Multiple Visual Cortical Areas Research Articles

Hue and orientation pinwheels in macaque area V4.

Area V4 is an intermediate-level area of the macaque visual cortical hierarchy that serves key functions in visual processing by integrating inputs from lower areas such as V1 and V2 and providing feedforward inputs to many higher cortical areas. Previous V4 imaging studies have focused on differential responses to color, orientation, disparity, and motion stimuli, but many details of the spatial organization of significant hue and orientation tuning have not been fully described. We used support vector machine (SVM) decoding of intrinsic cortical single-condition responses to generate high-resolution maps of hue and orientation tuning and to describe the organization of hue and orientation pinwheels in V4. Like V1 and V2, V4 contains maps of orientation that are organized as pinwheels. V4 also contains maps of hue that are organized as pinwheels, whose circular organization more closely represents the perception of hue than is observed in antecedent cortical areas. Unlike V1, where orientation is continuously mapped across the surface, V4 hue and orientation pinwheels are organized in limited numbers of pinwheel sequences. The organization of these sequences and the distance between pinwheels may provide insight into the functional organization of V4. Regions significantly tuned for hue occupy roughly four times that of the orientation, are largely separated from each other, and overlap by roughly 5%. This spatial organization is largely consistent with segregated inputs arising from V2 thin and interstripes. This modular organization of V4 suggests that further integration of color and shape might occur in higher areas in inferotemporal cortical.NEW & NOTEWORTHY The representation of hue and orientation in macaque monkey area V4 was determined by intrinsic cortical imaging of responses to isoluminant hues and achromatic grating stimuli. Vector summation of support vector machine (SVM) decoded single-condition responses was used to generate hue and orientation maps that, like V1 orientation maps, were both characterized by distinct pinwheel patterns. These data suggest that pinwheels are an important structure to represent different stimulus features across multiple visual cortical areas.

Developmental refinement of visual callosal inputs to ferret area 17.

Corticocortical connections link visual cortical areas in both the ipsilateral and contralateral hemispheres. We studied the postnatal refinement of callosal connections linking multiple cortical areas with ferret area 17 during the period from just before eye opening (4weeks) to 10weeks of age. We aimed to determine (1) whether callosal projections from multiple visual cortical areas to area 17 refine with a similar rate and (2) whether the refinement of callosal projections parallels that of intrahemispheric cortical circuits. We injected the bidirectional tracer CTb into area 17, and mapped the areal and laminar distribution of labeled cells in visual areas of the contralateral hemisphere. Like intrahemispheric projections, callosal inputs to area 17 before eye opening are dominated by Suprasylvian area Ssy (with lesser and comparable input from areas 17, 18, 19, and 21), but within 2 weeks of eye opening are jointly dominated by area 18 and Ssy inputs; however, there are fewer labeled cells in the contralateral hemisphere. Unlike intrahemispheric projections, there is no laminar reorganization of callosal inputs; in all visual areas and at all ages studied, the greatest proportion of callosal projections arises from the infragranular layers. Also, unlike intrahemispheric projections, the peak density of callosal cells in each area projecting to area 17 declines more modestly. These results reveal important similarities and differences in the postnatal reorganization of inter- and intrahemispheric projections to area 17.

A Visual Encoding Model Based on Contrastive Self-Supervised Learning for Human Brain Activity along the Ventral Visual Stream.

Visual encoding models are important computational models for understanding how information is processed along the visual stream. Many improved visual encoding models have been developed from the perspective of the model architecture and the learning objective, but these are limited to the supervised learning method. From the view of unsupervised learning mechanisms, this paper utilized a pre-trained neural network to construct a visual encoding model based on contrastive self-supervised learning for the ventral visual stream measured by functional magnetic resonance imaging (fMRI). We first extracted features using the ResNet50 model pre-trained in contrastive self-supervised learning (ResNet50-CSL model), trained a linear regression model for each voxel, and finally calculated the prediction accuracy of different voxels. Compared with the ResNet50 model pre-trained in a supervised classification task, the ResNet50-CSL model achieved an equal or even relatively better encoding performance in multiple visual cortical areas. Moreover, the ResNet50-CSL model performs hierarchical representation of input visual stimuli, which is similar to the human visual cortex in its hierarchical information processing. Our experimental results suggest that the encoding model based on contrastive self-supervised learning is a strong computational model to compete with supervised models, and contrastive self-supervised learning proves an effective learning method to extract human brain-like representations.

Aligning one’s sights: The pulvinar provides context for visual information processing

The pulvinar (lateral posterior [LP]), like other higher-order thalamic nuclei, receives input from-and sends output to-multiple neocortical structures. In this issue of Neuron, Blot etal. (2021) demonstrate that LP integrates multimodal inputs to put visual information in context.

Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis.

Neuronal morphology is characterized by salient features such as complex axonal and dendritic arbors. In the mammalian brain, variations in dendritic morphology among cell classes, brain regions, and animal species are thought to underlie known differences in neuronal function. In this work, we obtained a large dataset from http://neuromorpho.org/ comprising layer III pyramidal cells in different cortical areas of the ventral visual pathway (V1, V2, V4, TEO, and TE) of the macaque monkey at different developmental stages. We performed an in depth quantitative analysis of pyramidal cell morphology throughout development in an effort to determine which aspects mature early in development and which features require a protracted period of maturation. We were also interested in establishing if developmental changes in morphological features occur simultaneously or hierarchically in multiple visual cortical areas. We addressed these questions by performing principal component analysis (PCA) and hierarchical clustering analysis on relevant morphological features. Our analysis indicates that the maturation of pyramidal cell morphology is largely based on early development of topological features in most visual cortical areas. Moreover, the maturation of pyramidal cell morphology in V1, V2, V4, TEO, and TE is characterized by unique developmental trajectories.

Visual Corticocortical Inputs to Ferret Area 18.

Visual cortical areas in the adult mammalian brain are linked by a network of interareal feedforward and feedback circuits. We investigated the topography of feedback projections to ferret (Mustela putorius furo) area 18 from extrastriate areas 19, 21, and Ssy. Our objective was to characterize the anatomical organization of the extrastriate feedback pool to area 18. We also wished to determine if feedback projections to area 18 share similar features as feedback projections to area 17. We injected the tracer cholera toxin B subunit (CTb) into area 18 of adult ferrets to visualize the distribution and pattern of retrogradely labeled cells in extrastriate cortex. We find several similarities to the feedback projection to area 17: (i) Multiple visual cortical areas provide feedback to area 18: areas 19, 21, Ssy, and weaker inputs from posterior parietal and lateral temporal visual areas. Within each area a greater proportion of feedback projections arises from the infragranular than from the supragranular layers. (ii) The cortical area immediately rostral to area 18 provides the greatest proportion of total cortical feedback, and has the greatest peak density of cells providing feedback to area 18. (iii) The spacing (peak cell density and nearest neighbor distances) of cells in extrastriate cortex providing feedback to areas 17 and 18 are similar. However, peak density of feedback cells to area 18 is comparable in the supra- and infragranular layers, whereas peak density of feedback cells to area 17 is higher in the infragranular layers. Another prominent difference is that dorsal area 18 receives a cortical input that area 17 does not: from ventral cortex representing the upper visual field; this appears to be roughly 25% of the feedback input to area 18. Lastly, area 17 receives a greater proportion of cortical feedback from area 21 than from Ssy, whereas area 18 receives more feedback from Ssy than from area 21. While the organization of feedback projections from extrastriate cortex to areas 17 and 18 is broadly similar, the main difference in input topography might arise due to differences in visual field representations of the two areas.

Visual Cortical Representation of Whole Words and Hemifield-split Word Parts.

Reading requires the neural integration of visual word form information that is split between our retinal hemifields. We examined multiple visual cortical areas involved in this process by measuring fMRI responses while observers viewed words that changed or repeated in one or both hemifields. We were specifically interested in identifying brain areas that exhibit decreased fMRI responses as a result of repeated versus changing visual word form information in each visual hemifield. Our method yielded highly significant effects of word repetition in a previously reported visual word form area (VWFA) in occipitotemporal cortex, which represents hemifield-split words as whole units. We also identified a more posterior occipital word form area (OWFA), which represents word form information in the right and left hemifields independently and is thus both functionally and anatomically distinct from the VWFA. Both the VWFA and the OWFA were left-lateralized in our study and strikingly symmetric in anatomical location relative to known face-selective visual cortical areas in the right hemisphere. Our findings are consistent with the observation that category-selective visual areas come in pairs and support the view that neural mechanisms in left visual cortex--especially those that evolved to support the visual processing of faces--are developmentally malleable and become incorporated into a left-lateralized visual word form network that supports rapid word recognition and reading.

A Growth-Cone Model for the Spread of Object-Based Attention during Contour Grouping

Object-based attention can group image elements of spatially extended objects into coherent representations, but its mechanisms have remained unclear. The mechanisms for object-based attention may include shape-selective neurons in higher visual cortical areas that feed back to lower areas to simultaneously enhance the representation of all image elements of a relevant shape. Another, nonexclusive mechanism is the spread of attention in early visual cortex according to Gestalt rules, which could successively add new elements to a growing object representation. We investigated the dynamics of object-based attention in the primary visual cortex of monkeys trained to perform a contour-grouping task. The animals mentally traced a target curve through the visual field and ignored a distracting curve. Neuronal responses elicited by the target curve were enhanced relative to those elicited by distracting curve. Remarkably, the response enhancement was delayed for neurons with receptive fields farther from the start of the tracing process. We could therefore measure propagation speed and found that it was low if curves were nearby and that it increased if curves were far apart. The results are well explained by an "attentional growth-cone" model, which holds that the response enhancement can spread in multiple visual cortical areas with different receptive field sizes at a speed of approximately 50 ms per receptive field. Our findings support an active role for early visual areas in object-based attention because neurons in these areas gradually spread enhanced activity over the representation of relevant objects.

Developmental remodeling of corticocortical feedback circuits in ferret visual cortex

Visual cortical areas in the mammalian brain are linked through a system of interareal feedforward and feedback connections, which presumably underlie different visual functions. We characterized the refinement of feedback projections to primary visual cortex (V1) from multiple sources in juvenile ferrets ranging in age from 4-10 weeks postnatal. We studied whether the refinement of different aspects of feedback circuitry from multiple visual cortical areas proceeds at a similar rate in all areas. We injected the neuronal tracer cholera toxin B (CTb) into V1 and mapped the areal and laminar distribution of retrogradely labeled cells in extrastriate cortex. Around the time of eye opening at 4 weeks postnatal, the retinotopic arrangement of feedback appears essentially adult-like; however, suprasylvian cortex supplies the greatest proportion of feedback, whereas area 18 supplies the greatest proportion in the adult. The density of feedback cells and the ratio of supragranular/infragranular feedback contribution declined in this period at a similar rate in all cortical areas. We also found significant feedback to V1 from layer IV of all extrastriate areas. The regularity of cell spacing, the proportion of feedback arising from layer IV, and the tangential extent of feedback in each area all remained essentially unchanged during this period, except for the infragranular feedback source in area 18, which expanded. Thus, while much of the basic pattern of cortical feedback to V1 is present before eye opening, there is major synchronous reorganization after eye opening, suggesting a crucial role for visual experience in this remodeling process.

Inferential constraint sets in the organization of visual expectation.

Many lines of evidence indicate that considering visual perception as a passive, stimulus-driven, feedforward decoding process is no longer tenable. Visual perception naturally occurs within the context of an integrated array of ongoing cognitive processes involving memory, perception in other modalities, and motor control. In many situations, these processes allow expectations to be formed for likely visual events. This article explores the idea that the formation of visual expectations involves the active organization of visual cortical areas, providing a framework of contextual information within which expected events are interpreted. Retinal inputs are treated as constraints that feed into a complex system of interacting visual cortical areas and thalamic nuclei, which are concurrently imposing constraints on one another. Although the nature of expectational organization in the visual cortex is not well-understood, a reasonable hypothesis is that expectation involves the mutual constraint of spatiotemporal activity patterns in multiple visual cortical areas. In this scenario, expectation is instantiated by a set of activity patterns in high-level visual cortical areas that impose constraints on one another as well as on low-level areas according to the partial information that is available about expected retinal inputs. One approach to testing this proposal is through the analysis of simultaneously recorded local field potentials (LFPs) from local neuronal assemblies in multiple visual cortical areas. Analysis of LFPs by multivariate autoregressive modeling is showing promise in revealing the organization of expectation in visual cortex.

Local and global attention are mapped retinotopically in human occipital cortex.

Clinical evidence suggests that control mechanisms for local and global attention are lateralized in the temporal-parietal cortex. However, in the human occipital (visual) cortex, the evidence for lateralized local/global attention is controversial. To clarify this matter, we used functional MRI to map activity in the human occipital cortex, during local and global attention, with sustained visual fixation. Data were analyzed in a flattened cortical format, relative to maps of retinotopy and spatial frequency peak tuning. Neither local nor global attention was lateralized in the occipital cortex. Instead, local attention and global attention appear to be special cases of visual spatial attention, which are mapped consistently with the maps of retinotopy and spatial frequency tuning, in multiple visual cortical areas.

The neural mechanisms of top-down attentional control.

Selective visual attention involves dynamic interplay between attentional control systems and sensory brain structures. We used event-related functional magnetic resonance imaging (fMRI) during a cued spatial-attention task to dissociate brain activity related to attentional control from that related to selective processing of target stimuli. Distinct networks were engaged by attention-directing cues versus subsequent targets. Superior frontal, inferior parietal and superior temporal cortex were selectively activated by cues, indicating that these structures are part of a network for voluntary attentional control. This control biased activity in multiple visual cortical areas, resulting in selective sensory processing of relevant visual targets.

A forward-inverse optics model of reciprocal connections between visual cortical areas

We propose that the feedforward connection from the lower visual cortical area to the higher visual cortical area provides an approximated inverse model of the imaging process (optics), while the backprojection connection from the higher area to the lower area provides a forward model of the optics. By mathematical analysis and computer simulation, we show that a small number of relaxation computations circulating this forward-inverse optics hierarchy achieves fast and reliable integration of vision modules, and therefore might resolve the following problems. (i) How are parallel visual modules (multiple visual cortical areas) integrated to allow a coherent scene perception? (ii) How can ill-posed vision problems be solved by the brain within several hundreds of milliseconds?

A forward-inverse optics model of reciprocal connections between visual cortical areas

AbstractWe propose that the feedforward connection from the lower visual cortical area to the higher visual cortical area provides an approximated inverse model of the imaging process (optics), while the backprojection connection from the higher area to the lower area provides a forward model of the optics. By mathematical analysis and computer simulation, we show that a small number of relaxation computations circulating this forward-inverse optics hierarchy achieves fast and reliable integration of vision modules, and therefore might resolve the following problems. (i) How are parallel visual modules (multiple visual cortical areas) integrated to allow a coherent scene perception? (ii) How can ill-posed vision problems be solved by the brain within several hundreds of milliseconds?

The projections of single thalamic neurons onto multiple visual cortical areas in the cat

Fluorescent dyes Fast Blue and Nuclear Yellow injected into pairs of visual cortical and parietal 'association' cortical areas in the cat revealed the presence of retrogradely double-labeled cells in the intralaminar nuclei and lateral posterior-pulvinar complex of the thalamus. These results demonstrate the projection of individual thalamic neurons onto multiple cortical areas.

Connections of the multiple visual cortical areas with the lateral posterior-pulvinar complex and adjacent thalamic nuclei in the cat

The present report describes the patterns of cat thalamocortical interconnections for each of the 13 retinotopically ordered visual areas and additional visual areas for which no retinotopy has yet emerged. Small injections (75 nl) of a mixture of horseradish peroxidase and [3H]leucine were made through a recording pipette at cortical injection sites identified by retinotopic mapping. The patterns of thalamic label show that the lateral posterior-pulvinar complex of the cat is divided into three distinct functional zones, each of which contains a representation of the visual hemifield and shows unique afferent and efferent connectivity patterns. The pulvinar nucleus projects to areas 19, 20a, 20b, 21a, 21b, 5, 7, the splenial visual area, and the cingulate gyrus. The lateral division of the lateral posterior nucleus projects to areas 17, 18, 19, 20a, 20b, 21a, 21b, and the anterior medial (AMLS), posterior medial (PMLS), and ventral (VLS) lateral suprasylvian areas. The medial division of the lateral posterior nucleus projects to areas AMLS, PMLS, VLS, and the anterior lateral (ALLS), posterior lateral (PLLS), dorsal (DLS) lateral suprasylvian areas, and the posterior suprasylvian areas. In addition, many of these visual areas are also interconnected with subdivisions of the dorsal lateral geniculate nucleus (LGd). Every retinotopically ordered cortical area (except ALLS and AMLS) is reciprocally interconnected with the parvocellular C layers of the LGd. The medial intralaminar nucleus of the LGd projects to areas 17, 18, 19, AMLS, and PMLS. Finally, each cortical area (except area 17) receives a projection from thalamic intralaminar nuclei. These results help to define the pathways by which visual information gains access to the vast system of extrastriate cortex in the cat.