The Development of Spatial Cognition and Its Malleability Assessed in Mass Population via a Mobile Game.

Spatial cognition is a fundamental aspect of human intelligence, but our understanding of its developmental trajectory across the life span is limited. Here, we applied game-based assessment on mobile devices to engage a large sample from China (N = 216,713) with a wide age range (from under 10 years old to above 60) in multiple participations of a mental rotation task, a typical measure of spatial cognition. We found that spatial ability developed asynchronously with its malleability. Whereas mental rotation performance peaked at the age of 28, with males performing better than females, the effect of training from repeated participation peaked at 18, probably laying the foundation for the development of spatial ability. In contrast, children showed particularly low malleability, and a follow-up experiment revealed that the underdeveloped ability of mirror-image discrimination likely hindered the malleability of spatial cognition during this period. The intermingled relation of ability and malleability illustrates dynamics in the development of spatial cognition, inviting broad research on the development of other cognitive functions.

Development of a sensitive droplet digital PCR according to the HPV infection specificity in Chinese population.

HPV16 and 18 are positively correlated with cervical carcinogenesis. However, HPV prevalence tends to vary according to region, nationality, and environment. The most prevalent high-risk (HR) HPV genotypes are HPV16, 52, 58, 56, 18, 33, and 45), while the low-risk (LR) genotypes are HPV6 and 11 in the Chinese population. Importantly, undetectable low-copy HPV DNA could be an important indicator of integration into the human genome and may be a precursor to cancer progression. The HPV viral load changes dramatically, either increasing or decreasing rapidly during carcinogenesis, and traditional quantitative real-time PCR (qPCR) cannot accurately capture this subtle change. Therefore, in this study, a reliable droplet digital PCR (ddPCR) method was developed to simultaneously detect and quantify HPV genotypes. The ddPCR quantitative results showed high accuracy, sensitivity, and specificity compared to qPCR results employing the same clinical specimens and supplemented the ddPCR assay for HPV52/56/58/6 genotypes according to the infection specificity of the Chinese population. In summary, this procedure is valuable for quantifying HPV DNA, especially under conditions of low template copy number in cervical intraepithelial neoplasia (CIN) and/or cervical cancer. Additionally, this method can dynamically observe the prognosis and outcome of HPV infection and thus be used as an effective means for real-time monitoring of tumor load.

Behavioral and neural correlates of social network size: The unique and common contributions of face recognition and extraversion.

OBJECTIVES: Humans are inherently social creatures and can gain advantages from larger network size. Researches have shown that different cognitive and personality factors may result in individual differences of social network size (SNS). Here, we focused on whether face recognition ability and extraversion were related to SNS and the neural basis underlying the relations. METHODS: Behaviorally, we adopted the face-inversion task, NEO personality inventory, and computerized SNS test to explore the relationships between face recognition, extraversion, and SNS. Neurally, we used resting state functional magnetic resonance imaging and fractional amplitude of low-frequency fluctuation (fALFF) analysis method to investigate the neural correlates of SNS and then revealed whether face recognition and extraversion were related to SNS relevant brain regions. RESULTS: We found that individuals with better face recognition ability and more extraverted personality had larger size of social network. In addition, we found that SNS was positively associated with the fALFF in the ventromedial prefrontal cortex (vmPFC), right superior temporal sulcus, and precuneus. Interestingly, the fALFF in the vmPFC significantly correlated with face recognition ability. CONCLUSIONS: Our study suggests that both face recognition and extraversion may be important correlates of SNS, and the underlying spontaneous neural substrates are partially dissociable.

Quantifying the variability of neural activation in working memory: A functional probabilistic atlas.

Working memory is a fundamental cognitive ability that allows the maintenance and manipulation of information for a brief period of time. Previous studies found a set of brain regions activated during working memory tasks, such as the prefrontal and parietal cortex. However, little is known about the variability of neural activation in working memory. Here, we used functional magnetic resonance imaging to quantify individual, hemispheric, and sex differences of working memory activation in a large cohort of healthy adults (N = 477). We delineated subject-specific activated regions in each individual, including the frontal pole, middle frontal gyrus, frontal eye field, superior parietal lobule, insular, precuneus, and anterior cingulate cortex. A functional probabilistic atlas was created to quantify individual variability in working memory regions. More than 90% of the participants activated all seven regions in both hemispheres, but the intersection of regions across participants was markedly less (50%), indicating significant individual differences in working memory activations. Moreover, we found hemispheric and sex differences in activation location, extent, and magnitude. Most activation regions were larger in the right than in the left hemisphere, but the magnitude of activation did not follow a similar pattern. Men showed more extensive and stronger activations than women. Taken together, our functional probabilistic atlas quantified variabilities of neural activation in working memory, providing a robust spatial reference for standardization of functional localization.

Development of navigation network revealed by resting-state and task-state functional connectivity.

Humans possess the essential capacity to navigate in environment, supported by multiple brain regions constituting the navigation network. Recent studies on development of the navigation network mainly examined activation changes in the medial temporal regions. It is unclear how the large-scale organization of the whole navigation network develops and whether the network organizations under resting-state and task-state develop differently. We addressed these questions by examining functional connectivity (FC) of the navigation network in 122 children (10-13 years) and 260 adults. First, we identified a modular structure in the navigation network during resting-state that included a ventral and a dorsal module. Then, we found that the intrinsic modular structure was strengthened from children to adults, that is, adults showed stronger FC within the ventral module and weaker FC between ventral and dorsal modules than children. Further, the intrinsic modular structure was loosened when performing scene-viewing task, that is, both adults and children showed decreased within-ventral FC and increased between-module FC during task- than resting-state. Finally, the task-modulated FC changes were greater in adults than in children. In sum, our study reveals age-related changes in the navigation network organization as increasing modularity under resting-state and increasing flexibility under task-state.

Multi-Item Discriminability Pattern to Faces in Developmental Prosopagnosia Reveals Distinct Mechanisms of Face Processing.

Previous studies have shown that individuals with developmental prosopagnosia (DP) show specific deficits in face processing. However, the mechanism underlying the deficits remains largely unknown. One hypothesis suggests that DP shares the same mechanism as normal population, though their faces processing is disproportionally impaired. An alternative hypothesis emphasizes a qualitatively different mechanism of DP processing faces. To test these hypotheses, we instructed DP and normal individuals to perceive faces and objects. Instead of calculating accuracy averaging across stimulus items, we used the discrimination accuracy for each item to construct a multi-item discriminability pattern. We found DP's discriminability pattern was less similar to that of normal individuals when perceiving faces than perceiving objects, suggesting that DP has qualitatively different mechanism in representing faces. A functional magnetic resonance imaging study was conducted to reveal the neural basis and found that multi-voxel activation patterns for faces in the right fusiform face area and occipital face area of DP were deviated away from the mean activation pattern of normal individuals. Further, the face representation was more heterogeneous in DP, suggesting that deficits of DP may come from multiple sources. In short, our study provides the first direct evidence that DP processes faces qualitatively different from normal population.

Developmental Reorganization of the Core and Extended Face Networks Revealed by Global Functional Connectivity.

Prior studies on development of functional specialization in human brain mainly focus on age-related increases in regional activation and connectivity among regions. However, a few recent studies on the face network demonstrate age-related decrease in face-specialized activation in the extended face network (EFN), in addition to increase in activation in the core face network (CFN). Here we used a voxel-based global brain connectivity approach to investigate whether development of the face network exhibited both increase and decrease in network connectivity. We found the voxel-wise resting-state functional connectivity (FC) within the CFN increased with age in bilateral posterior superior temporal sulcus, suggesting the integration of the CFN during development. Interestingly, the FC of the voxels in the EFN to the right fusiform face area and occipital face area decreased with age, suggesting that the CFN segregated from the EFN during development. Moreover, the age-related connectivity in the CFN was related to behavioral performance in face processing. Overall, our study demonstrated developmental reorganization of the face network achieved by both integration within the CFN and segregation of the CFN from the EFN, which may account for the simultaneous increases and decreases in neural activation during the development of the face network.

The neural network for face recognition: Insights from an fMRI study on developmental prosopagnosia.

Face recognition is supported by collaborative work of multiple face-responsive regions in the brain. Based on findings from individuals with normal face recognition ability, a neural model has been proposed with the occipital face area (OFA), fusiform face area (FFA), and face-selective posterior superior temporal sulcus (pSTS) as the core face network (CFN) and the rest of the face-responsive regions as the extended face network (EFN). However, little is known about how these regions work collaboratively for face recognition in our daily life. Here we focused on individuals suffering developmental prosopagnosia (DP), a neurodevelopmental disorder specifically impairing face recognition, to shed light on the infrastructure of the neural model of face recognition. Specifically, we used a variant of global brain connectivity method to comprehensively explore resting-state functional connectivity (FC) among face-responsive regions in a large sample of DPs (N = 64). We found that both the FCs within the CFN and those between the CFN and EFN were largely reduced in DP. Importantly, the right OFA and FFA served as the dysconnectivity hubs within the CFN, i.e., FCs concerning these two regions within the CFN were largely disrupted. In addition, DPs' right FFA also showed reduced FCs with the EFN. Moreover, these disrupted FCs were related to DP's behavioral deficit in face recognition, with the FCs from the FFA to the anterior temporal lobe (ATL) and pSTS the most predictive. Based on these findings, we proposed a revised neural model of face recognition demonstrating the relatedness of interactions among face-responsive regions to face recognition.

Genetic Variation in S100B Modulates Neural Processing of Visual Scenes in Han Chinese.

Spatial navigation is a crucial ability for living. Previous animal studies have shown that the S100B gene is causally related to spatial navigation performance in mice. However, the genetic factors influencing human navigation and its neural substrates remain unclear. Here, we provided the first evidence that the S100B gene modulates neural processing of navigationally relevant scenes in humans. First, with a novel protocol, we demonstrated that the spatial pattern of S100B gene expression in postmortem brains was associated with brain activation pattern for spatial navigation in general, and for scene processing in particular. Further, in a large fMRI cohort of healthy adults of Han Chinese (N = 202), we found that S100B gene polymorphisms modulated scene selectivity in the retrosplenial cortex (RSC) and parahippocampal place area. Finally, the serum levels of S100B protein mediated the association between S100B gene polymorphism and scene selectivity in the RSC. Our study takes the first step toward understanding the neurogenetic mechanism of human spatial navigation and suggests a novel approach to discover candidate genes modulating cognitive functions.

The Hierarchical Structure of the Face Network Revealed by Its Functional Connectivity Pattern.

A major principle of human brain organization is "integrating" some regions into networks while "segregating" other sets of regions into separate networks. However, little is known about the cognitive function of the integration and segregation of brain networks. Here, we examined the well-studied brain network for face processing, and asked whether the integration and segregation of the face network (FN) are related to face recognition performance. To do so, we used a voxel-based global brain connectivity method based on resting-state fMRI to characterize the within-network connectivity (WNC) and the between-network connectivity (BNC) of the FN. We found that 95.4% of voxels in the FN had a significantly stronger WNC than BNC, suggesting that the FN is a relatively encapsulated network. Importantly, individuals with a stronger WNC (i.e., integration) in the right fusiform face area were better at recognizing faces, whereas individuals with a weaker BNC (i.e., segregation) in the right occipital face area performed better in the face recognition tasks. In short, our study not only demonstrates the behavioral relevance of integration and segregation of the FN but also provides evidence supporting functional division of labor between the occipital face area and fusiform face area in the hierarchically organized FN. Significance statement: Although the integration and segregation are major principles of human brain organization, little is known about whether they support the cognitive processes. By correlating the within-network connectivity (WNC) and between-network connectivity (BNC) of the face network with face recognition performance, we found that individuals with stronger WNC in the right fusiform face area or weaker BNC in the right occipital face area were better at recognizing faces. Our study not only demonstrates the behavioral relevance of the integration and segregation but also provides evidence supporting functional division of labor between the occipital face area and fusiform face area in the hierarchically organized face network.

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.

Typical and Atypical Development of Functional Connectivity in the Face Network.

Extensive studies have demonstrated that face recognition performance does not reach adult levels until adolescence. However, there is no consensus on whether such prolonged improvement stems from development of general cognitive factors or face-specific mechanisms. Here, we used behavioral experiments and functional magnetic resonance imaging (fMRI) to evaluate these two hypotheses. With a large cohort of children (n = 379), we found that the ability of face-specific recognition in humans increased with age throughout childhood and into late adolescence in both face memory and face perception. Neurally, to circumvent the potential problem of age differences in task performance, attention, or cognitive strategies in task-state fMRI studies, we measured the resting-state functional connectivity (RSFC) between the occipital face area (OFA) and fusiform face area (FFA) in human brain and found that the OFA-FFA RSFC increased until 11-13 years of age. Moreover, the OFA-FFA RSFC was selectively impaired in adults with developmental prosopagnosia (DP). In contrast, no age-related changes or differences between DP and normal adults were observed for RSFCs in the object system. Finally, the OFA-FFA RSFC matured earlier than face selectivity in either the OFA or FFA. These results suggest the critical role of the OFA-FFA RSFC in the development of face recognition. Together, our findings support the hypothesis that prolonged development of face recognition is face specific, not domain general.

Dissociable roles of internal feelings and face recognition ability in facial expression decoding.

The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding.

Functional integration of the posterior superior temporal sulcus correlates with facial expression recognition.

Face perception is essential for daily and social activities. Neuroimaging studies have revealed a distributed face network (FN) consisting of multiple regions that exhibit preferential responses to invariant or changeable facial information. However, our understanding about how these regions work collaboratively to facilitate facial information processing is limited. Here, we focused on changeable facial information processing, and investigated how the functional integration of the FN is related to the performance of facial expression recognition. To do so, we first defined the FN as voxels that responded more strongly to faces than objects, and then used a voxel-based global brain connectivity method based on resting-state fMRI to characterize the within-network connectivity (WNC) of each voxel in the FN. By relating the WNC and performance in the "Reading the Mind in the Eyes" Test across participants, we found that individuals with stronger WNC in the right posterior superior temporal sulcus (rpSTS) were better at recognizing facial expressions. Further, the resting-state functional connectivity (FC) between the rpSTS and right occipital face area (rOFA), early visual cortex (EVC), and bilateral STS were positively correlated with the ability of facial expression recognition, and the FCs of EVC-pSTS and OFA-pSTS contributed independently to facial expression recognition. In short, our study highlights the behavioral significance of intrinsic functional integration of the FN in facial expression processing, and provides evidence for the hub-like role of the rpSTS for facial expression recognition. Hum Brain Mapp 37:1930-1940, 2016. © 2016 Wiley Periodicals, Inc.

Extraversion mediates the relationship between structural variations in the dorsolateral prefrontal cortex and social well-being.

Social well-being reflects the appraisal of one's circumstance and functioning in society, which is crucial for individuals' mental and physical health. However, little is known about the neural processes associated with social well-being. In this study, we used voxel-based morphometry (VBM) to identify the brain regions underlying individual differences in social well-being, as measured by the Social Well-being Scale (SWBS), in a large sample of young healthy adults. We found that social well-being was negatively correlated with gray matter volume in left mid-dorsolateral prefrontal cortex (mid-DLPFC) that is implicated in executive functioning, emotional regulation and social reasoning. The results remained significant even after controlling for the effect of socioeconomic status. Furthermore, although basic personality factors such as neuroticism, extraversion, and conscientiousness (as measured by the NEO Personality Inventory) all contributed to social well-being, only extraversion acted as a mediational mechanism underlying the association between the left mid-DLPFC volume and social well-being. Together, our findings provide the first evidence for the structural basis of individual differences in social well-being, and suggest that the personality trait of extraversion might play an important role in the acquisition and process of social well-being.

Neural correlates of the happy life: the amplitude of spontaneous low frequency fluctuations predicts subjective well-being.

Subjective well-being is assumed to be distributed in the hedonic hotspots of subcortical and cortical structures. However, the precise neural correlates underlying this construct, especially how it is maintained during the resting state, are still largely unknown. Here, we explored the neural basis of subjective well-being by correlating the regional fractional amplitude of low frequency fluctuations (fALFF) with the self-reported subjective well-being of healthy individuals. Behaviorally, we demonstrated that subjective well-being contained two related but distinct components: cognitive and affective well-being. Neurally, we showed that the fALFF in the bilateral posterior superior temporal gyrus (pSTG), right posterior mid-cingulate cortex (pMCC), right thalamus, left postcentral gyrus (PCG), right lingual gyrus, and left planum temporale (PT) positively predicted cognitive well-being, whereas the fALFF in the bilateral superior frontal gyrus (SFG), right orbitofrontal cortex (OFC), and left inferior temporal gyrus (ITG) negatively predicted cognitive well-being. In contrast, only the fALFF in the right amygdala reliably predicted affective well-being. Furthermore, emotional intelligence partially mediated the effects of the right pSTG and thalamus on cognitive well-being, as well as the effect of the right amygdala on affective well-being. In summary, we provide the first evidence that spontaneous brain activity in multiple regions associated with sensation, social perception, cognition, and emotion contributes to cognitive well-being, whereas the spontaneous brain activity in only one emotion-related region contributes to affective well-being, suggesting that the spontaneous activity of the human brain reflect the efficiency of subjective well-being.

Quantifying interindividual variability and asymmetry of face-selective regions: a probabilistic functional atlas.

Face-selective regions (FSRs) are among the most widely studied functional regions in the human brain. However, individual variability of the FSRs has not been well quantified. Here we use functional magnetic resonance imaging (fMRI) to localize the FSRs and quantify their spatial and functional variabilities in 202 healthy adults. The occipital face area (OFA), posterior and anterior fusiform face areas (pFFA and aFFA), posterior continuation of the superior temporal sulcus (pcSTS), and posterior and anterior STS (pSTS and aSTS) were delineated for each individual with a semi-automated procedure. A probabilistic atlas was constructed to characterize their interindividual variability, revealing that the FSRs were highly variable in location and extent across subjects. The variability of FSRs was further quantified on both functional (i.e., face selectivity) and spatial (i.e., volume, location of peak activation, and anatomical location) features. Considerable interindividual variability and rightward asymmetry were found in all FSRs on these features. Taken together, our work presents the first effort to characterize comprehensively the variability of FSRs in a large sample of healthy subjects, and invites future work on the origin of the variability and its relation to individual differences in behavioral performance. Moreover, the probabilistic functional atlas will provide an adequate spatial reference for mapping the face network.

Serotonin transporter gene polymorphism (5-HTTLPR) influences trait anxiety by modulating the functional connectivity between the amygdala and insula in Han Chinese males.

A functional polymorphism (5-hydroxytryptamine transporter linked polymorphic region [5-HTTLPR]) in the promoter region of human serotonin transporter gene has been found to be associated with several dimensions of neuroticism and psychopathology, especially anxiety. However, the neural basis underlying the association between 5-HTTLPR and anxiety is less clear. Here, we explored how 5-HTTLPR influenced anxiety by modulating the spontaneous brain activities in Han Chinese. First, we found an association between 5-HTTLPR and anxiety only in the male and not in the female population, where male S/S homozygotes had a significantly higher level of anxiety than male L allele carriers. Then, we examined how 5-HTTLPR influenced anxiety at both regional and network levels in the brain at rest. At the regional level, we found a significantly higher fractional amplitude of low-frequency fluctuations in the amygdala in male S/S homozygotes relative to male L allele carriers. At the network level, male S/S homozygotes showed a weaker resting-state functional connectivity (RSFC) between the amygdala and various regions, including the insula, Heschl's gyrus, lateral occipital cortex, superior temporal gyrus, and hippocampus, and a stronger RSFC between the amygdala and various regions, including the supramariginal gyrus and middle frontal gyrus. However, at both levels, only was the amygdala-insula RSFC correlated with anxiety. Mediation analyses further revealed that the amygdala-insula RSFC mediated the association between 5-HTTLPR and anxiety. In short, our study provided the first empirical evidence that the amygdala-insula RSFC served as the neural basis underlying the association between 5-HTTLPR and anxiety, suggesting a potential neurogenetic susceptibility mechanism for anxiety.

Different neural pathways linking personality traits and eudaimonic well-being: a resting-state functional magnetic resonance imaging study.

Eudaimonic well-being (EWB) is the fulfillment of human potential and a meaningful life. Previous studies have shown that personality traits, especially extraversion, neuroticism, and conscientiousness, significantly contribute to EWB. However, the neurobiological pathways linking personality and EWB are not understood. Here, we used resting-state functional magnetic resonance imaging (rs-fMRI) to investigate this issue. Specifically, we correlated individuals' EWB scores with the regional fractional amplitude of low-frequency fluctuations (fALFF) of the brain, and then examined how personality traits predicted EWB-related spontaneous brain activity. We found that EWB was positively correlated with the fALFF in the right posterior superior temporal gyrus (pSTG) and thalamus, and negatively correlated with the strength of the thalamic-insular connectivity. More importantly, we found that personality traits influenced EWB in different ways. At the regional level, the fALFF in the pSTG and thalamus mediated the effects of neuroticism and extraversion on EWB, whereas the thalamus mediated the effect of conscientiousness on EWB. At the functional connectivity level, the thalamic-insular connectivity only mediated the effect of neuroticism on EWB. Taken together, our study provides the first evidence that EWB is associated with personality traits through different neural substrates.

Neural correlates of social interaction anxiety and their relation to emotional intelligence: A resting-state fMRI study.

Social interaction anxiety refers to a state of anxiety resulting from the prospect or presence of interpersonal evaluation in real or imagined social settings. Previous neuroimaging studies have revealed neural basis of social anxiety disorder. However, little is known about the neural correlates of individual differences in social interaction anxiety in nonclinical population. In the present study, we used resting-state functional magnetic resonance imaging to explore the relationship between individual's spontaneous neural activity and social interaction anxiety, and the role that emotional intelligence played in the relationship. To this end, the correlation between the regional fractional amplitude of low-frequency fluctuations (fALFF) of the brain and individuals' social interaction anxiety scores was examined. We found that social interaction anxiety was correlated with the fALFF in the insula, parahippocampal gyrus, bilateral superior temporal gyrus, and superior parietal lobule. Furthermore, we also found that emotional intelligence partially mediated the association between the fALFF in these regions and social interaction anxiety. Taken together, our study provided the first evidence for the spontaneous neural basis of social interaction anxiety in normal population, and highlighted the neural substrates through which emotional intelligence might play an important role in social interaction anxiety.