Functional MRI studies report insular activations across a wide range of tasks involving affective, sensory, and motor processing, but also during tasks of high-level perception, attention, and control. While insular cortical activations are often reported in the literature, the diverse functional roles of this region are still not well understood. We used a meta-analytic approach to analyze the coactivation profiles of insular subdivisions -- dorsal anterior, ventral anterior, and posterior insula -- across fMRI studies in terms of multiple task domains including emotion, memory, attention, and reasoning. We found extensive coactivation of each insular subdivision, with substantial overlap between coactivation partners for each subdivision. Functional fingerprint analyses revealed that all subdivisions cooperated with a functionally diverse set of regions. Graph-theoretic analyses revealed that the dorsal anterior insula was a highly “central” structure in the coactivation network. Furthermore, analysis of the studies that activate the insular cortex itself showed that the right dorsal anterior insula was a particularly “diverse” structure in that it was likely to be active across multiple task domains. These results highlight the nuanced functional profiles of insular subdivisions and are consistent with recent work suggesting that the dorsal anterior insula can be considered a critical functional hub in the human brain.
anterior insula; brain network; functional connectivity; coactivation meta-analysis; graph theory
Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood.
To examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD.
DESIGN, SETTING, AND PARTICIPANTS
Case-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children.
MAIN OUTCOMES AND MEASURES
Between-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD.
We observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual’s salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen–level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity.
CONCLUSIONS AND RELEVANCE
Salience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.
While there is almost universal agreement amongst researchers that autism is associated with alterations in brain connectivity, the precise nature of these alterations continues to be debated. Theoretical and empirical work is beginning to reveal that autism is associated with a complex functional phenotype characterized by both hypo- and hyper-connectivity of large-scale brain systems. It is not yet understood why such conflicting patterns of brain connectivity are observed across different studies, and the factors contributing to these heterogeneous findings have not been identified. Developmental changes in functional connectivity have received inadequate attention to date. We propose that discrepancies between findings of autism related hypo-connectivity and hyper-connectivity might be reconciled by taking developmental changes into account. We review neuroimaging studies of autism, with an emphasis on functional magnetic resonance imaging studies of intrinsic functional connectivity in children, adolescents and adults. The consistent pattern emerging across several studies is that while intrinsic functional connectivity in adolescents and adults with autism is generally reduced compared with age-matched controls, functional connectivity in younger children with the disorder appears to be increased. We suggest that by placing recent empirical findings within a developmental framework, and explicitly characterizing age and pubertal stage in future work, it may be possible to resolve conflicting findings of hypo- and hyper-connectivity in the extant literature and arrive at a more comprehensive understanding of the neurobiology of autism.
autism spectrum disorders; brain development; functional connectivity; puberty; fMRI
Recent evidence for the fractionation of the default mode network (DMN) into functionally distinguishable subdivisions with unique patterns of connectivity calls for a reconceptualization of the relationship between this network and self-referential processing. Advances in resting-state functional connectivity analyses are beginning to reveal increasingly complex patterns of organization within the key nodes of the DMN – medial prefrontal cortex and posterior cingulate cortex – as well as between these nodes and other brain systems. Here we review recent examinations of the relationships between the DMN and various aspects of self-relevant and social-cognitive processing in light of emerging evidence for heterogeneity within this network. Drawing from a rapidly evolving social-cognitive neuroscience literature, we propose that embodied simulation and mentalizing are processes which allow us to gain insight into another’s physical and mental state by providing privileged access to our own physical and mental states. Embodiment implies that the same neural systems are engaged for self- and other-understanding through a simulation mechanism, while mentalizing refers to the use of high-level conceptual information to make inferences about the mental states of self and others. These mechanisms work together to provide a coherent representation of the self and by extension, of others. Nodes of the DMN selectively interact with brain systems for embodiment and mentalizing, including the mirror neuron system, to produce appropriate mappings in the service of social-cognitive demands.
functional connectivity; embodiment; mentalizing; autobiographical memory; medial prefrontal cortex; posterior cingulate cortex
Over the past several years, the study of self-related cognition has garnered increasing interest amongst psychologists and cognitive neuroscientists. Concomitantly, lesion and neuroimaging studies have demonstrated the importance of intact cortico-cortical and cortico-subcortical connections for supporting high-level cognitive functions. Comissurotomy or “split-brain” patients provide unique insights into the role of the cerebral commissures in maintaining an individual’s sense of self, as well as into the unique self-representation capabilities of each cerebral hemisphere. Here we review empirical work examining the integrity of self-related processes in patients with various disconnection syndromes, focusing on studies of self-recognition, ownership, and agency. Taken together, this body of work suggests that an intact corpus callosum enabling interhemispheric transfer is necessary for some, but not all types of self-representations.
split-brain; commissurotomy; corpus callosum; self-recognition; self-awareness; brain network; brain connectivity; agency; alien hand; anarchic hand
The inferior parietal lobule (IPL) of the human brain is a heterogeneous region involved in visuospatial attention, memory, and mathematical cognition. Detailed description of connectivity profiles of subdivisions within the IPL is critical for accurate interpretation of functional neuroimaging studies involving this region. We separately examined functional and structural connectivity of the angular gyrus (AG) and the intraparietal sulcus (IPS) using probabilistic cytoarchitectonic maps. Regions-of-interest (ROIs) included anterior and posterior AG subregions (PGa, PGp) and 3 IPS subregions (hIP2, hIP1, and hIP3). Resting-state functional connectivity analyses showed that PGa was more strongly linked to basal ganglia, ventral premotor areas, and ventrolateral prefrontal cortex, while PGp was more strongly connected with ventromedial prefrontal cortex, posterior cingulate, and hippocampus—regions comprising the default mode network. The anterior-most IPS ROIs, hIP2 and hIP1, were linked with ventral premotor and middle frontal gyrus, while the posterior-most IPS ROI, hIP3, showed connectivity with extrastriate visual areas. In addition, hIP1 was connected with the insula. Tractography using diffusion tensor imaging revealed structural connectivity between most of these functionally connected regions. Our findings provide evidence for functional heterogeneity of cytoarchitectonically defined subdivisions within IPL and offer a novel framework for synthesis and interpretation of the task-related activations and deactivations involving the IPL during cognition.
attention; Brodmann area 39; default mode network; inferior parietal lobule; mathematical cognition
One of the defining characteristics of individuals with autism spectrum disorder (ASD) is difficulty with social interaction and communication with others, or interpersonal interaction. Accordingly, the majority of research efforts to date have focused on understanding the brain mechanisms underlying the deficits in social cognition and language associated with ASD. However, recent empirical and theoretical work has begun to reveal increasing evidence for altered self-representation, or intrapersonal cognition in ASD. Here we review recent studies of the self in ASD, focusing on paradigms examining ‘physical’ aspects of the self, including self-recognition, agency and perspective taking, and ‘psychological’ aspects of the self, including self-knowledge and autobiographical memory. A review of the existing literature suggests that psychological, but not physical, aspects of self-representation are altered in ASD. One key brain region that has emerged as a potential locus of self-related deficits in ASD is the medial prefrontal cortex, part of a larger ‘default mode network’. Collectively, the findings from these studies provide a more comprehensive framework for understanding the complex social, cognitive, and affective symptomatology of ASD.
Autism spectrum disorders; Agency; Perspective taking; Social cognition; Self-recognition; Self-knowledge; Brain development; Autobiographical memory; Personality traits; Default mode network
Autism is a complex neurodevelopmental disorder of unknown etiology. While the past decade has witnessed a proliferation of neuroimaging studies of autism, theoretical approaches for understanding systems-level brain abnormalities remain poorly developed. We propose a novel anterior insula-based systems-level model for investigating the neural basis of autism, synthesizing recent advances in brain network functional connectivity with converging evidence from neuroimaging studies in autism. The anterior insula is involved in interoceptive, affective and empathic processes, and emerging evidence suggests it is part of a “salience network” integrating external sensory stimuli with internal states. Network analysis indicates that the anterior insula is uniquely positioned as a hub mediating interactions between large-scale networks involved in externally- and internally-oriented cognitive processing. A recent meta-analysis identifies the anterior insula as a consistent locus of hypoactivity in autism. We suggest that dysfunctional anterior insula connectivity plays an important role in autism. Critical examination of these abnormalities from a systems neuroscience perspective should be a priority for further research on the neurobiology of autism.
connectivity; empathy; autism spectrum disorders; network; von Economoneuron; fMRI
Over the past several decades, structural MRI studies have provided remarkable insights into human brain development by revealing the trajectory of gray and white matter maturation from childhood to adolescence and adulthood. In parallel, functional MRI studies have demonstrated changes in brain activation patterns accompanying cognitive development. Despite these advances, studying the maturation of functional brain networks underlying brain development continues to present unique scientific and methodological challenges. Resting-state fMRI (rsfMRI) has emerged as a novel method for investigating the development of large-scale functional brain networks in infants and young children. We review existing rsfMRI developmental studies and discuss how this method has begun to make significant contributions to our understanding of maturing brain organization. In particular, rsfMRI has been used to complement studies in other modalities investigating the emergence of functional segregation and integration across short and long-range connections spanning the entire brain. We show that rsfMRI studies help to clarify and reveal important principles of functional brain development, including a shift from diffuse to focal activation patterns, and simultaneous pruning of local connectivity and strengthening of long-range connectivity with age. The insights gained from these studies also shed light on potentially disrupted functional networks underlying atypical cognitive development associated with neurodevelopmental disorders. We conclude by identifying critical gaps in the current literature, discussing methodological issues, and suggesting avenues for future research.
functional connectivity; brain maturation; resting-state fMRI; cognitive development; autism spectrum disorders; attention-deficit/hyperactivity disorder
Self–other discrimination is fundamental to social interaction, however, little is known about the neural systems underlying this ability. In a previous functional magnetic resonance imaging study, we demonstrated that a right fronto-parietal network is activated during viewing of self-faces as compared with the faces of familiar others. Here we used image-guided repetitive transcranial magnetic stimulation (rTMS) to create a ’virtual lesion’ over the parietal component of this network to test whether this region is necessary for discriminating self-faces from other familiar faces. The current results indeed show that 1 Hz rTMS to the right inferior parietal lobule (IPL) selectively disrupts performance on a self–other discrimination task. Applying 1 Hz rTMS to the left IPL had no effect. It appears that activity in the right IPL is essential to the task, thus providing for the first time evidence for a causal relation between a human brain area and this high-level cognitive capacity.
self-awareness; self-recognition; social cognition; inferior parietal lobule; mirror neurons
Self–other discrimination is fundamental to social interaction, however, little is known about the neural systems underlying this ability. In a previous functional magnetic resonance imaging study, we demonstrated that a right fronto-parietal network is activated during viewing of self-faces as compared with the faces of familiar others. Here we used image-guided repetitive transcranial magnetic stimulation (rTMS) to create a ‘virtual lesion’ over the parietal component of this network to test whether this region is necessary for discriminating self-faces from other familiar faces. The current results indeed show that 1 Hz rTMS to the right inferior parietal lobule (IPL) selectively disrupts performance on a self–other discrimination task. Applying 1 Hz rTMS to the left IPL had no effect. It appears that activity in the right IPL is essential to the task, thus providing for the first time evidence for a causal relation between a human brain area and this high-level cognitive capacity.
self-awareness; self-recognition; social cognition; inferior parietal lobule; mirror neurons
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 current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups.
We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11–18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or between-network differences in functional network connectivity compared with neurotypical age-matched individuals.
Characterizing within- and between-network functional connectivity in age-stratified cohorts of individuals with ASD and TD individuals demonstrates that functional connectivity atypicalities in the disorder are not uniform across the lifespan. These results demonstrate how explicitly characterizing participant age and adopting a developmental perspective can lead to a more nuanced understanding of atypicalities of functional brain connectivity in autism.
Autism spectrum disorder; Independent component analysis; Resting state fMRI; Functional connectivity; Salience network
In recent work, O’Reilly and colleagues demonstrate relatively intact interhemispheric functional connectivity in a macaque brain in the absence of major commissural fibers. This work adds to a growing body of literature challenging the notion that structural and functional brain connectivity metrics are related in a straightforward manner.
Autism spectrum disorders (ASD) represent a formidable challenge for
psychiatry and neuroscience because of their high prevalence, life-long nature,
complexity and substantial heterogeneity. Facing these obstacles requires
large-scale multidisciplinary efforts. While the field of genetics has pioneered
data sharing for these reasons, neuroimaging had not kept pace. In response, we
introduce the Autism Brain Imaging Data Exchange (ABIDE) – a grassroots
consortium aggregating and openly sharing 1112 existing resting-state functional
magnetic resonance imaging (R-fMRI) datasets with corresponding structural MRI
and phenotypic information from 539 individuals with ASD and 573 age-matched
typical controls (TC; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we
present this resource and demonstrate its suitability for advancing knowledge of
ASD neurobiology based on analyses of 360 males with ASD and 403 male
age-matched TC. We focused on whole-brain intrinsic functional connectivity and
also survey a range of voxel-wise measures of intrinsic functional brain
architecture. Whole-brain analyses reconciled seemingly disparate themes of both
hypo and hyperconnectivity in the ASD literature; both were detected, though
hypoconnectivity dominated, particularly for cortico-cortical and
interhemispheric functional connectivity. Exploratory analyses using an array of
regional metrics of intrinsic brain function converged on common loci of
dysfunction in ASD (mid and posterior insula, posterior cingulate cortex), and
highlighted less commonly explored regions such as thalamus. The survey of the
ABIDE R-fMRI datasets provides unprecedented demonstrations of both replication
and novel discovery. By pooling multiple international datasets, ABIDE is
expected to accelerate the pace of discovery setting the stage for the next
generation of ASD studies.
Resting state fMRI; Intrinsic functional connectivity; Data sharing; Large-scale networks; Default network; Interhemispheric connectivity; Thalamus
The default mode network (DMN), a brain system anchored in the posteromedial cortex, has been identified as under-connected 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.
Here we use resting-state fMRI and an anatomically informed approach to investigate the functional connectivity of the DMN in 20 children with ASD and 19 age-, gender-, and IQ-matched typically developing children. We utilize multivariate regression analyses to test whether altered patterns of connectivity are predictive of social impairment severity.
Compared to TD children, children with ASD demonstrated hyper-connectivity of the posterior cingulate and retrosplenial cortices with predominately medial and anterolateral temporal cortex. In contrast, the precuneus in ASD children demonstrated hypo-connectivity with visual cortex, basal ganglia, and locally within the posteromedial cortex. Aberrant posterior cingulate cortex hyper-connectivity was linked with severity of social impairments in ASD, whereas precuneus hypo-connectivity was unrelated to social deficits. Consistent with previous work in healthy adults, we observe a functionally heterogeneous profile of connectivity within the posteromedial cortex in both TD and ASD children.
This work links hyper-connectivity of DMN-related circuits to the core social deficits in young children with ASD and highlights fundamental aspects of posteromedial cortex heterogeneity.
autism spectrum disorders; default mode network; posteromedial cortex; posterior cingulate cortex; functional connectivity; resting-state fMRI
Electrophysiological studies have long demonstrated a high degree of correlated activity between the left and right hemispheres, however little is known about regional variation in this interhemispheric coordination. While cognitive models and neuroanatomical evidence suggest differences in coordination across primary sensory-motor cortices versus higher-order association areas, these have not been characterized. Here, we used resting-state functional magnetic resonance imaging data acquired from 62 healthy volunteers to examine interregional correlation in spontaneous low-frequency hemodynamic fluctuations. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions comprising the entire cerebrum. We then examined regional variation in correlated activity between homotopic regions, contrasting primary sensory-motor cortices, unimodal association areas, and heteromodal association areas. Consistent with previous studies, robustly correlated spontaneous activity was noted between all homotopic regions, which was significantly higher than that between nonhomotopic (heterotopic and intrahemispheric) regions. We further demonstrated substantial regional variation in homotopic interhemispheric correlations that was highly consistent across subjects. Specifically, there was a gradient of interhemispheric correlation, with highest correlations across primary sensory-motor cortices (0.758,sd=0.152), significantly lower correlations across unimodal association areas (0.597,sd=0.230) and still lower correlations across heteromodal association areas (0.517,sd=0.226). These results demonstrate functional differences in interhemispheric coordination related to the brain’s hierarchical subdivisions. Synchrony across primary cortices may reflect networks engaged in bilateral sensory integration and motor coordination while lower coordination across heteromodal association areas is consistent with functional lateralization of these regions. This novel method of examining interhemispheric coordination may yield insights regarding diverse disease processes as well as healthy development.
Interhemispheric; Synchrony; fMRI; Connectivity; Lateralization; Hemisphere; Coordination
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 there are more instances of greater functional connectivity in the brains of children with ASD compared with typically developing children. Hyper-connectivity in ASD was observed at the whole-brain and subsystems level, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyper-connectivity 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 in ASD is largely functionally hyper-connected in ways that contribute to social dysfunction. Our findings provide novel insights into brain mechanisms underlying childhood autism.
brain connectivity; multimodal imaging methods; diffusion tensor imaging; functional connectivity; autism spectrum disorders; white matter
Affective empathy (AE) is distinguished clinically and neurally from cognitive empathy (CE). While AE is selectively disrupted in psychopathy, autism is associated with deficits in CE. Despite such dissociations, AE and CE together contribute to normal human empathic experience. A dimensional measure of individual differences in AE ‘relative to’ CE captures this interaction and may reveal brain–behavior relationships beyond those detectable with AE and CE separately. Using resting-state fMRI and measures of empathy in healthy adults, we show that relative empathic ability (REA) is reflected in the brain's intrinsic functional dynamics. Dominance of AE was associated with stronger functional connectivity among social–emotional regions (ventral anterior insula, orbitofrontal cortex, amygdala, perigenual anterior cingulate). Dominance of CE was related to stronger connectivity among areas implicated in interoception, autonomic monitoring and social–cognitive processing (brainstem, superior temporal sulcus, ventral anterior insula). These patterns were distinct from those observed with AE and CE separately. Finally, REA and the strength of several functional connections were associated with symptoms of psychopathology. These findings suggest that REA provides a dimensional index of empathic function and pathological tendencies in healthy adults, which are reflected in the intrinsic functional dynamics of neural systems associated with social and emotional cognition.
affective empathy; cognitive empathy; fMRI; resting-state functional connectivity; social cognition
The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally-oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here we examined functional differentiation within the default mode network, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the default mode network are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated.
fMRI; resting state network; ventromedial prefrontal cortex; posterior cingulate; precuneus; Granger causality; effective connectivity; attention; self; social cognition
Autism spectrum disorders (ASD) are neurodevelopmental disorders with a prevalence of nearly 1:100. Structural imaging studies point to disruptions in multiple brain areas, yet the precise neuroanatomical nature of these disruptions remains unclear. Characterization of brain structural differences in children with ASD is critical for development of biomarkers that may eventually be used to improve diagnosis and monitor response to treatment.
We use voxel-based morphometry (VBM) along with a novel multivariate pattern analysis (MPA) approach and searchlight algorithm to classify structural magnetic resonance imaging data acquired from 24 children and adolescents with autism and 24 age-, gender-, and IQ-matched neurotypical participants.
Despite modest VBM differences, MPA revealed that the groups could be distinguished with accuracies of around 90% based on gray matter in the posterior cingulate cortex (PCC), medial prefrontal cortex, and bilateral medial temporal lobes, all regions within the default mode network (DMN). Abnormalities in the PCC were associated with impaired ADI-R communication scores. Gray matter in additional prefrontal, lateral temporal, and subcortical structures also discriminated between the two groups with accuracies between 81-90%. White matter in the inferior fronto-occipital and superior longitudinal fasciculi, and the genu and splenium of the corpus callosum, achieved up to 85% classification accuracy.
Multiple brain regions, including those belonging to the DMN, exhibit aberrant structural organization in children with autism. Brain-based biomarkers derived from structural MRI data may eventually contribute to identification of the neuroanatomical basis of symptom heterogeneity and to the development of more targeted early intervention.
voxel-based morphometry; autism spectrum disorders; default mode network; multivariate pattern analysis; support vector machine; biomarker
Functional and structural maturation of networks comprised of discrete regions is an important aspect of brain development. The default-mode network (DMN) is a prominent network which includes the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), medial temporal lobes (MTL), and angular gyrus (AG). Despite increasing interest in DMN function, little is known about its maturation from childhood to adulthood. Here we examine developmental changes in DMN connectivity using a multimodal imaging approach by combining resting-state fMRI, voxel-based morphometry and diffusion tensor imaging-based tractography. We found that the DMN undergoes significant developmental changes in functional and structural connectivity, but these changes are not uniform across all DMN nodes. Convergent structural and functional connectivity analyses suggest that PCC-mPFC connectivity along the cingulum bundle is the most immature link in the DMN of children. Both PCC and mPFC also showed gray matter volume differences, as well as prominent macrostructural and microstructural differences in the dorsal cingulum bundle linking these regions. Notably, structural connectivity between PCC and left MTL was either weak or non-existent in children, even though functional connectivity did not differ from that of adults. These results imply that functional connectivity in children can reach adult-like levels despite weak structural connectivity. We propose that maturation of PCC-mPFC structural connectivity plays an important role in the development of self-related and social-cognitive functions that emerge during adolescence. More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks.
brain development; default mode network; DTI; functional brain connectivity; structural brain connectivity
Resting-state functional magnetic resonance imaging (fMRI) has provided a novel approach for examining interhemispheric interaction, demonstrating a high degree of functional connectivity between homotopic regions in opposite hemispheres. However, heterotopic resting state functional connectivity (RSFC) remains relatively uncharacterized. In the present study, we examine non-homotopic regions, characterizing heterotopic RSFC and comparing it to intrahemispheric RSFC, to examine the impact of hemispheric separation on the integration and segregation of processing in the brain. Resting-state fMRI scans were acquired from 59 healthy participants to examine interregional correlations in spontaneous low frequency fluctuations in BOLD signal. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions (56 per hemisphere) distributed throughout the entire cerebrum. We compared RSFC for pairings of non-homologous regions located in different hemispheres (heterotopic connectivity) to RSFC for the same pairings when located within hemisphere (intrahemispheric connectivity). For positive connections, connectivity strength was greater within each hemisphere, consistent with integrated intrahemispheric processing. However, for negative connections, RSFC strength was greater between the hemispheres, consistent with segregated interhemispheric processing. These patterns were particularly notable for connections involving frontal and heteromodal regions. The distribution of positive and negative connectivity was nearly identical within and between the hemispheres, though we demonstrated detailed regional variation in distribution. We discuss implications for leading models of interhemispheric interaction. The future application of our analyses may provide important insight into impaired interhemispheric processing in clinical and aging populations.
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 anatomic 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.
fMRI; resting state; inferior frontal gyrus; language; clustering