The effective connectivity networks among overlapped core regions recruited by motor execution (ME) and motor imagery (MI) were explored by means of conditional Granger causality and graph-theoretic method, based on functional magnetic resonance imaging (fMRI) data. Our results demonstrated more circuits of effective connectivity among the selected seed regions during right-hand performance than during left-hand performance, implying the influences of brain asymmetry of right-handedness on effective connectivity networks. The increased causal connections were found during ME than during MI, suggesting that the ME network may have some additional connections compared to MI networks to execute the overt physical movement. Furthermore, the In-Out degrees of information flow suggested left dorsal premotor cortex (PMd), inferior parietal lobule (IPL) and superior parietal lobule (SPL) as causal sources in ME/MI tasks, highlighting the dominant function of left PMd, IPL and SPL. These findings depicted the causal connectivity of motor related core regions in fronto-parietal circuit and might indicate the conversion of causal networks between ME and MI.

Several functional MRI (fMRI) activation studies have highlighted specific differences in brain response in social anxiety disorder (SAD) patients. Little is known, so far, about the changes in the functional architecture of resting state networks (RSNs) in SAD during resting state. We investigated statistical differences in RSNs on 20 SAD and 20 controls using independent component analysis. A diffuse impact on widely distributed RSNs and selective changes of RSN intrinsic functional connectivity were observed in SAD. Functional connectivity was decreased in the somato-motor (primary and motor cortices) and visual (primary visual cortex) networks, increased in a network including medial prefrontal cortex which is thought to be involved in self-referential processes, and increased or decreased in the default mode network (posterior cingulate cortex/precuneus, bilateral inferior parietal gyrus, angular gyrus, middle temporal gyrus, and superior and medial frontal gyrus) which has been suggested to be involved in episodic memory, and self-projection, the dorsal attention network (middle and superior occipital gyrus, inferior and superior parietal gyrus, and middle and superior frontal gyrus) which is thought to mediate goal-directed top-down processing, the core network (insula-cingulate cortices) which is associated with task control function, and the central-executive network (fronto-parietal cortices). A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients.

Previous functional neuroimaging studies have uncovered partly separable neural substrates for perceiving different facial expressions presented below the level of conscious awareness. However, as one of the six basic emotions, the neural mechanism of unconsciously perceiving surprised faces has not yet been investigated. Using a backward masking procedure, we studied the neural activities in response to surprised faces presented below the threshold of conscious visual perception by means of functional magnetic resonance imaging (fMRI). Eighteen healthy adults were scanned while viewing surprised faces, which presented for 33 ms and immediately "masked" by a neutral face for 467 ms. As a control, they viewed masked happy or neutral faces as well. In comparison to both control conditions, masked surprised faces yielded significantly greater activation in the parahippocampal gyrus and fusiform gyrus, which associated previously with novelty detection. In the present study, automatic activation of these areas to masked surprised faces was investigated as a function of individual differences in the ability of identifying and differentiating one's emotions, as assessed by the 20-item Toronto Alexithymia Scale (TAS-20). The correlation results showed that, the subscale, Difficulty Identifying Feelings, was negatively correlated with the neural response of these areas to masked surprised faces, which suggest that decreased activation magnitude in specific brain regions may reflect increased difficulties in recognizing one's emotions in everyday life. Additionally, we confirmed activation of the right amygdala and right thalamus to the masked surprised faces, which was previously proved to be involved in the unconscious emotional perception system.

Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during a period in early childhood when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety.

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior.

Altered function of the medial temporal lobe (MTL) is a valuable indicator of conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease. This study is to delineate the functional circuitry of multiple subdivisions of parahippocampal gyrus and hippocampus (HIP) and to examine how this knowledge contributes to a more principled understanding of the contributions of its subregions to memory in aMCI. The functional connectivity (FC) analysis was performed in 85 aMCI and 129 healthy controls. The aMCI demonstrated the distinct disruptive patterns of the MTL subregional connectivity with the whole-brain. The right entorhinal cortex (ERC) and perirhinal cortex (PRC) showed increased connectivity with the left inferior and middle occipital gyrus, respectively, which potentially indicated a compensatory mechanism. Furthermore, the right altered MTL subregional FC was associated with episodic memory performance in aMCI. These results provide novel insights into the heterogeneous nature of its large-scale connectivity in MTL subregions in memory system underlying the memory deficits in aMCI. It further suggests that altered FC of MTL subregions is associated with the impairment of the differential encoding stages of memories and the functional changes in the specific right HIP-ERC-PRC-temporal circuitry may contribute to the impairment of episodic memory in aMCI.

Autism spectrum disorder (ASD) is associated with disruption of local- and long-range functional connectivity (FC). The direction of those changes in FC (increase or decrease), however, is inconsistent across studies. Further, age-dependent changes of distance-specific FC in ASD remain unclear. In this study, we used resting-state functional magnetic resonance imaging data from sixty-four typical controls (TC) and sixty-four patients with ASD, whom we further classified into child (<11 years), adolescent (11-18 years) and adult cohorts (>18 years). Functional connectivity (FC) analysis was conducted at voxel level. We employed a three-way analysis of covariance on FC to conduct statistical analyses. Results revealed that patients with ASD had lower FC than TC in cerebellum, fusiform gyrus, inferior occipital gyrus and posterior inferior temporal gyrus. Significant diagnosis-by-distance interaction was observed in ASD patients with reduced short-range and long-range FC in posterior cingulate cortex and medial prefrontal cortex. Importantly, we found significant diagnosis-by-age-by-distance interaction in orbitofrontal cortex with short-range FC being lower in autistic children, but -to a less extent- higher in autistic adults. Our findings suggest a major role of connection length in development changes of FC in ASD. We hope our study will facilitate deeper understanding of the neural mechanisms underlying ASD.

Examination of spontaneous intrinsic brain activity is drawing increasing interest, thus methods for such analyses are rapidly evolving. Here we describe a novel measure, "network homogeneity", that allows for assessment of cohesiveness within a specified functional network, and apply it to resting-state fMRI data from adult ADHD and control participants. We examined the default mode network, a medial-wall based network characterized by high baseline activity that decreases during attention-demanding cognitive tasks. We found reduced network homogeneity within the default mode network in ADHD subjects compared to age-matched controls, particularly between the precuneus and other default mode network regions. This confirms previously published results using seed-based functional connectivity measures, and provides further evidence that altered precuneus connectivity is involved in the neuropathology of ADHD. Network homogeneity provides a potential alternative method for assessing functional connectivity of specific large-scale networks in clinical populations.

Although evidence is accumulating that autism spectrum disorder (ASD) is associated with disruption of functional connections between and within brain networks, it remains largely unknown whether these abnormalities are related to specific frequency bands. To address this question, network contingency analysis was performed on brain functional connectomes obtained from 213 adolescent participants across nine sites in the Autism Brain Imaging Data Exchange (ABIDE) multisite sample, to determine the disrupted connections between and within seven major cortical networks in adolescents with ASD at Slow-5, Slow-4 and Slow-3 frequency bands and further assess whether the aberrant intra- and inter-network connectivity varied as a function of ASD symptoms. Overall under-connectivity within and between large-scale intrinsic networks in ASD was revealed across the three frequency bands. Specifically, decreased connectivity strength within the default mode network (DMN), between DMN and visual network (VN), ventral attention network (VAN), and between dorsal attention network (DAN) and VAN was observed in the lower frequency band (slow-5, slow-4), while decreased connectivity between limbic network (LN) and frontal-parietal network (FPN) was observed in the higher frequency band (slow-3). Furthermore, weaker connectivity within and between specific networks correlated with poorer communication and social interaction skills in the slow-5 band, uniquely. These results demonstrate intrinsic under-connectivity within and between multiple brain networks within predefined frequency bands in ASD, suggesting that frequency-related properties underlie abnormal brain network organization in the disorder.

This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.

Most previous studies regarding social anxiety disorder (SAD) have focused on the role of emotional dysfunction, while impairments in self- and theory of mind (ToM)-processing have relatively been neglected. This study utilised functional connectivity density (FCD), resting-state functional connectivity (RSFC) and discriminant analyses to investigate impairments in self- and ToM-related networks in patients with SAD. Patients with SAD exhibited decreased long-range FCD in the right rostral anterior cingulate cortex (rACC) and decreased short-range FCD in the right superior temporal gyrus (STG)-key nodes involved in self- and ToM-processing, respectively. Decreased RSFC of the right rACC and STG with widespread frontal, temporal, posteromedial, sensorimotor, and somatosensory, regions was also observed in patients with SAD. Altered RSFC between the right rACC and bilateral superior frontal gyrus, between the right rACC and right middle frontal gyrus, and within the right STG itself provided the greatest contribution to individual diagnoses of SAD, with an accuracy of 84.5%. These results suggest that a lack of cognitive inhibition on emotional self-referential processing as well as impairments in social information integration may play critical roles in the pathomechanism of SAD and highlight the importance of recognising such features in the diagnosis and treatment of SAD.

Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts and behaviours in response to changing environmental demands. Brain mechanisms enabling flexibility have been examined using non-invasive neuroimaging and behavioural approaches in humans alongside pharmacological and lesion studies in animals. This work has identified large-scale functional brain networks encompassing lateral and orbital frontoparietal, midcingulo-insular and frontostriatal regions that support flexibility across the lifespan. Flexibility can be compromised in early-life neurodevelopmental disorders, clinical conditions that emerge during adolescence and late-life dementias. We critically evaluate evidence for the enhancement of flexibility through cognitive training, physical activity and bilingual experience.

Even with an overarching functional dysconnectivity model of adolescent-onset schizophrenia (AOS), there have been no functional connectome (FC) biomarkers identified for predicting patients' specific symptom domains. Adolescence is a period of dramatic brain maturation, with substantial interindividual variability in brain anatomy. However, existing group-level hypotheses of AOS lack precision in terms of neuroanatomical boundaries. This study aimed to identify individual-specific FC biomarkers associated with schizophrenic symptom manifestation during adolescent brain maturation. We used a reliable individual-level cortical parcellation approach to map functional brain regions in each subject, that were then used to identify FC biomarkers for predicting dimension-specific psychotic symptoms in 30 antipsychotic-naïve first-episode AOS patients (recruited sample of 39). Age-related changes in biomarker expression were compared between these patients and 31 healthy controls. Moreover, 29 antipsychotic-naïve first-episode AOS patients (analyzed sample of 25) were recruited from another center to test the generalizability of the prediction model. Individual-specific FC biomarkers could significantly and better predict AOS positive-dimension symptoms with a relatively stronger generalizability than at the group level. Specifically, positive symptom domains were estimated based on connections between the frontoparietal control network (FPN) and salience network and within FPN. Consistent with the neurodevelopmental hypothesis of schizophrenia, the FPN-SN connection exhibited aberrant age-associated alteration in AOS. The individual-level findings reveal reproducible FPN-based FC biomarkers associated with AOS positive symptom domains, and highlight the importance of accounting for individual variation in the study of adolescent-onset disorders.

Neuroimaging studies have uncovered the neural roots of individual differences in human general fluid intelligence (Gf). Gf is characterized by the function of specific neural circuits in brain gray-matter; however, the association between Gf and neural function in brain white-matter (WM) remains unclear. Given reliable detection of blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals in WM, we used a functional, rather than an anatomical, neuromarker in WM to identify individual Gf. We collected longitudinal BOLD-fMRI data (in total three times, ~11 months between time 1 and time 2, and ~29 months between time 1 and time 3) in normal volunteers at rest, and identified WM functional connectomes that predicted the individual Gf at time 1 (n = 326). From internal validation analyses, we demonstrated that the constructed predictive model at time 1 predicted an individual's Gf from WM functional connectomes at time 2 (time 1 ∩ time 2: n = 105) and further at time 3 (time 1 ∩ time 3: n = 83). From external validation analyses, we demonstrated that the predictive model from time 1 was generalized to unseen individuals from another center (n = 53). From anatomical aspects, WM functional connectivity showing high predictive power predominantly included the superior longitudinal fasciculus system, deep frontal WM, and ventral frontoparietal tracts. These results thus demonstrated that WM functional connectomes offer a novel applicable neuromarker of Gf and supplement the gray-matter connectomes to explore brain-behavior relationships.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by substantial clinical and biological heterogeneity. Quantitative and individualized metrics for delineating the heterogeneity of brain structure in ASD are still lacking. Likewise, the extent to which brain structural metrics of ASD deviate from typical development (TD) and whether deviations can be used for parsing brain structural phenotypes of ASD is unclear.

Brodmann areas 6, 44 and 45 in the ventrolateral frontal cortex of the left hemisphere of the human brain constitute the anterior language production zone. The anatomical connectivity of these areas with parietal and temporal cortical regions was recently examined in an autoradiographic tract-tracing study in the macaque monkey. Studies suggest strong correspondence between human resting state functional connectivity (RSFC) based on functional magnetic resonance imaging data and experimentally demonstrated anatomical connections in non-human primates. Accordingly, we hypothesized that areas 6, 44 and 45 of the human brain would exhibit patterns of RSFC consistent with patterns of anatomical connectivity observed in the macaque. In a primary analysis, we examined the RSFC associated with regions-of-interest placed in ventrolateral frontal areas 6, 44 and 45, on the basis of local sulcal and gyral anatomy. We validated the results of the primary hypothesis-driven analysis with a data-driven partitioning of ventrolateral frontal cortex into regions exhibiting distinct RSFC patterns, using a spectral clustering algorithm. The RSFC of ventrolateral frontal areas 6, 44 and 45 was consistent with patterns of anatomical connectivity shown in the macaque. We observed a striking dissociation between RSFC for the ventral part of area 6 that is involved in orofacial motor control and RSFC associated with Broca's region (areas 44 and 45). These findings indicate rich and differential RSFC patterns for the ventrolateral frontal areas controlling language production, consistent with known anatomical connectivity in the macaque brain, and suggest conservation of connectivity during the evolution of the primate brain.

Functional connectivity (FC) between the amygdala and the ventromedial prefrontal cortex underlies socioemotional functioning, a core domain of impairment in autism spectrum disorder (ASD). Although frontoamygdala circuitry undergoes dynamic changes throughout development, little is known about age-related changes in frontoamygdala networks in ASD. Here we characterize frontoamygdala resting-state FC in a cross-sectional sample (ages 7-25) of 58 typically developing (TD) individuals and 53 individuals with ASD. Contrary to hypotheses, individuals with ASD did not show different age-related patterns of frontoamygdala FC compared with TD individuals. However, overall group differences in frontoamygdala FC were observed. Specifically, relative to TD individuals, individuals with ASD showed weaker frontoamygdala FC between the right basolateral (BL) amygdala and the rostral anterior cingulate cortex (rACC). These findings extend prior work to a broader developmental range in ASD, and indicate ASD-related differences in frontoamygdala FC that may underlie core socioemotional impairments in children and adolescents with ASD.

The human insular cortex consists of functionally diverse subdivisions that engage during tasks ranging from interoception to cognitive control. The multiplicity of functions subserved by insular subdivisions calls for a nuanced investigation of their functional connectivity profiles. Four insula subdivisions (dorsal anterior, dAI; ventral, VI; posterior, PI; middle, MI) derived using a data-driven approach were subjected to static- and dynamic functional network connectivity (s-FNC and d-FNC) analyses. Static-FNC analyses replicated previous work demonstrating a cognition-emotion-interoception division of the insula, where the dAI is functionally connected to frontal areas, the VI to limbic areas, and the PI and MI to sensorimotor areas. Dynamic-FNC analyses consisted of k-means clustering of sliding windows to identify variable insula connectivity states. The d-FNC analysis revealed that the most frequently occurring dynamic state mirrored the cognition-emotion-interoception division observed from the s-FNC analysis, with less frequently occurring states showing overlapping and unique subdivision connectivity profiles. In two of the states, all subdivisions exhibited largely overlapping profiles, consisting of subcortical, sensory, motor, and frontal connections. Two other states showed the dAI exhibited a unique connectivity profile compared with other insula subdivisions. Additionally, the dAI exhibited the most variable functional connections across the s-FNC and d-FNC analyses, and was the only subdivision to exhibit dynamic functional connections with regions of the default mode network. These results highlight how a d-FNC approach can capture functional dynamics masked by s-FNC approaches, and reveal dynamic functional connections enabling the functional flexibility of the insula across time. Hum Brain Mapp 37:1770-1787, 2016. © 2016 Wiley Periodicals, Inc.

Two neural systems for goal-directed and stimulus-driven attention have been described in the adult human brain; the dorsal attention network (DAN) centered in the frontal eye fields (FEF) and intraparietal sulcus (IPS), and the ventral attention network (VAN) anchored in the temporoparietal junction (TPJ) and ventral frontal cortex (VFC). Little is known regarding the processes governing typical development of these attention networks in the brain. Here we use resting state functional MRI data collected from thirty 7 to 12 year-old children and thirty 18 to 31 year-old adults to examine two key regions of interest from the dorsal and ventral attention networks. We found that for the DAN nodes (IPS and FEF), children showed greater functional connectivity with regions within the network compared with adults, whereas adults showed greater functional connectivity between the FEF and extra-network regions including the posterior cingulate cortex. For the VAN nodes (TPJ and VFC), adults showed greater functional connectivity with regions within the network compared with children. Children showed greater functional connectivity between VFC and nodes of the salience network. This asymmetric pattern of development of attention networks may be a neural signature of the shift from over-representation of bottom-up attention mechanisms to greater top-down attentional capacities with development.

Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD.