Neurons In Primary Visual Cortex Research Articles

Brightness illusions drive a neuronal response in the primary visual cortex under top-down modulation

Brightness illusions are a powerful tool in studying vision, yet their neural correlates are poorly understood. Based on a human paradigm, we presented illusory drifting gratings to mice. Primary visual cortex (V1) neurons responded to illusory gratings, matching their direction selectivity for real gratings, and they tracked the spatial phase offset between illusory and real gratings. Illusion responses were delayed compared to real gratings, in line with the theory that processing illusions requires feedback from higher visual areas (HVAs). We provide support for this theory by showing a reduced V1 response to illusions, but not real gratings, following HVAs optogenetic inhibition. Finally, we used the pupil response (PR) as an indirect perceptual report and showed that the mouse PR matches the human PR to perceived luminance changes. Our findings resolve debates over whether V1 neurons are involved in processing illusions and highlight the involvement of feedback from HVAs.

Predicting Single Neuron Responses of the Primary Visual Cortex with Deep Learning Model.

Modeling neuron responses to stimuli can shed light on next-generation technologies such as brain-chip interfaces. Furthermore, high-performing models can serve to help formulate hypotheses and reveal the mechanisms underlying neural responses. Here the state-of-the-art computational model is presented for predicting single neuron responses to natural stimuli in the primary visual cortex (V1) of mice. The algorithm incorporates object positions and assembles multiple models with different train-validation data, resulting in a 15%-30% improvement over the existing models in cross-subject predictions and ranking first in the SENSORIUM 2022 Challenge, which benchmarks methods for neuron-specific prediction based on thousands of images. Importantly, The model reveals evidence that the spatial organizations of V1 are conserved across mice. This model will serve as an important noninvasive tool for understanding and utilizing the response patterns of primary visual cortex neurons.

A power law describes the magnitude of adaptation in neural populations of primary visual cortex

How do neural populations adapt to the time-varying statistics of sensory input? We used two-photon imaging to measure the activity of neurons in mouse primary visual cortex adapted to different sensory environments, each defined by a distinct probability distribution over a stimulus set. We find that two properties of adaptation capture how the population response to a given stimulus, viewed as a vector, changes across environments. First, the ratio between the response magnitudes is a power law of the ratio between the stimulus probabilities. Second, the response direction to a stimulus is largely invariant. These rules could be used to predict how cortical populations adapt to novel, sensory environments. Finally, we show how the power law enables the cortex to preferentially signal unexpected stimuli and to adjust the metabolic cost of its sensory representation to the entropy of the environment.

Joint encoding of stimulus and decision in monkey primary visual cortex.

We investigated whether neurons in monkey primary visual cortex (V1) exhibit mixed selectivity for sensory input and behavioral choice. Parallel multisite spiking activity was recorded from area V1 of awake monkeys performing a delayed match-to-sample task. The monkeys had to make a forced choice decision of whether the test stimulus matched the preceding sample stimulus. The population responses evoked by the test stimulus contained information about both the identity of the stimulus and with some delay but before the onset of the motor response the forthcoming choice. The results of subspace identification analysis indicate that stimulus-specific and decision-related information coexists in separate subspaces of the high-dimensional population activity, and latency considerations suggest that the decision-related information is conveyed by top-down projections.

TrkB receptor-dependent PV neurons regulate visual orientation discrimination in mice

The neurotrophin-tyrosine receptor kinase B (TrkB) signaling pathway plays an important role in regulating the balance of excitation and inhibition in the primary visual cortex (V1). Previous studies have revealed its mechanism of regulating the level of cortical excitability by increasing the efficiency of excitatory transmission, but it has not been elucidated how TrkB receptors regulate the balance of excitation and inhibition through the inhibitory system, which in turn affects visual cortex function. Therefore, the objective of this study was to investigate how the TrkB signaling pathway specifically regulates the most important inhibitory neuron-PV neurons affects the visual cortex function of mice. The expression of TrkB receptor on PV neurons in the V1 region was specifically reduced by the virus, the functional changes of inhibitory and excitatory neurons in the primary visual cortex were recorded by multi-channel electrophysiological in vivo. The orientation discrimination ability of mice was tested by behavioral experiments, and altered orientation discrimination ability of mice was tested by behavioral experiments. The results showed that reduced expression of TrkB receptors on PV inhibitory neurons in primary visual cortex significantly increased the response intensity of excitatory neurons, reduced the orientation discrimination ability of inhibitory and excitatory neurons, and increased the signal-to-noise ratio, but the orientation discrimination ability at the individual level in mice showed a decrease. These results suggest that the TrkB signaling pathway does not modulate the function of PV neurons solely by increasing excitatory transmission targeting PV neurons, and its effect on neuronal signal-to-noise ratio is not due to enhancement of the inhibitory system.

Hierarchical temporal prediction captures motion processing along the visual pathway.

Visual neurons respond selectively to features that become increasingly complex from the eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) neurons prefer moving bars, and those in higher cortical areas favor complex features like moving textures. Previously, we showed that V1 simple cell tuning can be accounted for by a basic model implementing temporal prediction - representing features that predict future sensory input from past input (Singer et al., 2018). Here, we show that hierarchical application of temporal prediction can capture how tuning properties change across at least two levels of the visual system. This suggests that the brain does not efficiently represent all incoming information; instead, it selectively represents sensory inputs that help in predicting the future. When applied hierarchically, temporal prediction extracts time-varying features that depend on increasingly high-level statistics of the sensory input.

Poster Session: Dynamic visual processing in post-saccadic V1 visual responses of the marmoset monkey.

All animals with image-forming eyes sample visual information through a "saccade and fixate" pattern of eye movements (Land and Nilsson, 2012). Here, we investigated how perisaccadic neural responses during free-viewing of natural images relate to the tuning properties of neurons in primary visual cortex (V1). We recorded from V1 in two marmoset monkeys using linear arrays as they freely viewed full-field natural scenes. We found that on average neural responses time-locked to saccade onset exhibited an early suppression followed by a post-saccadic rebound in excitatory activity. To determine whether the latency of these saccade dynamics varied with neural tuning properties we mapped tuning for spatial and temporal frequency, and orientation selectivity. In those trials marmosets free-viewed flashed full-field gratings that varied in spatial frequency and orientation. Among the neurons with significant orientation tuning, we observe a significant correlation between spatial frequency preference and the latency of post-saccadic rebound, with neurons tuned to higher spatial frequencies responding later. These results support the idea that neural responses during the saccade-fixation cycle follow coarse-to-fine distinctions proposed to operate in early visual processing (Burr, 1981; Watt, 1987; Hedge, 2008, Boi et al., 2017).

Invited Session IV: Studies of the visual cortex with sub-millimeter resolution: Imaging the visual brain at high spatiotemporal resolution.

Since the discovery of orientation-selective neurons in the cat primary visual cortex (V1), how the mammalian nervous system computes the orientation of visual stimuli has been a flagship question in neuroscience. With the recent advances in in vivo imaging of neural activity using genetically encoded indicators and two-photon fluorescence microscopy, we can now achieve synapse-resolving functional imaging and kilohertz imaging of membrane voltage in the mouse V1. I will describe our recent advancements in imaging visual processing at high spatiotemporal resolution, as well as two studies on the orientation selectivity of neurons in the mouse visual pathway.

A role for ocular dominance in binocular integration

Neurons in the primate primary visual cortex (V1) combine left- and right-eye information to form a binocular output. Controversy surrounds whether ocular dominance, the preference of these neurons for one eye over the other, is functionally relevant. Here, we demonstrate that ocular dominance impacts gain control during binocular combination. We recorded V1 spiking activity while monkeys passively viewed grating stimuli. Gratings were either presented to one eye (monocular), both eyes with the same contrasts (binocular balanced), or both eyes with different contrasts (binocular imbalanced). We found that contrast placed in a neuron's dominant eye was weighted more strongly than contrast placed in a neuron's non-dominant eye. This asymmetry covaried with neurons' ocular dominance. We then tested whether accounting for ocular dominance within divisive normalization improves the fit to neural data. We found that ocular dominance significantly improved model performance, with interocular normalization providing the best fits. These findings suggest that V1 ocular dominance is relevant for response normalization during binocular stimulation.

Cortical recurrence supports resilience to sensory variance in the primary visual cortex

Our daily endeavors occur in a complex visual environment, whose intrinsic variability challenges the way we integrate information to make decisions. By processing myriads of parallel sensory inputs, our brain is theoretically able to compute the variance of its environment, a cue known to guide our behavior. Yet, the neurobiological and computational basis of such variance computations are still poorly understood. Here, we quantify the dynamics of sensory variance modulations of cat primary visual cortex neurons. We report two archetypal neuronal responses, one of which is resilient to changes in variance and co-encodes the sensory feature and its variance, improving the population encoding of orientation. The existence of these variance-specific responses can be accounted for by a model of intracortical recurrent connectivity. We thus propose that local recurrent circuits process uncertainty as a generic computation, advancing our understanding of how the brain handles naturalistic inputs.

Dynamic Modeling of Spike Count Data With Conway-Maxwell Poisson Variability.

In many areas of the brain, neural spiking activity covaries with features of the external world, such as sensory stimuli or an animal's movement. Experimental findings suggest that the variability of neural activity changes over time and may provide information about the external world beyond the information provided by the average neural activity. To flexibly track time-varying neural response properties, we developed a dynamic model with Conway-Maxwell Poisson (CMP) observations. The CMP distribution can flexibly describe firing patterns that are both under- and overdispersed relative to the Poisson distribution. Here we track parameters of the CMP distribution as they vary over time. Using simulations, we show that a normal approximation can accurately track dynamics in state vectors for both the centering and shape parameters (λ and ν). We then fit our model to neural data from neurons in primary visual cortex, "place cells" in the hippocampus, and a speed-tuned neuron in the anterior pretectal nucleus. We find that this method outperforms previous dynamic models based on the Poisson distribution. The dynamic CMP model provides a flexible framework for tracking time-varying non-Poisson count data and may also have applications beyond neuroscience.

Investigating the Serotonergic Modulation of Orientation Tuning of Neurons in Primary Visual Cortex of Anesthetized Mice

Introduction: Sensory processing is profoundly regulated by brain neuromodulatory systems. One of the main neuromodulators is serotonin which influences higher cognitive functions, such as different aspects of perceptual processing. Accordingly, malfunction in the serotonergic system may lead to visual illusion in psychiatric disorders, such as autism and schizophrenia. This study aims to investigate the serotonergic modulation of visual responses of neurons to stimulus orientation in the primary visual cortex. Methods: Eight-week-old naive mice were anesthetized and a craniotomy was done on the region of interest in the primary visual cortex. Spontaneous and visual-evoked activities of neurons were recorded before and during the electrical stimulation of the dorsal raphe nucleus using in vivo whole-cell patch-clamp recording. The square-wave grating of 12 orientations was presented. The data were analyzed and the Wilcoxon signed-rank test was used to compare the data of two conditions that belong to the same neurons, with or without electrical stimulation. Results: The serotonergic system changed the orientation tuning of nearly 60% of recorded neurons by decreasing the mean firing rate in two independent visual response components, namely gain and baseline response. It also increased the mean firing rate in a small number of neurons (about 20%). Additionally, it left the preferred orientation and sensitivity of neurons unchanged. Conclusion: Serotonergic modulation showed a bidirectional effect. It causes predominately divisive and subtractive decreases in the visual responses of the neurons in the primary visual cortex that can modify the balance between internal and external sensory signals and result in disorders.

Effective and efficient neural networks for spike inference from in vivo calcium imaging

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS2 (effective and efficient neural networks for spike inference from calcium signals) system for spike-rate and spike-event predictions using ΔF/F0 calcium inputs based on a U-Net deep neural network. When testing on a large, ground-truth public database, it consistently outperformed state-of-the-art algorithms in both spike-rate and spike-event predictions with reduced computational load. We further demonstrated that ENS2 can be applied to analyses of orientation selectivity in primary visual cortex neurons. We conclude that it would be a versatile inference system that may benefit diverse neuroscience studies.

Monocular deprivation during the critical period alters neuronal tuning and the composition of visual circuitry.

Abnormal visual experience during a developmental critical period degrades cortical responsiveness. Yet how experience-dependent plasticity alters the response properties of individual neurons and composition of visual circuitry is unclear. Here, we measured with calcium imaging in alert mice how monocular deprivation (MD) during the developmental critical period affects tuning for binocularity, orientation, and spatial frequency for neurons in primary visual cortex. MD of the contralateral eye did not uniformly shift ocular dominance (OD) of neurons towards the fellow ipsilateral eye but reduced the number of monocular contralateral neurons and increased the number of monocular ipsilateral neurons. MD also impaired matching of preferred orientation for binocular neurons and reduced the percentage of neurons responsive at most spatial frequencies for the deprived contralateral eye. Tracking the tuning properties for several hundred neurons before and after MD revealed that the shift in OD is complex and dynamic, with many previously monocular neurons becoming binocular and binocular neurons becoming monocular. Binocular neurons that became monocular were more likely to lose responsiveness to the deprived contralateral eye if they were better matched for orientation prior to deprivation. In addition, the composition of visual circuitry changed as population of neurons more responsive to the deprived eye were exchanged for neurons with tuning properties more similar to the network of responsive neurons altered by MD. Thus, plasticity during the critical period adapts to recent experience by both altering the tuning of responsive neurons and recruiting neurons with matching tuning properties.

Impact of acute visual experience on development of LGN receptive fields in the ferret.

Selectivity for direction of motion is a key feature of primary visual cortical neurons. Visual experience is required for direction selectivity in carnivore and primate visual cortex, but the circuit mechanisms of its formation remain incompletely understood. Here we examined how developing lateral geniculate nucleus (LGN) neurons may contribute to cortical direction selectivity. Using in vivo electrophysiology techniques, we examined LGN receptive field properties of visually naïve female ferrets before and after exposure to 6 hours of motion stimuli in order to assess the effect of acute visual experience on LGN cell development. We found that acute experience with motion stimuli did not significantly affect the weak orientation or direction selectivity of LGN neurons. In addition, we found that neither latency nor sustainedness or transience of LGN neurons significantly changed with acute experience. These results suggest that the direction selectivity that emerges in cortex after acute experience is computed in cortex and cannot be explained by changes in LGN cells.SIGNIFICANCE STATEMENT:The development of typical neural circuitry requires experience-independent and experience-dependent factors. In the visual cortex of carnivores and primates, selectivity for motion arises as a result of experience, but we do not understand whether the major brain area that sits between the retina and the visual cortex - the lateral geniculate nucleus of the thalamus - also participates. Here we found that lateral geniculate neurons do not exhibit changes as a result of several hours of visual experience with moving stimuli, at a time when visual cortical neurons undergo a rapid change. We conclude that lateral geniculate neurons do not participate in this plasticity, and that changes in cortex are likely responsible for the development of direction selectivity in carnivores and primates.

Coherent mapping of position and head direction across auditory and visual cortex.

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.

Weak evidence for neural correlates of task-switching in macaque V1.

A central goal of systems neuroscience is to understand how populations of sensory neurons encode and relay information to the rest of the brain. Three key quantities of interest are 1) how mean neural activity depends on the stimulus (sensitivity), 2) how neural activity (co)varies around the mean (noise correlations), and 3) how predictive these variations are of the subject's behavior (choice probability). Previous empirical work suggests that both choice probability and noise correlations are affected by task training, with decision-related information fed back to sensory areas and aligned to neural sensitivity on a task-by-task basis. We used Utah arrays to record activity from populations of primary visual cortex (V1) neurons from two macaque monkeys that were trained to switch between two coarse orientation-discrimination tasks. Surprisingly, we find no evidence for significant trial-by-trial changes in noise covariance between tasks, nor do we find a consistent relationship between neural sensitivity and choice probability, despite recording from well-tuned task-sensitive neurons, many of which were histologically confirmed to be in supragranular V1, and despite behavioral evidence that the monkeys switched their strategy between tasks. Thus our data at best provide weak support for the hypothesis that trial-by-trial task-switching induces changes to noise correlations and choice probabilities in V1. However, our data agree with a recent finding of a single "choice axis" across tasks. They also raise the intriguing possibility that choice-related signals in early sensory areas are less indicative of task learning per se and instead reflect perceptual learning that occurs in highly overtrained subjects.NEW & NOTEWORTHY Converging evidence suggests that decision processes affect sensory neural activity, and this has informed numerous theories of neural processing. We set out to replicate and extend previous results on decision-related information and noise correlations in V1 of macaque monkeys. However, in our data, we find little evidence for a number of expected effects. Our null results therefore call attention to differences in task training, stimulus design, recording, and analysis techniques between our and prior studies.

Postnatal development of electrophysiological and morphological properties in layer 2/3 and layer 5 pyramidal neurons in the mouse primary visual cortex.

Eye-opening is a critical point for laminar maturation of pyramidal neurons (PNs) in primary visual cortex. Knowing both the intrinsic properties and morphology of PNs from the visual cortex during development is crucial to contextualize the integration of visual inputs at different age stages. Few studies have reported changes in intrinsic excitability in these neurons but were restricted to only one layer or one stage of cortical development. Here, we used in vitro whole-cell patch-clamp to investigate the developmental impact on electrophysiological properties of layer 2/3 and layer 5 PNs in mouse visual cortex. Additionally, we evaluated the morphological changes before and after eye-opening and compared these in adult mice. Overall, we found a decrease in intrinsic excitability in both layers after eye-opening which remained stable between juvenile and adult mice. The basal dendritic length increased in layer 5 neurons, whereas spine density increased in layer 2/3 neurons after eye-opening. These data show increased number of synapses after onset of sensory input paralleled with a reduced excitability, presumably as homeostatic mechanism. Altogether, we provide a database of the properties of PNs in mouse visual cortex by considering the layer- and time-specific changes of these neurons during sensory development.

Vision: Neuronal mechanisms enabling stable perception

Eye movements cause rapid motion of the retinal image, potentially confusable with external motion. A recent study shows that neurons in mouse primary visual cortex distinguish self-generated from external motion by combining sensory input with saccade-related signals from the thalamic pulvinar nucleus.

Pattern Motion Direction Is Encoded in the Population Activity of Macaque Area MT.

Direction selective neurons in macaque primary visual cortex are narrowly tuned for orientation, and are thus afflicted by the aperture problem. At the next stage of motion processing, in the middle temporal (MT) area, some cells appear to solve this problem, responding to the pattern motion direction of plaids. Models have been proposed to account for this computation, but they do not replicate the diversity of responses observed in MT. We recorded from 386 cells in area MT of two male macaques, while presenting a wide range of random-line stimuli and their compositions into noise plaids. As we broadened the range of stimuli used to probe the cells, yielding ever more challenging conditions for extracting pattern motion, the diversity of the responses observed increased, and the fraction of cells that faithfully encoded pattern motion direction shrank. However, we show here that a pattern motion signal is present at the population level. We identified four mechanisms, one never proposed before, that together might account for the observed diversity in single-cell responses. Pattern motion is thus extracted in area MT, but it is encoded across the population, and not in a small subset of pattern neurons.SIGNIFICANCE STATEMENT Some neurons in the middle temporal area of macaques solve the aperture problem, signaling the direction of motion of complex patterns. As the number of pattern types used to probe this mechanism is increased, fewer and fewer cells retain this capability. We show here that different cells fail in different ways, and that simply summing their responses averages away their failures, yielding a clear pattern motion signal. Similar encodings, which unequivocally violate the "neuron as a feature detector" hypothesis that has dominated sensory processing theories for the past 50 years, might apply throughout the brain.