Primate Primary Visual Cortex Research Articles

Where Do Core Thalamocortical Axons Terminate in Mammalian Neocortex When There Is No Cytoarchitecturally Distinct Layer 4?

Although the mammalian cerebral cortex is most often described as a hexalaminar structure, there are cortical areas (primary motor cortex) and species (elephants, cetaceans, and hippopotami), where a cytoarchitecturally indistinct, or absent, layer 4 is noted. Thalamocortical projections from the core, or first order, thalamic system terminate primarily in layers 4/inner 3. We explored the termination sites of core thalamocortical projections in cortical areas and in species where there is no cytoarchitecturally distinct layer 4 using the immunolocalization of vesicular glutamate transporter 2, a known marker of core thalamocortical axon terminals, in 31 mammal species spanning the eutherian radiation. Several variations from the canonical cortical column outline of layer 4 and core thalamocortical inputs were noted. In shrews/microchiropterans, layer 4 was present, but many core thalamocortical projections terminated in layer 1 in addition to layers 4 and inner 3. In primate primary visual cortex, the sublaminated layer 4 was associated with a specialized core thalamocortical projection pattern. In primate primary motor cortex, no cytoarchitecturally distinct layer 4 was evident and the core thalamocortical projections terminated throughout layer 3. In the African elephant, cetaceans, and river hippopotamus, no cytoarchitecturally distinct layer 4 was observed and core thalamocortical projections terminated primarily in inner layer 3 and less densely in outer layer 3. These findings are contextualized in terms of cortical processing, perception, and the evolutionary trajectory leading to an indistinct or absent cortical layer 4.

Nonuniform and pathway-specific laminar processing of spatial frequencies in the primary visual cortex of primates

The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

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.

Cascaded normalizations for spatial integration in the primary visual cortex of primates.

Spatial integration of visual information is an important function in the brain. However, neural computation for spatial integration in the visual cortex remains unclear. In this study, we recorded laminar responses in V1 of awake monkeys driven by visual stimuli with grating patches and annuli of different sizes. We find three important response properties related to spatial integration that are significantly different between input and output layers: neurons in output layers have stronger surround suppression, smaller receptive field (RF), and higher sensitivity to grating annuli partially covering their RFs. These interlaminar differences canbe explained by a descriptive model composed of two global divisions (normalization) and a local subtraction. Our results suggest suppressions with cascaded normalizations (CNs) are essential for spatial integration and laminar processing in the visual cortex. Interestingly, the features of spatial integration in convolutional neural networks, especially in lower layers, are different from our findings in V1.

Gamma oscillations in primate primary visual cortex are severely attenuated by small stimulus discontinuities.

Gamma oscillations (30 to 80 Hz) have been hypothesized to play an important role in feature binding, based on the observation that continuous long bars induce stronger gamma in the visual cortex than bars with a small gap. Recently, many studies have shown that natural images, which have discontinuities in several low-level features, do not induce strong gamma oscillations, questioning their role in feature binding. However, the effect of different discontinuities on gamma has not been well studied. To address this, we recorded spikes and local field potential from 2 monkeys while they were shown gratings with discontinuities in 4 attributes: space, orientation, phase, or contrast. We found that while these discontinuities only had a modest effect on spiking activity, gamma power drastically reduced in all cases, suggesting that gamma could be a resonant phenomenon. An excitatory-inhibitory population model with stimulus-tuned recurrent inputs showed such resonant properties. Therefore, gamma could be a signature of excitation-inhibition balance, which gets disrupted due to discontinuities.

Binocular Integration in the Primate Primary Visual Cortex

binocular vision, binocular fusion, binocular combination, LGN, V1.

Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis.

Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.

Color and orientation are jointly coded and spatially organized in primate primary visual cortex.

Previous studies support the textbook model that shape and color are extracted by distinct neurons in primate primary visual cortex (V1). However, rigorous testing of this model requires sampling a larger stimulus space than previously possible. We used stable GCaMP6f expression and two-photon calcium imaging to probe a very large spatial and chromatic visual stimulus space and map functional microarchitecture of thousands of neurons with single-cell resolution. Notable proportions of V1 neurons strongly preferred equiluminant color over achromatic stimuli and were also orientation selective, indicating that orientation and color in V1 are mutually processed by overlapping circuits. Single neurons could precisely and unambiguously code for both color and orientation. Further analyses revealed systematic spatial relationships between color tuning, orientation selectivity, and cytochrome oxidase histology.

Rethinking primary visual cortex function

Neuroscience Understanding how color is coded in the brain is central to vision research. The presently dominant model suggests that color and orientation are separately extracted in the primate primary visual cortex. These characteristics are thought to be represented by neurons located in different cortical columns that project separately to higher visual areas for further processing. Working with macaques, Garg et al. recorded from thousands of neurons using two-photon calcium imaging with single-neuron resolution. Nearly half of sampled hue-selective neurons responded more strongly to equiluminant colored stimuli than to full-contrast achromatic stimuli. A majority of strongly color-preferring neurons were also orientation selective. Processing of orientation and color is thus combined at the earliest stages of visual processing, which challenges existing models. Science , this issue p. [1275][1] [1]: /lookup/doi/10.1126/science.aaw5868

A Stable Visual World in Primate Primary Visual Cortex

Humans and other primates rely on eye movements to explore visual scenes and to track moving objects. As a result, the image that is projected onto the retina-and propagated throughout the visual cortical hierarchy-is almost constantly changing and makes little sense without taking into account the momentary direction of gaze. How is this achieved in the visual system? Here, we show that in primary visual cortex (V1), the earliest stage of cortical vision, neural representations carry an embedded "eye tracker" that signals the direction of gaze associated with each image. Using chronically implanted multi-electrode arrays, we recorded the activity of neurons in area V1 of macaque monkeys during tasks requiring fast (exploratory) and slow (pursuit) eye movements. Neurons were stimulated with flickering, full-field luminance noise at all times. As in previous studies, we observed neurons that were sensitive to gaze direction during fixation, despite comparable stimulation of their receptive fields. We trained a decoder to translate neural activity into metric estimates of gaze direction. This decoded signal tracked the eye accurately not only during fixation but also during fast and slow eye movements. After a fast eye movement, the eye-position signal arrived in V1 at approximately the same time at which the new visual information arrived from the retina. Using simulations, we show that this V1 eye-position signal could be used to take into account the sensory consequences of eye movements and map the fleeting positions of objects on the retina onto their stable position in the world.

Distinct Laminar Processing of Local and Global Context in Primate Primary Visual Cortex

Visual perception is affected by spatial context. In visual cortex, neuronal responses to stimuli inside the receptive field (RF) are suppressed by stimuli in the RF surround. To understand the circuits and cortical layers processing spatial context, we simultaneously recorded across all layers of macaque primary visual cortex while presenting stimuli at increasing distances from the recorded cells' RF. We find that near versus far-surround stimuli activate distinct layers, thus revealing unique laminar contributions to the processing of local and global spatial context. Stimuli in the near-surround evoke the earliest subthreshold responses in superficial and upper-deep layers, and earliest suppression of spiking responses in superficial layers. Conversely, far-surround stimuli evoke the earliest subthreshold responses in feedback-recipient layer 1 and lower-deep layers, and earliest suppression of spiking responses almost simultaneously in all layers, except 4C, where suppression emerges last. Our results suggest distinct circuits for local and global signal integration.

Top-down feedback controls spatial summation and response amplitude in primate visual cortex

Sensory information travels along feedforward connections through a hierarchy of cortical areas, which, in turn, send feedback connections to lower-order areas. Feedback has been implicated in attention, expectation, and sensory context, but the mechanisms underlying these diverse feedback functions are unknown. Using specific optogenetic inactivation of feedback connections from the secondary visual area (V2), we show how feedback affects neural responses in the primate primary visual cortex (V1). Reducing feedback activity increases V1 cells’ receptive field (RF) size, decreases their responses to stimuli confined to the RF, and increases their responses to stimuli extending into the proximal surround, therefore reducing surround suppression. Moreover, stronger reduction of V2 feedback activity leads to progressive increase in RF size and decrease in response amplitude, an effect predicted by a recurrent network model. Our results indicate that feedback modulates RF size, surround suppression and response amplitude, similar to the modulatory effects of visual spatial attention.

Long-wavelength (reddish) hues induce unusually large gamma oscillations in the primate primary visual cortex

Gamma oscillations (∼30-80 Hz) are a prominent signature of electrophysiological signals, with a purported role in natural vision. Previous studies in the primary visual cortex (area V1) have shown that achromatic gratings or gabor stimuli generate salient gamma oscillations, whose strength and frequency depend on stimulus properties such as their size, contrast, and orientation. Surprisingly, although natural images are rarely achromatic, the effect of chromatic input on gamma has not been thoroughly investigated. Recording from primate V1, we show that gamma oscillations of extremely high magnitude (peak increase of ∼300-fold in some cases), far exceeding the gamma generated by optimally tuned achromatic gratings, are induced in the local field potentials by full-field color stimuli of different hues. Furthermore, gamma oscillations are sensitive to the hue of the chromatic input, with the strongest oscillations for long-wavelength (reddish) hues and another, smaller gamma response peak for hues in the short-wavelength (bluish) range, which lie approximately on the two cardinal chromatic response axes of the upstream lateral geniculate nucleus neurons. These oscillations depended critically on the purity of the hue, decreasing with hue desaturation, but remained robust for pure hue stimuli even at reduced luminance. Importantly, the magnitude of gamma oscillations was highly correlated with positive L-M cone contrast produced by the stimuli, suggesting that gamma could be a marker of the specific mechanisms underlying this computation. These findings provide insights into the generation of gamma oscillations, as well as the processing of color along the visual pathway.

Local Circuits of V1 Layer 4B Neurons Projecting to V2 Thick Stripes Define Distinct Cell Classes and Avoid Cytochrome Oxidase Blobs.

Conventional diagrams of primate primary visual cortex (V1) depict neuronal connections within and between different V1 layers, but lack information about the cells' downstream targets. This information is critical to understanding how local processing in V1 relates to downstream processing. We have identified the local circuits of a population of cells in V1 layer (L)4B that project to area V2. These cells' local circuits differ from classical descriptions of L4B circuits in both the laminar and functional compartments targeted by their axons, and identify two neuron classes. Our results demonstrate that both local intra-V1 and extrinsic V1-to-V2 connections of L4B neurons preserve CO-stream segregation, suggesting that across-stream integration occurs downstream of V1, and that output targets dictate local V1 circuitry.

Functional implications of orientation maps in primary visual cortex.

Stimulus orientation in the primary visual cortex of primates and carnivores is mapped as iso-orientation domains radiating from pinwheel centres, where orientation preferences of neighbouring cells change circularly. Whether this orientation map has a function is currently debated, because many mammals, such as rodents, do not have such maps. Here we show that two fundamental properties of visual cortical responses, contrast saturation and cross-orientation suppression, are stronger within cat iso-orientation domains than at pinwheel centres. These differences develop when excitation (not normalization) from neighbouring oriented neurons is applied to different cortical orientation domains and then balanced by inhibition from un-oriented neurons. The functions of the pinwheel mosaic emerge from these local intra-cortical computations: Narrower tuning, greater cross-orientation suppression and higher contrast gain of iso-orientation cells facilitate extraction of object contours from images, whereas broader tuning, greater linearity and less suppression of pinwheel cells generate selectivity for surface patterns and textures.

Spatial spread of local field potential is band-pass in the primary visual cortex.

Local field potential (LFP) is a valuable tool in understanding brain function and in brain machine-interfacing applications. However, there is no consensus on the spatial extent of the cortex that contributes to the LFP (its "spatial spread"), with different studies reporting values between a few hundred micrometers and several millimeters. Furthermore, the dependency of the spatial spread on frequency, which could reflect properties of the network architecture and extracellular medium, is not well studied, with theory and models predicting either "all-pass" (frequency-independent) or "low-pass" behavior. Surprisingly, we found the LFP spread to be "band-pass" in the primate primary visual cortex, with the greatest spread in the high-gamma range (60-150 Hz). This was accompanied by an increase in phase coherency across neighboring sites in the same frequency range, consistent with the findings of a recent model that reconciles previous studies by suggesting that spatial spread depends on neuronal correlations.

Dynamic Signal Tracking in a Simple V1 Spiking Model.

This work is part of an effort to understand the neural basis for our visual system's ability, or failure, to accurately track moving visual signals. We consider here a ring model of spiking neurons, intended as a simplified computational model of a single hypercolumn of the primary visual cortex of primates. Signals that consist of edges with time-varying orientations localized in space are considered. Our model is calibrated to produce spontaneous and driven firing rates roughly consistent with experiments, and our two main findings, for which we offer dynamical explanation on the level of neuronal interactions, are the following. First, we have documented consistent transient overshoots in signal perception following signal switches due to emergent interactions of the E- and I-populations. Second, for continuously moving signals, we have found that accuracy is considerably lower at reversals of orientation than when continuing in the same direction (as when the signal is a rotating bar). To measure performance, we use two metrics, called fidelity and reliability, to compare signals reconstructed by the system to the ones presented and assess trial-to-trial variability. We propose that the same population mechanisms responsible for orientation selectivity also impose constraints on dynamic signal tracking that manifest in perception failures consistent with psychophysical observations.

Relating functional connectivity in V1 neural circuits and 3D natural scenes using Boltzmann machines

Bayesian theory has provided a compelling conceptualization for perceptual inference in the brain. Central to Bayesian inference is the notion of statistical priors. To understand the neural mechanisms of Bayesian inference, we need to understand the neural representation of statistical regularities in the natural environment. In this paper, we investigated empirically how statistical regularities in natural 3D scenes are represented in the functional connectivity of disparity-tuned neurons in the primary visual cortex of primates. We applied a Boltzmann machine model to learn from 3D natural scenes, and found that the units in the model exhibited cooperative and competitive interactions, forming a “disparity association field”, analogous to the contour association field. The cooperative and competitive interactions in the disparity association field are consistent with constraints of computational models for stereo matching. In addition, we simulated neurophysiological experiments on the model, and found the results to be consistent with neurophysiological data in terms of the functional connectivity measurements between disparity-tuned neurons in the macaque primary visual cortex. These findings demonstrate that there is a relationship between the functional connectivity observed in the visual cortex and the statistics of natural scenes. They also suggest that the Boltzmann machine can be a viable model for conceptualizing computations in the visual cortex and, as such, can be used to predict neural circuits in the visual cortex from natural scene statistics.

Ongoing Alpha Activity in V1 Regulates Visually Driven Spiking Responses.

The interlaminar connections in the primate primary visual cortex (V1) are well described, as is the presence of ongoing alpha-range (7-14 Hz) fluctuations in this area. Less well understood is how these interlaminar connections and ongoing fluctuations contribute to the regulation of visual spiking responses. Here, we investigate the relationship between alpha fluctuations and spiking responses to visual stimuli across cortical layers. Using laminar probes in macaque V1, we show that neural firing couples with the phase of alpha fluctuations, and that magnitude of this coupling is particularly pronounced during visual stimulation. The strongest modulation of spiking activity was observed in layers 2/3. Alpha-spike coupling and current source density analysis pointed to an infragranular origin of the alpha fluctuations. Taken together, these results indicate that ongoing infragranular alpha-range fluctuations in V1 play a role in regulating columnar visual activity.

Director Field Model of the Primary Visual Cortex for Contour Detection

We aim to build the simplest possible model capable of detecting long, noisy contours in a cluttered visual scene. For this, we model the neural dynamics in the primate primary visual cortex in terms of a continuous director field that describes the average rate and the average orientational preference of active neurons at a particular point in the cortex. We then use a linear-nonlinear dynamical model with long range connectivity patterns to enforce long-range statistical context present in the analyzed images. The resulting model has substantially fewer degrees of freedom than traditional models, and yet it can distinguish large contiguous objects from the background clutter by suppressing the clutter and by filling-in occluded elements of object contours. This results in high-precision, high-recall detection of large objects in cluttered scenes. Parenthetically, our model has a direct correspondence with the Landau - de Gennes theory of nematic liquid crystal in two dimensions.