A Possible Neural Basis for Attentional Capture of Faces Revealed by Functional Magnetic Resonance Imaging and Causal Pharmacological Inactivation in Macaques.

In primates, the presence of a face in a visual scene captures attention and rapidly directs the observer's gaze to the face, even when the face is not relevant to the task at hand. Here, we explored a neural circuit that might potentially play a causal role in this powerful behavior. In our previous research, two monkeys received microinfusions of muscimol, a GABAA-receptor agonist, or saline (as a control condition) in separate sessions into individual or pairs of four inferotemporal face patches (middle and anterior lateral and fundal), as identified by a preceding face localizer experiment. Then, using fMRI, we measured the impact of each inactivation condition on responses in the other face patches relative to the control condition. In this study, we used the same method and measured the impact of each inactivation condition on responses in the FEF and the lateral intraparietal area, two regions associated with attentional processing, while face and nonface object stimuli were viewed. Our results revealed potential relationships between inferotemporal face patches and these two attention-related regions: The inactivation of the middle lateral and anterior fundal face patches had a pronounced impact on FEF, whereas the inactivation of the middle and anterior lateral face patches might have a noticeable influence on lateral intraparietal area. Together, these initial exploratory findings document a circuit that potentially underlies the attentional capture of faces. Confirmation of the role of this circuit remains to be accomplished in the context of paradigm explicitly testing the attentional capture of faces.

Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions in overweight population could be reflected in brain morphology. In the DIRECT-PLUS clinical trial, participants with criterion for metabolic syndrome underwent an 18-month lifestyle intervention. Structural brain MRIs were acquired before and after the intervention. We utilized an ensemble learning framework to predict Body-Mass Index (BMI) scores, which correspond to adiposity-related clinical measurements from brain MRIs. We revealed that patient-specific reduction in BMI predictions was associated with actual weight loss and was significantly higher in active diet groups compared to a control group. Moreover, explainable AI (XAI) maps highlighted brain regions contributing to BMI predictions that were distinct from regions associated with age prediction. Our DIRECT-PLUS analysis results imply that predicted BMI and its reduction are unique neural biomarkers for obesity-related brain modifications and weight loss.

Perceptual narrowing continues throughout childhood: Evidence from specialization of face processing.

Face recognition shows a long trajectory of development and is known to be closely associated with the development of social skills. However, it is still debated whether this long trajectory is perceptually based and what the role is of experience-based refinements of face representations throughout development. We examined the effects of short and long-term experienced stimulus history on face processing, using regression biases of face representations towards the experienced mean. Children and adults performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. The results show that face recognition continues to improve after 9 years of age, with more pronounced improvements for own-race faces. This increased narrowing with age is also indicated by similar use of stimulus statistics for own-race and other-race faces in children, contrary to the different use of the overall stimulus history for these two face types in adults. Increased face proficiency in adulthood renders the perceptual system less tuned to other-race face statistics. Altogether, the results demonstrate associations between levels of specialization and the extent to which perceptual representations become narrowly tuned with age.

Reliability and validity of brain-gastric phase synchronization.

Recent studies have reported that various brain regions, mainly sensory, unimodal regions, display phase synchronization with the stomach's slow (0.05 Hz) myoelectrical rhythm. These gastric-brain interactions have broad implications, from feeding behavior to functional gastrointestinal disorders. However, in contrast to other interoceptive signals (e.g., heart rate) and their relation to the brain, little is known about the reliability of these gastric-brain interactions, their robustness to artifacts such as motion, and whether they can be generalized to new samples. Here we examined these aspects in 43 subjects that had undergone multiple runs of concurrent electrogastrography (EGG), brain fMRI, and pulse oximetry. We also repeated all analyses in an open dataset of a highly sampled individual. We found a set of brain regions that were coupled with the EGG signal after controlling for non-grey matter (GM) signals, head motion, and cardiac artifacts. These regions exhibited significant overlap with previous work. However, we also showed that prior to confound regression, the spatial extent of the gastric network was largely overestimated. Finally, we found substantial test-retest reliability in both the brain and the gastric signals when estimated alone, but not for measures of gastric-brain synchrony. Together, these results provide methodological scaffolding for future research into brain-stomach interactions and for a better understanding of the role of the gastric network.

Modular community structure of the face network supports face recognition.

Face recognition is dependent on computations conducted in specialized brain regions and the communication among them, giving rise to the face-processing network. We examined whether modularity of this network may underlie the vast individual differences found in human face recognition abilities. Modular networks, characterized by strong within and weaker between-network connectivity, were previously suggested to promote efficacy and reduce interference among cognitive systems and also correlated with better cognitive abilities. The study was conducted in a large sample (n = 409) with diffusion-weighted imaging, resting-state fMRI, and a behavioral face recognition measure. We defined a network of face-selective regions and derived a novel measure of communication along with structural and functional connectivity among them. The modularity of this network was positively correlated with recognition abilities even when controlled for age. Furthermore, the results were specific to the face network when compared with the place network or to spatially permuted null networks. The relation to behavior was also preserved at the individual-edge level such that a larger correlation to behavior was found within hemispheres and particularly within the right hemisphere. This study provides the first evidence of modularity-behavior relationships in the domain of face processing and more generally in visual perception.

Recognition of Masked Faces in the Era of the Pandemic: No Improvement Despite Extensive Natural Exposure.

Face masks, which became prevalent across the globe during the COVID-19 pandemic, have had a negative impact on face recognition despite the availability of critical information from uncovered face parts, especially the eyes. An outstanding question is whether face-mask effects would be attenuated following extended natural exposure. This question also pertains, more generally, to face-recognition training protocols. We used the Cambridge Face Memory Test in a cross-sectional study (N = 1,732 adults) at six different time points over a 20-month period, alongside a 12-month longitudinal study (N = 208). The results of the experiments revealed persistent deficits in recognition of masked faces and no sign of improvement across time points. Additional experiments verified that the amount of individual experience with masked faces was not correlated with the mask effect. These findings provide compelling evidence that the face-processing system does not easily adapt to visual changes in face stimuli, even following prolonged real-life exposure.

The Compositionality of Facial Expressions.

The principle of compositionality, an important postulation in language and cognition research, posits that the meaning of a complex expression is determined by the meaning of its constituting parts and the operation performed on those parts. Here, we provide strong evidence that this principle plays a significant role also in interpreting facial expressions. In three studies in which perceivers interpreted sequences of two emotional facial expression images, we show that the composite meaning of facial expressions results from the meaning of its constituting expressions and an algebraic operation performed on those expressions. Our study offers a systematic account as to how the meaning of facial expressions (single and sequences) are being formed and perceived. In a broader context, our results raise the possibility that the principle of compositionality may apply to human communication modalities beyond spoken language, whereby a minimal number of components are expanded to a much greater number of meanings.

Mapping individual differences across brain network structure to function and behavior with connectome embedding.

The connectome, a comprehensive map of the brain's anatomical connections, is often summarized as a matrix comprising all dyadic connections among pairs of brain regions. This representation cannot capture higher-order relations within the brain graph. Connectome embedding (CE) addresses this limitation by creating compact vectorized representations of brain nodes capturing their context in the global network topology. Here, nodes "context" is defined as random walks on the brain graph and as such, represents a generative model of diffusive communication around nodes. Applied to group-averaged structural connectivity, CE was previously shown to capture relations between inter-hemispheric homologous brain regions and uncover putative missing edges from the network reconstruction. Here we extend this framework to explore individual differences with a novel embedding alignment approach. We test this approach in two lifespan datasets (NKI: n = 542; Cam-CAN: n = 601) that include diffusion-weighted imaging, resting-state fMRI, demographics and behavioral measures. We demonstrate that modeling functional connectivity with CE substantially improves structural to functional connectivity mapping both at the group and subject level. Furthermore, age-related differences in this structure-function mapping, are preserved and enhanced. Importantly, CE captures individual differences by out-of-sample prediction of age and intelligence. The resulting predictive accuracy was higher compared to using structural connectivity and functional connectivity. We attribute these findings to the capacity of the CE to incorporate aspects of both anatomy (the structural graph) and function (diffusive communication). Our novel approach allows mapping individual differences in the connectome through structure to function and behavior.

Neural correlates of future weight loss reveal a possible role for brain-gastric interactions.

Lifestyle dietary interventions are an essential practice in treating obesity, hence neural factors that may assist in predicting individual treatment success are of great significance. Here, in a prospective, open-label, three arms study, we examined the correlation between brain resting-state functional connectivity measured at baseline and weight loss following 6 months of lifestyle intervention in 92 overweight participants. We report a robust subnetwork composed mainly of sensory and motor cortical regions, whose edges correlated with future weight loss. This effect was found regardless of intervention group. Importantly, this main finding was further corroborated using a stringent connectivity-based prediction model assessed with cross-validation thus attesting to its robustness. The engagement of senso-motor regions in this subnetwork is consistent with the over-sensitivity to food cues theory of weight regulation. Finally, we tested an additional hypothesis regarding the role of brain-gastric interaction in this subnetwork, considering recent findings of a cortical network synchronized with gastric activity. Accordingly, we found a significant spatial overlap with the subnetwork reported in the present study. Moreover, power in the gastric basal electric frequency within our reported subnetwork negatively correlated with future weight loss. This finding was specific to the weight loss related subnetwork and to the gastric basal frequency. These findings should be further corroborated by combining direct recordings of gastric activity in future studies. Taken together, these intriguing results may have important implications for our understanding of the etiology of obesity and the mechanism of response to dietary intervention.

From a deep learning model back to the brain-Identifying regional predictors and their relation to aging.

We present a Deep Learning framework for the prediction of chronological age from structural magnetic resonance imaging scans. Previous findings associate increased brain age with neurodegenerative diseases and higher mortality rates. However, the importance of brain age prediction goes beyond serving as biomarkers for neurological disorders. Specifically, utilizing convolutional neural network (CNN) analysis to identify brain regions contributing to the prediction can shed light on the complex multivariate process of brain aging. Previous work examined methods to attribute pixel/voxel-wise contributions to the prediction in a single image, resulting in "explanation maps" that were found noisy and unreliable. To address this problem, we developed an inference scheme for combining these maps across subjects, thus creating a population-based, rather than a subject-specific map. We applied this method to a CNN ensemble trained on predicting subjects' age from raw T1 brain images in a lifespan sample of 10,176 subjects. Evaluating the model on an untouched test set resulted in mean absolute error of 3.07 years and a correlation between chronological and predicted age of r = 0.98. Using the inference method, we revealed that cavities containing cerebrospinal fluid, previously found as general atrophy markers, had the highest contribution for age prediction. Comparing maps derived from different models within the ensemble allowed to assess differences and similarities in brain regions utilized by the model. We showed that this method substantially increased the replicability of explanation maps, converged with results from voxel-based morphometry age studies and highlighted brain regions whose volumetric variability correlated the most with the prediction error.

Visual Aversive Learning Compromises Sensory Discrimination.

Aversive learning is thought to modulate perceptual thresholds, which can lead to overgeneralization. However, it remains undetermined whether this modulation is domain specific or a general effect. Moreover, despite the unique role of the visual modality in human perception, it is unclear whether this aspect of aversive learning exists in this modality. The current study was designed to examine the effect of visual aversive outcomes on the perception of basic visual and auditory features. We tested the ability of healthy participants, both males and females, to discriminate between neutral stimuli, before and after visual learning. In each experiment, neutral stimuli were associated with aversive images in an experimental group and with neutral images in a control group. Participants demonstrated a deterioration in discrimination (higher discrimination thresholds) only after aversive learning. This deterioration was measured for both auditory (tone frequency) and visual (orientation and contrast) features. The effect was replicated in five different experiments and lasted for at least 24 h. fMRI neural responses and pupil size were also measured during learning. We showed an increase in neural activations in the anterior cingulate cortex, insula, and amygdala during aversive compared with neutral learning. Interestingly, the early visual cortex showed increased brain activity during aversive compared with neutral context trials, with identical visual information. Our findings imply the existence of a central multimodal mechanism, which modulates early perceptual properties, following exposure to negative situations. Such a mechanism could contribute to abnormal responses that underlie anxiety states, even in new and safe environments.SIGNIFICANCE STATEMENT Using a visual aversive-learning paradigm, we found deteriorated discrimination abilities for visual and auditory stimuli that were associated with visual aversive stimuli. We showed increased neural activations in the anterior cingulate cortex, insula, and amygdala during aversive learning, compared with neutral learning. Importantly, similar findings were also evident in the early visual cortex during trials with aversive/neutral context, but with identical visual information. The demonstration of this phenomenon in the visual modality is important, as it provides support to the notion that aversive learning can influence perception via a central mechanism, independent of input modality. Given the dominance of the visual system in human perception, our findings hold relevance to daily life, as well as imply a potential etiology for anxiety disorders.

Minimal Recognizable Configurations Elicit Category-selective Responses in Higher Order Visual Cortex.

Visual object recognition is performed effortlessly by humans notwithstanding the fact that it requires a series of complex computations, which are, as yet, not well understood. Here, we tested a novel account of the representations used for visual recognition and their neural correlates using fMRI. The rationale is based on previous research showing that a set of representations, termed "minimal recognizable configurations" (MIRCs), which are computationally derived and have unique psychophysical characteristics, serve as the building blocks of object recognition. We contrasted the BOLD responses elicited by MIRC images, derived from different categories (faces, objects, and places), sub-MIRCs, which are visually similar to MIRCs, but, instead, result in poor recognition and scrambled, unrecognizable images. Stimuli were presented in blocks, and participants indicated yes/no recognition for each image. We confirmed that MIRCs elicited higher recognition performance compared to sub-MIRCs for all three categories. Whereas fMRI activation in early visual cortex for both MIRCs and sub-MIRCs of each category did not differ from that elicited by scrambled images, high-level visual regions exhibited overall greater activation for MIRCs compared to sub-MIRCs or scrambled images. Moreover, MIRCs and sub-MIRCs from each category elicited enhanced activation in corresponding category-selective regions including fusiform face area and occipital face area (faces), lateral occipital cortex (objects), and parahippocampal place area and transverse occipital sulcus (places). These findings reveal the psychological and neural relevance of MIRCs and enable us to make progress in developing a more complete account of object recognition.

Stimulus Dependent Dynamic Reorganization of the Human Face Processing Network.

Using the "face inversion effect", a hallmark of face perception, we examined network mechanisms supporting face representation by tracking functional magnetic resonance imaging (fMRI) stimulus-dependent dynamic functional connectivity within and between brain networks associated with the processing of upright and inverted faces. We developed a novel approach adapting the general linear model (GLM) framework classically used for univariate fMRI analysis to capture stimulus-dependent fMRI dynamic connectivity of the face network. We show that under the face inversion manipulation, the face and non-face networks have complementary roles that are evident in their stimulus-dependent dynamic connectivity patterns as assessed by network decomposition into components or communities. Moreover, we show that connectivity patterns are associated with the behavioral face inversion effect. Thus, we establish "a network-level signature" of the face inversion effect and demonstrate how a simple physical transformation of the face stimulus induces a dramatic functional reorganization across related brain networks. Finally, we suggest that the dynamic GLM network analysis approach, developed here for the face network, provides a general framework for modeling the dynamics of blocked stimulus-dependent connectivity experimental designs and hence can be applied to a host of neuroimaging studies.

Three-Dimensional Representations of Objects in Dorsal Cortex are Dissociable from Those in Ventral Cortex.

An established conceptualization of visual cortical function is one in which ventral regions mediate object perception while dorsal regions support spatial information processing and visually guided action. This division has been contested by evidence showing that dorsal regions are also engaged in the representation of object shape, even when actions are not required. The critical question is whether these dorsal, object-based representations are dissociable from ventral representations, and whether they play a functional role in object recognition. We examined the neural and behavioral profile of patients with impairments in object recognition following ventral cortex damage. In a functional magnetic resonanace imaging experiment, the blood oxygen level-dependent response in the ventral, but not dorsal, cortex of the patients evinced less sensitivity to object 3D structure compared with that of healthy controls. Consistently, in psychophysics experiments, the patients exhibited significant impairments in object perception, but still revealed residual sensitivity to object-based structural information. Together, these findings suggest that, although in the intact system there is considerable crosstalk between dorsal and ventral cortices, object representations in dorsal cortex can be computed independently from those in ventral cortex. While dorsal representations alone are unable to support normal object perception, they can, nevertheless, support a coarse description of object structural information.

Adults' Markers of Face Processing Are Present at Age 6 and Are Interconnected Along Development.

Recent studies on the development of face processing argue for a late, quantitative, domain-specific development of face processing, and face memory in particular. Most previous findings were based on separately tracking the developmental course of face perception skills, comparing performance across different age groups. Here, we adopted a different approach studying the mechanisms underlying the development of face processing by focusing on how different face skills are interrelated over the years (age 6 to adulthood). Specifically, we examined correlations within and between different categories of tasks: face domain-specific skills involving face recognition based on long-term representations (famous face), and short-term memory retention (Cambridge Face Memory Test), perceptual face-specific marker (inversion effect), global effects in scene perception (global-local task), and the perception of facial expressions. Factor analysis revealed that face identity skills have a similar pattern of interrelations throughout development, identifying two factors: a face domain-specific factor comprising adultlike markers of face processing and a general factor incorporating related, but nonspecific perceptual skills. Domain-specific age-related changes in face recognition entailing short- and long-term retention of face representations were observed, along with mature perceptual face-specific markers and more general perceptual effects predicting face perception skills already at age 6. The results suggest that the domain-specific changes in face processing are unlikely to result from developmental changes in perceptual skills driving face recognition. Instead, development may either involve improvement in the ability to retain face representations in memory or changes in the interactions between the perceptual representations of faces and their representations in long-term memory.

Sensitivity to object impossibility in the human visual cortex: evidence from functional connectivity.

Processing spatial configuration is a fundamental requirement for object recognition. Using fMRI, the neural basis underlying this ability was examined while human participants viewed possible and visually similar, but spatially impossible, objects presented for either long or short exposure duration. Response profiles in object-selective cortical regions exhibited sensitivity to object possibility, but only for the long exposure duration. Contrary, functional connectivity, indexed by the pairwise correlations between activation profiles across ROIs, revealed sensitivity to possibility, evident in enhanced correlations for impossible compared with possible objects. Such sensitivity was found even following a brief exposure duration, which allowed only minimal awareness of possibility. Importantly, this sensitivity was correlated with participants' general spatial ability as assessed by an independent neuropsychological test. These results suggest that the visual system is highly susceptible to objects' 3-D structural information even with minimal perceptual awareness. Such sensitivity is captured at the level of functional connectivity between object-selective regions, rather than the absolute level of within-region activity, implicating the role of interregional synchronization in the representation of objects' 3-D structure.

Impossible expectations: fMRI adaptation in the lateral occipital complex (LOC) is modulated by the statistical regularities of 3D structural information.

fMRI adaptation (fMRIa), the attenuation of fMRI signal which follows repeated presentation of a stimulus, is a well-documented phenomenon. Yet, the underlying neural mechanisms supporting this effect are not fully understood. Recently, short-term perceptual expectations, induced by specific experimental settings, were shown to play an important modulating role in fMRIa. Here we examined the role of long-term expectations, based on 3D structural statistical regularities, in the modulation of fMRIa. To this end, human participants underwent fMRI scanning while performing a same-different task on pairs of possible (regular, expected) objects and spatially impossible (irregular, unexpected) objects. We hypothesized that given the spatial irregularity of impossible objects in relation to real-world visual experience, the visual system would always generate a prediction which is biased to the possible version of the objects. Consistently, fMRIa effects in the lateral occipital cortex (LOC) were found for possible, but not for impossible objects. Additionally, in alternating trials the order of stimulus presentation modulated LOC activity. That is, reduced activation was observed in trials in which the impossible version of the object served as the prime object (i.e. first object) and was followed by the possible version compared to the reverse order. These results were also supported by the behavioral advantage observed for trials that were primed by possible objects. Together, these findings strongly emphasize the importance of perceptual expectations in object representation and provide novel evidence for the role of real-world statistical regularities in eliciting fMRIa.

Selective dissociation between core and extended regions of the face processing network in congenital prosopagnosia.

There is growing consensus that accurate and efficient face recognition is mediated by a neural circuit composed of a posterior "core" and an anterior "extended" set of regions. Here, we characterize the distributed face network in human individuals with congenital prosopagnosia (CP)-a lifelong impairment in face processing-relative to that of matched controls. Using functional magnetic resonance imaging, we first uncover largely normal activation patterns in the posterior core face patches in CP. We also document normal activity of the amygdala (emotion processing) as well as normal or even enhanced functional connectivity between the amygdala and the core regions. Critically, in the same individuals, activation of the anterior temporal cortex (identity processing) is reduced and connectivity between this region and the posterior core regions is disrupted. The dissociation between the neural profiles of the anterior temporal lobe and amygdala was evident both during a task-related face scan and during a resting state scan, in the absence of visual stimulation. Taken together, these findings elucidate selective disruptions in neural circuitry in CP and offer an explanation for the known differential difficulty in identity versus emotional expression recognition in many individuals with CP.

Refinement of face representations by exposure reveals different time scales of biases in face processing.

Experience modulates face processing abilities so that face discrimination and recognition improve with development, especially for more frequently experienced faces (e.g., own-race faces). Although advanced models describe how experience generally modulates perception, the mechanism by which exposure refines internal perceptual representations of faces is unknown. To address this issue, we investigated the effect of short- and long-term experienced stimulus history on face processing. Participants performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. Use of stimulus statistics was measured by testing the gravitation of face representations towards the mean of a range of morphed faces around which they were sampled (regression-to-the-mean). The results demonstrated regression of face representations towards the experienced mean and the retention of stimulus statistics over days. In trials where regression facilitated discrimination, the bias diminished the otherwise disadvantage of other-race over own-races faces. The dynamics of the perceptual bias, probed by trial-by-trial performance, further indicated different timescales of the bias, depending on perceptual expertise: people with weak face-recognition skills showed the use of a stable reference, built on long-term statistics accumulated over many trials, along with an updating of this reference by recent trials. In contrast, the strong face recognizers showed a different pattern where sequential effects mostly contributed to discrimination, with relatively minimal reliance on the long-term average for other-race faces. The findings suggest a mechanism by which exposure refines face representations and reveal, for the first time in adults, associations between levels of specialization of perceptual representations and the extent to which these representations become narrowly tuned.

Representation of possible and impossible objects in the human visual cortex: evidence from fMRI adaptation.

Impossible objects are defined as 2D drawings that represent objects that could not exist in real 3D space. Previous studies have proposed that such objects are represented differently in long-term memory due to their invalid spatial structure. Nevertheless, it is not clear whether these discrepancies reflect early perceptual processes or late, post-recognition, processes. Here, we address this issue by using fMRI adaptation. Interestingly, equivalent adaptation levels were obtained for repeated compared to non-repeated possible and impossible objects in object selective regions within the human high-level visual cortex. Yet, a significant correlation between fMRI adaptation and behavioral facilitation was found for possible but not for impossible objects, thus exhibiting some dissociation in the representation of the two object categories. Overall, our findings suggest that the initial perception of possible and impossible objects is mediated by shared neural mechanisms whereas the observed differences between the two types of objects may reflect higher post-recognition processes.