Demonstration of tuning to stimulus orientation in the human visual cortex: a high-resolution fMRI study with a novel continuous and periodic stimulation paradigm

Bounded contribution of human early visual cortex to the topographic anisotropy in spatial extent perception

To interact successfully with objects, it is crucial to accurately perceive their spatial extent, an enclosed region they occupy in space. Although the topographic representation of space in the early visual cortex (EVC) has been favored as a neural correlate of spatial extent perception, its exact nature and contribution to perception remain unclear. Here, we inspect the topographic representations of human individuals' EVC and perception in terms of how much their anisotropy is influenced by the orientation (co-axiality) and radial position (radiality) of stimuli. We report that while the anisotropy is influenced by both factors, its direction is primarily determined by radiality in EVC but by co-axiality in perception. Despite this mismatch, the individual differences in both radial and co-axial anisotropy are substantially shared between EVC and perception. Our findings suggest that spatial extent perception builds on EVC's spatial representation but requires an additional mechanism to transform its topographic bias.

Ultra-High Field Imaging of Human Visual Cognition

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.

Natural scene sampling reveals reliable coarse-scale orientation tuning in human V1

Orientation selectivity in primate visual cortex is organized into cortical columns. Since cortical columns are at a finer spatial scale than the sampling resolution of standard BOLD fMRI measurements, analysis approaches have been proposed to peer past these spatial resolution limitations. It was recently found that these methods are predominantly sensitive to stimulus vignetting - a form of selectivity arising from an interaction of the oriented stimulus with the aperture edge. Beyond vignetting, it is not clear whether orientation-selective neural responses are detectable in BOLD measurements. Here, we leverage a dataset of visual cortical responses measured using high-field 7T fMRI. Fitting these responses using image-computable models, we compensate for vignetting and nonetheless find reliable tuning for orientation. Results further reveal a coarse-scale map of orientation preference that may constitute the neural basis for known perceptual anisotropies. These findings settle a long-standing debate in human neuroscience, and provide insights into functional organization principles of visual cortex.

Orientation anisotropies in macaque visual areas

Orientation selectivity is one of the most important functional features of visual neurons. In the primate visual cortex, whether all orientations are represented equally is still unclear. Previous electrophysiological recordings led to controversial findings. By analyzing a large set of optical imaging data, we found anisotropic representations of orientation in macaque visual areas and that different areas had different types of anisotropies. These findings not only shed light on the long-standing question regarding a basic property of the primate visual cortex, but also on the strategy the visual system takes to represent and analyze the visual world.

In mammals, a larger number of neurons in V1 are devoted to cardinal (horizontal and vertical) orientations than to oblique orientations. However, electrophysiological results from the macaque monkey visual cortex are controversial. Both isotropic and anisotropic orientation distributions have been reported. It is also unclear whether different visual areas along the visual hierarchy have different orientation anisotropies. We analyzed orientation maps in a large set of intrinsic signal optical imaging data and found that both V1 and V4 exhibited significant orientation anisotropies. However, their overrepresented orientations were very different: in V1, both cardinal and radial orientations were overrepresented, while in V4, only cardinal bias was presented. These findings suggest that different cortical areas have evolved to emphasize different features that are suitable for their functional purposes, a factor that needs to be considered when efforts are made to explain the relationships between the visual environment and the cortical representation and between the cortical representation and visual perception.

The relationship between numerosity perception and mathematics ability in adults: the moderating role of dots number

Background

It has been proposed that numerosity perception is the cognitive underpinning of mathematics ability. However, the existence of the association between numerosity perception and mathematics ability is still under debate, especially in adults. The present study examined the relationship between numerosity perception and mathematics ability and the moderating role of dots number (i.e., the numerosity of items in dot set) in adults.

Methods

Sixty-four adult participants from Anshun University completed behavioral measures that tested numerosity perception of small numbers and large numbers, mathematics ability, inhibition ability, visual-spatial memory, and set-switching ability.

Results

We found that numerosity perception of small numbers correlated significantly with mathematics ability after controlling the influence of inhibition ability, visual-spatial memory, and set-switching ability, but numerosity perception of large numbers was not related to mathematics ability in adults.

Conclusions

These findings suggest that the dots number moderates the relationship between numerosity perception and mathematics ability in adults and may contribute to explaining the contradictory findings in the previous literature about the link between numerosity perception and mathematics ability.

Voxel-Wise Linearity Analysis of Increments and Decrements in BOLD Responses in Human Visual Cortex Using a Contrast Adaptation Paradigm

The linearity of BOLD responses is a fundamental presumption in most analysis procedures for BOLD fMRI studies. Previous studies have examined the linearity of BOLD signal increments, but less is known about the linearity of BOLD signal decrements. The present study assessed the linearity of both BOLD signal increments and decrements in the human primary visual cortex using a contrast adaptation paradigm. Results showed that both BOLD signal increments and decrements kept linearity to long stimuli (e.g., 3 s, 6 s), yet, deviated from linearity to transient stimuli (e.g., 1 s). Furthermore, a voxel-wise analysis showed that the deviation patterns were different for BOLD signal increments and decrements: while the BOLD signal increments demonstrated a consistent overestimation pattern, the patterns for BOLD signal decrements varied from overestimation to underestimation. Our results suggested that corrections to deviations from linearity of transient responses should consider the different effects of BOLD signal increments and decrements.

The development of active binocular vision under normal and alternate rearing conditions

The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions with naturalistic input, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereograms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.

Population Models, Not Analyses, of Human Neuroscience Measurements

Selectivity for many basic properties of visual stimuli, such as orientation, is thought to be organized at the scale of cortical columns, making it difficult or impossible to measure directly with noninvasive human neuroscience measurement. However, computational analyses of neuroimaging data have shown that selectivity for orientation can be recovered by considering the pattern of response across a region of cortex. This suggests that computational analyses can reveal representation encoded at a finer spatial scale than is implied by the spatial resolution limits of measurement techniques. This potentially opens up the possibility to study a much wider range of neural phenomena that are otherwise inaccessible through noninvasive measurement. However, as we review in this article, a large body of evidence suggests an alternative hypothesis to this superresolution account: that orientation information is available at the spatial scale of cortical maps and thus easily measurable at the spatial resolution of standard techniques. In fact, a population model shows that this orientation information need not even come from single-unit selectivity for orientation tuning, but instead can result from population selectivity for spatial frequency. Thus, a categorical error of interpretation can result whereby orientation selectivity can be confused with spatial frequency selectivity. This is similarly problematic for the interpretation of results from numerous studies of more complex representations and cognitive functions that have built upon the computational techniques used to reveal stimulus orientation. We suggest in this review that these interpretational ambiguities can be avoided by treating computational analyses as models of the neural processes that give rise to measurement. Building upon the modeling tradition in vision science using considerations of whether population models meet a set of core criteria is important for creating the foundation for a cumulative and replicable approach to making valid inferences from human neuroscience measurements. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Neurophysiological basis of contrast dependent BOLD orientation tuning

Recent work in early visual cortex of humans has shown that the BOLD signal exhibits contrast dependent orientation tuning, with an inverse oblique effect (oblique > cardinal) at high contrast and a horizontal effect (vertical > horizontal) at low contrast. This finding is at odds with decades of neurophysiological research demonstrating contrast invariant orientation tuning in primate visual cortex, yet the source of this discrepancy is unclear. We hypothesized that contrast dependent BOLD orientation tuning may arise due to contrast dependent influences of feedforward (FF) and feedback (FB) synaptic activity, indexed through gamma and alpha rhythms, respectively. To quantify this, we acquired EEG and BOLD in healthy humans to generate and compare orientation tuning curves across all neural frequency bands with BOLD. As expected, BOLD orientation selectivity in V1 was contrast dependent, preferring oblique orientations at high contrast and vertical at low contrast. On the other hand, EEG orientation tuning was contrast invariant, though frequency-specific, with an inverse-oblique effect in the gamma band (FF) and a horizontal effect in the alpha band (FB). Therefore, high-contrast BOLD orientation tuning closely matched FF activity, while at low contrast, BOLD best resembled FB orientation tuning. These results suggest that contrast dependent BOLD orientation tuning arises due to the reduced contribution of FF input to overall neurophysiological activity at low contrast, shifting BOLD orientation tuning towards the orientation preferences of FB at low contrast.

Categorical Biases in Human Occipitoparietal Cortex

Categorization allows organisms to generalize existing knowledge to novel stimuli and to discriminate between physically similar yet conceptually different stimuli. Humans, nonhuman primates, and rodents can readily learn arbitrary categories defined by low-level visual features, and learning distorts perceptual sensitivity for category-defining features such that differences between physically similar yet categorically distinct exemplars are enhanced, whereas differences between equally similar but categorically identical stimuli are reduced. We report a possible basis for these distortions in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivoxel and multielectrode patterns of human brain activity while human participants (both sexes) classified continuous stimulus sets into discrete groups. In each experiment, reconstructed representations of to-be-categorized stimuli were systematically biased toward the center of the appropriate category. These biases were largest for exemplars near a category boundary, predicted participants' overt category judgments, emerged shortly after stimulus onset, and could not be explained by mechanisms of response selection or motor preparation. Collectively, our findings suggest that category learning can influence processing at the earliest stages of cortical visual processing.SIGNIFICANCE STATEMENT Category learning enhances perceptual sensitivity for physically similar yet categorically different stimuli. We report a possible mechanism for these changes in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivariate patterns in occipitoparietal cortex while participants categorized sets of continuous stimuli into discrete groups. The recovered representations were systematically biased by category membership, with larger biases for exemplars adjacent to a category boundary. These results suggest that mechanisms of categorization shape information processing at the earliest stages of the visual system.

Stimulus vignetting and orientation selectivity in human visual cortex

Neural selectivity to orientation is one of the simplest and most thoroughly-studied cortical sensory features. Here, we show that a large body of research that purported to measure orientation tuning may have in fact been inadvertently measuring sensitivity to second-order changes in luminance, a phenomenon we term 'vignetting'. Using a computational model of neural responses in primary visual cortex (V1), we demonstrate the impact of vignetting on simulated V1 responses. We then used the model to generate a set of predictions, which we confirmed with functional MRI experiments in human observers. Our results demonstrate that stimulus vignetting can wholly determine the orientation selectivity of responses in visual cortex measured at a macroscopic scale, and suggest a reinterpretation of a well-established literature on orientation processing in visual cortex.

Inverted Encoding Models of Human Population Response Conflate Noise and Neural Tuning Width

Channel-encoding models offer the ability to bridge different scales of neuronal measurement by interpreting population responses, typically measured with BOLD imaging in humans, as linear sums of groups of neurons (channels) tuned for visual stimulus properties. Inverting these models to form predicted channel responses from population measurements in humans seemingly offers the potential to infer neuronal tuning properties. Here, we test the ability to make inferences about neural tuning width from inverted encoding models. We examined contrast invariance of orientation selectivity in human V1 (both sexes) and found that inverting the encoding model resulted in channel response functions that became broader with lower contrast, thus apparently violating contrast invariance. Simulations showed that this broadening could be explained by contrast-invariant single-unit tuning with the measured decrease in response amplitude at lower contrast. The decrease in response lowers the signal-to-noise ratio of population responses that results in poorer population representation of orientation. Simulations further showed that increasing signal to noise makes channel response functions less sensitive to underlying neural tuning width, and in the limit of zero noise will reconstruct the channel function assumed by the model regardless of the bandwidth of single units. We conclude that our data are consistent with contrast-invariant orientation tuning in human V1. More generally, our results demonstrate that population selectivity measures obtained by encoding models can deviate substantially from the behavior of single units because they conflate neural tuning width and noise and are therefore better used to estimate the uncertainty of decoded stimulus properties.SIGNIFICANCE STATEMENT It is widely recognized that perceptual experience arises from large populations of neurons, rather than a few single units. Yet, much theory and experiment have examined links between single units and perception. Encoding models offer a way to bridge this gap by explicitly interpreting population activity as the aggregate response of many single neurons with known tuning properties. Here we use this approach to examine contrast-invariant orientation tuning of human V1. We show with experiment and modeling that due to lower signal to noise, contrast-invariant orientation tuning of single units manifests in population response functions that broaden at lower contrast, rather than remain contrast-invariant. These results highlight the need for explicit quantitative modeling when making a reverse inference from population response profiles to single-unit responses.

The hemodynamic signal as a first-order low-pass temporal filter: Evidence and implications for neuroimaging studies

Neuronal activation triggers local changes in blood flow and hemoglobin oxygenation. These hemodynamic signals can be recorded through functional magnetic resonance imaging or intrinsic optical imaging, and allows inferring neural activity in response to stimuli. These techniques are widely used to uncover functional brain architectures. However, their accuracy suffers from distortions inherent to hemodynamic responses and noise. The analysis of these signals currently relies on models of impulse hemodynamic responses to brief stimuli. Here, in order to infer precise functional architectures, we focused on integrated signals associated to the dynamic response of functional maps. To this end, we recorded orientation and direction maps in cat primary visual cortex and compared two protocols: the conventional episodic stimulation technique and a continuous, periodic stimulation paradigm. Conventional methods show that the dynamics of activation and deactivation of the functional maps follows a linear first-order differential equation representing a low-pass filter. Comparison with the periodic stimulation methods confirmed this observation: the phase shifts and magnitude attenuations extracted at various frequencies were consistent with a low-pass filter with a 5s time constant. This dynamics presumably reflects the variations in deoxyhemoglobin mediated by arterial dilations. This dynamics open new avenues in the analysis of neuroimaging data that differs from common methods based on the hemodynamic response function. In particular, we demonstrate that inverting this first-order low-pass filter minimized the distortions of the signal and enabled a much faster and accurate reconstruction of functional maps.

Exploration of human visual cortex using high spatial resolution functional magnetic resonance imaging

In this review focusing primarily on the work conducted in my group at the RIKEN Brain Science Institute, I will first briefly summarize what we have achieved in mapping columnar organizations in human primary visual cortex using blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI), including ocular dominance columns, temporal frequency dependent domains, and orientation selective columns. I will then touch upon a couple of recent successful attempts in the field in mapping functional architectures in human extrastriate cortices, including human middle temporal complex and secondary and tertiary visual areas (V2 and V3), and discuss what we have learned regarding the spatial specificity of BOLD fMRI. Finally, I will offer some of my personal thoughts on how functional architectures may be organized in relation to underlying microvasculature and how such functional architectures may be experimentally explored.

What insights can fMRI offer into the structure and function of mid-tier visual areas?

Inferring neural responses from functional magnetic resonance imaging (fMRI) data is challenging. Even if we take advantage of high-field systems to acquire data with submillimeter resolution, we are still acquiring data in which a single datum summarizes the responses of tens of thousands of neurons. Excitation and inhibition, spikes and subthreshold membrane potential modulations, local and long-range computations, and tuned and nonselective responses are mixed together in one signal. With a priori knowledge of the underlying neural population responses, careful experiment design allows us to manipulate the experiment or task design so that subpopulations are selectively modulated, and our experiments can reveal those tuning functions. However, because we want to be able to use fMRI to discover new kinds of tuning functions and selectivity, we cannot limit ourselves to experiments in which we already know what we are looking for. Broadly speaking, analyses that rely on classification of responses that are distributed across the local neural population [multi-voxel pattern analyses (MVPA)] offer the ability to discover new kinds of information representation and selectivities in neural subpopulations. There is, however, no way to determine how the information discovered with MVPA or other analyses is related to the underlying neuronal tuning functions. Therefore, we must continue to rely on behavioral, computational, and animal models to develop theories of information representation in mid-tier visual cortical areas. Once encoding models exist, fMRI can be powerful for testing these a priori models of information representation. As an aide in developing these models, an important contribution that fMRI can make to our understanding of mid-tier visual areas is derived from connectivity analyses and experiments that study information sharing between visual areas. This ability to quantify localized population average responses throughout the brain is the strength we can best leverage to discover new properties of local and long-range neural networks.

Functional optical coherence tomography of rat olfactory bulb with periodic odor stimulation

In rodent olfactory bulb (OB), optical intrinsic signal imaging (OISI) is commonly used to investigate functional maps to odorant stimulations. However, in such studies, the spatial resolution in depth direction (z-axis) is lost because of the integration of light from different depths. To solve this problem, we propose functional optical coherence tomography (fOCT) with periodic stimulation and continuous recording. In fOCT experiments of in vivo rat OB, propionic acid and m-cresol were used as odor stimulus presentations. Such a periodic stimulation enabled us to detect the specific odor-responses from highly scattering brain tissue. Swept source OCT operating at a wavelength of 1334 nm and a frequency of 20 kHz, was employed with theoretical depth and lateral resolutions of 6.7 μm and 15.4 μm, respectively. We succeeded in visualizing 2D cross sectional fOCT map across the neural layer structure of OCT in vivo. The detected fOCT signals corresponded to a few glomeruli of the medial and lateral parts of dorsal OB. We also obtained 3D fOCT maps, which upon integration across z-axis agreed well with OISI results. We expect such an approach to open a window for investigating and possibly addressing toward inter/intra-layer connections at high resolutions in the future.

Radial bias is not necessary for orientation decoding

Multivariate pattern analysis can be used to decode the orientation of a viewed grating from fMRI signals in early visual areas. Although some studies have reported identifying multiple sources of the orientation information that make decoding possible, a recent study argued that orientation decoding is only possible because of a single source: a coarse-scale retinotopically organized preference for radial orientations. Here we aim to resolve these discrepant findings. We show that there were subtle, but critical, experimental design choices that led to the erroneous conclusion that a radial bias is the only source of orientation information in fMRI signals. In particular, we show that the reliance on a fast temporal-encoding paradigm for spatial mapping can be problematic, as effects of space and time become conflated and lead to distorted estimates of a voxel's orientation or retinotopic preference. When we implement minor changes to the temporal paradigm or to the visual stimulus itself, by slowing the periodic rotation of the stimulus or by smoothing its contrast-energy profile, we find significant evidence of orientation information that does not originate from radial bias. In an additional block-paradigm experiment where space and time were not conflated, we apply a formal model comparison approach and find that many voxels exhibit more complex tuning properties than predicted by radial bias alone or in combination with other known coarse-scale biases. Our findings support the conclusion that radial bias is not necessary for orientation decoding. In addition, our study highlights potential limitations of using temporal phase-encoded fMRI designs for characterizing voxel tuning properties.

In Vivo Mapping of Cortical Columnar Networks in the Monkey with Focal Electrical and Optical Stimulation

There are currently largescale efforts to understand the brain as a connection machine. However, there has been little emphasis on understanding connection patterns between functionally specific cortical columns. Here, we review development and application of focal electrical and optical stimulation methods combined with optical imaging and fMRI mapping in the non-human primate. These new approaches, when applied systematically on a large scale, will elucidate functionally specific intra-areal and inter-areal network connection patterns. Such functionally specific network data can provide accurate views of brain network topology.

A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons with limited bandwidth to encode challengingly large input ranges. Natural scenes are not random, and peripheral visual systems in vertebrates and insects have evolved to respond efficiently to their typical spatial statistics. The mammalian visual cortex is also tuned to natural spatial statistics, but less is known about coding in higher order neurons in insects. To redress this we here record intracellularly from a higher order visual neuron in the hoverfly. We show that the cSIFE neuron, which is inhibited by stationary images, is maximally inhibited when the slope constant of the amplitude spectrum is close to the mean in natural scenes. The behavioural optomotor response is also strongest to images with naturalistic image statistics. Our results thus reveal a close coupling between the inherent statistics of natural scenes and higher order visual processing in insects.

Hue Selectivity in Human Visual Cortex Revealed by Functional Magnetic Resonance Imaging

The variability of color-selective neurons in human visual cortex is considered more diverse than cone-opponent mechanisms. We addressed this issue by deriving histograms of hue-selective voxels measured using fMRI with a novel stimulation paradigm, where the stimulus hue changed continuously. Despite the large between-subject difference in hue-selective histograms, individual voxels exhibited selectivity for intermediate hues, such as purple, cyan, and orange, in addition to those along cone-opponent axes. In order to rule the possibility out that the selectivity for intermediate hues emerged through spatial summation of activities of neurons selectively responding to cone-opponent signals, we further tested hue-selective adaptations in intermediate directions of cone-opponent axes, by measuring responses to 4 diagonal hues during concurrent adaptation to 1 of the 4 hues. The selective and unidirectional reduction in response to the adapted hue lends supports to our argument that cortical neurons respond selectively to intermediate hues.

Motion direction biases and decoding in human visual cortex

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity.

Featural and temporal attention selectively enhance task-appropriate representations in human primary visual cortex

Our perceptions are often shaped by focusing our attention towards specific features or periods of time irrespective of location. Here we explore the physiological bases of these non-spatial forms of attention by imaging brain activity while subjects perform a challenging change-detection task. The task employs a continuously varying visual stimulus that, for any moment in time, selectively activates functionally distinct subpopulations of primary visual cortex (V1) neurons. When subjects are cued to the timing and nature of the change, the mapping of orientation preference across V1 systematically shifts towards the cued stimulus just prior to its appearance. A simple linear model can explain this shift: attentional changes are selectively targeted towards neural subpopulations, representing the attended feature at the times the feature was anticipated. Our results suggest that featural attention is mediated by a linear change in the responses of task-appropriate neurons across cortex during appropriate periods of time.

Vascular Supply of the Cerebral Cortex is Specialized for Cell Layers but Not Columns

The vascular supply to layers and columns was compared in macaque primary visual cortex (V1) by labeling red blood cells via their endogenous peroxidase activity. Alternate sections were processed for cytochrome oxidase to reveal "patches" or "blobs," which anchor the interdigitated column systems of striate cortex. More densely populated cell layers received the most profuse blood supply. In the superficial layers the blood supply was organized into microvascular lobules, consisting of a central venule surrounded by arterioles. Each vessel was identified as an arteriole or venule by matching it with the penetration site where it entered the cortex from a parent arteriole or venule in the pial circulation. Although microvascular lobules and cytochrome oxidase patches had a similar periodicity, they bore no mutual relationship. The size and density of penetrating arterioles and venules did not differ between patches and interpatches. The red blood cell labeling in patches and interpatches was equal. Moreover, patches and interpatches were supplied by an anastomotic pial arteriole system, with no segregation of blood supply to the two compartments. Often a focal constriction was present at the origin of pial arterial branches, indicating that local control of cortical perfusion may be accomplished by vascular sphincters.

Oblique effect in visual area 2 of macaque monkeys

The neural basis of an oblique effect, a reduced visual sensitivity for obliquely oriented stimuli, has been a matter of considerable debate. We have analyzed the orientation tuning of a relatively large number of neurons in the primary visual cortex (V1) and visual area 2 (V2) of anesthetized and paralyzed macaque monkeys. Neurons in V2 but not V1 of macaque monkeys showed clear oblique effects. This orientation anisotropy in V2 was more robust for those neurons that preferred higher spatial frequencies. We also determined whether V1 and V2 neurons exhibit a similar orientation anisotropy soon after birth. The oblique effect was absent in V1 of 4- and 8-week-old infant monkeys, but their V2 neurons showed a significant oblique effect. This orientation anisotropy in infant V2 was milder than that in adults. The results suggest that the oblique effect emerges in V2 based on the pattern of the connections that are established before birth and enhanced by the prolonged experience-dependent modifications of the neural circuitry in V2.

Integration of motion responses underlying directional motion anisotropy in human early visual cortical areas

Recent imaging studies have reported directional motion biases in human visual cortex when perceiving moving random dot patterns. It has been hypothesized that these biases occur as a result of the integration of motion detector activation along the path of motion in visual cortex. In this study we investigate the nature of such motion integration with functional MRI (fMRI) using different motion stimuli. Three types of moving random dot stimuli were presented, showing either coherent motion, motion with spatial decorrelations or motion with temporal decorrelations. The results from the coherent motion stimulus reproduced the centripetal and centrifugal directional motion biases in V1, V2 and V3 as previously reported. The temporally decorrelated motion stimulus resulted in both centripetal and centrifugal biases similar to coherent motion. In contrast, the spatially decorrelated motion stimulus resulted in small directional motion biases that were only present in parts of visual cortex coding for higher eccentricities of the visual field. In combination with previous results, these findings indicate that biased motion responses in early visual cortical areas most likely depend on the spatial integration of a simultaneously activated motion detector chain.