The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex

Neural manifolds in V1 change with top-down signals from V4 targeting the foveal region

High-dimensional brain activity is often organized into lower-dimensional neural manifolds. However, the neural manifolds of the visual cortex remain understudied. Here, we study large-scale multi-electrode electrophysiological recordings of macaque (Macaca mulatta) areas V1, V4, and DP with a high spatiotemporal resolution. We find that the population activity of V1 contains two separate neural manifolds, which correlate strongly with eye closure (eyes open/closed) and have distinct dimensionalities. Moreover, we find strong top-down signals from V4 to V1, particularly to the foveal region of V1, which are significantly stronger during the eyes-open periods. Finally, in silico simulations of a balanced spiking neuron network qualitatively reproduce the experimental findings. Taken together, our analyses and simulations suggest that top-down signals modulate the population activity of V1. We postulate that the top-down modulation during the eyes-open periods prepares V1 for fast and efficient visual responses, resulting in a type of visual stand-by state.

Population coding for figure-ground texture segregation in macaque V1 and V4

Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

Dependence of Contextual Modulation in Macaque V1 on Interlaminar Signal Flow

In visual cortex, neural correlates of subjective perception can be generated by modulation of activity from beyond the classical receptive field (CRF). In macaque V1, activity generated by nonclassical receptive field (nCRF) stimulation involves different intracortical circuitry than activity generated by CRF stimulation, suggesting that interactions between neurons across V1 layers differ under CRF and nCRF stimulus conditions. We measured border ownership modulation within large populations of V1 neurons. We found that neurons in single columns preferred the same side of objects located outside of the CRF. In addition, we found that interactions between pairs of neurons situated across feedback/horizontal and input layers differed between CRF and nCRF stimulation. Furthermore, the magnitude of border ownership modulation was predicted by greater information flow from feedback/horizontal to input layers. These results demonstrate that the flow of signals between layers covaries with the degree to which neurons integrate information from beyond the CRF.

Involvement of superior colliculus in complex figure detection of mice

Object detection is an essential function of the visual system. Although the visual cortex plays an important role in object detection, the superior colliculus can support detection when the visual cortex is ablated or silenced. Moreover, it has been shown that superficial layers of mouse SC (sSC) encode visual features of complex objects, and that this code is not inherited from the primary visual cortex. This suggests that mouse sSC may provide a significant contribution to complex object vision. Here, we use optogenetics to show that mouse sSC is involved in figure detection based on differences in figure contrast, orientation, and phase. Additionally, our neural recordings show that in mouse sSC, image elements that belong to a figure elicit stronger activity than those same elements when they are part of the background. The discriminability of this neural code is higher for correct trials than for incorrect trials. Our results provide new insight into the behavioral relevance of the visual processing that takes place in sSC.

How deep is the brain? The shallow brain hypothesis

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

The exclusionary approach to consciousness

The standard approach in the field of consciousness research involves identifying the neural correlates of consciousness (NCCs) by comparing neural activity between conscious and unconscious trials. However, this method has been met with criticism due to the lack of consensus on how to operationalize and measure consciousness. In this paper, I propose an alternative approach: the exclusionary approach. Rather than utilizing near-threshold conditions to contrast conscious and unconscious trials, this approach leverages the widely accepted notion that subjective reports are reliable under normal conditions. I propose that this can be done by assessing whether consciousness remains stable across trials while manipulating other factors such as reports, tasks, stimulation, or attention. We can use the resulting contrast to exclude certain kinds of neural activity as candidate NCCs. This method produces results that are less contentious, allowing for the establishment of hard criteria for theories of consciousness. Additionally, this approach does not require the development of new research paradigms, but can incorporate existing studies, particularly those aimed at identifying confounding factors in the standard approach. It is important to note, however, that the proposed exclusionary approach does not negate the value of the identification approach. Rather, they should be considered as complementary methods.

Different patterns of foreground and background processing contribute to texture segregation in humans: an electrophysiological study

Background

Figure-ground segregation is a necessary process for accurate visual recognition. Previous neurophysiological and human brain imaging studies have suggested that foreground-background segregation relies on both enhanced foreground representation and suppressed background representation. However, in humans, it is not known when and how foreground and background processing play a role in texture segregation.

Methods

To answer this question, it is crucial to extract and dissociate the neural signals elicited by the foreground and background of a figure texture with high temporal resolution. Here, we combined an electroencephalogram (EEG) recording and a temporal response function (TRF) approach to specifically track the neural responses to the foreground and background of a figure texture from the overall EEG recordings in the luminance-tracking TRF. A uniform texture was included as a neutral condition. The texture segregation visual evoked potential (tsVEP) was calculated by subtracting the uniform TRF from the foreground and background TRFs, respectively, to index the specific segregation activity.

Results

We found that the foreground and background of a figure texture were processed differently during texture segregation. In the posterior region of the brain, we found a negative component for the foreground tsVEP in the early stage of foreground-background segregation, and two negative components for the background tsVEP in the early and late stages. In the anterior region, we found a positive component for the foreground tsVEP in the late stage, and two positive components for the background tsVEP in the early and late stages of texture processing.

Discussion

In this study we investigated the temporal profile of foreground and background processing during texture segregation in human participants at a high time resolution. The results demonstrated that the foreground and background jointly contribute to figure-ground segregation in both the early and late phases of texture processing. Our findings provide novel evidence for the neural correlates of foreground-background modulation during figure-ground segregation in humans.

Feedforward attentional selection in sensory cortex

Salient objects grab attention because they stand out from their surroundings. Whether this phenomenon is accomplished by bottom-up sensory processing or requires top-down guidance is debated. We tested these alternative hypotheses by measuring how early and in which cortical layer(s) neural spiking distinguished a target from a distractor. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of male macaque monkeys performing visual search for a color singleton. A neural signature of attentional capture was observed in the earliest response in the input layer 4. The magnitude of this response predicted response time and accuracy. Errant behavior followed errant selection. Because this response preceded top-down influences and arose in the cortical layer not targeted by top-down connections, these findings demonstrate that feedforward activation of sensory cortex can underlie attentional priority.

The representation of occluded image regions in area V1 of monkeys and humans

Neuronal activity in the primary visual cortex (V1) is driven by feedforward input from within the neurons' receptive fields (RFs) and modulated by contextual information in regions surrounding the RF. The effect of contextual information on spiking activity occurs rapidly and is therefore challenging to dissociate from feedforward input. To address this challenge, we recorded the spiking activity of V1 neurons in monkeys viewing either natural scenes or scenes where the information in the RF was occluded, effectively removing the feedforward input. We found that V1 neurons responded rapidly and selectively to occluded scenes. V1 responses elicited by occluded stimuli could be used to decode individual scenes and could be predicted from those elicited by non-occluded images, indicating that there is an overlap between visually driven and contextual responses. We used representational similarity analysis to show that the structure of V1 representations of occluded scenes measured with electrophysiology in monkeys correlates strongly with the representations of the same scenes in humans measured with functional magnetic resonance imaging (fMRI). Our results reveal that contextual influences rapidly alter V1 spiking activity in monkeys over distances of several degrees in the visual field, carry information about individual scenes, and resemble those in human V1. VIDEO ABSTRACT.

Eye movements are made to the centre of gravity of texture-defined targets

Saccadic localisation of targets of various properties has been extensively studied, but rarely for texture-defined figures. In this paper, three experiments that investigate the way information from a texture target is processed in order to provide a signal for eye movement control are presented. Participants made saccades to target regions embedded in a background structure, and the saccade landing position and latency were measured. The textures comprised line elements, with orientations of the lines configured to form the figure and ground. Various orientation profile configurations (Block, Blur, and Cornsweet), were used in order to measure the role of edge profiles in driving eye movements and producing salience. We found that in all cases the visual system is in fact able to effectively segregate a texture figure from the ground in order to accurately plan a saccade to the target-figure. While saccadic latency was the highest for the Blur profile, the mean saccadic landing position was mostly unaffected by the various profiles (Experiment 1). More specifically, we showed that saccades were directed to the centre-of-gravity of the target (Experiment 2). We also found that figures with information of orientation contrast at both the edge and centre of figure (i.e. Block) produced the highest level of saliency in attracting eye movements (Experiment 3). Overall, the results show that saccades are planned on the representation of the whole target shape rather than a local salient region based on orientation contrast cues, and that the various texture profiles were important only to the extent that they affected the time to programme a saccade.

Solving the binding problem: Assemblies form when neurons enhance their firing rate-they don't need to oscillate or synchronize

When we look at an image, its features are represented in our visual system in a highly distributed manner, calling for a mechanism that binds them into coherent object representations. There have been different proposals for the neuronal mechanisms that can mediate binding. One hypothesis is that binding is achieved by oscillations that synchronize neurons representing features of the same perceptual object. This view allows separate communication channels between different brain areas. Another hypothesis is that binding of features that are represented in different brain regions occurs when the neurons in these areas that respond to the same object simultaneously enhance their firing rate, which would correspond to directing object-based attention to these features. This review summarizes evidence in favor of and against these two hypotheses, examining the neuronal correlates of binding and assessing the time course of perceptual grouping. I conclude that enhanced neuronal firing rates bind features into coherent object representations, whereas oscillations and synchrony are unrelated to binding.

Mice and primates use distinct strategies for visual segmentation

The rodent visual system has attracted great interest in recent years due to its experimental tractability, but the fundamental mechanisms used by the mouse to represent the visual world remain unclear. In the primate, researchers have argued from both behavioral and neural evidence that a key step in visual representation is 'figure-ground segmentation', the delineation of figures as distinct from backgrounds. To determine if mice also show behavioral and neural signatures of figure-ground segmentation, we trained mice on a figure-ground segmentation task where figures were defined by gratings and naturalistic textures moving counterphase to the background. Unlike primates, mice were severely limited in their ability to segment figure from ground using the opponent motion cue, with segmentation behavior strongly dependent on the specific carrier pattern. Remarkably, when mice were forced to localize naturalistic patterns defined by opponent motion, they adopted a strategy of brute force memorization of texture patterns. In contrast, primates, including humans, macaques, and mouse lemurs, could readily segment figures independent of carrier pattern using the opponent motion cue. Consistent with mouse behavior, neural responses to the same stimuli recorded in mouse visual areas V1, RL, and LM also did not support texture-invariant segmentation of figures using opponent motion. Modeling revealed that the texture dependence of both the mouse's behavior and neural responses could be explained by a feedforward neural network lacking explicit segmentation capabilities. These findings reveal a fundamental limitation in the ability of mice to segment visual objects compared to primates.

Contextual drive of neuronal responses in mouse V1 in the absence of feedforward input

Neurons in the primary visual cortex (V1) respond to stimuli in their receptive field (RF), which is defined by the feedforward input from the retina. However, V1 neurons are also sensitive to contextual information outside their RF, even if the RF itself is unstimulated. Here, we examined the cortical circuits for V1 contextual responses to gray disks superimposed on different backgrounds. Contextual responses began late and were strongest in the feedback-recipient layers of V1. They differed between the three main classes of inhibitory neurons, with particularly strong contextual drive of VIP neurons, indicating a contribution of disinhibitory circuits to contextual drive. Contextual drive was strongest when the gray disk was perceived as figure, occluding its background, rather than a hole. Our results link contextual drive in V1 to perceptual organization and provide previously unknown insight into how recurrent processing shapes the response of sensory neurons to facilitate figure perception.

Correlation between neural responses and human perception in figure-ground segregation

Segmentation of a natural scene into objects (figures) and background (ground) is one of crucial functions for object recognition and scene understanding. Recent studies have investigated neural mechanisms underlying figure-ground (FG) segregation and reported neural modulation to FG in the intermediate-level visual area, V4, of macaque monkeys (FG neurons). However, whether FG neurons contribute to the perception of FG segregation has not been clarified. To examine the contribution of FG neurons, we examined the correlations between perceptual consistency (PC), which quantified perceptual ambiguity in FG determination, and the reliability of neural signals in response to FG. First, we evaluated PCs for the images that were used in the previous neural recording in V4; specifically, we measured how consistently FG can be determined across trials and participants for each stimulus. The PCs were widely distributed, so that we identified the ambiguity in FG segregation for each stimulus. Next, we analyzed the correlation between the PCs and the reliability of neural modulation to FG. We found that the stimuli with higher PCs evoked more consistent and greater modulation in the responses of single neurons than those with lower PCs. Since perception is expected to show a greater correlation with responses of neural population compared to those of single neurons, we examined the correlation between the PCs and the consistency of the population responses in FG determination. Stimuli with higher PCs evoked higher population consistency than those with lower PCs. Finally, we analyzed the correlation between the PCs and neural latencies in FG modulation. We found that the stimuli with higher PCs showed shorter reaction times in FG perception and evoked shorter modulation latencies in FG neurons. These results indicate that the responses of FG neurons recorded from macaque monkeys show significant correlations with human FG perception, suggesting that V4 neurons with FG-dependent responses contribute to the perception of FG segregation.

Independent repetition suppression in macaque area V2 and inferotemporal cortex

When a complexly structured natural image is presented twice in succession, first as adapter and then as test, neurons in area TE of macaque inferotemporal cortex exhibit repetition suppression, responding less strongly to the second presentation than to the first. This phenomenon, which has been studied primarily in TE, might plausibly be argued to arise in TE because TE neurons respond selectively to complex images and thus carry information adequate for determining whether an image is or is not a repeat. However, the idea has never been put to a direct test. To resolve this issue, we monitored neuronal responses to sequences of complex natural images under identical conditions in areas V2 and TE. We found that repetition suppression occurs in both areas. Moreover, in each area, suppression takes the form of a dynamic alteration whereby the initial peak of excitation is followed by a trough and then a rebound of firing rate. To assess whether repetition suppression in either area is transmitted from the other area, we analyzed the timing of the phenomenon and its degree of spatial generalization. Suppression occurs at shorter latency in V2 than in TE. Therefore it is not simply fed back from TE. Suppression occurs in TE but not in V2 under conditions in which the test and adapter are presented in different visual field quadrants. Therefore it is not simply fed forward from V2. We conclude that repetition suppression occurs independently in V2 and TE.NEW & NOTEWORTHY When a complexly structured natural image is presented twice in rapid succession, neurons in inferotemporal area TE exhibit repetition suppression, responding less strongly to the second than to the first presentation. We have explored whether this phenomenon is confined to high-order areas where neurons respond selectively to such images and thus carry information relevant to recognizing a repeat. We have found surprisingly that repetition suppression occurs even in low-order visual area V2.

How Do Neural Networks Estimate Optical Flow? A Neuropsychology-Inspired Study

End-to-end trained convolutional neural networks have led to a breakthrough in optical flow estimation. The most recent advances focus on improving the optical flow estimation by improving the architecture and setting a new benchmark on the publicly available MPI-Sintel dataset. Instead, in this article, we investigate how deep neural networks estimate optical flow. A better understanding of how these networks function is important for (i) assessing their generalization capabilities to unseen inputs, and (ii) suggesting changes to improve their performance. For our investigation, we focus on FlowNetS, as it is the prototype of an encoder-decoder neural network for optical flow estimation. Furthermore, we use a filter identification method that has played a major role in uncovering the motion filters present in animal brains in neuropsychological research. The method shows that the filters in the deepest layer of FlowNetS are sensitive to a variety of motion patterns. Not only do we find translation filters, as demonstrated in animal brains, but thanks to the easier measurements in artificial neural networks, we even unveil dilation, rotation, and occlusion filters. Furthermore, we find similarities in the refinement part of the network and the perceptual filling-in process which occurs in the mammal primary visual cortex.

Cognitive penetrability of scene representations based on horizontal image disparities

The structure of natural scenes is signaled by many visual cues. Principal amongst them are the binocular disparities created by the laterally separated viewpoints of the two eyes. Disparity cues are believed to be processed hierarchically, first in terms of local measurements of absolute disparity and second in terms of more global measurements of relative disparity that allow extraction of the depth structure of a scene. Psychophysical and oculomotor studies have suggested that relative disparities are particularly relevant to perception, whilst absolute disparities are not. Here, we compare neural responses to stimuli that isolate the absolute disparity cue with stimuli that contain additional relative disparity cues, using the high temporal resolution of EEG to determine the temporal order of absolute and relative disparity processing. By varying the observers' task, we assess the extent to which each cue is cognitively penetrable. We find that absolute disparity is extracted before relative disparity, and that task effects arise only at or after the extraction of relative disparity. Our results indicate a hierarchy of disparity processing stages leading to the formation of a proto-object representation upon which higher cognitive processes can act.

Visual hallucinosis during hypoperfusion of the right occipito-temporal cortex

Objectives

Positive visual phenomena, although reported in lesions of visual cortex, are often overlooked in patients with acute neurological conditions. Yet, their occurrence without structural abnormalities or other underlying neurological disorders represents a unique observation. This report aims to raise awareness of these phenomena, their implications for understanding visual consciousness and to propose a practical, structured algorithm for the clinical assessment of visual hallucinations related to neurological conditions.

Methods

We describe the clinical presentation and imaging findings in two patients with isolated visual hallucinosis secondary to transitory hypoperfusion.

Results

One patient presented with subocclusion of the right posterior cerebral artery and the other with multifocal arterial abnormalities suggestive of reversible cerebral vasoconstriction syndrome (RCVS). Both presented isolated visual hallucinations and hypoperfusion of the right mesial occipito-temporal cortex. Hallucinated images exhibited peculiarities of certain attributes that were recognized only through guided perceptual analysis performed during their occurrence.

Discussion

Dysfunctions in the visual and attentional networks due to the uneven impact of hypoperfusion on the regions of the mesial occipito-temporal cortex likely contributed to the occurrence of visual hallucinations. The initial impaired awareness of certain image attributes obscured an altered, non-realistic rendering of the hallucinated images. Enhancement of awareness through clinical guidance indicates improved attentional deployment, modulation of visual information processing and hallucination–background integration. These features of the hallucinatory phenomena highlight the critical role of semiological analysis during their occurrence and question the validity of post hoc inquiries.

Horizontal connectivity in V1: Prediction of coherence in contour and motion integration

This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150–250°/s when it matches the propagation speed of horizontal connectivity (0.15–0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal “prediction” wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.

Figure-ground responsive fields of monkey V4 neurons estimated from natural image patches

Neurons in visual area V4 modulate their responses depending on the figure-ground (FG) organization in natural images containing a variety of shapes and textures. To clarify whether the responses depend on the extents of the figure and ground regions in and around the classical receptive fields (CRFs) of the neurons, we estimated the spatial extent of local figure and ground regions that evoked FG-dependent responses (RF-FGs) in natural images and their variants. Specifically, we applied the framework of spike triggered averaging (STA) to the combinations of neural responses and human-marked segmentation images (FG labels) that represent the extents of the figure and ground regions in the corresponding natural image stimuli. FG labels were weighted by the spike counts in response to the corresponding stimuli and averaged over. The bias due to the nonuniformity of FG labels was compensated by subtracting the ensemble average of FG labels from the weighted average. Approximately 50% of the neurons showed effective RF-FGs, and a large number exhibited structures that were similar to those observed in virtual neurons with ideal FG-dependent responses. The structures of the RF-FGs exhibited a subregion responsive to a preferred side (figure or ground) around the CRF center and a subregion responsive to a non-preferred side in the surroundings. The extents of the subregions responsive to figure were smaller than those responsive to ground in agreement with the Gestalt rule. We also estimated RF-FG by an adaptive filtering (AF) method, which does not require spherical symmetry (whiteness) in stimuli. RF-FGs estimated by AF and STA exhibited similar structures, supporting the veridicality of the proposed STA. To estimate the contribution of nonlinear processing in addition to linear processing, we estimated nonlinear RF-FGs based on the framework of spike triggered covariance (STC). The analyses of the models based on STA and STC did not show inconsiderable contribution of nonlinearity, suggesting spatial variance of FG regions. The results lead to an understanding of the neural responses that underlie the segregation of figures and the construction of surfaces in intermediate-level visual areas.

Purkinje Cell Activity in the Medial and Lateral Cerebellum During Suppression of Voluntary Eye Movements in Rhesus Macaques

Volitional suppression of responses to distracting external stimuli enables us to achieve our goals. This volitional inhibition of a specific behavior is supposed to be mainly mediated by the cerebral cortex. However, recent evidence supports the involvement of the cerebellum in this process. It is currently not known whether different parts of the cerebellar cortex play differential or synergistic roles in the planning and execution of this behavior. Here, we measured Purkinje cell (PC) responses in the medial and lateral cerebellum in two rhesus macaques during pro- and anti-saccade tasks. During an antisaccade trial, non-human primates (NHPs) were instructed to make a saccadic eye movement away from a target, rather than toward it, as in prosaccade trials. Our data show that the cerebellum plays an important role not only during the execution of the saccades but also during the volitional inhibition of eye movements toward the target. Simple spike (SS) modulation during the instruction and execution periods of pro- and anti-saccades was prominent in PCs of both the medial and lateral cerebellum. However, only the SS activity in the lateral cerebellar cortex contained information about stimulus identity and showed a strong reciprocal interaction with complex spikes (CSs). Moreover, the SS activity of different PC groups modulated bidirectionally in both of regions, but the PCs that showed facilitating and suppressive activity were predominantly associated with instruction and execution, respectively. These findings show that different cerebellar regions and PC groups contribute to goal-directed behavior and volitional inhibition, but with different propensities, highlighting the rich repertoire of the cerebellar control in executive functions.

Attention impedes neural representation of interpolated orientation during perceptual completion

One of the most remarkable functional feats accomplished by visual system is the interpolation of missing retinal inputs based on surrounding information, a process known as perceptual completion. Perceptual completion enables the active construction of coherent, vivid percepts from spatially discontinuous visual information that is prevalent in real-life visual scenes. Despite mounting evidence linking sensory activity enhancement and perceptual completion, surprisingly little is known about whether and how attention, a fundamental modulator of sensory activities, affects perceptual completion. Using EEG-based time-resolved inverted encoding model (IEM), we reconstructed the moment-to-moment representation of the illusory grating that resulted from spatially interpolating the orientation of surrounding inducers. We found that, despite manipulation of observers' attentional focus, the illusory grating representation unfolded in time in a similar manner. Critically, attention to the surrounding inducers simultaneously attenuated the illusory grating representation and delayed its temporal development. Our findings disclosed, for the first time, the suppressive role of selective attention in perceptual completion and were suggestive of a fast, automatic neural machinery that implements the interpolation of missing visual information.

Revisiting horizontal connectivity rules in V1: from like-to-like towards like-to-all

Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the similar length scale for the regularity found in cortical orientation maps, the currently accepted theoretical standpoint is that these maps are underpinned by a like-to-like connectivity rule: horizontal axons connect preferentially to neurons with similar preferred orientation. However, there is reason to doubt the rule's explanatory power, since a growing number of quantitative studies show that the like-to-like connectivity preference and bias mostly observed at short-range scale, are highly variable on a neuron-to-neuron level and depend on the origin of the presynaptic neuron. Despite the wide availability of published data, the accepted model of visual processing has never been revised. Here, we review three lines of independent evidence supporting a much-needed revision of the like-to-like connectivity rule, ranging from anatomy to population functional measures, computational models and to theoretical approaches. We advocate an alternative, distance-dependent connectivity rule that is consistent with new structural and functional evidence: from like-to-like bias at short horizontal distance to like-to-all at long horizontal distance. This generic rule accounts for the observed high heterogeneity in interactions between the orientation and retinotopic domains, that we argue is necessary to process non-trivial stimuli in a task-dependent manner.

Skeletal representations of shape in the human visual cortex

Shape perception is crucial for object recognition. However, it remains unknown exactly how shape information is represented and used by the visual system. Here, we tested the hypothesis that the visual system represents object shape via a skeletal structure. Using functional magnetic resonance imaging (fMRI) and representational similarity analysis (RSA), we found that a model of skeletal similarity explained significant unique variance in the response profiles of V3 and LO. Moreover, the skeletal model remained predictive in these regions even when controlling for other models of visual similarity that approximate low-to high-level visual features (i.e., Gabor-jet, GIST, HMAX, and AlexNet), and across different surface forms, a manipulation that altered object contours while preserving the underlying skeleton. Together, these findings shed light on shape processing in human vision, as well as the computational properties of V3 and LO. We discuss how these regions may support two putative roles of shape skeletons: namely, perceptual organization and object recognition.

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified "feature columns" which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4's superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Perceptual learning as a result of concerted changes in prefrontal and visual cortex

Our perceptual ability remarkably improves with training. Some studies on visual perceptual learning have shown refined neural representation of the trained stimulus in the visual cortex, whereas others have exclusively argued for improved readout and decision-making processes in the frontoparietal cortex. The mixed results have rendered the underlying neural mechanisms puzzling and hotly debated. By simultaneously recording from monkey visual area V4 and ventrolateral prefrontal cortex (PFC) implanted with microelectrode arrays, we dissected learning-induced cortical changes over the course of training the monkeys in a global form detection task. Decoding analysis dissociated two distinct components of neuronal population codes that were progressively and markedly enhanced in both V4 and PFC. One component was closely related to the target stimulus feature and was subject to task-dependent top-down modulation; it emerged earlier in V4 than PFC and its enhancement was specific to the trained configuration of the target stimulus. The other component of the neural code was entirely related to the animal's behavioral choice; it emerged earlier in PFC than V4 and its enhancement completely generalized to an untrained stimulus configuration. These results implicate two concurrent and synergistic learning processes: a perceptual process that is specific to the details of the trained stimulus feature and a cognitive process that is dependent on the total amount of learning experience in the trained task. When combined, these two learning processes were well predictive of the animal's learning behavior.

A parameter-free statistical test for neuronal responsiveness

Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that (1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations and (2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.

The Certainty of Ambiguity in Visual Neural Representations

Some images evoke bistable percepts: two different visual experiences seen in alternation while continuously viewing an unchanged stimulus. The Necker Cube and Rubin's Vase are classic examples, each of which gives alternating percepts of different shapes. Other bistable percepts are alternating colors or directions of motion. Although stimuli that result in salient bistability are rare and sometimes cleverly constructed to emphasize ambiguity, they have been influential for over 150 years, since the work of von Helmholtz, who considered them to be evidence for perceptual visual processes that interpret retinal stimuli. While bistability in natural viewing is uncommon, the main point of this review is that implicit ambiguity in visual neural representations is pervasive. Resolving ambiguity, therefore, is a fundamental and ubiquitous process of vision that routinely affects what we see, not an oddity arising from cleverly crafted images. This review focuses on the causes of widespread ambiguity, historical perspectives on it, and modern knowledge and theory about resolving it.

Perceived and mentally rotated contents are differentially represented in cortical depth of V1

Primary visual cortex (V1) in humans is known to represent both veridically perceived external input and internally-generated contents underlying imagery and mental rotation. However, it is unknown how the brain keeps these contents separate thus avoiding a mixture of the perceived and the imagined which could lead to potentially detrimental consequences. Inspired by neuroanatomical studies showing that feedforward and feedback connections in V1 terminate in different cortical layers, we hypothesized that this anatomical compartmentalization underlies functional segregation of external and internally-generated visual contents, respectively. We used high-resolution layer-specific fMRI to test this hypothesis in a mental rotation task. We found that rotated contents were predominant at outer cortical depth bins (i.e. superficial and deep). At the same time perceived contents were represented stronger at the middle cortical bin. These results identify how through cortical depth compartmentalization V1 functionally segregates rather than confuses external from internally-generated visual contents. These results indicate that feedforward and feedback manifest in distinct subdivisions of the early visual cortex, thereby reflecting a general strategy for implementing multiple cognitive functions within a single brain region.

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.

Salient objects dominate the central fixation bias when orienting toward images

Short-latency saccades are often biased toward salient objects or toward the center of images, for example, when inspecting photographs of natural scenes. Here, we measured the contribution of salient objects and central fixation bias to visual selection over time. Participants made saccades to images containing one salient object on a structured background and were instructed to either look at (i) the image center, (ii) the salient object, or (iii) at a cued position halfway in between the two. Results revealed, first, an early involuntary bias toward the image center irrespective of strategic behavior or the location of objects in the image. Second, the salient object bias was stronger than the center bias and prevailed over the latter when they directly competed for visual selection. In a second experiment, we tested whether the center bias depends on how well the image can be segregated from the monitor background. We asked participants to explore images that either did or did not contain a salient object while we manipulated the contrast between image background and monitor background to make the image borders more or less visible. The initial orienting toward the image was not affected by the image-monitor contrast, but only by the presence of objects-with a strong bias toward the center of images containing no object. Yet, a low image-monitor contrast reduced this center bias during the subsequent image exploration.

The essential role of recurrent processing for figure-ground perception in mice

The segregation of figures from the background is an important step in visual perception. In primary visual cortex, figures evoke stronger activity than backgrounds during a delayed phase of the neuronal responses, but it is unknown how this figure-ground modulation (FGM) arises and whether it is necessary for perception. Here, we show, using optogenetic silencing in mice, that the delayed V1 response phase is necessary for figure-ground segregation. Neurons in higher visual areas also exhibit FGM and optogenetic silencing of higher areas reduced FGM in V1. In V1, figures elicited higher activity of vasoactive intestinal peptide-expressing (VIP) interneurons than the background, whereas figures suppressed somatostatin-positive interneurons, resulting in an increased activation of pyramidal cells. Optogenetic silencing of VIP neurons reduced FGM in V1, indicating that disinhibitory circuits contribute to FGM. Our results provide insight into how lower and higher areas of the visual cortex interact to shape visual perception.

Vergence eye movements during figure-ground perception

Figure-ground, that is the segmentation of visual information into objects and their surrounding backgrounds, provides structure for visual attention. Recent evidence shows a novel role of vergence eye movements in visual attention. In the present work, vergence responses during figure-ground segregation tasks are psychophysically investigated. We show that during a figure-ground detection task, subjects convergence their eyes. Vergence eye movements are larger in figure trials than in ground trials. In detected figures trials, vergence are stronger than in trials where the figure went unnoticed. Moreover in figure trials, vergence responses are stronger to low-contrast figures than to high-contrast figures. We argue that these discriminative vergence responses have a role in figure-ground.

Correlated structure of neuronal firing in macaque visual cortex limits information for binocular depth discrimination

Variability in cortical neural activity potentially limits sensory discriminations. Theoretical work shows that information required to discriminate two similar stimuli is limited by the correlation structure of cortical variability. We investigated these information-limiting correlations by recording simultaneously from visual cortical areas primary visual cortex (V1) and extrastriate area V4 in macaque monkeys performing a binocular, stereo depth discrimination task. Within both areas, noise correlations on a rapid temporal scale (20–30 ms) were stronger for neuron pairs with similar selectivity for binocular depth, meaning that these correlations potentially limit information for making the discrimination. Between-area correlations (V1 to V4) were different, being weaker for neuron pairs with similar tuning and having a slower temporal scale (100+ ms). Fluctuations in these information-limiting correlations just prior to the detection event were associated with changes in behavioral accuracy. Although these correlations limit the recovery of information about sensory targets, their impact may be curtailed by integrative processing of signals across multiple brain areas.

NEW & NOTEWORTHY Correlated noise reduces the stimulus information in visual cortical neurons during experimental performance of binocular depth discriminations. The temporal scale of these correlations is important. Rapid (20–30 ms) correlations reduce information within and between areas V1 and V4, whereas slow (>100 ms) correlations between areas do not. Separate cortical areas appear to act together to maintain signal fidelity. Rapid correlations reduce the neuronal signal difference between stimuli and adversely affect perceptual discrimination.

Numerosity representation in a deep convolutional neural network

Enumerating objects in the environment (i.e., “number sense”) is crucial for survival in many animal species, and foundational for the construction of more abstract and complex mathematical knowledge in humans. Perhaps surprisingly, deep convolutional neural networks (DCNNs) spontaneously emerge a similar number sense even without any explicit training for numerosity estimation. However, little is known about how the number sense emerges, and the extent to which it is comparable with human number sense. Here, we examined whether the numerosity underestimation effect, a phenomenon indicating that numerosity perception acts upon the perceptual number rather than the physical number, can be observed in DCNNs. In a typical DCNN, AlexNet, we found that number-selective units at late layers operated on the perceptual number, like humans do. More importantly, this perceptual number sense did not emerge abruptly, rather developed progressively along the hierarchy in the DCNN, shifting from the physical number sense at early layers to perceptual number sense at late layers. Our finding hence provides important implications for the neural implementation of number sense in the human brain and advocates future research to determine whether the representation of numerosity also develops gradually along the human visual stream from physical number to perceptual number.

Correspondence between Monkey Visual Cortices and Layers of a Saliency Map Model Based on a Deep Convolutional Neural Network for Representations of Natural Images

Attentional selection is a function that allocates the brain’s computational resources to the most important part of a visual scene at a specific moment. Saliency map models have been proposed as computational models to predict attentional selection within a spatial location. Recent saliency map models based on deep convolutional neural networks (DCNNs) exhibit the highest performance for predicting the location of attentional selection and human gaze, which reflect overt attention. Trained DCNNs potentially provide insight into the perceptual mechanisms of biological visual systems. However, the relationship between artificial and neural representations used for determining attentional selection and gaze location remains unknown. To understand the mechanism underlying saliency map models based on DCNNs and the neural system of attentional selection, we investigated the correspondence between layers of a DCNN saliency map model and monkey visual areas for natural image representations. We compared the characteristics of the responses in each layer of the model with those of the neural representation in the primary visual (V1), intermediate visual (V4), and inferior temporal (IT) cortices. Regardless of the DCNN layer level, the characteristics of the responses were consistent with that of the neural representation in V1. We found marked peaks of correspondence between V1 and the early level and higher-intermediate-level layers of the model. These results provide insight into the mechanism of the trained DCNN saliency map model and suggest that the neural representations in V1 play an important role in computing the saliency that mediates attentional selection, which supports the V1 saliency hypothesis.

A Direct Comparison of Spatial Attention and Stimulus-Response Compatibility between Mice and Humans

Mice are becoming an increasingly popular model for investigating the neural substrates of visual processing and higher cognitive functions. To validate the translation of mouse visual attention and sensorimotor processing to humans, we compared their performance in the same visual task. Mice and human participants judged the orientation of a grating presented on either the right or left side in the visual field. To induce shifts of spatial attention, we varied the stimulus probability on each side. As expected, human participants showed faster RTs and a higher accuracy for the side with a higher probability, a well-established effect of visual attention. The attentional effect was only present in mice when their response was slow. Although the task demanded a judgment of grating orientation, the accuracy of the mice was strongly affected by whether the side of the stimulus corresponded to the side of the behavioral response. This stimulus-response compatibility (Simon) effect was much weaker in humans and only significant for their fastest responses. Both species exhibited a speed-accuracy trade-off in their responses, because slower responses were more accurate than faster responses. We found that mice typically respond very fast, which contributes to the stronger stimulus-response compatibility and weaker attentional effects, which were only apparent in the trials with slowest responses. Humans responded slower and had stronger attentional effects, combined with a weak influence of stimulus-response compatibility, which was only apparent in trials with fast responses. We conclude that spatial attention and stimulus-response compatibility influence the responses of humans and mice but that strategy differences between species determine the dominance of these effects.

Sparse deep predictive coding captures contour integration capabilities of the early visual system

Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to process context-dependent information in the early visual cortex. While numerous models have accounted for feedback effects at either neural or representational level, none of them were able to bind those two levels of analysis. Is it possible to describe feedback effects at both levels using the same model? We answer this question by combining Predictive Coding (PC) and Sparse Coding (SC) into a hierarchical and convolutional framework applied to realistic problems. In the Sparse Deep Predictive Coding (SDPC) model, the SC component models the internal recurrent processing within each layer, and the PC component describes the interactions between layers using feedforward and feedback connections. Here, we train a 2-layered SDPC on two different databases of images, and we interpret it as a model of the early visual system (V1 & V2). We first demonstrate that once the training has converged, SDPC exhibits oriented and localized receptive fields in V1 and more complex features in V2. Second, we analyze the effects of feedback on the neural organization beyond the classical receptive field of V1 neurons using interaction maps. These maps are similar to association fields and reflect the Gestalt principle of good continuation. We demonstrate that feedback signals reorganize interaction maps and modulate neural activity to promote contour integration. Third, we demonstrate at the representational level that the SDPC feedback connections are able to overcome noise in input images. Therefore, the SDPC captures the association field principle at the neural level which results in a better reconstruction of blurred images at the representational level.

A source for awareness-dependent figure-ground segregation in human prefrontal cortex

Figure-ground modulation, i.e., the enhancement of neuronal responses evoked by the figure relative to the background, has three complementary components: edge modulation (boundary detection), center modulation (region filling), and background modulation (background suppression). However, the neuronal mechanisms mediating these three modulations and how they depend on awareness remain unclear. For each modulation, we compared both the cueing effect produced in a Posner paradigm and fMRI blood oxygen-level dependent (BOLD) signal in primary visual cortex (V1) evoked by visible relative to invisible orientation-defined figures. We found that edge modulation was independent of awareness, whereas both center and background modulations were strongly modulated by awareness, with greater modulations in the visible than the invisible condition. Effective-connectivity analysis further showed that the awareness-dependent region-filling and background-suppression processes in V1 were not derived through intracortical interactions within V1, but rather by feedback from the frontal eye field (FEF) and dorsolateral prefrontal cortex (DLPFC), respectively. These results indicate a source for an awareness-dependent figure-ground segregation in human prefrontal cortex.

Visual Functions of Primate Area V4

Area V4-the focus of this review-is a mid-level processing stage along the ventral visual pathway of the macaque monkey. V4 is extensively interconnected with other visual cortical areas along the ventral and dorsal visual streams, with frontal cortical areas, and with several subcortical structures. Thus, it is well poised to play a broad and integrative role in visual perception and recognition-the functional domain of the ventral pathway. Neurophysiological studies in monkeys engaged in passive fixation and behavioral tasks suggest that V4 responses are dictated by tuning in a high-dimensional stimulus space defined by form, texture, color, depth, and other attributes of visual stimuli. This high-dimensional tuning may underlie the development of object-based representations in the visual cortex that are critical for tracking, recognizing, and interacting with objects. Neurophysiological and lesion studies also suggest that V4 responses are important for guiding perceptual decisions and higher-order behavior.

Neural signs and mechanisms of consciousness: Is there a potential convergence of theories of consciousness in sight?

Various theories for the neural basis of consciousness have been proposed, suggesting a diversity of neural signs and mechanisms. We ask to what extent this diversity is real, or whether many theories share the same basic ideas with a potential for convergence towards a more unified theory of the neural basis of consciousness. For that purpose, we review and compare the various neural signs, measures, and mechanisms proposed in the different theories. We demonstrate that different theories focus on neural signs and measures of distinct aspects of neural activity including stimulus-related, prestimulus, and resting state activity as well as on distinct features of consciousness. Therefore, the various mechanisms proposed in the different theories may, in part, complement each other. Together, we provide insight into the shared basis and convergences (and, in part, discrepancies) of the different theories of consciousness. We conclude that the different theories concern distinct aspects of both neural activity and consciousness which, as we suppose, may be integrated and nested within the brain's overall temporo-spatial dynamics.

Population coding of figure and ground in natural image patches by V4 neurons

Segmentation of a natural scene into objects and background is a fundamental but challenging task for recognizing objects. Investigating intermediate-level visual cortical areas with a focus on local information is a crucial step towards understanding the formation of the cortical representations of figure and ground. We examined the activity of a population of macaque V4 neurons during the presentation of natural image patches and their respective variations. The natural image patches were optimized to exclude the influence of global context but included various characteristics of local stimulus. Around one fourth of the patch-responsive V4 neurons exhibited significant modulation of firing activity that was dependent on the positional relation between the figural region of the stimulus and the classical receptive field of the neuron. However, the individual neurons showed low consistency in figure-ground modulation across a variety of image patches (55–62%), indicating that individual neurons were capable of correctly signaling figure and ground only for a limited number of stimuli. We examined whether integration of the activity of multiple neurons enabled higher consistency across a variety of natural patches by training a support vector machine to classify figure and ground of the stimuli from the population firing activity. The integration of the activity of a few tens of neurons yielded discrimination accuracy much greater than that of single neurons (up to 85%), suggesting a crucial role of population coding for figure-ground discrimination in natural images.

Fast and reversible neural inactivation in macaque cortex by optogenetic stimulation of GABAergic neurons

Optogenetic techniques for neural inactivation are valuable for linking neural activity to behavior but they have serious limitations in macaques. To achieve powerful and temporally precise neural inactivation, we used an adeno-associated viral (AAV) vector carrying the channelrhodopsin-2 gene under the control of a Dlx5/6 enhancer, which restricts expression to GABAergic neurons. We tested this approach in the primary visual cortex, an area where neural inactivation leads to interpretable behavioral deficits. Optical stimulation modulated spiking activity and reduced visual sensitivity profoundly in the region of space represented by the stimulated neurons. Rebound firing, which can have unwanted effects on neural circuits following inactivation, was not observed, and the efficacy of the optogenetic manipulation on behavior was maintained across >1000 trials. We conclude that this inhibitory cell-type-specific optogenetic approach is a powerful and spatiotemporally precise neural inactivation tool with broad utility for probing the functional contributions of cortical activity in macaques.

Topographic signatures of global object perception in human visual cortex

Our visual system readily groups dynamic fragmented input into global objects. How the brain represents global object perception remains however unclear. To address this question, we recorded brain responses using functional magnetic resonance imaging whilst observers viewed a dynamic bistable stimulus that could either be perceived globally (i.e., as a grouped and coherently moving shape) or locally (i.e., as ungrouped and incoherently moving elements). We further estimated population receptive fields and used these to back-project the brain activity measured during stimulus perception into visual space via a searchlight procedure. Global perception resulted in universal suppression of responses in lower visual cortex accompanied by wide-spread enhancement in higher object-sensitive cortex. However, follow-up experiments indicated that higher object-sensitive cortex is suppressed if global perception lacks shape grouping, and that grouping-related suppression can be diffusely confined to stimulated sites and accompanied by background enhancement once stimulus size is reduced. These results speak to a non-generic involvement of higher object-sensitive cortex in perceptual grouping and point to an enhancement-suppression mechanism mediating the perception of figure and ground.

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Lower visual cortex activity to grouped vs ungrouped dynamic stimuli is suppressed.

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When grouping a shape, activity in higher object-sensitive cortex is enhanced.

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Without shape grouping, activity in higher object-sensitive cortex is suppressed.

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Grouping-related suppression can be diffusely confined to stimulated cortical sites.

Searching for object pointers in the visual cortex

We perceive objects as permanent and stable despite frequent occlusions and eye movements, but their representation in the visual cortex is neither permanent nor stable. Feature selective cells respond only as long as objects are visible, and their responses depend on eye position. We explored the hypothesis that the system maintains object pointers that provide permanence and stability. Pointers should send facilitatory signals to the feature cells of an object, and these signals should persist across temporary occlusions and remap to compensate for image displacements caused by saccades. Here, we searched for such signals in monkey areas V2 and V4 (Macaca mulatta). We developed a new paradigm in which a monkey freely inspects an array of objects in search for reward while some of the objects are being occluded temporarily by opaque drifting strips. Two types of objects were used to manipulate attention. The results were as follows. 1) Eye movements indicated a robust representation of location and type of the occluded objects; 2) in neurons of V4, but not V2, occluded objects produced elevated activity relative to blank condition; 3) the elevation of activity was reduced for objects that had been fixated immediately before the current fixation ('inhibition of return'); and 4) when attended, or when the target of a saccade, visible objects produced enhanced responses in V4, but occluded objects produced no modulation. Although results 1-3 confirm the hypothesis, the absence of modulation under occlusion is not consistent. Further experiments are needed to resolve this discrepancy.NEW & NOTEWORTHY The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.

Resolving the Spatial Profile of Figure Enhancement in Human V1 through Population Receptive Field Modeling

The detection and segmentation of meaningful figures from their background is one of the primary functions of vision. While work in nonhuman primates has implicated early visual mechanisms in this figure-ground modulation, neuroimaging in humans has instead largely ascribed the processing of figures and objects to higher stages of the visual hierarchy. Here, we used high-field fMRI at 7 Tesla to measure BOLD responses to task-irrelevant orientation-defined figures in human early visual cortex (N = 6, four females). We used a novel population receptive field mapping-based approach to resolve the spatial profiles of two constituent mechanisms of figure-ground modulation: a local boundary response, and a further enhancement spanning the full extent of the figure region that is driven by global differences in features. Reconstructing the distinct spatial profiles of these effects reveals that figure enhancement modulates responses in human early visual cortex in a manner consistent with a mechanism of automatic, contextually driven feedback from higher visual areas.SIGNIFICANCE STATEMENT A core function of the visual system is to parse complex 2D input into meaningful figures. We do so constantly and seamlessly, both by processing information about visible edges and by analyzing large-scale differences between figure and background. While influential neurophysiology work has characterized an intriguing mechanism that enhances V1 responses to perceptual figures, we have a poor understanding of how the early visual system contributes to figure-ground processing in humans. Here, we use advanced computational analysis methods and high-field human fMRI data to resolve the distinct spatial profiles of local edge and global figure enhancement in the early visual system (V1 and LGN); the latter is distinct and consistent with a mechanism of automatic, stimulus-driven feedback from higher-level visual areas.

Tracking the completion of parts into whole objects: Retinotopic activation in response to illusory figures in the lateral occipital complex

Illusory figures demonstrate the visual system's ability to integrate separate parts into coherent, whole objects. The present study was performed to track the neuronal object construction process in human observers, by incrementally manipulating the grouping strength within a given configuration until the emergence of a whole-object representation. Two tasks were employed: First, in the spatial localization task, object completion could facilitate performance and was task-relevant, whereas it was irrelevant in the second, luminance discrimination task. Concurrent functional magnetic resonance imaging (fMRI) used spatial localizers to locate brain regions representing task-critical illusory-figure parts to investigate whether the step-wise object construction process would modulate neural activity in these localized brain regions. The results revealed that both V1 and the lateral occipital complex (LOC, with sub-regions LO1 and LO2) were involved in Kanizsa figure processing. However, completion-specific activations were found predominantly in LOC, where neural activity exhibited a modulation in accord with the configuration's grouping strength, whether or not the configuration was relevant to performing the task at hand. Moreover, right LOC activations were confined to LO2 and responded primarily to surface and shape completions, whereas left LOC exhibited activations in both LO1 and LO2 and was related to encoding shape structures with more detail. Together, these results demonstrate that various grouping properties within a visual scene are integrated automatically in LOC, with sub-regions located in different hemispheres specializing in the component sub-processes that render completed objects.

Normalization governs attentional modulation within human visual cortex

Although attention is known to increase the gain of visuocortical responses, its underlying neural computations remain unclear. Here, we use fMRI to test the hypothesis that a neural population’s ability to be modulated by attention is dependent on divisive normalization. To do so, we leverage the feature-tuned properties of normalization and find that visuocortical responses to stimuli sharing features normalize each other more strongly. Comparing these normalization measures to measures of attentional modulation, we demonstrate that subpopulations which exhibit stronger normalization also exhibit larger attentional benefits. In a converging experiment, we reveal that attentional benefits are greatest when a subpopulation is forced into a state of stronger normalization. Taken together, these results suggest that the degree to which a subpopulation exhibits normalization plays a role in dictating its potential for attentional benefits.

Attention is known to enhance relevant information in our environment, yet its underlying neural computations remain unclear. Here, the authors provide evidence that the degree to which a neural population can normalize itself results in greater potential for attentional benefits.