Showing papers on "Receptive field published in 2019"

Selective Kernel Networks

Abstract: In standard Convolutional Neural Networks (CNNs), the receptive fields of artificial neurons in each layer are designed to share the same size. It is well-known in the neuroscience community that the receptive field size of visual cortical neurons are modulated by the stimulus, which has been rarely considered in constructing CNNs. We propose a dynamic selection mechanism in CNNs that allows each neuron to adaptively adjust its receptive field size based on multiple scales of input information. A building block called Selective Kernel (SK) unit is designed, in which multiple branches with different kernel sizes are fused using softmax attention that is guided by the information in these branches. Different attentions on these branches yield different sizes of the effective receptive fields of neurons in the fusion layer. Multiple SK units are stacked to a deep network termed Selective Kernel Networks (SKNets). On the ImageNet and CIFAR benchmarks, we empirically show that SKNet outperforms the existing state-of-the-art architectures with lower model complexity. Detailed analyses show that the neurons in SKNet can capture target objects with different scales, which verifies the capability of neurons for adaptively adjusting their receptive field sizes according to the input. The code and models are available at https://github.com/implus/SKNet.

Selective Kernel Networks

Abstract: In standard Convolutional Neural Networks (CNNs), the receptive fields of artificial neurons in each layer are designed to share the same size. It is well-known in the neuroscience community that the receptive field size of visual cortical neurons are modulated by the stimulus, which has been rarely considered in constructing CNNs. We propose a dynamic selection mechanism in CNNs that allows each neuron to adaptively adjust its receptive field size based on multiple scales of input information. A building block called Selective Kernel (SK) unit is designed, in which multiple branches with different kernel sizes are fused using softmax attention that is guided by the information in these branches. Different attentions on these branches yield different sizes of the effective receptive fields of neurons in the fusion layer. Multiple SK units are stacked to a deep network termed Selective Kernel Networks (SKNets). On the ImageNet and CIFAR benchmarks, we empirically show that SKNet outperforms the existing state-of-the-art architectures with lower model complexity. Detailed analyses show that the neurons in SKNet can capture target objects with different scales, which verifies the capability of neurons for adaptively adjusting their receptive field sizes according to the input. The code and models are available at this https URL.

Sensorimotor experience remaps visual input to a heading-direction network.

Abstract: In the Drosophila brain, ‘compass’ neurons track the orientation of the body and head (the fly’s heading) during navigation 1,2. In the absence of visual cues, the compass neuron network estimates heading by integrating self-movement signals over time3,4. When a visual cue is present, the estimate of the network is more accurate1,3. Visual inputs to compass neurons are thought to originate from inhibitory neurons called R neurons (also known as ring neurons); the receptive fields of R neurons tile visual space5. The axon of each R neuron overlaps with the dendrites of every compass neuron6, raising the question of how visual cues are integrated into the compass. Here, using in vivo whole-cell recordings, we show that a visual cue can evoke synaptic inhibition in compass neurons and that R neurons mediate this inhibition. Each compass neuron is inhibited only by specific visual cue positions, indicating that many potential connections from R neurons onto compass neurons are actually weak or silent. We also show that the pattern of visually evoked inhibition can reorganize over minutes as the fly explores an altered virtual-reality environment. Using ensemble calcium imaging, we demonstrate that this reorganization causes persistent changes in the compass coordinate frame. Taken together, our data suggest a model in which correlated pre- and postsynaptic activity triggers associative long-term synaptic depression of visually evoked inhibition in compass neurons. Our findings provide evidence for the theoretical proposal that associative plasticity of sensory inputs, when combined with attractor dynamics, can reconcile self-movement information with changing external cues to generate a coherent sense of direction7–12. Visual inputs to compass neurons can reorganize over minutes as a fly explores an altered virtual-reality environment.

The M6 cell: A small-field bistratified photosensitive retinal ganglion cell.

Abstract: We have identified a novel, sixth type of intrinsically photosensitive retinal ganglion cell (ipRGC) in the mouse-the M6 cell. Its spiny, highly branched dendritic arbor is bistratified, with dendrites restricted to the inner and outer margins of the inner plexiform layer, co-stratifying with the processes of other ipRGC types. We show that M6 cells are by far the most abundant ganglion cell type labeled in adult pigmented Cdh3-GFP BAC transgenic mice. A few M5 ipRGCs are also labeled, but no other RGC types were encountered. Several distinct subnuclei in the geniculate complex and the pretectum contain labeled retinofugal axons in the Cdh3-GFP mouse. These are presumably the principle central targets of M6 cells (as well as M5 cells). Projections from M6 cells to the dorsal lateral geniculate nucleus were confirmed by retrograde tracing, suggesting they contribute to pattern vision. M6 cells have low levels of melanopsin expression and relatively weak melanopsin-dependent light responses. They also exhibit strong synaptically driven light responses. Their dendritic fields are the smallest and most abundantly branched of all ipRGCs. They have small receptive fields and strong antagonistic surrounds. Despite deploying dendrites partly in the OFF sublamina, M6 cells appear to be driven exclusively by the ON pathway, suggesting that their OFF arbor, like those of certain other ipRGCs, may receive ectopic input from passing ON bipolar cells axons in the OFF sublayer.

Neuromodulatory control of localized dendritic spiking in critical period cortex

Abstract: Sensory experience in early postnatal life, during so-called critical periods, restructures neural circuitry to enhance information processing1. Why the cortex is susceptible to sensory instruction in early life and why this susceptibility wanes with age are unclear. Here we define a developmentally restricted engagement of inhibitory circuitry that shapes localized dendritic activity and is needed for vision to drive the emergence of binocular visual responses in the mouse primary visual cortex. We find that at the peak of the critical period for binocular plasticity, acetylcholine released from the basal forebrain during periods of heightened arousal directly excites somatostatin (SST)-expressing interneurons. Their inhibition of pyramidal cell dendrites and of fast-spiking, parvalbumin-expressing interneurons enhances branch-specific dendritic responses and somatic spike rates within pyramidal cells. By adulthood, this cholinergic sensitivity is lost, and compartmentalized dendritic responses are absent but can be re-instated by optogenetic activation of SST cells. Conversely, suppressing SST cell activity during the critical period prevents the normal development of binocular receptive fields by impairing the maturation of ipsilateral eye inputs. This transient cholinergic modulation of SST cells, therefore, seems to orchestrate two features of neural plasticity-somatic disinhibition and compartmentalized dendritic spiking. Loss of this modulation may contribute to critical period closure.

A Sensorimotor Pathway via Higher-Order Thalamus.

Abstract: We now know that sensory processing in cortex occurs not only via direct communication between primary to secondary areas, but also via their parallel cortico-thalamo-cortical (i.e., trans-thalamic) pathways. Both corticocortical and trans-thalamic pathways mainly signal through glutamatergic class 1 (driver) synapses, which have robust and efficient synaptic dynamics suited for the transfer of information such as receptive field properties, suggesting the importance of class 1 synapses in feedforward, hierarchical processing. However, such a parallel arrangement has only been identified in sensory cortical areas: visual, somatosensory, and auditory. To test the generality of trans-thalamic pathways, we sought to establish its presence beyond purely sensory cortices to determine whether there is a trans-thalamic pathway parallel to the established primary somatosensory (S1) to primary motor (M1) pathway. We used trans-synaptic viral tracing, optogenetics in slice preparations, and bouton size analysis in the mouse (both sexes) to document that a circuit exists from layer 5 of S1 through the posterior medial nucleus of the thalamus to M1 with glutamatergic class 1 properties. This represents a hitherto unknown, robust sensorimotor linkage and suggests that the arrangement of parallel direct and trans-thalamic corticocortical circuits may be present as a general feature of cortical functioning.SIGNIFICANCE STATEMENT During sensory processing, feedforward pathways carry information such as receptive field properties via glutamatergic class 1 synapses, which have robust and efficient synaptic dynamics. As expected, class 1 synapses subserve the feedforward projection from primary to secondary sensory cortex, but also a route through specific higher-order thalamic nuclei, creating a parallel feedforward trans-thalamic pathway. We now extend the concept of cortical areas being connected via parallel, direct, and trans-thalamic circuits from purely sensory cortices to a sensorimotor cortical circuit (i.e., primary sensory cortex to primary motor cortex). This suggests a generalized arrangement for corticocortical communication.

Egocentric boundary vector tuning of the retrosplenial cortex

Abstract: The retrosplenial cortex is reciprocally connected with a majority of structures implicated in spatial cognition and damage to the region itself produces numerous spatial impairments. However, in many ways the retrosplenial cortex remains understudied. Here, we sought to characterize spatial correlates of neurons within the region during free exploration in two-dimensional environments. We report that a large percentage of retrosplenial cortex neurons have spatial receptive fields that are active when environmental boundaries are positioned at a specific orientation and distance relative to the animal itself. We demonstrate that this vector-based location signal is encoded in egocentric coordinates, localized to the dysgranular retrosplenial sub-region, independent of self-motion, and context invariant. Further, we identify a sub-population of neurons with this response property that are synchronized with the hippocampal theta oscillation. Accordingly, the current work identifies a robust egocentric spatial code in retrosplenial cortex that can facilitate spatial coordinate system transformations and support the anchoring, generation, and utilization of allocentric representations.

Neural Coding for Shape and Texture in Macaque Area V4.

Abstract: The distinct visual sensations of shape and texture have been studied separately in cortex; therefore, it remains unknown whether separate neuronal populations encode each of these properties or one population carries a joint encoding. We directly compared shape and texture selectivity of individual V4 neurons in awake macaques (1 male, 1 female) and found that V4 neurons lie along a continuum from strong tuning for boundary curvature of shapes to strong tuning for perceptual dimensions of texture. Among neurons tuned to both attributes, tuning for shape and texture were largely separable, with the latter delayed by ∼30 ms. We also found that shape stimuli typically evoked stronger, more selective responses than did texture patches, regardless of whether the latter were contained within or extended beyond the receptive field. These results suggest that there are separate specializations in mid-level cortical processing for visual attributes of shape and texture.SIGNIFICANCE STATEMENT Object recognition depends on our ability to see both the shape of the boundaries of objects and properties of their surfaces. However, neuroscientists have never before examined how shape and texture are linked together in mid-level visual cortex. In this study, we used systematically designed sets of simple shapes and texture patches to probe the responses of individual neurons in the primate visual cortex. Our results provide the first evidence that some cortical neurons specialize in processing shape whereas others specialize in processing textures. Most neurons lie between the ends of this continuum, and in these neurons we find that shape and texture encoding are largely independent.

Nonlinear Processing of Shape Information in Rat Lateral Extrastriate Cortex.

Abstract: In rodents, the progression of extrastriate areas located laterally to primary visual cortex (V1) has been assigned to a putative object-processing pathway (homologous to the primate ventral stream), based on anatomical considerations. Recently, we found functional support for such attribution (Tafazoli et al., 2017), by showing that this cortical progression is specialized for coding object identity despite view changes, the hallmark property of a ventral-like pathway. Here, we sought to clarify what computations are at the base of such specialization. To this aim, we performed multielectrode recordings from V1 and laterolateral area LL (at the apex of the putative ventral-like hierarchy) of male adult rats, during the presentation of drifting gratings and noise movies. We found that the extent to which neuronal responses were entrained to the phase of the gratings sharply dropped from V1 to LL, along with the quality of the receptive fields inferred through reverse correlation. Concomitantly, the tendency of neurons to respond to different oriented gratings increased, whereas the sharpness of orientation tuning declined. Critically, these trends are consistent with the nonlinear summation of visual inputs that is expected to take place along the ventral stream, according to the predictions of hierarchical models of ventral computations and a meta-analysis of the monkey literature. This suggests an intriguing homology between the mechanisms responsible for building up shape selectivity and transformation tolerance in the visual cortex of primates and rodents, reasserting the potential of the latter as models to investigate ventral stream functions at the circuitry level. SIGNIFICANCE STATEMENT Despite the growing popularity of rodents as models of visual functions, it remains unclear whether their visual cortex contains specialized modules for processing shape information. To addresses this question, we compared how neuronal tuning evolves from rat primary visual cortex (V1) to a downstream visual cortical region (area LL) that previous work has implicated in shape processing. In our experiments, LL neurons displayed a stronger tendency to respond to drifting gratings with different orientations while maintaining a sustained response across the whole duration of the drift cycle. These trends match the increased complexity of pattern selectivity and the augmented tolerance to stimulus translation found in monkey visual temporal cortex, thus revealing a homology between shape processing in rodents and primates.

The role of prefrontal cortex in the control of feature attention in area V4.

Abstract: When searching for an object in a cluttered scene, we can use our memory of the target object features to guide our search, and the responses of neurons in multiple cortical visual areas are enhanced when their receptive field contains a stimulus sharing target object features. Here we tested the role of the ventral prearcuate region (VPA) of prefrontal cortex in the control of feature attention in cortical visual area V4. VPA was unilaterally inactivated in monkeys performing a free-viewing visual search for a target stimulus in an array of stimuli, impairing monkeys' ability to find the target in the array in the affected hemifield, but leaving intact their ability to make saccades to targets presented alone. Simultaneous recordings in V4 revealed that the effects of feature attention on V4 responses were eliminated or greatly reduced while leaving the effects of spatial attention on responses intact. Altogether, the results suggest that feedback from VPA modulates processing in visual cortex during attention to object features.

A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs

Abstract: The vertebrate visual system is hierarchically organized to process visual information in successive stages. Neural representations vary drastically across the first stages of visual processing: at the output of the retina, ganglion cell receptive fields (RFs) exhibit a clear antagonistic center-surround structure, whereas in the primary visual cortex (V1), typical RFs are sharply tuned to a precise orientation. There is currently no unified theory explaining these differences in representations across layers. Here, using a deep convolutional neural network trained on image recognition as a model of the visual system, we show that such differences in representation can emerge as a direct consequence of different neural resource constraints on the retinal and cortical networks, and for the first time we find a single model from which both geometries spontaneously emerge at the appropriate stages of visual processing. The key constraint is a reduced number of neurons at the retinal output, consistent with the anatomy of the optic nerve as a stringent bottleneck. Second, we find that, for simple downstream cortical networks, visual representations at the retinal output emerge as nonlinear and lossy feature detectors, whereas they emerge as linear and faithful encoders of the visual scene for more complex cortical networks. This result predicts that the retinas of small vertebrates (e.g. salamander, frog) should perform sophisticated nonlinear computations, extracting features directly relevant to behavior, whereas retinas of large animals such as primates should mostly encode the visual scene linearly and respond to a much broader range of stimuli. These predictions could reconcile the two seemingly incompatible views of the retina as either performing feature extraction or efficient coding of natural scenes, by suggesting that all vertebrates lie on a spectrum between these two objectives, depending on the degree of neural resources allocated to their visual system.

Audio-visual experience strengthens multisensory assemblies in adult mouse visual cortex

Abstract: We experience the world through multiple senses simultaneously. To better understand mechanisms of multisensory processing we ask whether inputs from two senses (auditory and visual) can interact and drive plasticity in neural-circuits of the primary visual cortex (V1). Using genetically-encoded voltage and calcium indicators, we find coincident audio-visual experience modifies both the supra and subthreshold response properties of neurons in L2/3 of mouse V1. Specifically, we find that after audio-visual pairing, a subset of multimodal neurons develops enhanced auditory responses to the paired auditory stimulus. This cross-modal plasticity persists over days and is reflected in the strengthening of small functional networks of L2/3 neurons. We find V1 processes coincident auditory and visual events by strengthening functional associations between feature specific assemblies of multimodal neurons during bouts of sensory driven co-activity, leaving a trace of multisensory experience in the cortical network. Sensory stimuli usually arrive simultaneously but the neural-circuit mechanisms that combine multiple streams of sensory information are incompletely understood. The authors here show that visual-auditory pairing drives plasticity in multi-modal neuron networks within the mouse visual cortex.

Estimating average single-neuron visual receptive field sizes by fMRI

Abstract: The noninvasive estimation of neuronal receptive field (RF) properties in vivo allows a detailed understanding of brain organization as well as its plasticity by longitudinal following of potential changes. Visual RFs measured invasively by electrophysiology in animal models have traditionally provided a great extent of our current knowledge about the visual brain and its disorders. Voxel-based estimates of population RF (pRF) by functional magnetic resonance imaging (fMRI) in humans revolutionized the field and have been used extensively in numerous studies. However, current methods cannot estimate single-neuron RF sizes as they reflect large populations of neurons with individual RF scatter. Here, we introduce an approach to estimate RF size using spatial frequency selectivity to checkerboard patterns. This method allowed us to obtain noninvasive, average single-neuron RF estimates over a large portion of human early visual cortex. These estimates were significantly smaller compared with prior pRF methods. Furthermore, fMRI and electrophysiology experiments in nonhuman primates demonstrated an exceptionally good match, validating the approach.

Cortical Balance Between ON and OFF Visual Responses Is Modulated by the Spatial Properties of the Visual Stimulus.

Abstract: The primary visual cortex of carnivores and primates is dominated by the OFF visual pathway and responds more strongly to dark than light stimuli. Here, we demonstrate that this cortical OFF dominance is modulated by the size and spatial frequency of the stimulus in awake primates and we uncover a main neuronal mechanism underlying this modulation. We show that large grating patterns with low spatial frequencies drive five times more OFF-dominated than ON-dominated neurons, but this pronounced cortical OFF dominance is strongly reduced when the grating size decreases and the spatial frequency increases, as when the stimulus moves away from the observer. We demonstrate that the reduction in cortical OFF dominance is not caused by a selective reduction of visual responses in OFF-dominated neurons but by a change in the ON/OFF response balance of neurons with diverse receptive field properties that can be ON or OFF dominated, simple, or complex. We conclude that cortical OFF dominance is continuously adjusted by a neuronal mechanism that modulates ON/OFF response balance in multiple cortical neurons when the spatial properties of the visual stimulus change with viewing distance and/or optical blur.

Excitatory neurons are more disinhibited than inhibitory neurons by chloride dysregulation in the spinal dorsal horn.

Abstract: Neuropathic pain is a debilitating condition caused by the abnormal processing of somatosensory input. Synaptic inhibition in the spinal dorsal horn plays a key role in that processing. Mechanical allodynia - the misperception of light touch as painful - occurs when inhibition is compromised. Disinhibition is due primarily to chloride dysregulation caused by hypofunction of the potassium-chloride co-transporter KCC2. Here we show, in rats, that excitatory neurons are disproportionately affected. This is not because chloride is differentially dysregulated in excitatory and inhibitory neurons, but, rather, because excitatory neurons rely more heavily on inhibition to counterbalance strong excitation. Receptive fields in both cell types have a center-surround organization but disinhibition unmasks more excitatory input to excitatory neurons. Differences in intrinsic excitability also affect how chloride dysregulation affects spiking. These results deepen understanding of how excitation and inhibition are normally balanced in the spinal dorsal horn, and how their imbalance disrupts somatosensory processing.

Connectomic Identification and Three-Dimensional Color Tuning of S-OFF Midget Ganglion Cells in the Primate Retina.

Abstract: In the trichromatic primate retina, the "midget" retinal ganglion cell is the classical substrate for red-green color signaling, with a circuitry that enables antagonistic responses between long (L)- and medium (M)-wavelength-sensitive cone inputs. Previous physiological studies showed that some OFF midget ganglion cells may receive sparse input from short (S)-wavelength-sensitive cones, but the effect of S-cone inputs on the chromatic tuning properties of such cells has not been explored. Moreover, anatomical evidence for a synaptic pathway from S cones to OFF midget ganglion cells through OFF midget bipolar cells remains ambiguous. In this study, we address both questions for the macaque monkey retina. First, we used serial block-face electron microscopy to show that every S cone in the parafoveal retina synapses principally with a single OFF midget bipolar cell, which in turn forms a private-line connection with an OFF midget ganglion cell. Second, we used patch electrophysiology to characterize the chromatic tuning of OFF midget ganglion cells in the near peripheral retina that receive combined input from L, M, and S cones. These "S-OFF" midget cells have a characteristic S-cone spatial signature, but demonstrate heterogeneous color properties due to the variable strength of L, M, and S cone input across the receptive field. Together, these findings strongly support the hypothesis that the OFF midget pathway is the major conduit for S-OFF signals in primate retina and redefines the pathway as a chromatically complex substrate that encodes color signals beyond the classically recognized L versus M and S versus L+M cardinal mechanisms.SIGNIFICANCE STATEMENT The first step of color processing in the visual pathway of primates occurs when signals from short (S)-, middle (M)-, and long (L)-wavelength-sensitive cone types interact antagonistically within the retinal circuitry to create color-opponent pathways. The midget (L versus M or "red-green") and small bistratified (S vs L+M, or "blue-yellow") ganglion cell pathways appear to provide the physiological origin of the cardinal axes of human color vision. Here we confirm the presence of an additional S-OFF midget circuit in the macaque monkey fovea with scanning block-face electron microscopy and show physiologically that a subpopulation of S-OFF midget cells combine S, L, and M cone inputs along noncardinal directions of color space, expanding the retinal role in color coding.

A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs

Abstract: The visual system is hierarchically organized to process visual information in successive stages. Neural representations vary drastically across the first stages of visual processing: at the output of the retina, ganglion cell receptive fields (RFs) exhibit a clear antagonistic center-surround structure, whereas in the primary visual cortex, typical RFs are sharply tuned to a precise orientation. There is currently no unified theory explaining these differences in representations across layers. Here, using a deep convolutional neural network trained on image recognition as a model of the visual system, we show that such differences in representation can emerge as a direct consequence of different neural resource constraints on the retinal and cortical networks, and we find a single model from which both geometries spontaneously emerge at the appropriate stages of visual processing. The key constraint is a reduced number of neurons at the retinal output, consistent with the anatomy of the optic nerve as a stringent bottleneck. Second, we find that, for simple cortical networks, visual representations at the retinal output emerge as nonlinear and lossy feature detectors, whereas they emerge as linear and faithful encoders of the visual scene for more complex cortices. This result predicts that the retinas of small vertebrates should perform sophisticated nonlinear computations, extracting features directly relevant to behavior, whereas retinas of large animals such as primates should mostly encode the visual scene linearly and respond to a much broader range of stimuli. These predictions could reconcile the two seemingly incompatible views of the retina as either performing feature extraction or efficient coding of natural scenes, by suggesting that all vertebrates lie on a spectrum between these two objectives, depending on the degree of neural resources allocated to their visual system.

Reconciling Color Vision Models With Midget Ganglion Cell Receptive Fields.

Abstract: Midget retinal ganglion cells make up the majority of foveal ganglion cells in the primate retina. The receptive fields of midget ganglion cells exhibit both spectral and spatial opponency and are implicated in both color and achromatic form vision, yet the exact mechanisms linking their responses to visual perception remain unclear. Efforts to develop color vision models that accurately predict all the features of human color and form vision based on midget ganglion cells provide a case study connecting experimental and theoretical neuroscience, drawing on diverse research areas such as anatomy, physiology, psychophysics, and computer vision. Recent technological advances have allowed researchers to test some predictions of color vision models in new and precise ways, producing results that challenge traditional views. Here, we review the progress in developing models of color-coding receptive fields that are consistent with human psychophysics, the biology of the primate visual system and the response properties of midget retinal ganglion cells.

Neurons of the inferior olive respond to broad classes of sensory input while subject to homeostatic control.

Abstract: KEY POINTS: Purkinje cells in the cerebellum integrate input from sensory organs with that from premotor centres. Purkinje cells use a variety of sensory inputs relaying information from the environment to modify motor control. Here we asked to what extent the climbing fibre inputs to Purkinje cells signal mono- or multi-sensory information, and to what extent this signalling is subject to recent history of activity. We show that individual climbing fibres convey multiple types of sensory information, together providing a rich mosaic projection pattern of sensory signals across the cerebellar cortex. Moreover, firing probability of climbing fibres following sensory stimulation strongly depends on the recent history of activity, showing a tendency to homeostatic dampening. ABSTRACT: Cerebellar Purkinje cells integrate sensory information with motor efference copies to adapt movements to behavioural and environmental requirements. They produce complex spikes that are triggered by the activity of climbing fibres originating in neurons of the inferior olive. These complex spikes can shape the onset, amplitude and direction of movements and the adaptation of such movements to sensory feedback. Clusters of nearby inferior olive neurons project to parasagittally aligned stripes of Purkinje cells, referred to as 'microzones'. It is currently unclear to what extent individual Purkinje cells within a single microzone integrate climbing fibre inputs from multiple sources of different sensory origins, and to what extent sensory-evoked climbing fibre responses depend on the strength and recent history of activation. Here we imaged complex spike responses in cerebellar lobule crus 1 to various types of sensory stimulation in awake mice. We find that different sensory modalities and receptive fields have a mild, but consistent, tendency to converge on individual Purkinje cells, with climbing fibres showing some degree of input-specificity. Purkinje cells encoding the same stimulus show increased events with coherent complex spike firing and tend to lie close together. Moreover, whereas complex spike firing is only mildly affected by variations in stimulus strength, it strongly depends on the recent history of climbing fibre activity. Our data point towards a mechanism in the olivo-cerebellar system that regulates complex spike firing during mono- or multisensory stimulation around a relatively low set-point, highlighting an integrative coding scheme of complex spike firing under homeostatic control. This article is protected by copyright. All rights reserved.

Retinal direction selectivity in the absence of asymmetric starburst amacrine cell responses.

Abstract: In the mammalian retina, direction-selectivity is thought to originate in the dendrites of GABAergic/cholinergic starburst amacrine cells, where it is first observed. However, here we demonstrate that direction selectivity in downstream ganglion cells remains remarkably unaffected when starburst dendrites are rendered non-directional, using a novel strategy combining a conditional GABAA α2 receptor knockout mouse with optogenetics. We show that temporal asymmetries between excitation/inhibition, arising from the differential connectivity patterns of starburst cholinergic and GABAergic synapses to ganglion cells, form the basis for a parallel mechanism generating direction selectivity. We further demonstrate that these distinct mechanisms work in a coordinated way to refine direction selectivity as the stimulus crosses the ganglion cell’s receptive field. Thus, precise spatiotemporal patterns of inhibition and excitation that determine directional responses in ganglion cells are shaped by two ‘core’ mechanisms, both arising from distinct specializations of the starburst network.

Superficial Layers Suppress the Deep Layers to Fine-tune Cortical Coding.

Abstract: The descending microcircuit from layer 2/3 (L2/3) to layer 5 (L5) is one of the strongest excitatory pathways in the cortex, presumably forming a core component of its feedforward hierarchy. To date, however, no experiments have selectively tested the impact of L2/3 activity on L5 during active sensation. We used optogenetic, cell-type-specific manipulation of L2/3 neurons in the barrel cortex of actively sensing mice (of either sex) to elucidate the significance of this pathway to sensory coding in L5. Contrary to standard models, activating L2/3 predominantly suppressed spontaneous activity in L5, whereas deactivating L2/3 mainly facilitated touch responses in L5. Somatostatin interneurons are likely important to this suppression because their optogenetic deactivation significantly altered the functional impact of L2/3 onto L5. The net effect of L2/3 was to enhance the stimulus selectivity and expand the range of L5 output. These data imply that the core cortical pathway increases the selectivity and expands the range of cortical output through feedforward inhibition. SIGNIFICANCE STATEMENT The primary sensory cortex contains six distinct layers that interact to form the basis of our perception. While rudimentary patterns of connectivity between the layers have been outlined quite extensively in vitro, functional relationships in vivo, particularly during active sensation, remain poorly understood. We used cell-type-specific optogenetics to test the functional relationship between layer 2/3 and layer 5. Surprisingly, we discovered that L2/3 primarily suppresses cortical output from L5. The recruitment of somatostatin-positive interneurons is likely fundamental to this relationship. The net effect of this translaminar suppression is to enhance the selectivity and expand the range of receptive fields, therefore potentially sharpening the perception of space.

Integration of cortical population signals for visual perception.

Abstract: Visual stimuli evoke heterogeneous responses across nearby neural populations. These signals must be locally integrated to contribute to perception, but the principles underlying this process are unknown. Here, we exploit the systematic organization of orientation preference in macaque primary visual cortex (V1) and perform causal manipulations to examine the limits of signal integration. Optogenetic stimulation and visual stimuli are used to simultaneously drive two neural populations with overlapping receptive fields. We report that optogenetic stimulation raises firing rates uniformly across conditions, but improves the detection of visual stimuli only when activating cells that are preferentially-tuned to the visual stimulus. Further, we show that changes in correlated variability are exclusively present when the optogenetically and visually-activated populations are functionally-proximal, suggesting that correlation changes represent a hallmark of signal integration. Our results demonstrate that information from functionally-proximal neurons is pooled for perception, but functionally-distal signals remain independent. Primary visual cortical neurons exhibit diverse responses to visual stimuli yet how these signals are integrated during visual perception is not well understood. Here, the authors show that optogenetic stimulation of neurons situated near the visually‐driven population leads to improved orientation detection in monkeys through changes in correlated variability.

The statistics of how natural images drive the responses of neurons.

Abstract: To model the responses of neurons in the early visual system, at least three basic components are required: a receptive field, a normalization term, and a specification of encoding noise. Here, we examine how the receptive field, the normalization factor, and the encoding noise affect the drive to model-neuron responses when stimulated with natural images. We show that when these components are modeled appropriately, the response drives elicited by natural stimuli are Gaussian-distributed and scale invariant, and very nearly maximize the sensitivity (d') for natural-image discrimination. We discuss the statistical models of natural stimuli that can account for these response statistics, and we show how some commonly used modeling practices may distort these results. Finally, we show that normalization can equalize important properties of neural response across different stimulus types. Specifically, narrowband (stimulus- and feature-specific) normalization causes model neurons to yield Gaussian response-drive statistics when stimulated with natural stimuli, 1/f noise stimuli, and white-noise stimuli. The current work makes recommendations for best practices and lays a foundation, grounded in the response statistics to natural stimuli, upon which to build principled models of more complex visual tasks.