The neural substrates and timing of top-down processes during coarse-to-fine categorization of visual scenes: a combined fMRI and ERP study

Reduced spatial frequency differentiation and sex-related specificities in fearful face detection in autism: Insights from EEG and the predictive brain model

Face processing relies on predictive processes driven by low spatial frequencies (LSF) that convey coarse information prior to fine information conveyed by high spatial frequencies. However, autistic individuals might have atypical predictive processes, contributing to facial processing difficulties. This may be more normalized in autistic females, who often exhibit better socio-communicational abilities than males. We hypothesized that autistic females would display a more typical coarse-to-fine processing for socio-emotional stimuli compared to autistic males. To test this hypothesis, we asked adult participants (44 autistic, 51 non-autistic) to detect fearful faces among neutral faces, filtered in two orders: from coarse-to-fine (CtF) and from fine-to-coarse (FtC). Results show lower d' values and longer reaction times for fearful detection in autism compared to non-autistic (NA) individuals, regardless of the filtering order. Both groups presented shorter P100 latency after CtF compared to FtC, and larger amplitude for N170 after FtC compared to CtF. However, autistic participants presented a reduced difference in source activity between CtF and FtC in the fusiform. There was also a more spatially spread activation pattern in autistic females compared to NA females. Finally, females had faster P100 and N170 latencies, as well as larger occipital activation for FtC sequences than males, irrespective of the group. Overall, the results do not suggest impaired predictive processes from LSF in autism despite behavioral differences in fear detection. However, they do indicate reduced brain modulation by spatial frequency in autism. In addition, the findings highlight sex differences that warrant consideration in understanding autistic females.

Sex modulation of faces prediction error in the autistic brain

Recent research suggests that autistic females may have superior socio-cognitive abilities compared to autistic males, potentially contributing to underdiagnosis in females. However, it remains unclear whether these differences arise from distinct neurophysiological functioning in autistic males and females. This study addresses this question by presenting 41 autistic and 48 non-autistic adults with a spatially filtered faces oddball paradigm. Analysis of event-related potentials from scalp electroencephalography reveal a neurophysiological profile in autistic females that fell between those of autistic males and non-autistic females, highlighting sex differences in autism from the initial stages of face processing. This finding underscores the urgent need to explore neurophysiological sex differences in autism and encourages efforts toward a better comprehension of compensation mechanism and a clearer definition of what is meant by camouflaging.

Interaction between central and peripheral vision: Influence of distance and spatial frequencies

Visual scene perception is based on reciprocal interactions between central and peripheral information. Such interactions are commonly investigated through the semantic congruence effect, which usually reveals a congruence effect of central vision on peripheral vision as strong as the reverse. The aim of the present study was to further investigate the mechanisms underlying central-peripheral visual interactions using a central-peripheral congruence paradigm through three behavioral experiments. We presented simultaneously a central and a peripheral stimulus, that could be either semantically congruent or incongruent. To assess the congruence effect of central vision on peripheral vision, participants had to categorize the peripheral target stimulus while ignoring the central distractor stimulus. To assess the congruence effect of the peripheral vision on central vision, they had to categorize the central target stimulus while ignoring the peripheral distractor stimulus. Experiment 1 revealed that the physical distance between central and peripheral stimuli influences central-peripheral visual interactions: Congruence effect of central vision is stronger when the distance between the target and the distractor is the shortest. Experiments 2 and 3 revealed that the spatial frequency content of distractors also influence central-peripheral interactions: Congruence effect of central vision is observed only when the distractor contained high spatial frequencies while congruence effect of peripheral vision is observed only when the distractor contained low spatial frequencies. These results raise the question of how these influences are exerted (bottom-up vs. top-down) and are discussed based on the retinocortical properties of the visual system and the predictive brain hypothesis.

Glaucoma-associated abnormalities in cortical activity during a visuocognitive task

OBJECTIVE

To investigate neurophysiological dynamics during a visuocognitive task in glaucoma patients vs. healthy controls.

METHODS

Fifteen patients with early-stage primary open-angle glaucoma (POAG) and fifteen age-matched healthy participants underwent a "go/no-go" task, monitored with EEG. Participants had to semantically categorize visual objects in central vision, with animal or furniture as targets according to the experimental block.

RESULTS

Early visual processing was delayed by 50 ms in patients with POAG compared to controls. The patients displayed a smaller difference between animal and furniture categorization during higher-level cognitive processing (at 400-600 ms). Regarding behavioral data, the groups differed in accuracy performance and decision criterion. As opposed to the control group, patients did not display facilitation and a higher accuracy rate for animal stimuli. However, patients maintained a consistent decision criterion throughout the experiment, whereas controls displayed a shift towards worse decision criteria in furniture trials, with higher error rate.

CONCLUSIONS

The comparative analysis of behavioral and neurophysiological data revealed in POAG patients a delay in early visual processing, and potential high-level cognitive compensation during late, task-dependent activations.

SIGNIFICANCE

To our knowledge, our findings provide the first evidence of modification in cognitive brain dynamics associated with POAG.

Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding

The human visual system rapidly recognizes the categories and global properties of complex natural scenes. The present study investigated the spatiotemporal dynamics of neural signals involved in visual scene processing using electroencephalography (EEG) decoding. We recorded visual evoked potentials from 11 human observers for 232 natural scenes, each of which belonged to one of 13 natural scene categories (e.g., a bedroom or open country) and had three global properties (naturalness, openness, and roughness). We trained a deep convolutional classification model of the natural scene categories and global properties using EEGNet. Having confirmed that the model successfully classified natural scene categories and the three global properties, we applied Grad-CAM to the EEGNet model to visualize the EEG channels and time points that contributed to the classification. The analysis showed that EEG signals in the occipital electrodes at short latencies (approximately 80 ~ ms) contributed to the classifications, whereas those in the frontal electrodes at relatively long latencies (200 ~ ms) contributed to the classification of naturalness and the individual scene category. These results suggest that different global properties are encoded in different cortical areas and with different timings, and that the combination of the EEGNet model and Grad-CAM can be a tool to investigate both temporal and spatial distribution of natural scene processing in the human brain.

Detection of emotional faces: The role of spatial frequencies and local features

Models of emotion processing suggest that threat-related stimuli such as fearful faces can be detected based on the rapid extraction of low spatial frequencies. However, this remains debated as other models argue that the decoding of facial expressions occurs with a more flexible use of spatial frequencies. The purpose of this study was to clarify the role of spatial frequencies and differences in luminance contrast between spatial frequencies, on the detection of facial emotions. We used a saccadic choice task in which emotional-neutral face pairs were presented and participants were asked to make a saccade toward the neutral or the emotional (happy or fearful) face. Faces were displayed either in low, high, or broad spatial frequencies. Results showed that participants were better to saccade toward the emotional face. They were also better for high or broad than low spatial frequencies, and the accuracy was higher with a happy target. An analysis of the eye and mouth saliency ofour stimuli revealed that the mouth saliency of the target correlates with participants' performance. Overall, this study underlines the importance of local more than global information, and of the saliency of the mouth region in the detection of emotional and neutral faces.

Backward masking reveals coarse-to-fine dynamics in human V1

Natural images exhibit luminance variations aligned across a broad spectrum of spatial frequencies (SFs). It has been proposed that, at early stages of processing, the coarse signals carried by the low SF (LSF) of the visual input are sent rapidly from primary visual cortex (V1) to ventral, dorsal and frontal regions to form a coarse representation of the input, which is later sent back to V1 to guide the processing of fine-grained high SFs (i.e., HSF). We used functional resonance imaging (fMRI) to investigate the role of human V1 in the coarse-to-fine integration of visual input. We disrupted the processing of the coarse and fine content of full-spectrum human face stimuli via backward masking of selective SF ranges (LSFs: <1.75cpd and HSFs: >1.75cpd) at specific times (50, 83, 100 or 150ms). In line with coarse-to-fine proposals, we found that (1) the selective masking of stimulus LSF disrupted V1 activity in the earliest time window, and progressively decreased in influence, while (2) an opposite trend was observed for the masking of stimulus' HSF. This pattern of activity was found in V1, as well as in ventral (i.e. the Fusiform Face area, FFA), dorsal and orbitofrontal regions. We additionally presented subjects with contrast negated stimuli. While contrast negation significantly reduced response amplitudes in the FFA, as well as coupling between FFA and V1, coarse-to-fine dynamics were not affected by this manipulation. The fact that V1 response dynamics to strictly identical stimulus sets differed depending on the masked scale adds to growing evidence that V1 role goes beyond the early and quasi-passive transmission of visual information to the rest of the brain. It instead indicates that V1 may yield a 'spatially registered common forum' or 'blackboard' that integrates top-down inferences with incoming visual signals through its recurrent interaction with high-level regions located in the inferotemporal, dorsal and frontal regions.

Automatic adaptive emotion regulation is associated with lower emotion-related activation in the frontoparietal cortex and other cortical regions with multi-componential organization

Although some researchers consider automatic adaptive emotion regulation to be an automatized strategy whereas others consider it to be implicit disengagement of deliberative process, to date, its neural correlates have been poorly investigated. In addition, the valence specificity of automatic adaptive emotion regulation and levels of activation relative to the neutral condition are controversial; the former is relevant to the attribution of resilient emotion regulation to positivity bias or emotional stability, and the latter to determining whether regulation is based on emotion-specific or emotion-non-specific processes. In this functional magnetic resonance imaging (fMRI) study, we presented positive and negative emotional pictures to healthy young participants and investigated the neural correlates of automatic adaptive emotion regulation in spontaneous emotional response. A significant negative trait effect (i.e., regression coefficient) on activation was identified both for positive and negative emotional responses in various cortical regions. A cluster analysis identified three clusters among these regions based on the valence specificity of the trait effect and level of activation relative to neutral stimuli. Cluster 1 included regions in the sensorimotor cortex characterized by negative emotion-specific decreases in activation relative to neutral stimuli in adaptive individuals. Cluster 2 included several cortical regions including the bilateral dorsal executive network, anterior cingulate, and inferior frontal gyrus, which were characterized by valence-independent decreases in activation in adaptive individuals. Cluster 3 included the bilateral ventrolateral and dorsomedial prefrontal cortices, right insula, and other posterior regions, which were characterized by increased activation for negative stimuli in non-adaptive individuals. These findings support the assumption that automatic adaptive emotion regulation involves the implicit disengagement of deliberative process and suggest the relevance of different cortical networks to the potential emotion- and valence-specificity of adaptive regulation.

Impact of glaucoma on the spatial frequency processing of scenes in central vision

Glaucoma is an eye disease characterized by a progressive vision loss usually starting in peripheral vision. However, a deficit for scene categorization is observed even in the preserved central vision of patients with glaucoma. We assessed the processing and integration of spatial frequencies in the central vision of patients with glaucoma during scene categorization, considering the severity of the disease, in comparison to age-matched controls. In the first session, participants had to categorize scenes filtered in low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs) as a natural or an artificial scene. Results showed that the processing of spatial frequencies was impaired only for patients with severe glaucoma, in particular for HFS scenes. In the light of proactive models of visual perception, we investigated how LSF could guide the processing of HSF in a second session. We presented hybrid scenes (combining LSF and HSF from two scenes belonging to the same or different semantic category). Participants had to categorize the scene filtered in HSF while ignoring the scene filtered in LSF. Surprisingly, results showed that the semantic influence of LSF on HSF was greater for patients with early glaucoma than controls, and then disappeared for the severe cases. This study shows that a progressive destruction of retinal ganglion cells affects the spatial frequency processing in central vision. This deficit may, however, be compensated by increased reliance on predictive mechanisms at early stages of the disease which would however decline in more severe cases.

The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings

Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for drawings and natural images, which suggests that similar mechanisms underlie the recognition of both. However, other work has proposed that representations of drawings and natural images become similar only after substantial processing has taken place, suggesting distinct mechanisms. To arbitrate between those alternatives, we measured brain responses resolved in space and time using fMRI and MEG, respectively, while human participants (female and male) viewed images of objects depicted as photographs, line drawings, or sketch-like drawings. Using multivariate decoding, we demonstrate that object category information emerged similarly fast and across overlapping regions in occipital, ventral-temporal, and posterior parietal cortex for all types of depiction, yet with smaller effects at higher levels of visual abstraction. In addition, cross-decoding between depiction types revealed strong generalization of object category information from early processing stages on. Finally, by combining fMRI and MEG data using representational similarity analysis, we found that visual information traversed similar processing stages for all types of depiction, yet with an overall stronger representation for photographs. Together, our results demonstrate broad commonalities in the neural dynamics of object recognition across types of depiction, thus providing clear evidence for shared neural mechanisms underlying recognition of natural object images and abstract drawings.SIGNIFICANCE STATEMENT When we see a line drawing, we effortlessly recognize it as an object in the world despite its simple and abstract style. Here we asked to what extent this correspondence in perception is reflected in the brain. To answer this question, we measured how neural processing of objects depicted as photographs and line drawings with varying levels of detail (from natural images to abstract line drawings) evolves over space and time. We find broad commonalities in the spatiotemporal dynamics and the neural representations underlying the perception of photographs and even abstract drawings. These results indicate a shared basic mechanism supporting recognition of drawings and natural images.

Threat shapes visual context sensitivity selectively through low-spatial-frequency channels

Threat has long been supposed to affect human cognitive processing including visual size perception. Whether such threat-related modulation effect varies as a function of spatial frequency is largely unexplored. Here we used low- or high-pass filtered threatening animal and fearful face images as primes and measured their effects on the processing of the Ebbinghaus illusion. Results showed that threatening-animal primes relative to neutral ones significantly decreased the illusion magnitude in low-spatial-frequency rather than in high-spatial-frequency ranges. However, fearful- and neutral-face primes had a comparable effect on the illusion magnitude in both spatial frequency ranges. Notably, when inhibitory transcranial magnetic stimulation was applied to the left temporo-parietal junction (TPJ), fearful-face primes significantly decreased the illusion magnitude in low-spatial-frequency rather than in high-spatial-frequency ranges. However, the opposite pattern of results was observed with right TPJ stimulation. The findings suggest that threat shapes basic aspects of visual perception in a spatial frequency-specific manner, possibly via magnocellular projections from both subcortical and cortical fear-processing systems to early visual cortex.

High spatial frequencies disrupt conscious visual recognition: evidence from an attentional blink paradigm

In this article, we tested the respective importance of low spatial frequencies (LSF) and high spatial frequencies (HSF) for conscious visual recognition of emotional stimuli by using an attentional blink paradigm. Thirty-eight participants were asked to identify and report two targets (happy faces) embedded in a rapid serial visual presentation of distractors (angry faces). During attentional blink, conscious perception of the second target (T2) is usually altered when the lag between the two targets is short (200-500 ms) but is restored at longer lags. The distractors between T1 and T2 were either non-filtered (broad spatial frequencies, BSF), low-pass filtered (LSF), or high-pass filtered (HSF). Assuming that prediction abilities could be at the root of conscious visual recognition, we expected that LSF distractors could result in a greater disturbance of T2 reporting than HSF distractors. Results showed that both LSF and HSF play a role in the emergence of exogenous consciousness in the visual system. Furthermore, HSF distractors strongly affected T1 and T2 reporting irrespective of the lag between targets, suggesting their role for facial emotion processing. We discuss these results with regards to other models of visual recognition. .

Coarse-to-fine processing drives the efficient coding of natural scenes in mouse visual cortex

The visual system processes sensory inputs sequentially, perceiving coarse information before fine details. Here we study the neural basis of coarse-to-fine processing and its computational benefits in natural vision. We find that primary visual cortical neurons in awake mice respond to natural scenes in a coarse-to-fine manner, primarily driven by individual neurons rapidly shifting their spatial frequency preference from low to high over a brief response period. This shift transforms the population response in a way that counteracts the statistical regularities of natural scenes, thereby reducing redundancy and generating a more efficient neural representation. The increase in representational efficiency does not occur in either dark-reared or anesthetized mice, which show significantly attenuated coarse-to-fine spatial processing. Collectively, these results illustrate that coarse-to-fine processing is state dependent, develops postnatally via visual experience, and provides a computational advantage by generating more efficient representations of the complex spatial statistics of ethologically relevant natural scenes.

Skyberg et al. show that the visual cortex of mice processes natural scenes in a coarse-to-fine manner, driven by individual neuron’s temporal dynamics. These response dynamics, which require visual experience to develop, reduce redundancy in the neural code and lead to more efficient representations of complex visual stimuli.

Amygdala function in emotion, cognition, and behavior

The amygdala is a core structure in the anterior medial temporal lobe, with an important role in several brain functions involving memory, emotion, perception, social cognition, and even awareness. As a key brain structure for saliency detection, it triggers and controls widespread modulatory signals onto multiple areas of the brain, with a great impact on numerous aspects of adaptive behavior. Here we discuss the neural mechanisms underlying these functions, as established by animal and human research, including insights provided in both healthy and pathological conditions.

High spatial frequency filtered primes hastens happy faces categorization in autistic adults

Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging, and might be related to alterations in LSF predictive processes. We analyzed the data of 27 autistic and 34 non autistic (NA) adults on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs.LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face compared to HSF primes, in the NA group but not in autism. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups. Moreover, the advantage of HSF vs.LSF primes was stronger for angry than happy faces in NA, but was stronger for happy than angry faces in autistic participants. Drift diffusion modelling confirmed HSF advantage and showed a longer non-decision time (e.g., encoding) in autism. Despite LSF predictive impairments in autism was not corroborated, our analyses suggest low level processing specificities in autism.

Differential neurodynamics and connectivity in the dorsal and ventral visual pathways during perception of emotional crowds and individuals: a MEG study

Reading the prevailing emotion of groups of people ("crowd emotion") is critical to understanding their overall intention and disposition. It alerts us to potential dangers, such as angry mobs or panicked crowds, giving us time to escape. A critical aspect of processing crowd emotion is that it must occur rapidly, because delays often are costly. Although knowing the timing of neural events is crucial for understanding how the brain guides behaviors using coherent signals from a glimpse of multiple faces, this information is currently lacking in the literature on face ensemble coding. Therefore, we used magnetoencephalography to examine the neurodynamics in the dorsal and ventral visual streams and the periamygdaloid cortex to compare perception of groups of faces versus individual faces. Forty-six participants compared two groups of four faces or two individual faces with varying emotional expressions and chose which group or individual they would avoid. We found that the dorsal stream was activated as early as 68 msec after the onset of stimuli containing groups of faces. In contrast, the ventral stream was activated later and predominantly for individual face stimuli. The latencies of the dorsal stream activation peaks correlated with participants' response times for facial crowds. We also found enhanced connectivity earlier between the periamygdaloid cortex and the dorsal stream regions for crowd emotion perception. Our findings suggest that ensemble coding of facial crowds proceeds rapidly and in parallel by engaging the dorsal stream to mediate adaptive social behaviors, via a distinct route from single face perception.

Semantic and Physical Properties of Peripheral Vision Are Used for Scene Categorization in Central Vision

Theories of visual recognition postulate that our ability to understand our visual environment at a glance is based on the extraction of the gist of the visual scene, a first global and rudimentary visual representation. Gist perception would be based on the rapid analysis of low spatial frequencies in the visual signal and would allow a coarse categorization of the scene. We aimed to study whether the low spatial resolution information available in peripheral vision could modulate the processing of visual information presented in central vision. We combined behavioral measures (Experiments 1 and 2) and fMRI measures (Experiment 2). Participants categorized a scene presented in central vision (artificial vs. natural categories) while ignoring another scene, either semantically congruent or incongruent, presented in peripheral vision. The two scenes could either share the same physical properties (similar amplitude spectrum and spatial configuration) or not. Categorization of the central scene was impaired by a semantically incongruent peripheral scene, in particular when the two scenes were physically similar. This semantic interference effect was associated with increased activation of the inferior frontal gyrus. When the two scenes were semantically congruent, the dissimilarity of their physical properties impaired the categorization of the central scene. This effect was associated with increased activation in occipito-temporal areas. In line with the hypothesis of predictive mechanisms involved in visual recognition, results suggest that semantic and physical properties of the information coming from peripheral vision would be automatically used to generate predictions that guide the processing of signal in central vision.

Neural correlates of visuoperceptive changes in severe alcohol use disorder: A critical review of neuroimaging and electrophysiological findings

Visuoperceptive deficits are frequently reported in severe alcohol use disorder (SAUD) and are considered as pervasive and persistent in time. While this topic of investigation has previously driven researchers' interest, far fewer studies have focused on visuoperception in SAUD since the '90s, leaving open central questions regarding the origin and implications of these deficits. To renew research in the field and provide a solid background to work upon, this paper reviews the neural correlates of visuoperception in SAUD, based on data from neuroimaging and electrophysiological studies. Results reveal structural and functional changes within the visual system but also in the connections between occipital and frontal areas. We highlight the lack of integration of these findings in the dominant models of vision which stress the dynamic nature of the visual system and consider the presence of both bottom-up and top-down cerebral mechanisms. Visuoperceptive changes are also discussed in the framework of long-lasting debates regarding the influence of demographic and alcohol-related factors, together stressing the presence of inter-individual differences. Capitalizing on this review, we provide guidelines to inform future research, and ultimately improve clinical care.

Get Your Guidance Going: Investigating the Activation of Spatial Priors for Efficient Search in Virtual Reality

Repeated search studies are a hallmark in the investigation of the interplay between memory and attention. Due to a usually employed averaging, a substantial decrease in response times occurring between the first and second search through the same search environment is rarely discussed. This search initiation effect is often the most dramatic decrease in search times in a series of sequential searches. The nature of this initial lack of search efficiency has thus far remained unexplored. We tested the hypothesis that the activation of spatial priors leads to this search efficiency profile. Before searching repeatedly through scenes in VR, participants either (1) previewed the scene, (2) saw an interrupted preview, or (3) started searching immediately. The search initiation effect was present in the latter condition but in neither of the preview conditions. Eye movement metrics revealed that the locus of this effect lies in search guidance instead of search initiation or decision time, and was beyond effects of object learning or incidental memory. Our study suggests that upon visual processing of an environment, a process of activating spatial priors to enable orientation is initiated, which takes a toll on search time at first, but once activated it can be used to guide subsequent searches.

The Brain’s Asymmetric Frequency Tuning: Asymmetric Behavior Originates from Asymmetric Perception

To construct a coherent multi-modal percept, vertebrate brains extract low-level features (such as spatial and temporal frequencies) from incoming sensory signals. However, because frequency processing is lateralized with the right hemisphere favouring low frequencies while the left favours higher frequencies, this introduces asymmetries between the hemispheres. Here, we describe how this lateralization shapes the development of several cognitive domains, ranging from visuo-spatial and numerical cognition to language, social cognition, and even aesthetic appreciation, and leads to the emergence of asymmetries in behaviour. We discuss the neuropsychological and educational implications of these emergent asymmetries and suggest future research approaches.

Visual Hallucinations and Impaired Conscious Visual Perception in Parkinson Disease

Visual hallucinations (VHs) are common in patients with Parkinson disease (PD), especially those with dementia, whereas auditory hallucinations are quite rare. Recent studies have revealed the involvement of several regions along the visual information-processing system that contribute to the pathophysiological mechanism of VHs: the eyes and retina, retinofugal projection, lateral geniculate nucleus, striate cortex, ventral pathways in the temporal cortices, and frontal and parietal cortices. In addition, the concurrent involvement of other systems in the brainstem and basal forebrain further modify VHs in PD. In this review, we discuss the pathophysiological association between the regional involvement of these areas and VHs.

Learning Layer-Skippable Inference Network

The process of learning good representations for machine learning tasks can be very computationally expensive. Typically, we facilitate the same backbones learned on the training set to infer the labels of testing data. Interestingly, This learning and inference paradigm, however, is quite different from the typical inference scheme of human biological visual systems. Essentially, neuroscience studies have shown that the right hemisphere of the human brain predominantly makes a fast processing of low-frequency spatial signals, while the left hemisphere more focuses on analyzing high-frequency information in a slower way. And the low-pass analysis helps facilitate the high-pass analysis via a feedback form. Inspired by this biological vision mechanism, this paper explores the possibility of learning a layer-skippable inference network. Specifically, we propose a layer-skippable network that dynamically carries out coarse-tofine object categorization. Such a network has two branches to jointly deal with both coarse and fine-grained classification tasks. The layer-skipping mechanism is proposed to learn a gating network by generating dynamic inference graphs, and reducing the computational cost by detouring the inference path from some layers. This adaptive path inference strategy endows the network with better flexibility and larger capacity and makes the high-performance deep networks with dynamic structures. To efficiently train the gating network, a novel ranking-based loss function is presented. Furthermore, the learned representations are enhanced by the proposed top-down feedback facilitation and feature-wise affine transformation, individually. The former one employs features of a coarse branch to help the finegrained object recognition task, while the latter one encodes the selected path to enhance the final feature representations. Extensive experiments are conducted on several widely used coarse-to-fine object categorization benchmarks, and promising results are achieved by our proposed model. Quite surprisingly, our layer-skipping mechanism improves the network robustness to adversarial attacks. The codes and models are released on https://github.com/avalonstrel/DSN.

Cortical Thickness and Natural Scene Recognition in the Child's Brain

Visual scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information, whereas high spatial frequencies (HSF) subsequently carry information about fine details. The present magnetic resonance imaging study investigated how cortical thickness covaried with LSF/HSF processing abilities in ten-year-old children and adults. Participants indicated whether natural scenes that were filtered in either LSF or HSF represented outdoor or indoor scenes, while reaction times (RTs) and accuracy measures were recorded. In adults, faster RTs for LSF and HSF images were consistently associated with a thicker cortex (parahippocampal cortex, middle frontal gyrus, and precentral and insula regions for LSF; parahippocampal cortex and fronto-marginal and supramarginal gyri for HSF). On the other hand, in children, faster RTs for HSF were associated with a thicker cortex (posterior cingulate, supramarginal and calcarine cortical regions), whereas faster RTs for LSF were associated with a thinner cortex (subcallosal and insula regions). Increased cortical thickness in adults and children could correspond to an expansion mechanism linked to visual scene processing efficiency. In contrast, lower cortical thickness associated with LSF efficiency in children could correspond to a pruning mechanism reflecting an ongoing maturational process, in agreement with the view that LSF efficiency continues to be refined during childhood. This differing pattern between children and adults appeared to be particularly significant in anterior regions of the brain, in line with the proposed existence of a postero-anterior gradient of brain development. Taken together, our results highlight the dynamic brain processes that allow children and adults to perceive a visual natural scene in a coherent way.

Spatial frequency tuning of motor responses reveals differential contribution of dorsal and ventral systems to action comprehension

Understanding object-directed actions performed by others is central to everyday life. This ability is thought to rely on the interaction between the dorsal action observation network (AON) and a ventral object recognition pathway. On this view, the AON would encode action kinematics, and the ventral pathway, the most likely intention afforded by the objects. However, experimental evidence supporting this model is still scarce. Here, we aimed to disentangle the contribution of dorsal vs. ventral pathways to action comprehension by exploiting their differential tuning to low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs). We filtered naturalistic action images to contain only LSF or HSF and measured behavioral performance and corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS). Actions were embedded in congruent or incongruent scenarios as defined by the compatibility between grips and intentions afforded by the contextual objects. Behaviorally, participants were better at discriminating congruent actions in intact than LSF images. This effect was reversed for incongruent actions, with better performance for LSF than intact and HSF. These modulations were mirrored at the neurophysiological level, with greater CSE facilitation for congruent than incongruent actions for HSF and the opposite pattern for LSF images. Finally, only for LSF did we observe CSE modulations according to grip kinematics. While results point to differential dorsal (LSF) and ventral (HSF) contributions to action comprehension for grip and context encoding, respectively, the negative congruency effect for LSF images suggests that object processing may influence action perception not only through ventral-to-dorsal connections, but also through a dorsal-to-dorsal route involved in predictive processing.

Rapid scene categorization: From coarse peripheral vision to fine central vision

Studies on scene perception have shown that the rapid extraction of low spatial frequencies (LSF) allows a coarse parsing of the scene, prior to the analysis of high spatial frequencies (HSF) containing details. Many studies suggest that scene gist recognition can be achieved with only the low resolution of peripheral vision. Our study investigated the advantage of peripheral vision on central vision during a scene categorization task (indoor vs. outdoor). In Experiment 1, we used large scene photographs from which we built one central disk and four circular rings of different eccentricities. The central disk either contained or not an object semantically related to the scene category. Results showed better categorization performances for the peripheral rings, despite the presence of an object in central vision that was semantically related to the scene category that significantly improved categorization performances. In Experiment 2, the central disk and rings were assembled from Central to Peripheral vision (CtP sequence) or from Peripheral to Central vision (PtC sequence). Results revealed better performances for PtC than CtP sequences, except when no central object was present under rapid categorization constraints. As Experiment 3 suggested that the PtC advantage was not explained by a reduction of the visibility of the object in the central disk by the surrounding peripheral rings (CtP sequence), results are interpreted in the context of a predominant coarse-to-fine processing during scene categorization, with greater efficiency and utility of coarse peripheral vision relative to fine central vision during rapid scene categorization.

The cognitive penetrability of perception: A blocked debate and a tentative solution

Despite the extensive body of psychological findings suggesting that cognition influences perception, the debate between defenders and detractors of the cognitive penetrability of perception persists. While detractors demand more strictness in psychological experiments, proponents consider that empirical studies show that cognitive penetrability occurs. These considerations have led some theorists to propose that the debate has reached a dead end. The issue about where perception ends and cognition begins is, I argue, one of the reasons why the debate is cornered. Another reason is the inability of psychological studies to present uncontroversial interpretations of the results obtained. To dive into other kinds of empirical sources is, therefore, required to clarify the debate. In this paper, I explain where the debate is blocked, and suggest that neuroscientific evidence together with the predictive coding account, might decant the discussion on the side of the penetrability thesis.

Towards a Dynamic Exploration of Vision, Cognition and Emotion in Alcohol-Use Disorders

Abstract: Visuoperceptive impairments are among the most frequently reported deficits in alcohol-use disorders, but only very few studies have investigated their origin and interactions with other categories of dysfunctions. Besides, these deficits have generally been interpreted in a linear bottom-up perspective, which appears very restrictive with respect to the new models of vision developed in healthy populations. Indeed, new theories highlight the predictive nature of the visual system and demonstrate that it interacts with higher-level cognitive functions to generate top-down predictions. These models nota-bly posit that a fast but coarse visual analysis involving magnocellular pathways helps to compute heuristic guesses regard-ing the identity and affective value of inputs, which are used to facilitate conscious visual recognition. Building on these new proposals, the present review stresses the need to reconsider visual deficits in alcohol-use disorders as they might have cru-cial significance for core features of the pathology, such as attentional bias, loss of inhibitory control and emotion decoding impairments. Centrally, we suggest that individuals with severe alcohol-use disorders could present with magnocellular dam-age and we defend a dynamic explanation of the deficits. Rather than being restricted to high-level processes, deficits could start at early visual stages and then extend and potentially intensify during following steps due to reduced cerebral connec-tivity and dysfunctional cognitive/emotional regions. A new research agenda is specifically provided to test these hypotheses.

Spatial frequency supports the emergence of categorical representations in visual cortex during natural scene perception

In navigating our environment, we rapidly process and extract meaning from visual cues. However, the relationship between visual features and categorical representations in natural scene perception is still not well understood. Here, we used natural scene stimuli from different categories and filtered at different spatial frequencies to address this question in a passive viewing paradigm. Using representational similarity analysis (RSA) and cross-decoding of magnetoencephalography (MEG) data, we show that categorical representations emerge in human visual cortex at ∼180 ms and are linked to spatial frequency processing. Furthermore, dorsal and ventral stream areas reveal temporally and spatially overlapping representations of low and high-level layer activations extracted from a feedforward neural network. Our results suggest that neural patterns from extrastriate visual cortex switch from low-level to categorical representations within 200 ms, highlighting the rapid cascade of processing stages essential in human visual perception.

Aging modulates fronto-temporal cortical interactions during lexical production. A dynamic causal modeling study

In this dynamic causal modeling (DCM) study, we evaluated the effect of age on the effective connectivity of a cerebral network involved in lexical production. Younger and older adults performed an object naming task during fMRI. The DCM was used to explore the interactions between four regions of interest: the occipital cortex, OC; the lateral temporal cortex, LTC; the medial temporal cortex, MTC; and the inferior frontal cortex, IFC. We mainly focused on the modulation of the fronto-temporal interaction, according to the hypothesis that aging requires strategies that modulate the access to the semantic knowledge, either through a neural reserve mechanism (increased MTC-LTC connectivity) or through a neural compensation mechanism (supplementary IFC-MTC connectivity). For younger adults, our results indicated a bi-directional interaction between the left IFC and LTC suggesting a typical activation related to lexico-semantic representations. For older adults, our results reveal the existence of bi-directional interaction between the IFC and MTC, but not between the IFC and LTC - which in turn suggests that older adults adapt a new strategy, via supplemental access to conceptual access and semantic retrieval processes. This neural compensation strategy would be facilitated by a top-down mechanism from the IFC to the MTC. We discuss our results in the context of the possible additional strategies used by older compared to younger adults, to retrieve and produce words.

Three-stage processing of category and variation information by entangled interactive mechanisms of peri-occipital and peri-frontal cortices

Object recognition has been a central question in human vision research. The general consensus is that the ventral and dorsal visual streams are the major processing pathways undertaking objects' category and variation processing. This overlooks mounting evidence supporting the role of peri-frontal areas in category processing. Yet, many aspects of visual processing in peri-frontal areas have remained unattended including whether these areas play role only during active recognition and whether they interact with lower visual areas or process information independently. To address these questions, subjects were presented with a set of variation-controlled object images while their EEG were recorded. Considerable amounts of category and variation information were decodable from occipital, parietal, temporal and prefrontal electrodes. Using information-selectivity indices, phase and Granger causality analyses, three processing stages were identified showing distinct directions of information transaction between peri-frontal and peri-occipital areas suggesting their parallel yet interactive role in visual processing. A brain-plausible model supported the possibility of interactive mechanisms in peri-occipital and peri-frontal areas. These findings, while promoting the role of prefrontal areas in object recognition, extend their contributions from active recognition, in which peri-frontal to peri-occipital pathways are activated by higher cognitive processes, to the general sensory-driven object and variation processing.

Shared spatiotemporal category representations in biological and artificial deep neural networks

Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level accuracy using a feedforward architecture, providing neuroscientists with the opportunity to assess one successful series of representational transformations that enable categorization in silico. The goal of the current study is to assess the extent to which sequential scene category representations built by a CNN map onto those built in the human brain as assessed by high-density, time-resolved event-related potentials (ERPs). We found correspondence both over time and across the scalp: earlier (0–200 ms) ERP activity was best explained by early CNN layers at all electrodes. Although later activity at most electrode sites corresponded to earlier CNN layers, activity in right occipito-temporal electrodes was best explained by the later, fully-connected layers of the CNN around 225 ms post-stimulus, along with similar patterns in frontal electrodes. Taken together, these results suggest that the emergence of scene category representations develop through a dynamic interplay between early activity over occipital electrodes as well as later activity over temporal and frontal electrodes.

We categorize visual scenes rapidly and effortlessly, but still have little insight into the neural processing stages that enable this feat. In a parallel development, deep convolutional neural networks (CNNs) have been developed that perform visual categorization with human-like accuracy. We hypothesized that the stages of processing in a CNN may parallel the stages of processing in the human brain. We found that this is indeed the case, with early brain signals best explained by early stages of the CNN and later brain signals explained by later CNN layers. We also found that category-specific information seems to first emerge in sensory cortex and is then rapidly fed up to frontal areas. The similarities between biological brains and artificial neural networks provide neuroscientists with the opportunity to better understand the process of categorization by studying the artificial systems.

Ultra-Rapid serial visual presentation reveals dynamics of feedforward and feedback processes in the ventral visual pathway

Human visual recognition activates a dense network of overlapping feedforward and recurrent neuronal processes, making it hard to disentangle processing in the feedforward from the feedback direction. Here, we used ultra-rapid serial visual presentation to suppress sustained activity that blurs the boundaries of processing steps, enabling us to resolve two distinct stages of processing with MEG multivariate pattern classification. The first processing stage was the rapid activation cascade of the bottom-up sweep, which terminated early as visual stimuli were presented at progressively faster rates. The second stage was the emergence of categorical information with peak latency that shifted later in time with progressively faster stimulus presentations, indexing time-consuming recurrent processing. Using MEG-fMRI fusion with representational similarity, we localized recurrent signals in early visual cortex. Together, our findings segregated an initial bottom-up sweep from subsequent feedback processing, and revealed the neural signature of increased recurrent processing demands for challenging viewing conditions.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Stereo viewing modulates three-dimensional shape processing during object recognition: A high-density ERP study

The role of stereo disparity in the recognition of 3-dimensional (3D) object shape remains an unresolved issue for theoretical models of the human visual system. We examined this issue using high-density (128 channel) recordings of event-related potentials (ERPs). A recognition memory task was used in which observers were trained to recognize a subset of complex, multipart, 3D novel objects under conditions of either (bi-) monocular or stereo viewing. In a subsequent test phase they discriminated previously trained targets from untrained distractor objects that shared either local parts, 3D spatial configuration, or neither dimension, across both previously seen and novel viewpoints. The behavioral data showed a stereo advantage for target recognition at untrained viewpoints. ERPs showed early differential amplitude modulations to shape similarity defined by local part structure and global 3D spatial configuration. This occurred initially during an N1 component around 145-190 ms poststimulus onset, and then subsequently during an N2/P3 component around 260-385 ms poststimulus onset. For mono viewing, amplitude modulation during the N1 was greatest between targets and distracters with different local parts for trained views only. For stereo viewing, amplitude modulation during the N2/P3 was greatest between targets and distracters with different global 3D spatial configurations and generalized across trained and untrained views. The results show that image classification is modulated by stereo information about the local part, and global 3D spatial configuration of object shape. The findings challenge current theoretical models that do not attribute functional significance to stereo input during the computation of 3D object shape. (PsycINFO Database Record

The influence of spatial frequency content on facial expression processing: An ERP study using rapid serial visual presentation

Spatial frequency (SF) contents have been shown to play an important role in emotion perception. This study employed event-related potentials (ERPs) to explore the time course of neural dynamics involved in the processing of facial expression conveying specific SF information. Participants completed a dual-target rapid serial visual presentation (RSVP) task, in which SF-filtered happy, fearful, and neutral faces were presented. The face-sensitive N170 component distinguished emotional (happy and fearful) faces from neutral faces in a low spatial frequency (LSF) condition, while only happy faces were distinguished from neutral faces in a high spatial frequency (HSF) condition. The later P3 component differentiated between the three types of emotional faces in both LSF and HSF conditions. Furthermore, LSF information elicited larger P1 amplitudes than did HSF information, while HSF information elicited larger N170 and P3 amplitudes than did LSF information. Taken together, these results suggest that emotion perception is selectively tuned to distinctive SF contents at different temporal processing stages.

Slow and steady, not fast and furious: Slow temporal modulation strengthens continuous flash suppression

Continuous flash suppression (CFS) involves the presentation of a rapidly changing Mondrian sequence to one eye and a static target in the other eye. Targets presented in this manner remain suppressed for several seconds at a time, and this has seen the prevalent use of CFS in studies of unconscious visual processes. However, the mechanisms behind CFS remain unclear, complicating its use and the comprehension of results obtained with the paradigm. For example, some studies report observations indicative of faster, visual masking processes whereas others suggest slower, rivalry processes. To reconcile this discrepancy, this study investigates the effect of temporal frequency content and Mondrian pattern structure on CFS suppression. Our results show predominant influences of spatial edges and low temporal-frequency content, which are similar to binocular rivalry, affording a parsimonious alternative in unifying the two paradigms.

Attention to distinguishing features in object recognition: An interactive-iterative framework

This article advances a framework that casts object recognition as a process of discrimination between alternative object identities, in which top-down and bottom-up processes interact-iteratively when necessary-with attention to distinguishing features playing a critical role. In two experiments, observers discriminated between different types of artificial fish. In parallel, a secondary, variable-SOA visual-probe detection task was used to examine the dynamics of visual attention. In Experiment 1, the fish varied in three distinguishing features: one indicating the general category (saltwater, freshwater), and one of the two other features indicating the specific type of fish within each category. As predicted, in the course of recognizing each fish, attention was allocated iteratively to the distinguishing features in an optimal manner: first to the general category feature, and then, based on its value, to the second feature that identified the specific fish. In Experiment 2, two types of fish could be discriminated on the basis of either of two distinguishing features, one more visually discriminable than the other. On some of the trials, one of the two alternative distinguishing features was occluded. As predicted, in the course of recognizing each fish, attention was directed initially to the more discriminable distinguishing feature, but when this feature was occluded, it was then redirected to the less discriminable feature. The implications of these findings, and the interactive-iterative framework they support, are discussed with regard to several fundamental issues having a long history in the literatures on object recognition, object categorization, and visual perception in general.

Evidence for Separate Contributions of High and Low Spatial Frequencies during Visual Word Recognition

Previous studies have shown that different spatial frequency information processing streams interact during the recognition of visual stimuli. However, it is a matter of debate as to the contributions of high and low spatial frequency (HSF and LSF) information for visual word recognition. This study examined the role of different spatial frequencies in visual word recognition using event-related potential (ERP) masked priming. EEG was recorded from 32 scalp sites in 30 English-speaking adults in a go/no-go semantic categorization task. Stimuli were white characters on a neutral gray background. Targets were uppercase five letter words preceded by a forward-mask (#######) and a 50 ms lowercase prime. Primes were either the same word (repeated) or a different word (un-repeated) than the subsequent target and either contained only high, only low, or full spatial frequency information. Additionally within each condition, half of the prime-target pairs were high lexical frequency, and half were low. In the full spatial frequency condition, typical ERP masked priming effects were found with an attenuated N250 (sub-lexical) and N400 (lexical-semantic) for repeated compared to un-repeated primes. For HSF primes there was a weaker N250 effect which interacted with lexical frequency, a significant reversal of the effect around 300 ms, and an N400-like effect for only high lexical frequency word pairs. LSF primes did not produce any of the classic ERP repetition priming effects, however they did elicit a distinct early effect around 200 ms in the opposite direction of typical repetition effects. HSF information accounted for many of the masked repetition priming ERP effects and therefore suggests that HSFs are more crucial for word recognition. However, LSFs did produce their own pattern of priming effects indicating that larger scale information may still play a role in word recognition.

Conscious Vision Proceeds from Global to Local Content in Goal-Directed Tasks and Spontaneous Vision

The reverse hierarchy theory (Hochstein and Ahissar, 2002) makes strong, but so far untested, predictions on conscious vision. In this theory, local details encoded in lower-order visual areas are unconsciously processed before being automatically and rapidly combined into global information in higher-order visual areas, where conscious percepts emerge. Contingent on current goals, local details can afterward be consciously retrieved. This model therefore predicts that (1) global information is perceived faster than local details, (2) global information is computed regardless of task demands during early visual processing, and (3) spontaneous vision is dominated by global percepts. We designed novel textured stimuli that are, as opposed to the classic Navon's letters, truly hierarchical (i.e., where global information is solely defined by local information but where local and global orientations can still be manipulated separately). In line with the predictions, observers were systematically faster reporting global than local properties of those stimuli. Second, global information could be decoded from magneto-encephalographic data during early visual processing regardless of task demands. Last, spontaneous subjective reports were dominated by global information and the frequency and speed of spontaneous global perception correlated with the accuracy and speed in the global task. No such correlation was observed for local information. We therefore show that information at different levels of the visual hierarchy is not equally likely to become conscious; rather, conscious percepts emerge preferentially at a global level. We further show that spontaneous reports can be reliable and are tightly linked to objective performance at the global level.

SIGNIFICANCE STATEMENT

Is information encoded at different levels of the visual system (local details in low-level areas vs global shapes in high-level areas) equally likely to become conscious? We designed new hierarchical stimuli and provide the first empirical evidence based on behavioral and MEG data that global information encoded at high levels of the visual hierarchy dominates perception. This result held both in the presence and in the absence of task demands. The preferential emergence of percepts at high levels can account for two properties of conscious vision, namely, the dominance of global percepts and the feeling of visual richness reported independently of the perception of local details.

Quantifying the variability of scene-selective regions: Interindividual, interhemispheric, and sex differences

Scene-selective regions (SSRs), including the parahippocampal place area (PPA), retrosplenial cortex (RSC), and transverse occipital sulcus (TOS), are among the most widely characterized functional regions in the human brain. However, previous studies have mostly focused on the commonality within each SSR, providing little information on different aspects of their variability. In a large group of healthy adults (N = 202), we used functional magnetic resonance imaging to investigate different aspects of topographical and functional variability within SSRs, including interindividual, interhemispheric, and sex differences. First, the PPA, RSC, and TOS were delineated manually for each individual. We then demonstrated that SSRs showed substantial interindividual variability in both spatial topography and functional selectivity. We further identified consistent interhemispheric differences in the spatial topography of all three SSRs, but distinct interhemispheric differences in scene selectivity. Moreover, we found that all three SSRs showed stronger scene selectivity in men than in women. In summary, our work thoroughly characterized the interindividual, interhemispheric, and sex variability of the SSRs and invites future work on the origin and functional significance of these variabilities. Additionally, we constructed the first probabilistic atlases for the SSRs, which provide the detailed anatomical reference for further investigations of the scene network. Hum Brain Mapp 38:2260-2275, 2017. © 2017 Wiley Periodicals, Inc.

A Rapid Subcortical Amygdala Route for Faces Irrespective of Spatial Frequency and Emotion

There is significant controversy over the existence and function of a direct subcortical visual pathway to the amygdala. It is thought that this pathway rapidly transmits low spatial frequency information to the amygdala independently of the cortex, and yet the directionality of this function has never been determined. We used magnetoencephalography to measure neural activity while human participants discriminated the gender of neutral and fearful faces filtered for low or high spatial frequencies. We applied dynamic causal modeling to demonstrate that the most likely underlying neural network consisted of a pulvinar-amygdala connection that was uninfluenced by spatial frequency or emotion, and a cortical-amygdala connection that conveyed high spatial frequencies. Crucially, data-driven neural simulations revealed a clear temporal advantage of the subcortical connection over the cortical connection in influencing amygdala activity. Thus, our findings support the existence of a rapid subcortical pathway that is nonselective in terms of the spatial frequency or emotional content of faces. We propose that that the "coarseness" of the subcortical route may be better reframed as "generalized."SIGNIFICANCE STATEMENT The human amygdala coordinates how we respond to biologically relevant stimuli, such as threat or reward. It has been postulated that the amygdala first receives visual input via a rapid subcortical route that conveys "coarse" information, namely, low spatial frequencies. For the first time, the present paper provides direction-specific evidence from computational modeling that the subcortical route plays a generalized role in visual processing by rapidly transmitting raw, unfiltered information directly to the amygdala. This calls into question a widely held assumption across human and animal research that fear responses are produced faster by low spatial frequencies. Our proposed mechanism suggests organisms quickly generate fear responses to a wide range of visual properties, heavily implicating future research on anxiety-prevention strategies.