population? We measured adaptation in the responses of populations of cat V1 neurons to stimulus ensembles with markedly different statistics of stimulus orientation. We found that adaptation served two homeostatic goals. First, it maintained equality in the time-averaged responses across the population. Second, it maintained independence in selectivity across the population. Adaptation scaled and distorted population activity according to a simple multiplicative rule that depended on neuronal orientation preference and on stimulus orientation. We conclude that adaptation in V1 acts as a mechanism of homeostasis, enforcing a tendency toward equality and independence in neural activity across the population.
16885867
Adaptation-Induced Plasticity of Orientation Tuning in Adult Visual Cortex
A key emergent property of the primary visual cortex (V1) is the orientation selectivity of its neurons. The extent to which adult visual cortical neurons can exhibit changes in orientation selectivity is unknown. Here we use single-unit recording and intrinsic signal imaging in V1 of adult cats to demonstrate systematic repulsive shifts in orientation preference following short-term exposure (adaptation) to one stimulus orientation. In contrast to the common view of adaptation as a passive process by which responses around the adapting orientation are reduced, we show that changes in orientation tuning also occur due to response increases at orientations away from the adapting stimulus. Adaptation-induced orientation plasticity is thus an active time-dependent process that involves network interactions and includes both response depression and enhancement.
2906796
Electrical synapses convey orientation selectivity in the mouse retina
Sensory neurons downstream of primary receptors are selective for specific stimulus features, and they derive their selectivity both from excitatory and inhibitory synaptic inputs from other neurons and from their own intrinsic properties. Electrical synapses, formed by gap junctions, modulate sensory circuits. Retinal ganglion cells (RGCs) are diverse feature detectors carrying visual information to the brain, and receive excitatory input from bipolar cells and inhibitory input from amacrine cells (ACs). Here we describe a RGC that relies on gap junctions, rather than chemical synapses, to convey its selectivity for the orientation of a visual stimulus. This represents both a new functional role of electrical synapses as the primary drivers of feature selectivity and a new circuit mechanism for orientation selectivity in the retina.Visual input received by photoreceptors is relayed to retinal ganglion cells (RGCs), which have selectivity for inputs of certain orientations. Here, the authors show that gap junction-mediated input onto one type of RGC contributes to its orientation selectivity.
39427963
Synaptic Mechanisms Generating Orientation Selectivity in the ON Pathway of the Rabbit Retina
Neurons that signal the orientation of edges within the visual field have been widely studied in primary visual cortex. Much less is known about the mechanisms of orientation selectivity that arise earlier in the visual stream. Here we examine the synaptic and morphological properties of a subtype of orientation-selective ganglion cell in the rabbit retina. The receptive field has an excitatory ON center, flanked by excitatory OFF regions, a structure similar to simple cell receptive fields in primary visual cortex. Examination of the light-evoked postsynaptic currents in these ON-type orientation-selective ganglion cells (ON-OSGCs) reveals that synaptic input is mediated almost exclusively through the ON pathway. Orientation selectivity is generated by larger excitation for preferred relative to orthogonal stimuli, and conversely larger inhibition for orthogonal relative to preferred stimuli. Excitatory orientation selectivity arises in part from the morphology of the dendritic arbors. Blocking GABAA receptors reduces orientation selectivity of the inhibitory synaptic inputs and the spiking responses. Negative contrast stimuli in the flanking regions produce orientation-selective excitation in part by disinhibition of a tonic NMDA receptor-mediated input arising from ON bipolar cells. Comparison with earlier studies of OFF-type OSGCs indicates that diverse synaptic circuits have evolved in the retina to detect the orientation of edges in the visual input. SIGNIFICANCE STATEMENT A core goal for visual neuroscientists is to understand how neural circuits at each stage of the visual system extract and encode features from the visual scene. This study documents a novel type of orientation-selective ganglion cell in the retina and shows that the receptive field structure is remarkably similar to that of simple cells in primary visual cortex. However, the data indicate that, unlike in the cortex, orientation selectivity in the retina depends on the activity of inhibitory interneurons. The results further reveal the physiological basis for feature detection in the visual system, elucidate the synaptic mechanisms that generate orientation selectivity at an early stage of visual processing, and illustrate a novel role for NMDA receptors in retinal processing.
14801990
Receptive fields of single neurones in the cat's striate cortex
In the central nervous system the visual pathway from retina to striate cortex provides an opportunity to observe and compare single unit responses at several distinct levels. Patterns of light stimuli most effective in influencing units at one level may no longer be the most effective at the next. From differences in responses at successive stages in the pathway one may hope to gain some understanding of the part each stage plays in visual perception. By shining small spots of light on the light-adapted cat retina Kuffler (1953) showed that ganglion cells have concentric receptive fields, with an 'on' centre and an 'off ' periphery, or vice versa. The 'on' and 'off' areas within a receptive field were found to be mutually antagonistic, and a spot restricted to the centre of the field was more effective than one covering the whole receptive field (Barlow, FitzHugh & Kuffler, 1957). In the freely moving lightadapted cat it was found that the great majority of cortical cells studied gave little or no response to light stimuli covering most of the animal's visual field, whereas small spots shone in a restricted retinal region often evoked brisk responses (Hubel, 1959). A moving spot of light often produced stronger responses than a stationary one, and sometimes a moving spot gave more activation for one direction than for the opposite. The present investigation, made in acute preparations, includes a study of receptive fields of cells in the cat's striate cortex. Receptive fields of the cells considered in this paper were divided into separate excitatory and inhibitory ('on' and 'off') areas. In this respect they resembled retinal ganglion-cell receptive fields. However, the shape and arrangement of excitatory and inhibitory areas differed strikingly from the concentric pattern found in retinal ganglion cells. An attempt was made to correlate responses to moving stimuli
4455707
Synaptic organization of visual space in primary visual cortex
How a sensory stimulus is processed and perceived depends on the surrounding sensory scene. In the visual cortex, contextual signals can be conveyed by an extensive network of intra- and inter-areal excitatory connections that link neurons representing stimulus features separated in visual space. However, the connectional logic of visual contextual inputs remains unknown; it is not clear what information individual neurons receive from different parts of the visual field, nor how this input relates to the visual features that a neuron encodes, defined by its spatial receptive field. Here we determine the organization of excitatory synaptic inputs responding to different locations in the visual scene by mapping spatial receptive fields in dendritic spines of mouse visual cortex neurons using two-photon calcium imaging. We find that neurons receive functionally diverse inputs from extended regions of visual space. Inputs representing similar visual features from the same location in visual space are more likely to cluster on neighbouring spines. Inputs from visual field regions beyond the receptive field of the postsynaptic neuron often synapse on higher-order dendritic branches. These putative long-range inputs are more frequent and more likely to share the preference for oriented edges with the postsynaptic neuron when the receptive field of the input is spatially displaced along the axis of the receptive field orientation of the postsynaptic neuron. Therefore, the connectivity between neurons with displaced receptive fields obeys a specific rule, whereby they connect preferentially when their receptive fields are co-oriented and co-axially aligned. This organization of synaptic connectivity is ideally suited for the amplification of elongated edges, which are enriched in the visual environment, and thus provides a potential substrate for contour integration and object grouping.
23437078
Laminar differences in the orientation selectivity of geniculate afferents in mouse primary visual cortex
It has been debated whether orientation selectivity in mouse primary visual cortex (V1) is derived from tuned lateral geniculate nucleus (LGN) inputs or computed from untuned LGN inputs. However, few studies have measured orientation tuning of LGN axons projecting to V1. We measured the response properties of mouse LGN axons terminating in V1 and found that LGN axons projecting to layer 4 were generally less tuned for orientation than axons projecting to more superficial layers of V1. We also found several differences in response properties between LGN axons and V1 neurons in layer 4. These results suggest that orientation selectivity of mouse V1 may not simply be inherited from LGN inputs, but could also depend on thalamocortical or V1 circuits.
4409952
Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex
Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 µm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 µm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.
1226657
Eye Smarter than Scientists Believed: Neural Computations in Circuits of the Retina
We rely on our visual system to cope with the vast barrage of incoming light patterns and to extract features from the scene that are relevant to our well-being. The necessary reduction of visual information already begins in the eye. In this review, we summarize recent progress in understanding the computations performed in the vertebrate retina and how they are implemented by the neural circuitry. A new picture emerges from these findings that helps resolve a vexing paradox between the retina's structure and function. Whereas the conventional wisdom treats the eye as a simple prefilter for visual images, it now appears that the retina solves a diverse set of specific tasks and provides the results explicitly to downstream brain areas.
2598727
Adaptation to Stimulus Contrast and Correlations during Natural Visual Stimulation
In this study, we characterize the adaptation of neurons in the cat lateral geniculate nucleus to changes in stimulus contrast and correlations. By comparing responses to high- and low-contrast natural scene movie and white noise stimuli, we show that an increase in contrast or correlations results in receptive fields with faster temporal dynamics and stronger antagonistic surrounds, as well as decreases in gain and selectivity. We also observe contrast- and correlation-induced changes in the reliability and sparseness of neural responses. We find that reliability is determined primarily by processing in the receptive field (the effective contrast of the stimulus), while sparseness is determined by the interactions between several functional properties. These results reveal a number of adaptive phenomena and suggest that adaptation to stimulus contrast and correlations may play an important role in visual coding in a dynamic natural environment.
118292678
Visual Pattern Analyzers
PART I: INTRODUCTION 1. Neurophysiology and Psychophysics 2. Some Mathematics PART II: ADAPTION 3. Models of Selective Effects PART III: SUMMATION 4. Models for Far-Apart Values 5. Far-Apart Values on Spatial Dimensions 6. Close Values on Spatial Dimensions PART IV: UNCERTAINTY 7. Extrinsic Uncertainty and Summation Revisited 8. Intrinsic Uncertainty and Transducer Functions PART V: IDENTIFICATION 9. Discrimination 10. Three More Paradigms and Transducer Functions PART VI: MULTIPLE DIMENSIONS 11. Some General Considerations 12. Results of Analyzer-Revealing Experiments 13. Results of Parametric Experiments PART VII: EPILOGUE 14. The Assumptions Revisited
16818584
Synaptic Integration Gradients in Single Cortical Pyramidal Cell Dendrites
Cortical pyramidal neurons receive thousands of synaptic inputs arriving at different dendritic locations with varying degrees of temporal synchrony. It is not known if different locations along single cortical dendrites integrate excitatory inputs in different ways. Here we have used two-photon glutamate uncaging and compartmental modeling to reveal a gradient of nonlinear synaptic integration in basal and apical oblique dendrites of cortical pyramidal neurons. Excitatory inputs to the proximal dendrite sum linearly and require precise temporal coincidence for effective summation, whereas distal inputs are amplified with high gain and integrated over broader time windows. This allows distal inputs to overcome their electrotonic disadvantage, and become surprisingly more effective than proximal inputs at influencing action potential output. Thus, single dendritic branches can already exhibit nonuniform synaptic integration, with the computational strategy shifting from temporal coding to rate coding along the dendrite.
8485978
Active dendritic integration as a mechanism for robust and precise grid cell firing
Understanding how active dendrites are exploited for behaviorally relevant computations is a fundamental challenge in neuroscience. Grid cells in medial entorhinal cortex are an attractive model system for addressing this question, as the computation they perform is clear: they convert synaptic inputs into spatially modulated, periodic firing. Whether active dendrites contribute to the generation of the dual temporal and rate codes characteristic of grid cell output is unknown. We show that dendrites of medial entorhinal cortex neurons are highly excitable and exhibit a supralinear input–output function in vitro, while in vivo recordings reveal membrane potential signatures consistent with recruitment of active dendritic conductances. By incorporating these nonlinear dynamics into grid cell models, we show that they can sharpen the precision of the temporal code and enhance the robustness of the rate code, thereby supporting a stable, accurate representation of space under varying environmental conditions. Our results suggest that active dendrites may therefore constitute a key cellular mechanism for ensuring reliable spatial navigation.
54466996
Parametric Functional Maps of Visual Inputs to the Tectum
How features of the visual scene are encoded in the population activity of retinal ganglion cells (RGCs) targeting specific regions of the brain is not well understood. To address this, we have used a genetically encoded reporter of presynaptic function (SyGCaMP3) to record visually evoked activity in the population of RGC axons innervating the zebrafish tectum. Using unbiased voxel-wise analysis of SyGCaMP3 signals, we identify three subtypes of direction-selective and two subtypes of orientation-selective retinal input. Composite parametric functional maps generated across many larvae show laminar segregation of direction- and orientation-selective responses and unexpected retinotopic biases in the distribution of functional subtypes. These findings provide a systematic description of the form, organization, and dimensionality of visual inputs to the brain and will serve as a platform for understanding emergent properties in tectal circuits associated with visually driven behavior.
9921887
Divergence of visual channels in the inner retina
Bipolar cells form parallel channels that carry visual signals from the outer to the inner retina. Each type of bipolar cell is thought to carry a distinct visual message to select types of amacrine cells and ganglion cells. However, the number of ganglion cell types exceeds that of the bipolar cells providing their input, suggesting that bipolar cell signals diversify on transmission to ganglion cells. We explored in the salamander retina how signals from individual bipolar cells feed into multiple ganglion cells and found that each bipolar cell was able to evoke distinct responses among ganglion cells, differing in kinetics, adaptation and rectification properties. This signal divergence resulted primarily from interactions with amacrine cells that allowed each bipolar cell to send distinct signals to its target ganglion cells. Our findings indicate that individual bipolar cell–ganglion cell connections have distinct transfer functions. This expands the number of visual channels in the inner retina and enhances the computational power and feature selectivity of early visual processing.
2190361
Rapid mapping of visual receptive fields by filtered back projection: application to multi-neuronal electrophysiology and imaging
To understand vision, we must measure the spatio‐temporal receptive field of neurons in the visual system. We describe how the filtered back projection can be used to map the receptive fields of many neurons simultaneously, within a few minutes. This method can also reveal complex features of visual receptive fields such as the tuning of orientation selective neurons and the contributions from separate ON and OFF components. We demonstrate that the filtered back projection is suited to mapping receptive fields from populations of neurons recorded with imaging or electrophysiology and should therefore prove useful for investigations of visual processing throughout the visual pathway.
6560727
A Synaptic Mechanism for Retinal Adaptation to Luminance and Contrast
The gain of signaling in primary sensory circuits is matched to the stimulus intensity by the process of adaptation. Retinal neural circuits adapt to visual scene statistics, including the mean (background adaptation) and the temporal variance (contrast adaptation) of the light stimulus. The intrinsic properties of retinal bipolar cells and synapses contribute to background and contrast adaptation, but it is unclear whether both forms of adaptation depend on the same cellular mechanisms. Studies of bipolar cell synapses identified synaptic mechanisms of gain control, but the relevance of these mechanisms to visual processing is uncertain because of the historical focus on fast, phasic transmission rather than the tonic transmission evoked by ambient light. Here, we studied use-dependent regulation of bipolar cell synaptic transmission evoked by small, ongoing modulations of membrane potential (VM) in the physiological range. We made paired whole-cell recordings from rod bipolar (RB) and AII amacrine cells in a mouse retinal slice preparation. Quasi-white noise voltage commands modulated RB VM and evoked EPSCs in the AII. We mimicked changes in background luminance or contrast, respectively, by depolarizing the VM or increasing its variance. A linear systems analysis of synaptic transmission showed that increasing either the mean or the variance of the presynaptic VM reduced gain. Further electrophysiological and computational analyses demonstrated that adaptation to mean potential resulted from both Ca channel inactivation and vesicle depletion, whereas adaptation to variance resulted from vesicle depletion alone. Thus, background and contrast adaptation apparently depend in part on a common synaptic mechanism.
11828954
Encoding of Luminance and Contrast by Linear and Nonlinear Synapses in the Retina
Summary Understanding how neural circuits transmit information is technically challenging because the neural code is contained in the activity of large numbers of neurons and synapses. Here, we use genetically encoded reporters to image synaptic transmission across a population of sensory neurons—bipolar cells in the retina of live zebrafish. We demonstrate that the luminance sensitivities of these synapses varies over 104 with a log-normal distribution. About half the synapses made by ON and OFF cells alter their polarity of transmission as a function of luminance to generate a triphasic tuning curve with distinct maxima and minima. These nonlinear synapses signal temporal contrast with greater sensitivity than linear ones. Triphasic tuning curves increase the dynamic range over which bipolar cells signal light and improve the efficiency with which luminance information is transmitted. The most efficient synapses signaled luminance using just 1 synaptic vesicle per second per distinguishable gray level.
24029555
Bipolar cell–photoreceptor connectivity in the zebrafish (Danio rerio) retina
Bipolar cells convey luminance, spatial, and color information from photoreceptors to amacrine and ganglion cells. We studied the photoreceptor connectivity of 321 bipolar cells in the adult zebrafish retina. 1,1′‐Dioctadecyl‐3,3,3′,3′‐tetramethylindocarbocyanine perchlorate (DiI) was inserted into whole‐mounted transgenic zebrafish retinas to label bipolar cells. The photoreceptors that connect to these DiI‐labeled cells were identified by transgenic fluorescence or their positions relative to the fluorescent cones, as cones are arranged in a highly ordered mosaic: rows of alternating blue‐ (B) and ultraviolet‐sensitive (UV) single cones alternate with rows of red‐ (R) and green‐sensitive (G) double cones. Rod terminals intersperse among cone terminals. As many as 18 connectivity subtypes were observed, 9 of which—G, GBUV, RG, RGB, RGBUV, RGRod, RGBRod, RGBUVRod, and RRod bipolar cells—accounted for 96% of the population. Based on their axon terminal stratification, these bipolar cells could be further subdivided into ON, OFF, and ON–OFF cells. The dendritic spread size, soma depth and size, and photoreceptor connections of the 308 bipolar cells within the nine common connectivity subtypes were determined, and their dendritic tree morphologies and axonal stratification patterns compared. We found that bipolar cells with the same axonal stratification patterns could have heterogeneous photoreceptor connectivity whereas bipolar cells with the same dendritic tree morphology usually had the same photoreceptor connectivity, although their axons might stratify on different levels. J. Comp. Neurol. 520:3786–3802, 2012. © 2012 Wiley Periodicals, Inc.
3924963
Neural Mechanisms Generating Orientation Selectivity in the Retina
Summary The orientation of visual stimuli is a salient feature of visual scenes. In vertebrates, the first neural processing steps generating orientation selectivity take place in the retina. Here, we dissect an orientation-selective circuit in the larval zebrafish retina and describe its underlying synaptic, cellular, and molecular mechanisms. We genetically identify a class of amacrine cells (ACs) with elongated dendritic arbors that show orientation tuning. Both selective optogenetic ablation of ACs marked by the cell-adhesion molecule Teneurin-3 (Tenm3) and pharmacological interference with their function demonstrate that these cells are critical components for orientation selectivity in retinal ganglion cells (RGCs) by being a source of tuned GABAergic inhibition. Moreover, our morphological analyses reveal that Tenm3+ ACs and orientation-selective RGCs co-stratify their dendrites in the inner plexiform layer, and that Tenm3+ ACs require Tenm3 to acquire their correct dendritic stratification. Finally, we show that orientation tuning is present also among bipolar cell presynaptic terminals. Our results define a neural circuit underlying orientation selectivity in the vertebrate retina and characterize cellular and molecular requirements for its assembly.
14973392
Three forms of spatial temporal feedforward inhibition are common to different ganglion cell types in rabbit retina.
There exist more than 30 different morphological amacrine cell types, but there may be fewer physiological types. Here we studied the amacrine cell outputs by measuring the temporal and spatial properties of feedforward inhibition to four different types of ganglion cells. These ganglion cells, each with concentric receptive field organization, appear to receive a different relative contribution of the same three forms of feed-forward inhibition, namely: local glycinergic, local sustained GABAergic, and broad transient GABAergic inhibition. Two of these inhibitory components, local glycinergic inhibition and local sustained GABAergic inhibition were localized to narrow regions confined to the dendritic fields of the ganglion cells. The third, a broad transient GABAergic inhibition, was driven from regions peripheral to the dendritic area. Each inhibitory component is also correlated with characteristic kinetics expressed in all ganglion cells: broad transient GABAergic inhibition had the shortest latency, local glycinergic inhibition had an intermediate latency, and local sustained GABAergic inhibition had the longest latency. We suggest each of these three inhibitory components represents the output from a distinct class of amacrine cell, mediates a specific visual function, and each forms a basic functional component for the four ganglion cell types. Similar subunits likely exist in the circuits of other ganglion cell types as well.
976247
Inhibitory Interneurons in the Retina: Types, Circuitry, and Function.
Visual signals in the vertebrate retina are shaped by feedback and feedforward inhibition in two synaptic layers. In one, horizontal cells establish fundamental center-surround receptive-field properties via morphologically and physiologically complex synapses with photoreceptors and bipolar cells. In the other, a panoply of amacrine cells imbue ganglion cell responses with spatiotemporally complex information about the visual world. Here, I review current ideas about horizontal cell signaling, considering the evidence for and against the leading, competing theories. I also discuss recent work that has begun to make sense of the remarkable morphological and physiological diversity of amacrine cells. These latter efforts have been aided tremendously by increasingly complete connectivity maps of inner retinal circuitry and new genetic tools that enable study of individual, sparsely expressed amacrine cell types.
6527667
How Inhibition Shapes Cortical Activity
Cortical processing reflects the interplay of synaptic excitation and synaptic inhibition. Rapidly accumulating evidence is highlighting the crucial role of inhibition in shaping spontaneous and sensory-evoked cortical activity and thus underscores how a better knowledge of inhibitory circuits is necessary for our understanding of cortical function. We discuss current views of how inhibition regulates the function of cortical neurons and point to a number of important open questions.
9441276
Input normalization by global feedforward inhibition expands cortical dynamic range
The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mechanisms that enable this wide range of operation are not fully understood. We found that the amplitude of excitatory synaptic currents necessary to fire rodent pyramidal cells, the threshold excitatory current, increased with stimulus strength. Consequently, the relative contribution of individual afferents in firing a neuron was inversely proportional to the total number of active afferents. Feedforward inhibition, acting homogeneously across pyramidal cells, ensured that threshold excitatory currents increased with stimulus strength. In contrast, heterogeneities in the distribution of excitatory currents in the neuronal population determined the specific set of pyramidal cells recruited. Together, these mechanisms expand the range of afferent input strengths that neuronal populations can represent.
17465608
Inhibitory Gating of Input Comparison in the CA1 Microcircuit
Spatial and temporal features of synaptic inputs engage integration mechanisms on multiple scales, including presynaptic release sites, postsynaptic dendrites, and networks of inhibitory interneurons. Here we investigate how these mechanisms cooperate to filter synaptic input in hippocampal area CA1. Dendritic recordings from CA1 pyramidal neurons reveal that proximal inputs from CA3 as well as distal inputs from entorhinal cortex layer III (ECIII) sum sublinearly or linearly at low firing rates due to feedforward inhibition, but sum supralinearly at high firing rates due to synaptic facilitation, producing a high-pass filter. However, during ECIII and CA3 input comparison, supralinear dendritic integration is dynamically balanced by feedforward and feedback inhibition, resulting in suppression of dendritic complex spiking. We find that a particular subpopulation of CA1 interneurons expressing neuropeptide Y (NPY) contributes prominently to this dynamic filter by integrating both ECIII and CA3 input pathways and potently inhibiting CA1 pyramidal neuron dendrites.
7828382
Synaptic Rectification Controls Nonlinear Spatial Integration of Natural Visual Inputs
A central goal in the study of any sensory system is to predict neural responses to complex inputs, especially those encountered during natural stimulation. Nowhere is the transformation from stimulus to response better understood than the vertebrate retina. Nevertheless, descriptions of retinal computation are largely based on stimulation using artificial visual stimuli, and it is unclear how these descriptions map onto the encoding of natural stimuli. We demonstrate that nonlinear spatial integration, a common feature of retinal ganglion cell (RGC) processing, shapes neural responses to natural visual stimuli in primate Off parasol RGCs, whereas On parasol RGCs exhibit surprisingly linear spatial integration. Despite this asymmetry, both cell types show strong nonlinear integration when presented with artificial stimuli. We show that nonlinear integration of natural stimuli is a consequence of rectified excitatory synaptic input and that accounting for nonlinear spatial integration substantially improves models that predict RGC responses to natural images.
18870893
Energy limitation as a selective pressure on the evolution of sensory systems
SUMMARY Evolution of animal morphology, physiology and behaviour is shaped by the selective pressures to which they are subject. Some selective pressures act to increase the benefits accrued whilst others act to reduce the costs incurred, affecting the cost/benefit ratio. Selective pressures therefore produce a trade-off between costs and benefits that ultimately influences the fitness of the whole organism. The nervous system has a unique position as the interface between morphology, physiology and behaviour; the final output of the nervous system is the behaviour of the animal, which is a product of both its morphology and physiology. The nervous system is under selective pressure to generate adaptive behaviour, but at the same time is subject to costs related to the amount of energy that it consumes. Characterising this trade-off between costs and benefits is essential to understanding the evolution of nervous systems, including our own. Within the nervous system, sensory systems are the most amenable to analysing costs and benefits, not only because their function can be more readily defined than that of many central brain regions and their benefits quantified in terms of their performance, but also because recent studies of sensory systems have begun to directly assess their energetic costs. Our review focuses on the visual system in particular, although the principles we discuss are equally applicable throughout the nervous system. Examples are taken from a wide range of sensory modalities in both vertebrates and invertebrates. We aim to place the studies we review into an evolutionary framework. We combine experimentally determined measures of energy consumption from whole retinas of rabbits and flies with intracellular measurements of energy consumption from single fly photoreceptors and recently constructed energy budgets for neural processing in rats to assess the contributions of various components to neuronal energy consumption. Taken together, these studies emphasize the high costs of maintaining neurons at rest and whilst signalling. A substantial proportion of neuronal energy consumption is related to the movements of ions across the neuronal cell membrane through ion channels, though other processes such as vesicle loading and transmitter recycling also consume energy. Many of the energetic costs within neurons are linked to 3Na+/2K+ ATPase activity, which consumes energy to pump Na+ and K+ ions across the cell membrane and is essential for the maintenance of the resting potential and its restoration following signalling. Furthermore, recent studies in fly photoreceptors show that energetic costs can be related, via basic biophysical relationships, to their function. These findings emphasize that neurons are subject to a law of diminishing returns that severely penalizes excess functional capacity with increased energetic costs. The high energetic costs associated with neural tissue favour energy efficient coding and wiring schemes, which have been found in numerous sensory systems. We discuss the role of these efficient schemes in reducing the costs of information processing. Assessing evidence from a wide range of vertebrate and invertebrate examples, we show that reducing energy expenditure can account for many of the morphological features of sensory systems and has played a key role in their evolution.
4412010
Network anatomy and in vivo physiology of visual cortical neurons
In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron's function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property—the preferred stimulus orientation—of a group of neurons in the mouse primary visual cortex. Large-scale electron microscopy of serial thin sections was then used to trace a portion of these neurons’ local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.
28918892
Mechanisms of Orientation Selectivity in the Primary Visual Cortex.
The mechanisms underlying the emergence of orientation selectivity in the visual cortex have been, and continue to be, the subjects of intense scrutiny. Orientation selectivity reflects a dramatic change in the representation of the visual world: Whereas afferent thalamic neurons are generally orientation insensitive, neurons in the primary visual cortex (V1) are extremely sensitive to stimulus orientation. This profound change in the receptive field structure along the visual pathway has positioned V1 as a model system for studying the circuitry that underlies neural computations across the neocortex. The neocortex is characterized anatomically by the relative uniformity of its circuitry despite its role in processing distinct signals from region to region. A combination of physiological, anatomical, and theoretical studies has shed some light on the circuitry components necessary for generating orientation selectivity in V1. This targeted effort has led to critical insights, as well as controversies, concerning how neural circuits in the neocortex perform computations.
23272300
Recruitment of an inhibitory hippocampal network after bursting in a single granule cell
The hippocampal CA3 area, an associational network implicated in memory function, receives monosynaptic excitatory as well as disynaptic inhibitory input through the mossy-fiber axons of the dentate granule cells. Synapses made by mossy fibers exhibit low release probability, resulting in high failure rates at resting discharge frequencies of 0.1 Hz. In recordings from functionally connected pairs of neurons, burst firing of a granule cell increased the probability of glutamate release onto both CA3 pyramidal cells and inhibitory interneurons, such that subsequent low-frequency stimulation evoked biphasic excitatory/inhibitory responses in a CA3 pyramidal cell, an effect lasting for minutes. Analysis of the unitary connections in the circuit revealed that granule cell bursting caused powerful activation of an inhibitory network, thereby transiently suppressing excitatory input to CA3 pyramidal cells. This phenomenon reflects the high incidence of spike-to-spike transmission at granule cell to interneuron synapses, the numerically much greater targeting by mossy fibers of inhibitory interneurons versus principal cells, and the extensively divergent output of interneurons targeting CA3 pyramidal cells. Thus, mossy-fiber input to CA3 pyramidal cells appears to function in three distinct modes: a resting mode, in which synaptic transmission is ineffectual because of high failure rates; a bursting mode, in which excitation predominates; and a postbursting mode, in which inhibitory input to the CA3 pyramidal cells is greatly enhanced. A mechanism allowing the transient recruitment of inhibitory input may be important for controlling network activity in the highly interconnected CA3 pyramidal cell region.
7516662
Synaptic dynamics mediate sensitivity to motion independent of stimulus details
Humans and other animals generally perceive motion independently of the cues that define the moving object. To understand the underlying mechanisms of this generalization of stimulus attributes, we have examined the cellular properties of avian wide-field tectal neurons that are sensitive to a variety of moving stimuli but not to static stationary stimuli. This in vitro study showed phasic signal transfer at the retinotectal synapse and binary dendritic responses to synaptic inputs that interact in a mutually exclusive manner in the postsynaptic tectal neuron. A model of the tectal circuitry predicts that these two cellular properties mediate sensitivity to a wide range of dynamic spatiotemporal stimuli, including moving stimuli, but not to static stationary stimuli in a tectal neuron. The computation that is independent of stimulus detail is initiated by tectal neurons and is completed by rotundal neurons that integrate outputs from multiple tectal neurons in a directionally selective manner.
25288985
Towards a comprehensive catalog of zebrafish behavior 1.0 and beyond.
Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.
32698381
Neuroscience: Towards functional connectomics
To understand the brain, the thousands of synaptic connections made by each of billions of neurons should be mapped and related to neuronal function. First steps towards this formidable goal are now reported. See Articles p.177
 & p.183
 Connectivity forms the basis of functional computations performed by neural circuits, but it is notoriously difficult to follow the complex structural wiring between neurons to the function of individual cells. Now, using a combination of functional imaging and three-dimensional serial electron-microscopic reconstruction at an unprecedented scale, two groups present detailed representations of the connectivity of single cells in the mouse visual system. Davi Bock et al. in Clay Reid's lab investigate connectivity in the primary visual cortex, and find that inhibitory neurons receive input from excitatory cells with widely varying functions, consistent with predictions from recent physiological studies of the mouse cortex. Kevin Briggman, Moritz Helmstaedter and Winfried Denk show that direction-selective ganglion cells receive more synapses from a starburst amacrine cell dendrite if their preferred directions are opposites, suggesting that the directional sensitivity of retinal ganglion cells arises from the asymmetry in their wiring with amacrine cells.
1844177
Tol2: a versatile gene transfer vector in vertebrates
The medaka fish Tol2 element is an autonomous transposon that encodes a fully functional transposase. The transposase protein can catalyze transposition of a transposon construct that has 200 and 150 base pairs of DNA from the left and right ends of the Tol2 sequence, respectively. These sequences contain essential terminal inverted repeats and subterminal sequences. DNA inserts of fairly large sizes (as large as 11 kilobases) can be cloned between these sequences without reducing transpositional activity. The Tol2 transposon system has been shown to be active in all vertebrate cells tested thus far, including zebrafish, Xenopus, chicken, mouse, and human. In this review I describe and discuss how the Tol2 transposon is being applied to transgenic studies in these vertebrates, and possible future applications.
1024120
Synaptic Activity and Activity-Dependent Competition Regulates Axon Arbor Maturation, Growth Arrest, and Territory in the Retinotectal Projection
In the retinotectal projection, synapses guide retinal ganglion cell (RGC) axon arbor growth by promoting branch formation and by selectively stabilizing branches. To ask whether presynaptic function is required for this dual role of synapses, we have suppressed presynaptic function in single RGCs using targeted expression of tetanus toxin light-chain fused to enhanced green fluorescent protein (TeNT-Lc:EGFP). Time-lapse imaging of singly silenced axons as they arborize in the tectum of zebrafish larvae shows that presynaptic function is not required for stabilizing branches or for generating an arbor of appropriate complexity. However, synaptic activity does regulate two distinct aspects of arbor development. First, single silenced axons fail to arrest formation of highly dynamic but short-lived filopodia that are a feature of immature axons. Second, single silenced axons fail to arrest growth of established branches and so occupy significantly larger territories in the tectum than active axons. However, if activity-suppressed axons had neighbors that were also silent, axonal arbors appeared normal in size. A similar reversal in phenotype was observed when single TeNT-Lc:EGFP axons are grown in the presence of the NMDA receptor antagonist MK801 [(+)-5-methyl-10,11- dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate]. Although expansion of arbor territory is prevented when neighbors are silent, formation of transient filopodia is not. These results suggest that synaptic activity by itself regulates filopodia formation regardless of activity in neighboring cells but that the ability to arrest growth and focusing of axonal arbors in the target is an activity-dependent, competitive process.
22304169
Optimized Gal4 genetics for permanent gene expression mapping in zebrafish
Combinatorial genetics for conditional transgene activation allows studying gene function with temporal and tissue specific control like the Gal4-UAS system, which has enabled sophisticated genetic studies in Drosophila. Recently this system was adapted for zebrafish and promising applications have been introduced. Here, we report a systematic optimization of zebrafish Gal4-UAS genetics by establishing an optimized Gal4-activator (KalTA4). We provide quantitative data for KalTA4-mediated transgene activation in dependence of UAS copy numbers to allow for studying dosage effects of transgene expression. Employing a Tol2 transposon-mediated KalTA4 enhancer trap screen biased for central nervous system expression, we present a collection of self-reporting red fluorescent KalTA4 activator strains. These strains reliably transactivate UAS-dependent transgenes and can be rendered homozygous. Furthermore, we have characterized the transactivation kinetics of tissue-specific KalTA4 activation, which led to the development of a self-maintaining effector strain “Kaloop.” This strain relates transient KalTA4 expression during embryogenesis via a KalTA4-mediated autoregulatory mechanism to live adult structures. We demonstrate its use by showing that the secondary octaval nucleus in the adult hindbrain is likely derived from egr2b-expressing cells in rhombomere 5 during stages of early embryogenesis. These data demonstrate prolonged and maintained expression by Kalooping, a technique that can be used for permanent spatiotemporal genetic fate mapping and targeted transgene expression in zebrafish.
27687210
The Psychophysics Toolbox.
The Psychophysics Toolbox is a software package that supports visual psychophysics. Its routines provide an interface between a high-level interpreted language (MATLAB on the Macintosh) and the video display hardware. A set of example programs is included with the Toolbox distribution.
7386775
ScanImage: Flexible software for operating laser scanning microscopes
BackgroundLaser scanning microscopy is a powerful tool for analyzing the structure and function of biological specimens. Although numerous commercial laser scanning microscopes exist, some of the more interesting and challenging applications demand custom design. A major impediment to custom design is the difficulty of building custom data acquisition hardware and writing the complex software required to run the laser scanning microscope.ResultsWe describe a simple, software-based approach to operating a laser scanning microscope without the need for custom data acquisition hardware. Data acquisition and control of laser scanning are achieved through standard data acquisition boards. The entire burden of signal integration and image processing is placed on the CPU of the computer. We quantitate the effectiveness of our data acquisition and signal conditioning algorithm under a variety of conditions. We implement our approach in an open source software package (ScanImage) and describe its functionality.ConclusionsWe present ScanImage, software to run a flexible laser scanning microscope that allows easy custom design.
18772096
The Retinal Projectome Reveals Brain-Area-Specific Visual Representations Generated by Ganglion Cell Diversity
BACKGROUND
Visual information is transmitted to the vertebrate brain exclusively via the axons of retinal ganglion cells (RGCs). The functional diversity of RGCs generates multiple representations of the visual environment that are transmitted to several brain areas. However, in no vertebrate species has a complete wiring diagram of RGC axonal projections been constructed. We employed sparse genetic labeling and in vivo imaging of the larval zebrafish to generate a cellular-resolution map of projections from the retina to the brain.


RESULTS
Our data define 20 stereotyped axonal projection patterns, the majority of which innervate multiple brain areas. Morphometric analysis of pre- and postsynaptic RGC structure revealed more than 50 structural RGC types with unique combinations of dendritic and axonal morphologies, exceeding current estimates of RGC diversity in vertebrates. These single-cell projection mapping data indicate that specific projection patterns are nonuniformly specified in the retina to generate retinotopically biased visual maps throughout the brain. The retinal projectome also successfully predicted a functional subdivision of the pretectum.


CONCLUSIONS
Our data indicate that RGC projection patterns are precisely coordinated to generate brain-area-specific visual representations originating from RGCs with distinct dendritic morphologies and topographic distributions.
14464972
Whole-Brain Activity Maps Reveal Stereotyped, Distributed Networks for Visuomotor Behavior
Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain.
14876211
The First Stage of Cardinal Direction Selectivity Is Localized to the Dendrites of Retinal Ganglion Cells
Inferring the direction of image motion is a fundamental component of visual computation and essential for visually guided behavior. In the retina, the direction of image motion is computed in four cardinal directions, but it is not known at which circuit location along the flow of visual information the cardinal direction selectivity first appears. We recorded the concerted activity of the neuronal circuit elements of single direction-selective (DS) retinal ganglion cells at subcellular resolution by combining GCaMP3-functionalized transsynaptic viral tracing and two-photon imaging. While the visually evoked activity of the dendritic segments of the DS cells were direction selective, direction-selective activity was absent in the axon terminals of bipolar cells. Furthermore, the glutamate input to DS cells, recorded using a genetically encoded glutamate sensor, also lacked direction selectivity. Therefore, the first stage in which extraction of a cardinal motion direction occurs is the dendrites of DS cells.