Neuronal responses to texture-defined form in macaque visual area V2

A filter-rectify-filter model of the tactile perception of 3D-printed, texture-defined form

We show that a two-stage filter-rectify-filter (FRF) model, previously used to explain the visual perception of texture-defined form, can also account for the tactile perception of texture-defined form. This result is interesting because, first, relatively little is known about the neural mechanisms of tactile form perception, and second, the generalization of the model may reflect a canonical computation at work in both visual and somatosensory cortex. We 3D-printed test objects comprising a regular, rectangular array of raised, oriented bars measuring 0.75 × 0.75 × 3 mm (width × height × length) that were centre-to-centre spaced by 4 mm. Bars on the left-hand-side of a test object were horizontal, and those on the right were vertical, thus defining a texture boundary. We independently jittered the orientations of bars by drawing random numbers from a uniform distribution; across trials, we systematically increased jitter from 0° (i.e., no jitter) to ±90° (i.e., no boundary). Blindfolded participants (n = 25) used the preferred index finger pad to actively scan objects for 10 seconds before reporting the texture boundary's orientation (vertical or horizontal; randomised across trials). Results showed a threshold jitter of ±52.7° (i.e., the jitter at which the boundary orientation was only just discriminable). Computational modelling indicated that the first stage of the FRF model is a Gabor function tuned to spatial frequency = 0.23 cycles per mm with extent = 2.53 mm (full-width at half-maximum). We discuss this result with regard to neuronal receptive field structure in non-human primate somatosensory cortex.

Saturation of visual responses explains size tuning in rat collicular neurons

The receptive field of many visual neurons is composed of a central responsive area, the classical receptive field, and a non-classical receptive field, also called the "suppressive surround." A visual stimulus placed in the suppressive surround does not induce any response but modulates visual responses to stimuli within the classical receptive field, usually by suppressing them. Therefore, visual responses become smaller when stimuli exceed the classical receptive field size. The stimulus size inducing the maximal response is called the preferred stimulus size. In cortex, there is good correspondence between the sizes of the classical receptive field and the preferred stimulus. In contrast, in the rodent superior colliculus, the preferred size is often several fold smaller than the classical receptive field size. Here, we show that in the rat superior colliculus, the preferred stimulus size changes as a square root of the contrast inverse and the classical receptive field size is independent of contrast. In addition, responses to annulus were largely independent of the inner hole size. To explain these data, three models were tested: the divisive modulation of the gain by the suppressive surround (the "normalization" model), the difference of the Gaussians, and a divisive model that incorporates saturation to light flux. Despite the same number of free parameters, the model incorporating saturation to light performed the best. Thus, our data indicate that in rats, the saturation to light can be a dominant phenomenon even at relatively low illumination levels defining visual responses in the collicular neurons.

Feature representation under crowding in macaque V1 and V4 neuronal populations

Visual perception depends strongly on spatial context. A profound example is visual crowding, whereby the presence of nearby stimuli impairs the discriminability of object features. Despite extensive work on perceptual crowding and the spatial integrative properties of visual cortical neurons, the link between these two aspects of visual processing remains unclear. To understand better the neural basis of crowding, we recorded activity simultaneously from neuronal populations in V1 and V4 of fixating macaque monkeys. We assessed the information available from the measured responses about the orientation of a visual target both for targets presented in isolation and amid distractors. Both single neuron and population responses had less information about target orientation when distractors were present. Information loss was moderate in V1 and more substantial in V4. Information loss could be traced to systematic divisive and additive changes in neuronal tuning. Additive and multiplicative changes in tuning were more severe in V4; in addition, tuning exhibited other, non-affine transformations that were greater in V4, further restricting the ability of a fixed sensory readout strategy to extract accurate feature information across displays. Our results provide a direct test of crowding effects at different stages of the visual hierarchy. They reveal how crowded visual environments alter the spiking activity of cortical populations by which sensory stimuli are encoded and connect these changes to established mechanisms of neuronal spatial integration.

Macaque V1 responses to 2nd-order contrast-modulated stimuli and the possible subcortical and cortical contributions

Natural images comprise contours and boundaries defined by 1st-order luminance-modulated (LM) cues that are readily encoded by V1 neurons, and 2nd-order contrast-modulated (CM) cues that carry local, but not over-the-space, luminance changes. The neurophysiological foundations for CM processing remain unsolved. Here we used two-photon calcium imaging to demonstrate that V1 superficial-layer neurons respond to both LM and CM gratings in awake, fixating, macaques, with overall LM responses stronger than CM responses. Furthermore, adaptation experiments revealed that LM responses were similarly suppressed by LM and CM adaptation, with moderately larger effects by iso-orientation adaptation than by orthogonal adaptation, suggesting that LM and CM orientation responses likely share a strong orientation-non-selective subcortical origin. In contrast, CM responses were substantially more suppressed by iso-orientation than by orthogonal LM and CM adaptation, likely suggesting stronger orientation-specific intracortical influences for CM responses than for LM responses, besides shared orientation-non-selective subcortical influences. These results thus may indicate a subcortical-to-V1 filter-rectify-filter mechanism for CM processing: Local luminance changes in CM stimuli are initially encoded by orientation-non-selective subcortical neurons, and the outputs are half-wave rectified, and then summed by V1 neurons to signal CM orientation, which may be further substantially refined by intracortical influences.

Regional Downregulation of Dopamine Receptor D1 in Bilateral Dorsal Lateral Geniculate Nucleus of Monocular Form-Deprived Amblyopia Models

Amblyopia is a common eye disease characterized by impaired best-corrected visual acuity. It starts in early childhood and leads to permanent vision reduction if left untreated. Even though many young patients with amblyopia are well treated in clinical practice, the underlying mechanism remains to be elucidated, which limits not only our understanding of this disease but also the therapeutic approach. To investigate the molecular mechanism of amblyopia, primate and rodent models of monocular-deprived amblyopia were created for mRNA screening and confirmation. We obtained 818 differentially expressed genes from the dorsal lateral geniculate nucleus (dLGN) of a primate model of amblyopia. After Gene Ontology and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses, the main enriched pathways were related to neural development. Interestingly, a particular neurotransmitter pathway, the dopaminergic pathway, was identified. The downregulation of dopamine receptor D1 (DRD1) was confirmed in both monkey and mouse samples. Furthermore, the immunofluorescence staining indicated that DRD1 expression was downregulated in both ventrolateral region of the contralateral dLGN and the dorsomedial region of the ipsilateral dLGN in the mouse model. The regions with downregulated expression of DRD1 were the downstream targets of the visual projection from the amblyopic eye. This study suggested that the downregulation of DRD1 in the LGN may be a cause for amblyopia. This may also be a reason for the failure of some clinical cases of levodopa combined with carbidopa applied to amblyopes.

An image-computable model of how endogenous and exogenous attention differentially alter visual perception

Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: 1) the parafoveal advantage in segmentation, 2) the uniform improvements across eccentricity by endogenous attention, and 3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.

Processing of motion boundary orientation in macaque V2

Human and nonhuman primates are good at identifying an object based on its motion, a task that is believed to be carried out by the ventral visual pathway. However, the neural mechanisms underlying such ability remains unclear. We trained macaque monkeys to do orientation discrimination for motion boundaries (MBs) and recorded neuronal response in area V2 with microelectrode arrays. We found 10.9% of V2 neurons exhibited robust orientation selectivity to MBs, and their responses correlated with monkeys' orientation-discrimination performances. Furthermore, the responses of V2 direction-selective neurons recorded at the same time showed correlated activity with MB neurons for particular MB stimuli, suggesting that these motion-sensitive neurons made specific functional contributions to MB discrimination tasks. Our findings support the view that V2 plays a critical role in MB analysis and may achieve this through a neural circuit within area V2.

Dynamic Contextual Modulation in Superior Colliculus of Awake Mouse

The responses of neurons in the visual pathway depend on the context in which a stimulus is presented. Responses to predictable stimuli are usually suppressed, highlighting responses to unexpected stimuli that might be important for behavior. Here, we established how context modulates the response of neurons in the superior colliculus (SC), a region important in orienting toward or away from visual stimuli. We made extracellular recordings from single units in the superficial layers of SC in awake mice. We found strong suppression of visual response by spatial context (surround suppression) and temporal context (adaptation). Neurons showing stronger surround suppression also showed stronger adaptation effects. In neurons where it was present, surround suppression was dynamic and was reduced by adaptation. Adaptation's effects further revealed two components to surround suppression: one component that was weakly tuned for orientation and adaptable, and another component that was more strongly tuned but less adaptable. The selectivity of the tuned component was flexible, such that suppression was stronger when the stimulus over the surround matched that over the receptive field. Our results therefore reveal strong interactions between spatial and temporal context in regulating the flow of signals through mouse SC, and suggest the presence of a subpopulation of neurons that might signal novelty in either space or time.

Different luminance- and texture-defined contrast sensitivity profiles for school-aged children

Our current understanding of how the visual brain develops is based largely on the study of luminance-defined information processing. This approach, however, is somewhat limiting, since everyday scenes are composed of complex images, consisting of information characterized by physical attributes relating to both luminance and texture. Few studies have explored how contrast sensitivity to texture-defined information develops, particularly throughout the school-aged years. The current study investigated how contrast sensitivity to luminance- (luminance-modulated noise) and texture-defined (contrast-modulated noise) static gratings develops in school-aged children. Contrast sensitivity functions identified distinct profiles for luminance- and texture-defined gratings across spatial frequencies (SFs) and age. Sensitivity to luminance-defined gratings reached maturity in childhood by the ages of 9–10 years for all SFs (0.5, 1, 2, 4 and 8 cycles/degree or cpd). Sensitivity to texture-defined gratings reached maturity at 5–6 years for low SFs and 7–8 years for high SFs (i.e., 4 cpd). These results establish that the processing of luminance- and texture-defined information develop differently as a function of SF and age.

Deep neural networks capture texture sensitivity in V2

Deep convolutional neural networks (CNNs) trained on visual objects have shown intriguing ability to predict some response properties of visual cortical neurons. However, the factors (e.g., if the model is trained or not, receptive field size) and computations (e.g., convolution, rectification, pooling, normalization) that give rise to such ability, at what level, and the role of intermediate processing stages in explaining changes that develop across areas of the cortical hierarchy are poorly understood. We focused on the sensitivity to textures as a paradigmatic example, since recent neurophysiology experiments provide rich data pointing to texture sensitivity in secondary (but not primary) visual cortex (V2). We initially explored the CNN without any fitting to the neural data and found that the first two layers of the CNN showed qualitative correspondence to the first two cortical areas in terms of texture sensitivity. We therefore developed a quantitative approach to select a population of CNN model neurons that best fits the brain neural recordings. We found that the CNN could develop compatibility to secondary cortex in the second layer following rectification and that this was improved following pooling but only mildly influenced by the local normalization operation. Higher layers of the CNN could further, though modestly, improve the compatibility with the V2 data. The compatibility was reduced when incorporating random rather than learned weights. Our results show that the CNN class of model is effective for capturing changes that develop across early areas of cortex, and has the potential to help identify the computations that give rise to hierarchical processing in the brain (code is available in GitHub).

Spatial contextual effects in primary visual cortex limit feature representation under crowding

Crowding is a profound loss of discriminability of visual features, when a target stimulus is surrounded by distractors. Numerous studies of human perception have characterized how crowding depends on the properties of a visual display. Yet, there is limited understanding of how and where stimulus information is lost in the visual system under crowding. Here, we show that macaque monkeys exhibit perceptual crowding for target orientation that is similar to humans. We then record from neuronal populations in monkey primary visual cortex (V1). These populations show an appreciable loss of information about target orientation in the presence of distractors, due both to divisive and additive modulation of responses to targets by distractors. Our results show that spatial contextual effects in V1 limit the discriminability of visual features and can contribute substantively to crowding.

Visual crowding can strongly limit perceptual discriminability, yet its neural basis remains unclear. Here, the authors show that perceptual crowding is similar in monkeys and humans, and that feature encoding in neuronal populations in primary visual cortex is limited for displays inducing crowding.

Visual response properties of neurons in the superficial layers of the superior colliculus of awake mouse

KEY POINTS

In rodents, including mice, the superior colliculus is the major target of the retina, but its visual response is not well characterized. In the present study, extracellular recordings from single nerve cells in the superficial layers of the superior colliculus were made in awake, head-restrained mice, and their responses to visual stimuli were measured. It was found that these neurons show brisk, highly sensitive and short latency visual responses, a preference for black over white stimuli, and diverse responses to moving patterns. At least five broad classes can be defined by variation in functional properties among units. The results of the present study demonstrate that eye movements have a measurable impact on visual responses in awake animals and show how they may be mitigated in analyses.

ABSTRACT

The mouse is an increasingly important animal model of visual function in health and disease. In mice, most retinal signals are routed through the superficial layers of the midbrain superior colliculus, and it is well established that much of the visual behaviour of mice relies on activity in the superior colliculus. The functional organization of visual signals in the mouse superior colliculus is, however, not well established in awake animals. We therefore made extracellular recordings from the superficial layers of the superior colliculus in awake mice, while the animals were viewing visual stimuli including flashed spots and drifting gratings. We find that neurons in the superficial layers of the superior colliculus of awake mouse generally show short latency, brisk responses. Receptive fields are usually 'ON-OFF' with a preference for black stimuli, and are weakly non-linear in response to gratings and other forms of luminance modulation. Population responses to drifting gratings are highly contrast sensitive, with a robust response to spatial frequencies above 0.3 cycles degree-1 and temporal frequencies above 15 Hz. The receptive fields are also often speed-tuned or direction-selective. Analysis of the response across multiple stimulus dimensions reveals at least five functionally distinct groups of units. We also find that eye movements affect measurements of receptive field properties in awake animals, and show how these may be mitigated in analyses. Qualitatively similar responses were obtained in urethane-anaesthetized animals, although receptive fields in awake animals had higher contrast sensitivity, shorter visual latency and a stronger response to high temporal frequencies.

Temporal Contingencies Determine Whether Adaptation Strengthens or Weakens Normalization

A fundamental and nearly ubiquitous feature of sensory encoding is that neuronal responses are strongly influenced by recent experience, or adaptation. Theoretical and computational studies have proposed that many adaptation effects may result in part from changes in the strength of normalization signals. Normalization is a "canonical" computation in which a neuron's response is modulated (normalized) by the pooled activity of other neurons. Here, we test whether adaptation can alter the strength of cross-orientation suppression, or masking, a paradigmatic form of normalization evident in primary visual cortex (V1). We made extracellular recordings of V1 neurons in anesthetized male macaques and measured responses to plaid stimuli composed of two overlapping, orthogonal gratings before and after prolonged exposure to two distinct adapters. The first adapter was a plaid consisting of orthogonal gratings and led to stronger masking. The second adapter presented the same orthogonal gratings in an interleaved manner and led to weaker masking. The strength of adaptation's effects on masking depended on the orientation of the test stimuli relative to the orientation of the adapters, but was independent of neuronal orientation preference. Changes in masking could not be explained by altered neuronal responsivity. Our results suggest that normalization signals can be strengthened or weakened by adaptation depending on the temporal contingencies of the adapting stimuli. Our findings reveal an interplay between two widespread computations in cortical circuits, adaptation and normalization, that enables flexible adjustments to the structure of the environment, including the temporal relationships among sensory stimuli.SIGNIFICANCE STATEMENT Two fundamental features of sensory responses are that they are influenced by adaptation and that they are modulated by the activity of other nearby neurons via normalization. Our findings reveal a strong interaction between these two aspects of cortical computation. Specifically, we show that cross-orientation masking, a form of normalization, can be strengthened or weakened by adaptation depending on the temporal contingencies between sensory inputs. Our findings support theoretical proposals that some adaptation effects may involve altered normalization and offer a network-based explanation for how cortex adjusts to current sensory demands.

Scale-Invariant Visual Capabilities Explained by Topographic Representations of Luminance and Texture in Primate V1

Humans have remarkable scale-invariant visual capabilities. For example, our orientation discrimination sensitivity is largely constant over more than two orders of magnitude of variations in stimulus spatial frequency (SF). Orientation-selective V1 neurons are likely to contribute to orientation discrimination. However, because at any V1 location neurons have a limited range of receptive field (RF) sizes, we predict that at low SFs V1 neurons will carry little orientation information. If this were the case, what could account for the high behavioral sensitivity at low SFs? Using optical imaging in behaving macaques, we show that, as predicted, V1 orientation-tuned responses drop rapidly with decreasing SF. However, we reveal a surprising coarse-scale signal that corresponds to the projection of the luminance layout of low-SF stimuli to V1's retinotopic map. This homeomorphic and distributed representation, which carries high-quality orientation information, is likely to contribute to our striking scale-invariant visual capabilities.

Gradual Development of Visual Texture-Selective Properties Between Macaque Areas V2 and V4

Complex shape and texture representations are known to be constructed from V1 along the ventral visual pathway through areas V2 and V4, but the underlying mechanism remains elusive. Recent study suggests that, for processing of textures, a collection of higher-order image statistics computed by combining V1-like filter responses serves as possible representations of textures both in V2 and V4. Here, to gain a clue for how these image statistics are processed in the extrastriate visual areas, we compared neuronal responses to textures in V2 and V4 of macaque monkeys. For individual neurons, we adaptively explored their preferred textures from among thousands of naturalistic textures and fitted the obtained responses using a combination of V1-like filter responses and higher-order statistics. We found that, while the selectivity for image statistics was largely comparable between V2 and V4, V4 showed slightly stronger sensitivity to the higher-order statistics than V2. Consistent with that finding, V4 responses were reduced to a greater extent than V2 responses when the monkeys were shown spectrally matched noise images that lacked higher-order statistics. We therefore suggest that there is a gradual development in representation of higher-order features along the ventral visual hierarchy.

Contextual modulation of sensitivity to naturalistic image structure in macaque V2

The stimulus selectivity of neurons in V1 is well known, as is the finding that their responses can be affected by visual input to areas outside of the classical receptive field. Less well understood are the ways selectivity is modified as signals propagate to visual areas beyond V1, such as V2. We recently proposed a role for V2 neurons in representing the higher order statistical dependencies found in images of naturally occurring visual texture. V2 neurons, but not V1 neurons, respond more vigorously to "naturalistic" images that contain these dependencies than to "noise" images that lack them. In this work, we examine the dependency of these effects on stimulus size. For most V2 neurons, the preference for naturalistic over noise stimuli was modest when presented in small patches and gradually strengthened with increasing size, suggesting that the mechanisms responsible for this enhanced sensitivity operate over regions of the visual field that are larger than the classical receptive field. Indeed, we found that surround suppression was stronger for noise than for naturalistic stimuli and that the preference for large naturalistic stimuli developed over a delayed time course consistent with lateral or feedback connections. These findings are compatible with a spatially broad facilitatory mechanism that is absent in V1 and suggest that a distinct role for the receptive field surround emerges in V2 along with sensitivity for more complex image structure. NEW & NOTEWORTHY The responses of neurons in visual cortex are often affected by visual input delivered to regions of the visual field outside of the conventionally defined receptive field, but the significance of such contextual modulations are not well understood outside of area V1. We studied the importance of regions beyond the receptive field in establishing a novel form of selectivity for the statistical dependencies contained in natural visual textures that first emerges in area V2.

Dopamine Activation Preserves Visual Motion Perception Despite Noise Interference of Human V5/MT

When processing sensory signals, the brain must account for noise, both noise in the stimulus and that arising from within its own neuronal circuitry. Dopamine receptor activation is known to enhance both visual cortical signal-to-noise-ratio (SNR) and visual perceptual performance; however, it is unknown whether these two dopamine-mediated phenomena are linked. To assess this, we used single-pulse transcranial magnetic stimulation (TMS) applied to visual cortical area V5/MT to reduce the SNR focally and thus disrupt visual motion discrimination performance to visual targets located in the same retinotopic space. The hypothesis that dopamine receptor activation enhances perceptual performance by improving cortical SNR predicts that dopamine activation should antagonize TMS disruption of visual perception. We assessed this hypothesis via a double-blinded, placebo-controlled study with the dopamine receptor agonists cabergoline (a D2 agonist) and pergolide (a D1/D2 agonist) administered in separate sessions (separated by 2 weeks) in 12 healthy volunteers in a William's balance-order design. TMS degraded visual motion perception when the evoked phosphene and the visual stimulus overlapped in time and space in the placebo and cabergoline conditions, but not in the pergolide condition. This suggests that dopamine D1 or combined D1 and D2 receptor activation enhances cortical SNR to boost perceptual performance. That local visual cortical excitability was unchanged across drug conditions suggests the involvement of long-range intracortical interactions in this D1 effect. Because increased internal noise (and thus lower SNR) can impair visual perceptual learning, improving visual cortical SNR via D1/D2 agonist therapy may be useful in boosting rehabilitation programs involving visual perceptual training.

SIGNIFICANCE STATEMENT

In this study, we address the issue of whether dopamine activation improves visual perception despite increasing sensory noise in the visual cortex. We show specifically that dopamine D1 (or combined D1/D2) receptor activation enhances the cortical signal-to-noise-ratio to boost perceptual performance. Together with the previously reported effects of dopamine upon brain plasticity and learning (Wolf et al., 2003; Hansen and Manahan-Vaughan, 2014), our results suggest that combining rehabilitation with dopamine agonists could enhance both the saliency of the training signal and the long-term effects on brain plasticity to boost rehabilitation regimens for brain injury.

Nonlinear Y-Like Receptive Fields in the Early Visual Cortex: An Intermediate Stage for Building Cue-Invariant Receptive Fields from Subcortical Y Cells

Many of the neurons in early visual cortex are selective for the orientation of boundaries defined by first-order cues (luminance) as well as second-order cues (contrast, texture). The neural circuit mechanism underlying this selectivity is still unclear, but some studies have proposed that it emerges from spatial nonlinearities of subcortical Y cells. To understand how inputs from the Y-cell pathway might be pooled to generate cue-invariant receptive fields, we recorded visual responses from single neurons in cat Area 18 using linear multielectrode arrays. We measured responses to drifting and contrast-reversing luminance gratings as well as contrast modulation gratings. We found that a large fraction of these neurons have nonoriented responses to gratings, similar to those of subcortical Y cells: they respond at the second harmonic (F2) to high-spatial frequency contrast-reversing gratings and at the first harmonic (F1) to low-spatial frequency drifting gratings ("Y-cell signature"). For a given neuron, spatial frequency tuning for linear (F1) and nonlinear (F2) responses is quite distinct, similar to orientation-selective cue-invariant neurons. Also, these neurons respond to contrast modulation gratings with selectivity for the carrier (texture) spatial frequency and, in some cases, orientation. Their receptive field properties suggest that they could serve as building blocks for orientation-selective cue-invariant neurons. We propose a circuit model that combines ON- and OFF-center cortical Y-like cells in an unbalanced push-pull manner to generate orientation-selective, cue-invariant receptive fields.

SIGNIFICANCE STATEMENT

A significant fraction of neurons in early visual cortex have specialized receptive fields that allow them to selectively respond to the orientation of boundaries that are invariant to the cue (luminance, contrast, texture, motion) that defines them. However, the neural mechanism to construct such versatile receptive fields remains unclear. Using multielectrode recording, we found a large fraction of neurons in early visual cortex with receptive fields not selective for orientation that have spatial nonlinearities like those of subcortical Y cells. These are strong candidates for building cue-invariant orientation-selective neurons; we present a neural circuit model that pools such neurons in an imbalanced "push-pull" manner, to generate orientation-selective cue-invariant receptive fields.

Phase-Dependent Interactions in Visual Cortex to Combinations of First- and Second-Order Stimuli

A fundamental task of the visual system is to extract figure-ground boundaries between objects, which are often defined, not only by differences in luminance, but also by "second-order" contrast or texture differences. Responses of cortical neurons to both first- and second-order patterns have been studied extensively, but only for responses to either type of stimulus in isolation. Here, we examined responses of visual cortex neurons to the spatial relationship between superimposed periodic luminance modulation (LM) and contrast modulation (CM) stimuli, the contrasts of which were adjusted to give equated responses when presented alone. Extracellular single-unit recordings were made in area 18 of the cat, the neurons of which show responses to CM and LM stimuli very similar to those in primate area V2 (Li et al., 2014). Most neurons showed a significant dependence on the relative phase of the combined LM and CM patterns, with a clear overall optimal response when they were approximately phase aligned. The degree of this phase preference, and the contributions of suppressive and/or facilitatory interactions, varied considerably from one neuron to another. Such phase-dependent and phase-invariant responses were evident in both simple- and complex-type cells. These results place important constraints on any future model of the underlying neural circuitry for second-order responses. The diversity in the degree of phase dependence between LM and CM stimuli that we observed could help to disambiguate different kinds of boundaries in natural scenes.

SIGNIFICANCE STATEMENT

Many visual cortex neurons exhibit orientation-selective responses to boundaries defined by differences either in luminance or in texture contrast. Previous studies have examined responses to either type of boundary in isolation, but here we measured systematically responses of cortical neurons to the spatial relationship between superimposed periodic luminance-modulated (LM) and contrast-modulated (CM) stimuli with contrasts adjusted to give equated responses. We demonstrate that neuronal responses to these compound stimuli are highly dependent on the relative phase between the LM and CM components. Diversity in the degree of such phase dependence could help to disambiguate different kinds of boundaries in natural scenes, for example, those arising from surface reflectance changes or from illumination gradients such as shading or shadows.

The Contribution of Area MT to Visual Motion Perception Depends on Training

Perceptual decisions require the transformation of raw sensory inputs into cortical representations suitable for stimulus discrimination. One of the best-known examples of this transformation involves the middle temporal area (MT) of the primate visual cortex. Area MT provides a robust representation of stimulus motion, and previous work has shown that it contributes causally to performance on motion discrimination tasks. Here we report that the strength of this contribution can be highly plastic: depending on the recent training history, pharmacological inactivation of MT can severely impair motion discrimination, or it can have little detectable influence. Further analysis of neural and behavioral data suggests that training moves the readout of motion information between MT and lower-level cortical areas. These results show that the contribution of individual brain regions to conscious perception can shift flexibly depending on sensory experience.

Differences in selectivity to natural images in early visual areas (V1-V3)

High-level regions of the ventral visual pathway respond more to intact objects compared to scrambled objects. The aim of this study was to determine if this selectivity for objects emerges at an earlier stage of processing. Visual areas (V1–V3) were defined for each participant using retinotopic mapping. Participants then viewed intact and scrambled images from different object categories (bottle, chair, face, house, shoe) while neural responses were measured using fMRI. Our rationale for using scrambled images is that they contain the same low-level properties as the intact objects, but lack the higher-order combinations of features that are characteristic of natural images. Neural responses were higher for scrambled than intact images in all regions. However, the difference between intact and scrambled images was smaller in V3 compared to V1 and V2. Next, we measured the spatial patterns of response to intact and scrambled images from different object categories. We found higher within-category compared to between category correlations for both intact and scrambled images demonstrating distinct patterns of response. Spatial patterns of response were more distinct for intact compared to scrambled images in V3, but not in V1 or V2. These findings demonstrate the emergence of selectivity to natural images in V3.

Mice Can Use Second-Order, Contrast-Modulated Stimuli to Guide Visual Perception

Visual processing along the primate ventral stream takes place in a hierarchy of areas, characterized by an increase in both complexity of neuronal preferences and invariance to changes of low-level stimulus attributes. A basic type of invariance is form-cue invariance, where neurons have similar preferences in response to first-order stimuli, defined by changes in luminance, and global features of second-order stimuli, defined by changes in texture or contrast. Whether in mice, a now popular model system for early visual processing, visual perception can be guided by second-order stimuli is currently unknown. Here, we probed mouse visual perception and neural responses in areas V1 and LM using various types of second-order, contrast-modulated gratings with static noise carriers. These gratings differ in their spatial frequency composition and thus in their ability to invoke first-order mechanisms exploiting local luminance features. We show that mice can transfer learning of a coarse orientation discrimination task involving first-order, luminance-modulated gratings to the contrast-modulated gratings, albeit with markedly reduced discrimination performance. Consistent with these behavioral results, we demonstrate that neurons in area V1 and LM are less responsive and less selective to contrast-modulated than to luminance-modulated gratings, but respond with broadly similar preferred orientations. We conclude that mice can, at least in a rudimentary form, use second-order stimuli to guide visual perception.

SIGNIFICANCE STATEMENT

To extract object boundaries in natural scenes, the primate visual system does not only rely on differences in local luminance but can also take into account differences in texture or contrast. Whether the mouse, which has a much simpler visual system, can use such second-order information to guide visual perception is unknown. Here we tested mouse perception of second-order, contrast-defined stimuli and measured their neural representations in two areas of visual cortex. We find that mice can use contrast-defined stimuli to guide visual perception, although behavioral performance and neural representations were less robust than for luminance-defined stimuli. These findings shed light on basic steps of feature extraction along the mouse visual cortical hierarchy, which may ultimately lead to object recognition.

Selectivity and tolerance for visual texture in macaque V2

As information propagates along the ventral visual hierarchy, neuronal responses become both more specific for particular image features and more tolerant of image transformations that preserve those features. Here, we present evidence that neurons in area V2 are selective for local statistics that occur in natural visual textures, and tolerant of manipulations that preserve these statistics. Texture stimuli were generated by sampling from a statistical model, with parameters chosen to match the parameters of a set of visually distinct natural texture images. Stimuli generated with the same statistics are perceptually similar to each other despite differences, arising from the sampling process, in the precise spatial location of features. We assessed the accuracy with which these textures could be classified based on the responses of V1 and V2 neurons recorded individually in anesthetized macaque monkeys. We also assessed the accuracy with which particular samples could be identified, relative to other statistically matched samples. For populations of up to 100 cells, V1 neurons supported better performance in the sample identification task, whereas V2 neurons exhibited better performance in texture classification. Relative to V1, the responses of V2 show greater selectivity and tolerance for the representation of texture statistics.

3D Shape Perception in Posterior Cortical Atrophy: A Visual Neuroscience Perspective

Posterior cortical atrophy (PCA) is a rare focal neurodegenerative syndrome characterized by progressive visuoperceptual and visuospatial deficits, most often due to atypical Alzheimer's disease (AD). We applied insights from basic visual neuroscience to analyze 3D shape perception in humans affected by PCA. Thirteen PCA patients and 30 matched healthy controls participated, together with two patient control groups with diffuse Lewy body dementia (DLBD) and an amnestic-dominant phenotype of AD, respectively. The hierarchical study design consisted of 3D shape processing for 4 cues (shading, motion, texture, and binocular disparity) with corresponding 2D and elementary feature extraction control conditions. PCA and DLBD exhibited severe 3D shape-processing deficits and AD to a lesser degree. In PCA, deficient 3D shape-from-shading was associated with volume loss in the right posterior inferior temporal cortex. This region coincided with a region of functional activation during 3D shape-from-shading in healthy controls. In PCA patients who performed the same fMRI paradigm, response amplitude during 3D shape-from-shading was reduced in this region. Gray matter volume in this region also correlated with 3D shape-from-shading in AD. 3D shape-from-disparity in PCA was associated with volume loss slightly more anteriorly in posterior inferior temporal cortex as well as in ventral premotor cortex. The findings in right posterior inferior temporal cortex and right premotor cortex are consistent with neurophysiologically based models of the functional anatomy of 3D shape processing. However, in DLBD, 3D shape deficits rely on mechanisms distinct from inferior temporal structural integrity.

SIGNIFICANCE STATEMENT

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by progressive visuoperceptual dysfunction and most often an atypical presentation of Alzheimer's disease (AD) affecting the ventral and dorsal visual streams rather than the medial temporal system. We applied insights from fundamental visual neuroscience to analyze 3D shape perception in PCA. 3D shape-processing deficits were affected beyond what could be accounted for by lower-order processing deficits. For shading and disparity, this was related to volume loss in regions previously implicated in 3D shape processing in the intact human and nonhuman primate brain. Typical amnestic-dominant AD patients also exhibited 3D shape deficits. Advanced visual neuroscience provides insight into the pathogenesis of PCA that also bears relevance for vision in typical AD.

A Hierarchical Statistical Model of Natural Images Explains Tuning Properties in V2

Previous theoretical and experimental studies have demonstrated tight relationships between natural image statistics and neural representations in V1. In particular, receptive field properties similar to simple and complex cells have been shown to be inferable from sparse coding of natural images. However, whether such a relationship exists in higher areas has not been clarified. To address this question for V2, we trained a sparse coding model that took as input the output of a fixed V1-like model, which was in its turn fed a large variety of natural image patches as input. After the training, the model exhibited response properties that were qualitatively and quantitatively compatible with three major neurophysiological results on macaque V2, as follows: (1) homogeneous and heterogeneous integration of local orientations (Anzai et al., 2007); (2) a wide range of angle selectivities with biased sensitivities to one component orientation (Ito and Komatsu, 2004); and (3) exclusive length and width suppression (Schmid et al., 2014). The reproducibility was stable across variations in several model parameters. Further, a formal classification of the internal representations of the model units offered detailed interpretations of the experimental data, emphasizing that a novel type of model cell that could detect a combination of local orientations converging toward a single spatial point (potentially related to corner-like features) played an important role in reproducing tuning properties compatible with V2. These results are consistent with the idea that V2 uses a sparse code of natural images. Significance statement: Sparse coding theory has successfully explained a number of receptive field properties in V1; but how about in V2? This question has recently become important since a variety of properties distinct from V1 have been discovered in V2, and thus a more integrative understanding is called for. Our study shows that a hierarchical sparse coding model of natural images explains three major response properties known in the macaque V2. We further provide a detailed analysis revealing the roles of different kinds of model cells in explaining the V2-specific properties. Our results thus offer the first sparse coding account for receptive field properties in V2 that has extensive biological relevance.

Specificity of brain reactions to second-order visual stimuli

The second-order visual mechanisms perform the operation of integrating the spatially distributed local visual information. Their organization is traditionally considered within the framework of the filter-rectify-filter model. These are the second-order filters that provide the ability to detect texture gradients. However, the question of the mechanisms' selectivity to the modulation dimension remains open. The aim of this investigation is to answer the above question by using visual evoked potentials (VEPs). Stimuli were textures consisting of staggered Gabor patches. The base texture was nonmodulated (NM). Three other textures represented the base texture which was sinusoidally modulated in different dimensions: contrast, orientation, or spatial frequency. EEG was recorded with 20 electrodes. VEPs of 500 ms duration were obtained for each of the four textures. After that, VEP to the NM texture was subtracted from VEP to each modulated texture. As a result, three different waves (d-waves) were obtained for each electrode site. Each d-wave was then averaged across all the 48 observers. The revealed d-waves have a latency of about 200 ms and, in our opinion, reflect the second-order filters reactivation through the feedback connection. The d-waves for different modulation dimensions were compared with each other in time, amplitude, topography, and localization of the sources of activity that causes the d-wave (with sLORETA). We proceeded from the assumption that the d-wave (its first component) represents functioning of the second-order visual mechanisms and activity changes at the following processing stages. It was found that the d-waves for different modulation dimensions significantly differ in all parameters. The obtained results indicate that the spatial modulations of different texture parameters caused specific changes in the brain activity, which could be evidence supporting the specificity of the second-order visual mechanisms to modulation dimension.

Perceptual quality measurement of 3D images based on binocular vision

Three-dimensional (3D) technology has become immensely popular in recent years and widely adopted in various applications. Hence, perceptual quality measurement of symmetrically and asymmetrically distorted 3D images has become an important, fundamental, and challenging issue in 3D imaging research. In this paper, we propose a binocular-vision-based 3D image-quality measurement (IQM) metric. Consideration of the 3D perceptual properties of the primary visual cortex (V1) and the higher visual areas (V2) for 3D-IQM is the major technical contribution to this research. To be more specific, first, the metric simulates the receptive fields of complex cells (V1) using binocular energy response and binocular rivalry response and the higher visual areas (V2) using local binary patterns features. Then, three similarity scores of 3D perceptual properties between the reference and distorted 3D images are measured. Finally, by using support vector regression, three similarity scores are integrated into an overall 3D quality score. Experimental results for two public benchmark databases demonstrate that, in comparison with most current 2D and 3D metrics, the proposed metric achieves significantly higher consistency in alignment with subjective fidelity ratings.

Early monocular defocus disrupts the normal development of receptive-field structure in V2 neurons of macaque monkeys

Experiencing different quality images in the two eyes soon after birth can cause amblyopia, a developmental vision disorder. Amblyopic humans show the reduced capacity for judging the relative position of a visual target in reference to nearby stimulus elements (position uncertainty) and often experience visual image distortion. Although abnormal pooling of local stimulus information by neurons beyond striate cortex (V1) is often suggested as a neural basis of these deficits, extrastriate neurons in the amblyopic brain have rarely been studied using microelectrode recording methods. The receptive field (RF) of neurons in visual area V2 in normal monkeys is made up of multiple subfields that are thought to reflect V1 inputs and are capable of encoding the spatial relationship between local stimulus features. We created primate models of anisometropic amblyopia and analyzed the RF subfield maps for multiple nearby V2 neurons of anesthetized monkeys by using dynamic two-dimensional noise stimuli and reverse correlation methods. Unlike in normal monkeys, the subfield maps of V2 neurons in amblyopic monkeys were severely disorganized: subfield maps showed higher heterogeneity within each neuron as well as across nearby neurons. Amblyopic V2 neurons exhibited robust binocular suppression and the strength of the suppression was positively correlated with the degree of hereogeneity and the severity of amblyopia in individual monkeys. Our results suggest that the disorganized subfield maps and robust binocular suppression of amblyopic V2 neurons are likely to adversely affect the higher stages of cortical processing resulting in position uncertainty and image distortion.

Response priming evidence for feedforward processing of snake contours but not of ladder contours and textures

In contour integration, increased difficulty in detection and shape discrimination of a chain of parallel elements (a ladder contour) compared to collinear elements (a snake contour) suggests more extensive processing of ladders than of snakes. In addition, conceptual similarities between ladders and textures - which also involve grouping of parallel elements - raises the question whether ladder and texture processing requires feedback from higher visual areas while snakes are processed in a fast feedforward sweep. We tested this in a response priming paradigm, where participants responded as quickly and accurately as possible to the orientation of a diagonal contour in a Gabor array (target). The diagonal was defined either by a snake, ladder, texture, or a continuous line. The target was preceded with varying stimulus onset asynchrony (SOA) by a prime that was either a snake, ladder, or texture, and was consistent or inconsistent to the response demands of the target. Resulting priming effects clearly distinguished between processing of snakes, ladders, and textures. Effects generally increased with SOA but were stronger for snakes and textures compared to ladders. Importantly, only priming effects for snakes were fully present already in the fastest response times, in accordance with a simple feedforward processing model. We conclude that snakes, ladders, and textures do not share similar processing characteristics, with snakes exhibiting a pronounced processing advantage.

The efficiency of second order orientation coherence detection

Neurons in early visual cortex respond to both luminance- (1st order) and contrast-modulated (2nd order) local features in the visual field. In later extra-striate areas neurons with larger receptive fields integrate information across the visual field. For example, local luminance-defined features can be integrated into contours and shapes. Evidence for the global integration of features defined by contrast-modulation is less well established. While good performance in some shape tasks has been demonstrated with 2nd order stimuli, the integration of contours fails with 2nd order elements. Recently we developed a global orientation coherence task that is more basic than contour integration, bearing similarity to the well-established global motion coherence task. Similar to our previous 1st order result for this task, we find 2nd order coherence detection to be scale-invariant. There was a small but significant threshold elevation for 2nd order relative to 1st order. We used a noise masking approach to compare the efficiency of orientation integration for the 1st and 2nd order. We find a significant deficit for 2nd order detection at both the local and global level, however the small size of this effect stands in stark contrast against previous results from contour-integration experiments, which are almost impossible with 2nd order stimuli.

Image statistics underlying natural texture selectivity of neurons in macaque V4

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron's preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception.

A conceptual framework of computations in mid-level vision

If a picture is worth a thousand words, as an English idiom goes, what should those words-or, rather, descriptors-capture? What format of image representation would be sufficiently rich if we were to reconstruct the essence of images from their descriptors? In this paper, we set out to develop a conceptual framework that would be: (i) biologically plausible in order to provide a better mechanistic understanding of our visual system; (ii) sufficiently robust to apply in practice on realistic images; and (iii) able to tap into underlying structure of our visual world. We bring forward three key ideas. First, we argue that surface-based representations are constructed based on feature inference from the input in the intermediate processing layers of the visual system. Such representations are computed in a largely pre-semantic (prior to categorization) and pre-attentive manner using multiple cues (orientation, color, polarity, variation in orientation, and so on), and explicitly retain configural relations between features. The constructed surfaces may be partially overlapping to compensate for occlusions and are ordered in depth (figure-ground organization). Second, we propose that such intermediate representations could be formed by a hierarchical computation of similarity between features in local image patches and pooling of highly-similar units, and reestimated via recurrent loops according to the task demands. Finally, we suggest to use datasets composed of realistically rendered artificial objects and surfaces in order to better understand a model's behavior and its limitations.

Form-cue invariant second-order neuronal responses to contrast modulation in primate area V2

A fundamental task of the visual system is to extract figure-ground boundaries between images of objects, which in natural scenes are often defined not only by luminance differences but also by "second-order" contrast or texture differences. Responses to contrast modulation (CM) and other second-order stimuli have been extensively studied in human psychophysics, but the neuronal substrates of second-order responses in nonhuman primates remain poorly understood. In this study, we have recorded single neurons in area V2 of macaque monkeys, using both CM patterns as well as conventional luminance modulation (LM) gratings. CM stimuli were constructed from stationary sine wave grating carrier patterns, which were modulated by drifting envelope gratings of a lower spatial frequency. We found approximately one-third of visually responsive V2 neurons responded to CM stimuli with a pronounced selectivity to carrier spatial frequencies, and often orientations, that were clearly outside the neurons' passbands for LM gratings. These neurons were "form-cue invariant" in that their tuning to CM envelope spatial frequency and orientation was very similar to that for LM gratings. Neurons were tuned to carrier spatial frequencies that were typically 2-4 octaves higher than their optimal envelope spatial frequencies, similar to results from human psychophysics. These results are distinct from CM responses arising from surround suppression, but could be understood in terms of a filter-rectify-filter model. Such neurons could provide a functionally useful and explicit representation of segmentation boundaries as well as a plausible neural substrate for human perception of second-order boundaries.

Surround suppression supports second-order feature encoding by macaque V1 and V2 neurons

Single neurons in areas V1 and V2 of macaque visual cortex respond selectively to luminance-modulated stimuli. These responses are often influenced by context, for example when stimuli extend outside the classical receptive field (CRF). These contextual phenomena, observed in many sensory areas, reflect a fundamental cortical computation and may inform perception by signaling second-order visual features which are defined by spatial relationships of contrast, orientation and spatial frequency. In the anesthetized, paralyzed macaque, we measured single-unit responses to a drifting preferred sinusoidal grating; low spatial frequency sinusoidal contrast modulations were applied to the grating, creating contrast-modulated, second-order forms. Most neurons responded selectively to the orientation of the contrast modulation of the preferred grating and were therefore second-order orientation-selective. Second-order selectivity was created by the asymmetric spatial organization of the excitatory CRF and suppressive extraclassical surround. We modeled these receptive field subregions using spatial Gaussians, sensitive to the modulation of contrast (not luminance) of the preferred carrier grating, that summed linearly and were capable of recovering asymmetrical receptive field organizations. Our modeling suggests that second-order selectivity arises both from elongated excitatory CRFs, asymmetrically organized extraclassical surround suppression, or both. We validated the model by successfully testing its predictions against conventional surround suppression measurements and spike-triggered analysis of second-order form responses. Psychophysical adaptation measurements on human observers revealed a pattern of second-order form selectivity consistent with neural response patterns. We therefore propose that cortical cells in primates do double duty, providing signals about both first- and second-order forms.

Contextual modulation as de-texturizer

Contextual modulation refers to the effect of texture placed outside of a neuron's classical receptive field as well as the effect of surround texture on the perceptual properties of variegated regions within. In this minireview, we argue that one role of contextual modulation is to enhance the perception of contours at the expense of textures, in short to de-texturize the image. The evidence for this role comes mainly from three sources: psychophysical studies of shape after-effects, computational models of neurons that exhibit iso-orientation surround inhibition, and fMRI studies revealing specialized areas for contour as opposed to texture processing. The relationship between psychophysical studies that support the notion of contextual modulation as de-texturizer and those that investigate contour integration and crowding is discussed.

Orientation-cue invariant population responses to contrast-modulated and phase-reversed contour stimuli in macaque V1 and V2

Visual scenes can be readily decomposed into a variety of oriented components, the processing of which is vital for object segregation and recognition. In primate V1 and V2, most neurons have small spatio-temporal receptive fields responding selectively to oriented luminance contours (first order), while only a subgroup of neurons signal non-luminance defined contours (second order). So how is the orientation of second-order contours represented at the population level in macaque V1 and V2? Here we compared the population responses in macaque V1 and V2 to two types of second-order contour stimuli generated either by modulation of contrast or phase reversal with those to first-order contour stimuli. Using intrinsic signal optical imaging, we found that the orientation of second-order contour stimuli was represented invariantly in the orientation columns of both macaque V1 and V2. A physiologically constrained spatio-temporal energy model of V1 and V2 neuronal populations could reproduce all the recorded population responses. These findings suggest that, at the population level, the primate early visual system processes the orientation of second-order contours initially through a linear spatio-temporal filter mechanism. Our results of population responses to different second-order contour stimuli support the idea that the orientation maps in primate V1 and V2 can be described as a spatial-temporal energy map.

The synaptic and circuit mechanisms underlying a change in spatial encoding in the retina

Components of neural circuits are often repurposed so that the same biological hardware can be used for distinct computations. This flexibility in circuit operation is required to account for the changes in sensory computations that accompany changes in input signals. Yet we know little about how such changes in circuit operation are implemented. Here we show that a single retinal ganglion cell performs a different computation in dim light--averaging contrast within its receptive field--than in brighter light, when the cell becomes sensitive to fine spatial detail. This computational change depends on interactions between two parallel circuits that control the ganglion cell's excitatory synaptic inputs. Specifically, steady-state interactions through dendro-axonal gap junctions control rectification of the synapses providing excitatory input to the ganglion cell. These findings provide a clear example of how a simple synaptic mechanism can repurpose a neural circuit to perform diverse computations.

Responses to orientation discontinuities in V1 and V2: physiological dissociations and functional implications

Segmenting the visual image into objects is a crucial stage of visual processing. Object boundaries are typically associated with differences in luminance, but discontinuities in texture also play an important role. We showed previously that a subpopulation of neurons in V2 in anesthetized macaques responds to orientation discontinuities parallel to their receptive field orientation. Such single-cell responses could be a neurophysiological correlate of texture boundary detection. Neurons in V1, on the other hand, are known to have contextual response modulations such as iso-orientation surround suppression, which also produce responses to orientation discontinuities. Here, we use pseudorandom multiregion grating stimuli of two frame durations (20 and 40 ms) to probe and compare texture boundary responses in V1 and V2 in anesthetized macaque monkeys. In V1, responses to texture boundaries were observed for only the 40 ms frame duration and were independent of the orientation of the texture boundary. However, in transient V2 neurons, responses to such texture boundaries were robust for both frame durations and were stronger for boundaries parallel to the neuron's preferred orientation. The dependence of these processes on stimulus duration and orientation indicates that responses to texture boundaries in V2 arise independently of contextual modulations in V1. In addition, because the responses in transient V2 neurons are sensitive to the orientation of the texture boundary but those of V1 neurons are not, we suggest that V2 responses are the correlate of texture boundary detection, whereas contextual modulation in V1 serves other purposes, possibly related to orientation "pop-out."

Similar adaptation effects in primary visual cortex and area MT of the macaque monkey under matched stimulus conditions

Recent stimulus history, or adaptation, can alter neuronal response properties. Adaptation effects have been characterized in a number of visually responsive structures, from the retina to higher visual cortex. However, it remains unclear whether adaptation effects across stages of the visual system take a similar form in response to a particular sensory event. This is because studies typically probe a single structure or cortical area, using a stimulus ensemble chosen to provide potent drive to the cells of interest. Here we adopt an alternative approach and compare adaptation effects in primary visual cortex (V1) and area MT using identical stimulus ensembles. Previous work has suggested these areas adjust to recent stimulus drive in distinct ways. We show that this is not the case: adaptation effects in V1 and MT can involve weak or strong loss of responsivity and shifts in neuronal preference toward or away from the adapter, depending on stimulus size and adaptation duration. For a particular stimulus size and adaptation duration, however, effects are similar in nature and magnitude in V1 and MT. We also show that adaptation effects in MT of awake animals depend strongly on stimulus size. Our results suggest that the strategies for adjusting to recent stimulus history depend more strongly on adaptation duration and stimulus size than on the cortical area. Moreover, they indicate that different levels of the visual system adapt similarly to recent sensory experience.

Visual response properties of V1 neurons projecting to V2 in macaque

Visual area V2 of the primate cortex receives the largest projection from area V1. V2 is thought to use its striate inputs as the basis for computations that are important for visual form processing, such as signaling angles, object borders, illusory contours, and relative binocular disparity. However, it remains unclear how selectivity for these stimulus properties emerges in V2, in part because the functional properties of the inputs are unknown. We used antidromic electrical stimulation to identify V1 neurons that project directly to V2 (10% of all V1 neurons recorded) and characterized their electrical and visual responses. V2-projecting neurons were concentrated in the superficial and middle layers of striate cortex, consistent with the known anatomy of this cortico-cortical circuit. Most were fast conducting and temporally precise in their electrical responses, and had broad spike waveforms consistent with pyramidal regular-spiking excitatory neurons. Overall, projection neurons were functionally diverse. Most, however, were tuned for orientation and binocular disparity and were strongly suppressed by large stimuli. Projection neurons included those selective and invariant to spatial phase, with roughly equal proportions. Projection neurons found in superficial layers had longer conduction times, broader spike waveforms, and were more responsive to chromatic stimuli; those found in middle layers were more strongly selective for motion direction and binocular disparity. Collectively, these response properties may be well suited for generating complex feature selectivity in and beyond V2.

Adaptation to implied tilt: extensive spatial extrapolation of orientation gradients

To extract the global structure of an image, the visual system must integrate local orientation estimates across space. Progress is being made toward understanding this integration process, but very little is known about whether the presence of structure exerts a reciprocal influence on local orientation coding. We have previously shown that adaptation to patterns containing circular or radial structure induces tilt-aftereffects (TAEs), even in locations where the adapting pattern was occluded. These spatially “remote” TAEs have novel tuning properties and behave in a manner consistent with adaptation to the local orientation implied by the circular structure (but not physically present) at a given test location. Here, by manipulating the spatial distribution of local elements in noisy circular textures, we demonstrate that remote TAEs are driven by the extrapolation of orientation structure over remarkably large regions of visual space (more than 20°). We further show that these effects are not specific to adapting stimuli with polar orientation structure, but require a gradient of orientation change across space. Our results suggest that mechanisms of visual adaptation exploit orientation gradients to predict the local pattern content of unfilled regions of space.

Impaired texture segregation but spared contour integration following damage to right posterior parietal cortex

We examined the relations between texture segregation and contour integration in patients with deficits in spatial attention leading to left or right hemisphere extinction. Patients and control participants were presented with texture and contour stimuli consisting of oriented elements. We induced regularity in the stimuli by manipulating the element orientations resulting in an implicit texture border or explicit contour. Participants had to discriminate curved from straight shapes without making eye movements, while the stimulus presentation time was varied using a QUEST procedure. The results showed that only patients with right hemisphere extinction had a spatial bias, needing a longer presentation time to determine the shape of the border or contour on the contralesional side, especially for borders defined by texture. These results indicate that texture segregation is modulated by attention-related brain areas in the right posterior parietal cortex.

A functional and perceptual signature of the second visual area in primates

There is no generally accepted account of the function of the second visual cortical area (V2), partly because no simple response properties robustly distinguish V2 neurons from those in primary visual cortex (V1). We constructed synthetic stimuli replicating the higher-order statistical dependencies found in natural texture images and used them to stimulate macaque V1 and V2 neurons. Most V2 cells responded more vigorously to these textures than to control stimuli lacking naturalistic structure; V1 cells did not. Functional magnetic resonance imaging (fMRI) measurements in humans revealed differences between V1 and V2 that paralleled the neuronal measurements. The ability of human observers to detect naturalistic structure in different types of texture was well predicted by the strength of neuronal and fMRI responses in V2 but not in V1. Together, these results reveal a particular functional role for V2 in the representation of natural image structure.

A two-stage cascade model of BOLD responses in human visual cortex

Visual neuroscientists have discovered fundamental properties of neural representation through careful analysis of responses to controlled stimuli. Typically, different properties are studied and modeled separately. To integrate our knowledge, it is necessary to build general models that begin with an input image and predict responses to a wide range of stimuli. In this study, we develop a model that accepts an arbitrary band-pass grayscale image as input and predicts blood oxygenation level dependent (BOLD) responses in early visual cortex as output. The model has a cascade architecture, consisting of two stages of linear and nonlinear operations. The first stage involves well-established computations—local oriented filters and divisive normalization—whereas the second stage involves novel computations—compressive spatial summation (a form of normalization) and a variance-like nonlinearity that generates selectivity for second-order contrast. The parameters of the model, which are estimated from BOLD data, vary systematically across visual field maps: compared to primary visual cortex, extrastriate maps generally have larger receptive field size, stronger levels of normalization, and increased selectivity for second-order contrast. Our results provide insight into how stimuli are encoded and transformed in successive stages of visual processing.

Much has been learned about how stimuli are represented in the visual system from measuring responses to carefully designed stimuli. Typically, different studies focus on different types of stimuli. Making sense of the large array of findings requires integrated models that explain responses to a wide range of stimuli. In this study, we measure functional magnetic resonance imaging (fMRI) responses in early visual cortex to a wide range of band-pass filtered images, and construct a computational model that takes the stimuli as input and predicts the fMRI responses as output. The model has a cascade architecture, consisting of two stages of linear and nonlinear operations. A novel component of the model is a nonlinear operation that generates selectivity for second-order contrast, that is, variations in contrast-energy across the visual field. We find that this nonlinearity is stronger in extrastriate areas V2 and V3 than in primary visual cortex V1. Our results provide insight into how stimuli are encoded and transformed in the visual system.

Receptive-field subfields of V2 neurons in macaque monkeys are adult-like near birth

Infant primates can discriminate texture-defined form despite their relatively low visual acuity. The neuronal mechanisms underlying this remarkable visual capacity of infants have not been studied in nonhuman primates. Since many V2 neurons in adult monkeys can extract the local features in complex stimuli that are required for form vision, we used two-dimensional dynamic noise stimuli and local spectral reverse correlation to measure whether the spatial map of receptive-field subfields in individual V2 neurons is sufficiently mature near birth to capture local features. As in adults, most V2 neurons in 4-week-old monkeys showed a relatively high degree of homogeneity in the spatial matrix of facilitatory subfields. However, ∼25% of V2 neurons had the subfield map where the neighboring facilitatory subfields substantially differed in their preferred orientations and spatial frequencies. Over 80% of V2 neurons in both infants and adults had "tuned" suppressive profiles in their subfield maps that could alter the tuning properties of facilitatory profiles. The differences in the preferred orientations between facilitatory and suppressive profiles were relatively large but extended over a broad range. Response immaturities in infants were mild; the overall strength of facilitatory subfield responses was lower than that in adults, and the optimal correlation delay ("latency") was longer in 4-week-old infants. These results suggest that as early as 4 weeks of age, the spatial receptive-field structure of V2 neurons is as complex as in adults and the ability of V2 neurons to compare local features of neighboring stimulus elements is nearly adult like.

Distinct effects of brief and prolonged adaptation on orientation tuning in primary visual cortex

Recent stimulus history-adaptation-alters neuronal responses and perception. Previous electrophysiological and perceptual studies suggest that prolonged adaptation strengthens and makes more persistent the effects seen after briefer exposures. However, no systematic comparison has been made between the effects of adaptation lasting hundreds of milliseconds, which might arise during a single fixation, and the more prolonged adaptation typically used in imaging and perceptual studies. Here we determine how 0.4, 4, and 40 s of adaptation alters orientation tuning in primary visual cortex of anesthetized macaque monkeys, and how quickly responses recover after adapter offset. We measured responses to small (1.3°) and large (7.4°) gratings because previous work has shown that adaptation effects can depend on stimulus size. Adaptation with small gratings reduced responsivity and caused tuning to shift away from the adapter. These effects strengthened with more prolonged adaptation. For responses to large gratings, brief and prolonged adaptation produced indistinguishable effects on responsivity but caused opposite shifts in tuning preference. Recovery from adaptation was notably slower after prolonged adaptation, even when this did not induce stronger effects. We show that our results can be explained by an adaptation-induced weakening of surround suppression, the dynamics of this suppression, and differential effects of brief and prolonged adaptation across response epochs. Our findings show that effects do not simply scale with adaptation duration and suggest that distinct strategies exist for adjusting to moment-to-moment fluctuations in input and to more persistent visual stimuli.

A three-layer model of natural image statistics

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It is, however, unknown what should be selected or tolerated at each level of the hierarchy. We approach this issue by learning the computations from natural images. We propose and estimate a probabilistic model of natural images that consists of three processing layers. Two natural image data sets are considered: image patches, and complete visual scenes downsampled to the size of small patches. For both data sets, we find that in the first two layers, simple and complex cell-like computations are performed. In the third layer, we mainly find selectivity to longer contours; for patch data, we further find some selectivity to texture, while for the downsampled complete scenes, some selectivity to curvature is observed.

Differential effects of exogenous and endogenous attention on second-order texture contrast sensitivity

The visual system can use a rich variety of contours to segment visual scenes into distinct perceptually coherent regions. However, successfully segmenting an image is a computationally expensive process. Previously we have shown that exogenous attention--the more automatic, stimulus-driven component of spatial attention--helps extract contours by enhancing contrast sensitivity for second-order, texture-defined patterns at the attended location, while reducing sensitivity at unattended locations, relative to a neutral condition. Interestingly, the effects of exogenous attention depended on the second-order spatial frequency of the stimulus. At parafoveal locations, attention enhanced second-order contrast sensitivity to relatively high, but not to low second-order spatial frequencies. In the present study we investigated whether endogenous attention-the more voluntary, conceptually-driven component of spatial attention--affects second-order contrast sensitivity, and if so, whether its effects are similar to those of exogenous attention. To that end, we compared the effects of exogenous and endogenous attention on the sensitivity to second-order, orientation-defined, texture patterns of either high or low second-order spatial frequencies. The results show that, like exogenous attention, endogenous attention enhances second-order contrast sensitivity at the attended location and reduces it at unattended locations. However, whereas the effects of exogenous attention are a function of the second-order spatial frequency content, endogenous attention affected second-order contrast sensitivity independent of the second-order spatial frequency content. This finding supports the notion that both exogenous and endogenous attention can affect second-order contrast sensitivity, but that endogenous attention is more flexible, benefitting performance under different conditions.