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.

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.

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.

Functional connectivity of the human face network exhibits right hemispheric lateralization from infancy to adulthood.

Adults typically exhibit right hemispheric dominance in the processing of faces. In this cross-sectional study, we investigated age-dependent changes in face processing lateralization from infancy to adulthood (1-48 years old; N = 194). We co-registered anatomical and resting state functional Magnetic Resonance Imaging (fMRI) scans of toddlers, children, adolescents, and adults into a common space and examined functional connectivity across the face, as well as place, and object-selective regions identified in adults. As expected, functional connectivity between core face-selective regions was stronger in the right compared to the left hemisphere in adults. Most importantly, the same lateralization was evident in all other age groups (infants, children, adolescents) and appeared only in face-selective regions, and not in place or object-selective regions. These findings suggest that the physiological development of face-selective brain areas may differ from that of object and place-selective areas. Specifically, the functional connectivity of the core-face selective regions exhibits rightward lateralization from infancy, years before these areas develop mature face-selective responses.

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.

Fine-scale dynamics of functional connectivity in the face-processing network during movie watching.

Mapping the human face-processing network is typically done during rest or using isolated, static face images, overlooking widespread cortical interactions obtained in response to naturalistic face dynamics and context. To determine how inter-subject functional correlation (ISFC) relates to face recognition scores, we measure cortical connectivity patterns in response to a dynamic movie in typical adults (N = 517). We find a positive correlation with recognition scores in edges connecting the occipital visual and anterior temporal regions and a negative correlation in edges connecting the attentional dorsal, frontal default, and occipital visual regions. We measure the inter-subject stimulus-evoked response at a single TR resolution and demonstrate that co-fluctuations in face-selective edges are related to activity in core face-selective regions and that the ISFC patterns peak during boundaries between movie segments rather than during the presence of faces. Our approach demonstrates how face processing is linked to fine-scale dynamics in attentional, memory, and perceptual neural circuitry.

The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity.

Background: Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention. Methods: In a sub-study of 102 participants of the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on magnetic resonance imaging (MRI)-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age. Results: To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months' attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18 months of intervention. Finally, we showed that lower consumption of processed food, sweets and beverages were associated with attenuated brain age. Conclusions: Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging. Funding: The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11, Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission 09933838 SFB 105 (to I Shai).

Obesity is linked with the brain aging faster than would normally be expected. Researchers are able to capture this process by calculating a person's 'brain age' ­ how old their brain appears on detailed scans, regardless of chronological age. This approach also helps to monitor how certain factors, such as lifestyle, can influence brain aging over relatively short time scales. It is not clear whether lifestyle interventions that promote weight loss can help to slow obesity-driven brain aging. To answer this question, Levakov et al. studied 102 individuals who met the criteria for obesity and took part in a lifestyle intervention aimed to improve diet and physical activity levels over 18 months. The participants received a brain scan at the beginning and the end of the program; additional tests and measurements were also conducted at these times to capture other biological processes impacted by obesity, such as liver health. Levakov et al. used the brain scans taken at the start and end of the study to examine the impact of the lifestyle intervention on the aging trajectory. The results revealed that a reduction in body weight of 1% led to the participants' brain age being nearly 9 months younger than the expected brain age after 18 months. This attenuated aging was associated with changes in other biological measures, such as decreased liver fat and liver enzymes. Increases in liver fat and production of specific liver enzymes were previously shown to negatively impact brain health in Alzheimer's disease. Finally, examining more closely the food consumption reports completed by participants showed that reduced consumption of processed food, sweets and beverages were linked to attenuated brain aging. The findings show that lifestyle interventions which promote weight loss can have a beneficial impact on the aging trajectory of the brain observed with obesity. The next steps will include determining whether slowing down obesity-driven brain aging results in better clinical outcomes for patients. In addition, the work by Levakov et al. demonstrates a potential strategy to evaluate the success of lifestyle changes on brain health. With global rates of obesity rising, identifying interventions that have a positive impact on brain health could have important clinical, educational and social impacts.

Weaker face recognition in adults with autism arises from perceptually based alterations.

Face recognition has been shown to be impaired in autism spectrum disorders (ASD). However, it is still debated whether these face processing deficits arise from perceptually based alterations. We tested individuals with ASD and matched typically developing (TD) individuals using a delayed estimation task in which a single target face was shown either upright or inverted. Participants selected a face that best resembled the target face out of a cyclic space of morphed faces. To enable the disentanglement of visual from mnemonic processing, reports were required either following a 1 and 6 second retention interval, or simultaneously while the target face was still visible. Individuals with ASD made significantly more errors than TD individuals in both the simultaneous and delayed intervals, indicating that face recognition deficits in autism are also perceptual rather than strictly memory based. Moreover, individuals with ASD exhibited weaker inversion effects than the TD individuals, on all retention intervals. This finding, that was mostly evident in precision errors, suggests that contrary to the more precise representations of upright faces in TD individuals, individuals with ASD exhibit similar levels of precision for inverted and upright faces, for both simultaneous and delayed conditions. These results suggest that weakened memory for faces reported in ASD may be secondary to an underlying perceptual deficit in face processing.

Bidirectional and parallel relationships in macaque face circuit revealed by fMRI and causal pharmacological inactivation.

Although the presence of face patches in primate inferotemporal (IT) cortex is well established, the functional and causal relationships among these patches remain elusive. In two monkeys, muscimol was infused sequentially into each patch or pair of patches to assess their respective influence on the remaining IT face network and the amygdala, as determined using fMRI. The results revealed that anterior face patches required input from middle face patches for their responses to both faces and objects, while the face selectivity in middle face patches arose, in part, from top-down input from anterior face patches. Moreover, we uncovered a parallel fundal-lateral functional organization in the IT face network, supporting dual routes (dorsal-ventral) in face processing within IT cortex as well as between IT cortex and the amygdala. Our findings of the causal relationship among the face patches demonstrate that the IT face circuit is organized into multiple functional compartments.

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.

Face perception: computational insights from phylogeny.

Studies of face perception in primates elucidate the psychological and neural mechanisms that support this critical and complex ability. Recent progress in characterizing face perception across species, for example in insects and reptiles, has highlighted the ubiquity over phylogeny of this key ability for social interactions and survival. Here, we review the competence in face perception across species and the types of computation that support this behavior. We conclude that the computational complexity of face perception evinced by a species is not related to phylogenetic status and is, instead, largely a product of environmental context and social and adaptive pressures. Integrating findings across evolutionary data permits the derivation of computational principles that shed further light on primate face perception.

Face masks disrupt holistic processing and face perception in school-age children.

Face perception is considered a remarkable visual ability in humans that is subject to a prolonged developmental trajectory. In response to the COVID-19 pandemic, mask-wearing has become mandatory for adults and children alike. Recent research shows that mask-wearing hinders face recognition abilities in adults, but it is unknown if the same holds true in school-age children in whom face perception is not fully developed. Here we tested children (n = 72, ages 6-14 years old) on the Cambridge Face Memory Test - Kids (CFMT-K), a validated measure of face perception performance. Faces were presented with or without masks and across two orientations (upright/inverted). The inclusion of face masks led to a profound deficit in face perception abilities. This decrement was more pronounced in children compared to adults, but only when task difficulty was adjusted across the two age groups. Additionally, children exhibited reliable correlations between age and the CFMT-K score for upright faces for both the mask and no-mask conditions. Finally, as previously observed in adults, children also showed qualitative differences in the processing of masked versus non-masked faces. Specifically, holistic processing, a hallmark of face perception, was disrupted for masked faces as suggested by a reduced face-inversion effect. Together, these findings provide evidence for substantial quantitative and qualitative alterations in the processing of masked faces in school-age children.

The effect of a high-polyphenol Mediterranean diet (Green-MED) combined with physical activity on age-related brain atrophy: the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT PLUS).

BACKGROUND: The effect of diet on age-related brain atrophy is largely unproven. OBJECTIVES: We aimed to explore the effect of a Mediterranean diet (MED) higher in polyphenols and lower in red/processed meat (Green-MED diet) on age-related brain atrophy. METHODS: This 18-mo clinical trial longitudinally measured brain structure volumes by MRI using hippocampal occupancy score (HOC) and lateral ventricle volume (LVV) expansion score as neurodegeneration markers. Abdominally obese/dyslipidemic participants were randomly assigned to follow 1) healthy dietary guidelines (HDG), 2) MED, or 3) Green-MED diet. All subjects received free gym memberships and physical activity guidance. Both MED groups consumed 28 g walnuts/d (+440 mg/d polyphenols). The Green-MED group consumed green tea (3-4 cups/d) and Mankai (Wolffia-globosa strain, 100 g frozen cubes/d) green shake (+800 mg/d polyphenols). RESULTS: Among 284 participants (88% men; mean age: 51 y; BMI: 31.2 kg/m2; APOE-ε4 genotype = 15.7%), 224 (79%) completed the trial with eligible whole-brain MRIs. The pallidum (-4.2%), third ventricle (+3.9%), and LVV (+2.2%) disclosed the largest volume changes. Compared with younger participants, atrophy was accelerated among those ≥50 y old (HOC change: -1.0% ± 1.4% compared with -0.06% ± 1.1%; 95% CI: 0.6%, 1.3%; P < 0.001; LVV change: 3.2% ± 4.5% compared with 1.3% ± 4.1%; 95% CI: -3.1%, -0.8%; P = 0.001). In subjects ≥ 50 y old, HOC decline and LVV expansion were attenuated in both MED groups, with the best outcomes among Green-MED diet participants, as compared with HDG (HOC: -0.8% ± 1.6% compared with -1.3% ± 1.4%; 95% CI: -1.5%, -0.02%; P = 0.042; LVV: 2.3% ± 4.7% compared with 4.3% ± 4.5%; 95% CI: 0.3%, 5.2%; P = 0.021). Similar patterns were observed among younger subjects. Improved insulin sensitivity over the trial was the parameter most strongly associated with brain atrophy attenuation (P < 0.05). Greater Mankai, green tea, and walnut intake and less red and processed meat were significantly and independently associated with reduced HOC decline (P < 0.05). Elevated urinary concentrations of the polyphenols urolithin-A (r = 0.24; P = 0.013) and tyrosol (r = 0.26; P = 0.007) were significantly associated with lower HOC decline. CONCLUSIONS: A Green-MED (high-polyphenol) diet, rich in Mankai, green tea, and walnuts and low in red/processed meat, is potentially neuroprotective for age-related brain atrophy.This trial was registered at clinicaltrials.gov as NCT03020186.

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.

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.

Spatial Integration in Normal Face Processing and Its Breakdown in Congenital Prosopagnosia.

Congenital prosopagnosia (CP), a life-long impairment in face processing that occurs in the absence of any apparent brain damage, provides a unique model in which to explore the psychological and neural bases of normal face processing. The goal of this review is to offer a theoretical and conceptual framework that may account for the underlying cognitive and neural deficits in CP. This framework may also provide a novel perspective in which to reconcile some conflicting results that permits the expansion of the research in this field in new directions. The crux of this framework lies in linking the known behavioral and neural underpinnings of face processing and their impairments in CP to a model incorporating grid cell-like activity in the entorhinal cortex. Moreover, it stresses the involvement of active, spatial scanning of the environment with eye movements and implicates their critical role in face encoding and recognition. To begin with, we describe the main behavioral and neural characteristics of CP, and then lay down the building blocks of our proposed model, referring to the existing literature supporting this new framework. We then propose testable predictions and conclude with open questions for future research stemming from this model.

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.