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.

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.

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.

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.

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.

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.

The amygdala is composed of structurally and functionally distinct nuclei that contribute to the processing of emotion through interactions with other subcortical and cortical structures. While these circuits have been studied extensively in animals, human neuroimaging investigations of amygdala-based networks have typically considered the amygdala as a single structure, which likely masks contributions of individual amygdala subdivisions. The present study uses resting state functional magnetic resonance imaging (fMRI) to test whether distinct functional connectivity patterns, like those observed in animal studies, can be detected across three amygdala subdivisions: laterobasal, centromedial, and superficial. In a sample of 65 healthy adults, voxelwise regression analyses demonstrated positively-predicted ventral and negatively-predicted dorsal networks associated with the total amygdala, consistent with previous animal and human studies. Investigation of individual amygdala subdivisions revealed distinct differences in connectivity patterns within the amygdala and throughout the brain. Spontaneous activity in the laterobasal subdivision predicted activity in temporal and frontal regions, while activity in the centromedial nuclei predicted activity primarily in striatum. Activity in the superficial subdivision positively predicted activity throughout the limbic lobe. These findings suggest that resting state fMRI can be used to investigate human amygdala networks at a greater level of detail than previously appreciated, allowing for the further advancement of translational models.

Increased intraindividual variability (IIV) is a hallmark of disorders of attention. Recent work has linked these disorders to abnormalities in a "default mode" network, comprising brain regions routinely deactivated during goal-directed cognitive tasks. Findings from a study of the neural basis of attentional lapses suggest that a competitive relationship between the "task-negative" default mode network and regions of a "task-positive" attentional network is a potential locus of dysfunction in individuals with increased IIV. Resting state studies have shown that this competitive relationship is intrinsically represented in the brain, in the form of a negative correlation or antiphase relationship between spontaneous activity occurring in the two networks. We quantified the negative correlation between these two networks in 26 subjects, during active (Eriksen flanker task) and resting state scans. We hypothesized that the strength of the negative correlation is an index of the degree of regulation of activity in the default mode and task-positive networks and would be positively related to consistent behavioral performance. We found that the strength of the correlation between the two networks varies across individuals. These individual differences appear to be behaviorally relevant, as interindividual variation in the strength of the correlation was significantly related to individual differences in response time variability: the stronger the negative correlation (i.e., the closer to 180 degrees antiphase), the less variable the behavioral performance. This relationship was moderately consistent across resting and task conditions, suggesting that the measure indexes moderately stable individual differences in the integrity of functional brain networks. We discuss the implications of these findings for our understanding of the behavioral significance of spontaneous brain activity, in both healthy and clinical populations.

Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6-13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder.

Humans are a highly social species. Complex interactions for mutual support range from helping neighbors to building social welfare institutions. During times of distress or crisis, sharing life experiences within one's social circle is critical for well-being. By translating pattern-learning algorithms to the UK Biobank imaging-genetics cohort (n = ~40 000 participants), we have delineated manifestations of regular social support in multimodal whole-brain measurements. In structural brain variation, we identified characteristic volumetric signatures in the salience and limbic networks for high- versus low-social support individuals. In patterns derived from functional coupling, we also located interindividual differences in social support in action-perception circuits related to binding sensory cues and initiating behavioral responses. In line with our demographic profiling analysis, the uncovered neural substrates have potential implications for loneliness, substance misuse, and resilience to stress.

The default mode network (DMN), a brain system anchored in the posteromedial cortex, has been identified as underconnected in adults with autism spectrum disorder (ASD). However, to date there have been no attempts to characterize this network and its involvement in mediating social deficits in children with ASD. Furthermore, the functionally heterogeneous profile of the posteromedial cortex raises questions regarding how altered connectivity manifests in specific functional modules within this brain region in children with ASD.

Investigations of the human brain's connectomic architecture have produced two alternative models: one describes the brain's spatial structure in terms of static localized networks, and the other describes the brain's temporal structure in terms of dynamic whole-brain states. Here, we used tools from connectivity dynamics to develop a synthesis that bridges these models. Using resting fMRI data, we investigated the assumptions undergirding current models of the human connectome. Consistent with state-based models, our results suggest that static localized networks are superordinate approximations of underlying dynamic states. Furthermore, each of these localized, dynamic connectivity states is associated with global changes in the whole-brain functional connectome. By nesting localized dynamic connectivity states within their whole-brain contexts, we demonstrate the relative temporal independence of brain networks. Our assay for functional autonomy of coordinated neural systems is broadly applicable, and our findings provide evidence of structure in temporal state dynamics that complements the well-described static spatial organization of the brain.

Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control.

Despite extensive research into executive function (EF), the precise relationship between brain dynamics and flexible cognition remains unknown. Using a large, publicly available dataset (189 participants), we find that functional connections measured throughout 56min of resting state fMRI data comprise five distinct connectivity states. Elevated EF performance as measured outside of the scanner was associated with greater episodes of more frequently occurring connectivity states, and fewer episodes of less frequently occurring connectivity states. Frequently occurring states displayed metastable properties, where cognitive flexibility may be facilitated by attenuated correlations and greater functional connection variability. Less frequently occurring states displayed properties consistent with low arousal and low vigilance. These findings suggest that elevated EF performance may be associated with the propensity to occupy more frequently occurring brain configurations that enable cognitive flexibility, while avoiding less frequently occurring brain configurations related to low arousal/vigilance states. The current findings offer a novel framework for identifying neural processes related to individual differences in executive function.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits. While such deficits have been the focus of most research, recent evidence suggests that individuals with ASD may exhibit cognitive strengths in domains such as mathematics.

Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show that there are more instances of greater functional connectivity in the brains of children with ASD in comparison to those of typically developing children. Hyperconnectivity in ASD was observed at the whole-brain and subsystems levels, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyperconnectivity predicted symptom severity in ASD, such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain of children with ASD is largely functionally hyperconnected in ways that contribute to social dysfunction. Our findings provide unique insights into brain mechanisms underlying childhood autism.