Neurons In Primary Visual Cortex Research Articles

Fear: It's All in Your Line of Sight.

The brain circuits that create our sense of fear rely on ancient 'hard-wired' components of the limbic system,but also use sensory processing to determine what we become afraid of. A new study shows that,when viewing of simple oriented line stimuli is coupled with aversive experiences, neurons in primaryvisual cortex rapidly alter their responses in a manner that indicates the line stimuli become a source of fear.

Contribution of apical and basal dendrites to orientation encoding in mouse V1 L2/3 pyramidal neurons

Pyramidal neurons integrate synaptic inputs from basal and apical dendrites to generate stimulus-specific responses. It has been proposed that feed-forward inputs to basal dendrites drive a neuron’s stimulus preference, while feedback inputs to apical dendrites sharpen selectivity. However, how a neuron’s dendritic domains relate to its functional selectivity has not been demonstrated experimentally. We performed 2-photon dendritic micro-dissection on layer-2/3 pyramidal neurons in mouse primary visual cortex. We found that removing the apical dendritic tuft did not alter orientation-tuning. Furthermore, orientation-tuning curves were remarkably robust to the removal of basal dendrites: ablation of 2 basal dendrites was needed to cause a small shift in orientation preference, without significantly altering tuning width. Computational modeling corroborated our results and put limits on how orientation preferences among basal dendrites differ in order to reproduce the post-ablation data. In conclusion, neuronal orientation-tuning appears remarkably robust to loss of dendritic input.

Distinct Waking States for Strong Evoked Responses in Primary Visual Cortex and Optimal Visual Detection Performance.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multiunit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during high arousal with locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior.SIGNIFICANCE STATEMENT Cortical sensory processing strongly depends on arousal. In the mouse visual system, locomotion (associated with high arousal) has previously been shown to enhance the sensory responses of neurons in primary visual cortex (V1). Yet, arousal fluctuates on a moment-to-moment basis, even during quiescent periods. The characteristics of V1 sensory processing across the continuum of arousal are unclear. Furthermore, the arousal level corresponding to optimal visual detection performance is unknown. We show that the magnitude and reliability of sensory-evoked V1 responses are monotonic increasing functions of arousal, and largest during locomotion. Visual detection behavior, however, is suboptimal during high arousal with locomotion, and usually best during intermediate arousal. Our study provides a more complete picture of the dependence of V1 sensory processing on arousal.

Network Analysis of Murine Cortical Dynamics Implicates Untuned Neurons in Visual Stimulus Coding

Unbiased and dense sampling of large populations of layer 2/3 pyramidal neurons in mouse primary visual cortex (V1) reveals two functional sub-populations: neurons tuned and untuned to drifting gratings. Whether functional interactions between these two groups contribute to the representation of visual stimuli is unclear. To examine these interactions, we summarize the population partial pairwise correlation structure as a directed and weighted graph. We find that tuned and untuned neurons have distinct topological properties, with untuned neurons occupying central positions in functional networks. Implementation of a decoder that utilizes the topology of these functional networks yields accurate decoding of visual stimuli. We further show that decoding performance degrades comparably following manipulations of either tuned or untuned neurons. Our results demonstrate that untuned neurons are an integral component of V1 functional networks and suggest that network interactions contain information about the stimulus that is accessible to downstream elements.

The geometry of masking in neural populations

The normalization model provides an elegant account of contextual modulation in individual neurons of primary visual cortex. Understanding the implications of normalization at the population level is hindered by the heterogeneity of cortical neurons, which differ in the composition of their normalization pools and semi-saturation constants. Here we introduce a geometric approach to investigate contextual modulation in neural populations and study how the representation of stimulus orientation is transformed by the presence of a mask. We find that population responses can be embedded in a low-dimensional space and that an affine transform can account for the effects of masking. The geometric analysis further reveals a link between changes in discriminability and bias induced by the mask. We propose the geometric approach can yield new insights into the image processing computations taking place in early visual cortex at the population level while coping with the heterogeneity of single cell behavior.

Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics.

When probed with complex stimuli that extend beyond their classical receptive field, neurons in primary visual cortex display complex and non-linear response characteristics. Sparse coding models reproduce some of the observed contextual effects, but still fail to provide a satisfactory explanation in terms of realistic neural structures and cortical mechanisms, since the connection scheme they propose consists only of interactions among neurons with overlapping input fields. Here we propose an extended generative model for visual scenes that includes spatial dependencies among different features. We derive a neurophysiologically realistic inference scheme under the constraint that neurons have direct access only to local image information. The scheme can be interpreted as a network in primary visual cortex where two neural populations are organized in different layers within orientation hypercolumns that are connected by local, short-range and long-range recurrent interactions. When trained with natural images, the model predicts a connectivity structure linking neurons with similar orientation preferences matching the typical patterns found for long-ranging horizontal axons and feedback projections in visual cortex. Subjected to contextual stimuli typically used in empirical studies, our model replicates several hallmark effects of contextual processing and predicts characteristic differences for surround modulation between the two model populations. In summary, our model provides a novel framework for contextual processing in the visual system proposing a well-defined functional role for horizontal axons and feedback projections.

Synergy in Cortical Networks

A dot in this text can simultaneously stimulate thousands of neurons in primary visual cortex, a response that may seem unnecessarily redundant. Contrary to such a view, in this issue of Neuron, Nigam etal. (2019) demonstrate that these co-activated neurons generate abundant synergistic interactions that help to decode the stimulus.

Altered functional interactions between neurons in primary visual cortex of macaque monkeys with experimental amblyopia.

Amblyopia, a disorder in which vision through one of the eyes is degraded, arises because of defective processing of information by the visual system. Amblyopia often develops in humans after early misalignment of the eyes (strabismus) and can be simulated in macaque monkeys by artificially inducing strabismus. In such amblyopic animals, single-unit responses in primary visual cortex (V1) are appreciably reduced when evoked by the amblyopic eye compared with the other (fellow) eye. However, this degradation in single V1 neuron responsivity is not commensurate with the marked losses in visual sensitivity and resolution measured behaviorally. Here we explored the idea that changes in patterns of coordinated activity across populations of V1 neurons may contribute to degraded visual representations in amblyopia, potentially making it more difficult to read out evoked activity to support perceptual decisions. We studied the visually evoked activity of V1 neuronal populations in three macaques (Macaca nemestrina) with strabismic amblyopia and in one control animal. Activity driven through the amblyopic eye was diminished, and these responses also showed more interneuronal correlation at all stimulus contrasts than responses driven through the fellow eye or responses in the control animal. A decoding analysis showed that responses driven through the amblyopic eye carried less visual information than other responses. Our results suggest that part of the reduced visual capacity of amblyopes may be due to changes in the patterns of functional interaction among neurons in V1.NEW & NOTEWORTHY Previous work on the neurophysiological basis of amblyopia has largely focused on relating behavioral deficits to changes in visual processing by single neurons in visual cortex. In this study, we recorded simultaneously from populations of primary visual cortical (V1) neurons in macaques with amblyopia. We found changes in the strength and pattern of shared response variability between neurons. These changes in neuronal interactions could impair the visual representations of V1 populations driven by the amblyopic eye.

Strategic deployment of feature-based attentional gain in primate visual cortex

Attending to visual stimuli enhances the gain of those neurons in primate visual cortex that preferentially respond to the matching locations and features (on-target gain). Although this is well suited to enhance the neuronal representation of attended stimuli, it is nonoptimal under difficult discrimination conditions, as in the presence of similar distractors. In such cases, directing attention to neighboring neuronal populations (off-target gain) has been shown to be the most efficient strategy, but although such a strategic deployment of attention has been shown behaviorally, its underlying neural mechanisms are unknown. Here, we investigated how attention affects the population responses of neurons in the middle temporal (MT) visual area of rhesus monkeys to bidirectional movement inside the neurons’ receptive field (RF). The monkeys were trained to focus their attention onto the fixation spot or to detect a direction or speed change in one of the motion directions (the “target”), ignoring the distractor motion. Population activity profiles were determined by systematically varying the patterns’ directions while maintaining a constant angle between them. As expected, the response profiles show a peak for each of the 2 motion directions. Switching spatial attention from the fixation spot into the RF enhanced the peak representing the attended stimulus and suppressed the distractor representation. Importantly, the population data show a direction-dependent attentional modulation that does not peak at the target feature but rather along the slopes of the activity profile representing the target direction. Our results show that attentional gains are strategically deployed to optimize the discriminability of target stimuli, in line with an optimal gain mechanism proposed by Navalpakkam and Itti.

Rapid and active stabilization of visual cortical firing rates across light–dark transitions

The dynamics of neuronal firing during natural vision are poorly understood. Surprisingly, mean firing rates of neurons in primary visual cortex (V1) of freely behaving rodents are similar during prolonged periods of light and darkness, but it is unknown whether this reflects a slow adaptation to changes in natural visual input or insensitivity to rapid changes in visual drive. Here, we use chronic electrophysiology in freely behaving rats to follow individual V1 neurons across many dark-light (D-L) and light-dark (L-D) transitions. We show that, even on rapid timescales (1 s to 10 min), neuronal activity was only weakly modulated by transitions that coincided with the expected 12-/12-h L-D cycle. In contrast, a larger subset of V1 neurons consistently responded to unexpected L-D and D-L transitions, and disruption of the regular L-D cycle with 60 h of complete darkness induced a robust increase in V1 firing on reintroduction of visual input. Thus, V1 neurons fire at similar rates in the presence or absence of natural stimuli, and significant changes in activity arise only transiently in response to unexpected changes in the visual environment. Furthermore, although mean rates were similar in light and darkness, pairwise correlations were significantly stronger during natural vision, suggesting that information about natural scenes in V1 may be more strongly reflected in correlations than individual firing rates. Together, our findings show that V1 firing rates are rapidly and actively stabilized during expected changes in visual input and are remarkably stable at both short and long timescales.

A model for the origin and development of visual orientation selectivity.

Orientation selectivity is a key property of primary visual cortex that contributes, downstream, to object recognition. The origin of orientation selectivity, however, has been debated for decades. It is known that on- and off-centre subcortical pathways converge onto single neurons in primary visual cortex, and that the spatial offset between these pathways gives rise to orientation selectivity. On- and off-centre pathways are intermingled, however, so it is unclear how their inputs to cortex come to be spatially segregated. We here describe a model in which the segregation occurs through Hebbian strengthening and weakening of geniculocortical synapses during the development of the visual system. Our findings include the following. 1. Neighbouring on- and off-inputs to cortex largely cancelled each other at the start of development. At each receptive field location, the Hebbian process increased the strength of one input sign at the expense of the other sign, producing a spatial segregation of on- and off-inputs. 2. The resulting orientation selectivity was precise in that the bandwidths of the orientation tuning functions fell within empirical estimates. 3. The model produced maps of preferred orientation–complete with iso-orientation domains and pinwheels–similar to those found in real cortex. 4. These maps did not originate in cortical processes, but from clustering of off-centre subcortical pathways and the relative location of neighbouring on-centre clusters. We conclude that a model with intermingled on- and off-pathways shaped by Hebbian synaptic plasticity can explain both the origin and development of orientation selectivity.

Visual cortex neurons phase-lock selectively to subsets of LFP oscillations.

It is generally thought that apart from receptive field differences, such as preferred orientation and spatial frequency selectivity, primary visual cortex neurons are functionally similar to each other. However, the genetic diversity of cortical neurons plus the existence of inputs additional to those required to explain known receptive field properties might suggest otherwise. Here we report the existence of desynchronized states in anesthetized cat area 17 lasting up to 45 min, characterized by variable narrow-band local field potential (LFP) oscillations in the range 2-100 Hz and the absence of a synchronized 1/f frequency spectrum. During these periods, spontaneously active neurons phase-locked to variable subsets of LFP oscillations. Individual neurons often ignored frequencies that others phase-locked to. We suggest that these desynchronized periods may correspond to REM sleep-like episodes occurring under anesthesia. Frequency-selective codes may be used for signaling during these periods. Hence frequency-selective combination and frequency-labeled pathways may represent a previously unsuspected dimension of cortical organization. NEW & NOTEWORTHY We investigated spontaneous neuronal firing during periods of desynchronized local field potential (LFP) activity, resembling REM sleep, in anesthetized cats. During these periods, neurons synchronized their spikes to specific phases of multiple LFP frequency components, with some neurons ignoring frequencies that others were synchronized to. Some neurons fired at phase alignments of frequency pairs, thereby acting as phase coincidence detectors. These results suggest that internal brain signaling may use frequency combination codes to generate temporally structured spike trains.

Locomotion-dependent remapping of distributed cortical networks.

The interactions between neocortical areas are fluid and state-dependent, but how individual neurons couple to cortex-wide network dynamics remains poorly understood. We correlated the spiking of neurons in primary visual (V1) and retrosplenial (RSP) cortex to activity across dorsal cortex, recorded simultaneously by widefield calcium imaging. Neurons were correlated with distinct and reproducible patterns of activity across the cortical surface; while some fired predominantly with their local area, others coupled to activity in distal areas. The extent of distal coupling was predicted by how strongly neurons correlated with the local network. Changes in brain state triggered by locomotion strengthened affiliations of V1 neurons with higher visual and motor areas, while strengthening distal affiliations of RSP neurons with sensory cortices. Thus, the diverse coupling of individual neurons to cortex-wide activity patterns is restructured by running in an area-specific manner, resulting in a shift in the mode of cortical processing during locomotion.

Emergence of higher-level neuron properties using a hierarchical statistical distribution model

Essential to visual tasks such as object recognition is the formation of effective representations that generalize from specific instances of visual input. Neurons in primary visual cortex are typically hypothesized to efficiently encode image structures such as edge and textures from natural scenes. Here this paper proposed a novel hierarchical statistical distribution model to generalize higher-level neuron properties and encode distributed regularities that characterize local image regions. Two layers of our hierarchical model are presented to extract spiking activities of excitatory neurons decorrelated by inhibitory neurons and to construct the statistical patterns of input data, respectively. Trained on whitened natural images, parameters including neural connecting weights and distribution coding weights are estimated by their corresponding learning rules. To prove the feasibility and effectiveness of our model, several experiments on natural images are conducted. Adapting our model to natural scenes yields a distributed representation for higher-order statistical regularities. Comparison results provide insight into higher-level neurons which encode more abstract and invariant properties.

Differences in neurotropism and neurotoxicity among retrograde viral tracers

BackgroundNeurotropic virus-based tracers have been extensively applied in mapping and manipulation of neural circuits. However, their neurotropic and neurotoxic properties remain to be fully characterized.MethodsThrough neural circuit tracing, we systematically compared the neurotropism discrepancy among different multi-trans-synaptic and mono-synaptic retrograde viral tracers including pseudorabies virus (PRV), rabies virus (RV), and the newly engineered retro adeno-associated virus (rAAV2-retro) tracers. The (single-cell) RNA sequencing analysis was utilized for seeking possible attribution to neurotropism discrepancy and comparing cell toxicity caused by viral infection between glycoprotein-deleted RV (RV-∆G) and rAAV2-retro. Viral toxicity induced microglia activation and neuronal protein change were evaluated by immunohistochemistry.ResultsMulti-trans-synaptic retrograde viral tracers, PRV and RV, exhibit differential neurotropism when they were used for central neural circuit tracing from popliteal lymph nodes. Mono-synaptic retrograde tracers, including RV-∆G and rAAV2-retro, displayed discrepant neurotropic property, when they were applied to trace the inputs of lateral hypothalamic area and medial preoptic nucleus. rAAV2-retro demonstrated preference in cerebral cortex, whereas RV-∆G prefers to label basal ganglia and hypothalamus. Remarkably, we detected a distinct preference for specific cortical layer of rAAV2-retro in layer 5 and RV-∆G in layer 6 when they were injected into dorsal lateral geniculate nucleus to label corticothalamic neurons in primary visual cortex. Complementation of TVA receptor gene in RV-resistant neurons enabled EnvA-pseudotyped RV infection, supporting receptors attribution to viral neurotropism. Furthermore, both RV-∆G and rAAV2-retro exerted neurotoxic influence at the injection sites and retrogradely labeled sites, while the changes were more profound for RV-∆G infection. Finally, we demonstrated a proof-of-concept strategy for more comprehensive high-order circuit tracing of a specific target nucleus by combining rAAV2-retro, RV, and rAAV tracers.ConclusionsDifferent multi-trans-synaptic and mono-synaptic retrograde viral tracers exhibited discrepant neurotropism within certain brain regions, even cortical layer preference. More neurotoxicity was observed under RV-∆G infection as compared with rAAV2-retro. By combining rAAV2-retro, RV, and rAAV tracers, high-order circuit tracing can be achieved. Our findings provide important reference for appropriate application of viral tracers to delineate the landscape and dissect the function of neural network.

Sound Induces Change in Orientation Preference of V1 Neurons: Audio-Visual Cross-Influence

In the cortex, demarcated unimodal sensory regions often respond to unforeseen sensory stimuli and exhibit plasticity. The goal of the current investigation was to test evoked responses of primary visual cortex (V1) neurons when an adapting auditory stimulus is applied in isolation. Using extracellular recordings in anesthetized cats, we demonstrate that, unlike the prevailing observation of only slight modulations in the firing rates of the neurons, sound imposition in isolation entirely shifted the peaks of orientation tuning curves of neurons in both supra- and infragranular layers of V1. Our results suggest that neurons specific to either layer dynamically integrate features of sound and modify the organization of the orientation map of V1. Intriguingly, these experiments present novel findings that the mere presentation of a prolonged auditory stimulus may drastically recalibrate the tuning properties of the visual neurons and highlight the phenomenal neuroplasticity of V1 neurons.

Internal Gain Modulations, But Not Changes in Stimulus Contrast, Preserve the Neural Code.

Neurons in primary visual cortex are strongly modulated both by stimulus contrast and by fluctuations of internal inputs. An important question is whether the population code is preserved under these conditions. Changes in stimulus contrast are thought to leave the population code invariant, whereas the effect of internal gain modulations remains unknown. To address these questions we studied how the direction-of-motion of oriented gratings is encoded in layer 2/3 primary visual cortex of mouse (with C57BL/6 background, of either sex). We found that, because contrast gain responses across cells are heterogeneous, a change in contrast alters the information distribution profile across cells leading to a violation of contrast invariance. Remarkably, internal input fluctuations that cause commensurate firing rate modulations at the single-cell level result in more homogeneous gain responses, respecting population code invariance. These observations argue that the brain strives to maintain the stability of the neural code in the face of fluctuating internal inputs.SIGNIFICANCE STATEMENT Neuronal responses are modulated both by stimulus contrast and by the spontaneous fluctuation of internal inputs. It is not well understood how these different types of input impact the population code. Specifically, it is important to understand whether the neural code stays invariant in the face of significant internal input modulations. Here, we show that changes in stimulus contrast lead to different optimal population codes, whereas spontaneous internal input fluctuations leave the population code invariant. This is because spontaneous internal input fluctuations modulate the gain of neuronal responses more homogeneously across cells compared to changes in stimulus contrast.

Layer 3 Dynamically Coordinates Columnar Activity According to Spatial Context.

To reduce statistical redundancy of natural inputs and increase the sparseness of coding, neurons in primary visual cortex (V1) show tuning for stimulus size and surround suppression. This integration of spatial information is a fundamental, context-dependent neural operation involving extensive neural circuits that span across all cortical layers of a V1 column, and reflects both feedforward and feedback processing. However, how spatial integration is dynamically coordinated across cortical layers remains poorly understood. We recorded single- and multiunit activity and local field potentials across V1 layers of awake mice (both sexes) while they viewed stimuli of varying size and used dynamic Bayesian model comparisons to identify when laminar activity and interlaminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, where suppression is established within ∼10 ms after response onset, and receptive fields dynamically sharpen while suppression strength increases. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for connections from L3 targeting L5 and L1. Together, the results shed light on the different functional roles of cortical layers in spatial integration and on how L3 dynamically coordinates activity across a cortical column depending on spatial context.SIGNIFICANCE STATEMENT Neurons in primary visual cortex (V1) show tuning for stimulus size, where responses to stimuli exceeding the receptive field can be suppressed (surround suppression). We demonstrate that functional connectivity between V1 layers can also have a surround-suppressed profile. A particularly prominent role seems to have layer 3, the functional connections to layers 5 and 1 of which are strongest for stimuli of optimal size and decreased for large stimuli. Our results therefore point toward a key role of layer 3 in coordinating activity across the cortical column according to spatial context.

Segregated Subnetworks of Intracortical Projection Neurons in Primary Visual Cortex

The rules by which neurons in neocortex choose their synaptic partners are not fully understood. In sensory cortex, intermingled neurons encode different attributes of sensory inputs and relay them to different long-range targets. While neurons with similar responses to sensory stimuli make connections preferentially, the relationship between synaptic connectivity within an area and long-range projection target remains unclear. We examined the local connectivity and visual responses of primary visual cortex neurons projecting to anterolateral (AL) and posteromedial (PM) higher visual areas in mice. Although the response properties of layer 2/3 neurons projecting to different targets were often similar, they avoided making connections with each other. Thus, projection target, in addition to response similarity, constrains local synaptic connectivity of AL and PM projection neurons. We propose that reduced crosstalk between different populations of projection neurons permits independent function of these output channels.

Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex.

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, we have begun a pipeline project using multipatch electrophysiology, supplemented with two-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse primary visual cortex (V1) and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here, we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell classes and layers we sampled, and that most mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons, however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.