The development of human functional brain networks

The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity

Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n=117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r=.10-.35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability.

Groupwise whole-brain parcellation from resting-state fMRI data for network node identification

In this paper, we present a groupwise graph-theory-based parcellation approach to define nodes for network analysis. The application of network-theory-based analysis to extend the utility of functional MRI has recently received increased attention. Such analyses require first and foremost a reasonable definition of a set of nodes as input to the network analysis. To date many applications have used existing atlases based on cytoarchitecture, task-based fMRI activations, or anatomic delineations. A potential pitfall in using such atlases is that the mean timecourse of a node may not represent any of the constituent timecourses if different functional areas are included within a single node. The proposed approach involves a groupwise optimization that ensures functional homogeneity within each subunit and that these definitions are consistent at the group level. Parcellation reproducibility of each subunit is computed across multiple groups of healthy volunteers and is demonstrated to be high. Issues related to the selection of appropriate number of nodes in the brain are considered. Within typical parameters of fMRI resolution, parcellation results are shown for a total of 100, 200, and 300 subunits. Such parcellations may ultimately serve as a functional atlas for fMRI and as such three atlases at the 100-, 200- and 300-parcellation levels derived from 79 healthy normal volunteers are made freely available online along with tools to interface this atlas with SPM, BioImage Suite and other analysis packages.

WITHDRAWN: Mapping Connectivity in the Developing Brain

The Publisher regrets that this article is an accidental duplication of an article that has already been published, http://dx.doi.org/10.1016/j.ijdevneu.2013.05.007. The duplicate article has therefore been withdrawn.

Inter-subject alignment of human cortical anatomy using functional connectivity

Inter-subject alignment of functional MRI (fMRI) data is necessary for group analyses. The standard approach to this problem matches anatomical features of the brain, such as major anatomical landmarks or cortical curvature. Precise alignment of functional cortical topographies, however, cannot be derived using only anatomical features. We propose a new inter-subject registration algorithm that aligns intra-subject patterns of functional connectivity across subjects. We derive functional connectivity patterns by correlating fMRI BOLD time-series, measured during movie viewing, between spatially remote cortical regions. We validate our technique extensively on real fMRI experimental data and compare our method to two state-of-the-art inter-subject registration algorithms. By cross-validating our method on independent datasets, we show that the derived alignment generalizes well to other experimental paradigms.

Developmental heterochrony and the evolution of autistic perception, cognition and behavior

BACKGROUND

Autism is usually conceptualized as a disorder or disease that involves fundamentally abnormal neurodevelopment. In the present work, the hypothesis that a suite of core autism-related traits may commonly represent simple delays or non-completion of typical childhood developmental trajectories is evaluated.

DISCUSSION

A comprehensive review of the literature indicates that, with regard to the four phenotypes of (1) restricted interests and repetitive behavior, (2) short-range and long-range structural and functional brain connectivity, (3) global and local visual perception and processing, and (4) the presence of absolute pitch, the differences between autistic individuals and typically developing individuals closely parallel the differences between younger and older children.

SUMMARY

The results of this study are concordant with a model of 'developmental heterochrony', and suggest that evolutionary extension of child development along the human lineage has potentiated and structured genetic risk for autism and the expression of autistic perception, cognition and behavior.

Functional network architecture of reading-related regions across development

Reading requires coordinated neural processing across a large number of brain regions. Studying relationships between reading-related regions informs the specificity of information processing performed in each region. Here, regions of interest were defined from a meta-analysis of reading studies, including a developmental study. Relationships between regions were defined as temporal correlations in spontaneous fMRI signal; i.e., resting state functional connectivity MRI (RSFC). Graph theory based network analysis defined the community structure of the "reading-related" regions. Regions sorted into previously defined communities, such as the fronto-parietal and cingulo-opercular control networks, and the default mode network. This structure was similar in children, and no apparent "reading" community was defined in any age group. These results argue against regions, or sets of regions, being specific or preferential for reading, instead indicating that regions used in reading are also used in a number of other tasks.

Moment-to-moment brain signal variability: a next frontier in human brain mapping?

Neuroscientists have long observed that brain activity is naturally variable from moment-to-moment, but neuroimaging research has largely ignored the potential importance of this phenomenon. An emerging research focus on within-person brain signal variability is providing novel insights, and offering highly predictive, complementary, and even orthogonal views of brain function in relation to human lifespan development, cognitive performance, and various clinical conditions. As a result, brain signal variability is evolving as a bona fide signal of interest, and should no longer be dismissed as meaningless noise when mapping the human brain.

Individual variability in functional connectivity architecture of the human brain

The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.

Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders

The application of graph analysis methods to the topological organization of brain connectivity has been a useful tool in the characterization of brain related disorders. However, the availability of tools, which enable researchers to investigate functional brain networks, is still a major challenge. Most of the studies evaluating brain images are based on centrality and segregation measurements of complex networks. In this study, we applied the concept of graph spectral entropy (GSE) to quantify the complexity in the organization of brain networks. In addition, to enhance interpretability, we also combined graph spectral clustering to investigate the topological organization of sub-network's modules. We illustrate the usefulness of the proposed approach by comparing brain networks between attention deficit hyperactivity disorder (ADHD) patients and the brain networks of typical developing (TD) controls. The main findings highlighted that GSE involving sub-networks comprising the areas mostly bilateral pre and post central cortex, superior temporal gyrus, and inferior frontal gyri were statistically different (p-value=0.002) between ADHD patients and TD controls. In the same conditions, the other conventional graph descriptors (betweenness centrality, clustering coefficient, and shortest path length) commonly used to identify connectivity abnormalities did not show statistical significant difference. We conclude that analysis of topological organization of brain sub-networks based on GSE can identify networks between brain regions previously unobserved to be in association with ADHD.

Tool-use practice induces changes in intrinsic functional connectivity of parietal areas

Intrinsic functional connectivity from resting state functional magnetic resonance imaging (rsfMRI) has increasingly received attention as a possible predictor of cognitive function and performance. In this study, we investigated the influence of practicing skillful tool manipulation on intrinsic functional connectivity in the resting brain. Acquisition of tool-use skill has two aspects such as formation of motor representation for skillful manipulation and acquisition of the tool concept. To dissociate these two processes, we chose chopsticks-handling with the non-dominant hand. Because participants were already adept at chopsticks-handling with their dominant hand, practice with the non-dominant hand involved only acquiring the skill for tool manipulation with existing knowledge. Eight young participants practiced chopsticks-handling with their non-dominant hand for 8 weeks. They underwent functional magnetic resonance imaging (fMRI) sessions before and after the practice. As a result, functional connectivity among tool-use-related regions of the brain decreased after practice. We found decreased functional connectivity centered on parietal areas, mainly the supramarginal gyrus (SMG) and superior parietal lobule (SPL) and additionally between the primary sensorimotor area and cerebellum. These results suggest that the parietal lobe and cerebellum purely mediate motor learning for skillful tool-use. This decreased functional connectivity may represent increased efficiency of functional network.

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

Developmental changes in the transcriptome of human cerebral cortex tissue: long noncoding RNA transcripts

The human neocortex is characterized by protracted developmental intervals of synaptogenesis and myelination, which allow for an extended period of learning. The molecular basis of these and other postnatal developmental changes in the human cerebral cortex remain incompletely understood. Recently, a new large class of mammalian genes, encoding nonmessenger, long nonprotein-coding ribonucleic acid (lncRNA) molecules has been discovered. Although their function remains uncertain, numerous lncRNAs have primate-specific sequences and/or show evidence of rapid, lineage-specific evolution, making them potentially relevant to the evolution of unique human neural properties. To examine the hypothesis that lncRNA expression varies with age, potentially paralleling known developmental trends in synaptogenesis, myelination, and energetics, we quantified levels of nearly 6000 lncRNAs in 36 surgically resected human neocortical samples (primarily derived from temporal cortex) spanning infancy to adulthood. Our analysis identified 8 lncRNA genes with distinct developmental expression patterns. These lncRNA genes contained anthropoid-specific exons, as well as splice sites and polyadenylation signals that resided in primate-specific sequences. To our knowledge, our study is the first to describe developmental expression profiles of lncRNA in surgically resected in vivo human brain tissue. Future analysis of the functional relevance of these transcripts to neural development and energy metabolism is warranted.

Functional brain connectivity at rest changes after working memory training

Networks of functional connectivity are highly consistent across participants, suggesting that functional connectivity is for a large part predetermined. However, several studies have shown that functional connectivity may change depending on instructions or previous experience. In the present study, we investigated whether 6 weeks of practice with a working memory task changes functional connectivity during a resting period preceding the task. We focused on two task-relevant networks, the frontoparietal network and the default network, using seed regions in the right middle frontal gyrus (MFG) and the medial prefrontal cortex (PFC), respectively. After practice, young adults showed increased functional connectivity between the right MFG and other regions of the frontoparietal network, including bilateral superior frontal gyrus, paracingulate gyrus, and anterior cingulate cortex. In addition, they showed reduced functional connectivity between the medial PFC and right posterior middle temporal gyrus. Moreover, a regression with performance changes revealed a positive relation between performance increases and changes of frontoparietal connectivity, and a negative relation between performance increases and changes of default network connectivity. Next, to study whether experience-dependent effects would be different during development, we also examined practice effects in a pilot sample of 12-year-old children. No practice effects were found in this group, suggesting that practice-related changes of functional connectivity are age-dependent. Nevertheless, future studies with larger samples are necessary to confirm this hypothesis.

Hypotonia, jaundice, and Chiari malformations: relationships to executive functions

This article postulates that movement and action control are the underpinning of executive functioning. We selectively examine brain regions that have traditionally been almost exclusively understood as critical to the control and expression of movement-namely, the basal ganglia and the cerebellum. We first describe the relationship between movement and cognition. This is followed by a review of common developmental disorders that are known to exhibit abnormal executive functions and movement anomalies. Against that background, we examine hypotonia, neonatal jaundice, and Chiari I malformation, and we demonstrate why these are "at-risk" factors for neurodevelopmental disorders that can feature both motor control and executive function abnormalities. Our goal is to prepare the clinical neuropsychologist for gathering information about these features of a child's birth and developmental histories, while using this as a framework for interpreting test results and applying test data in a useful, practical way to guide descriptive diagnosis and treatment.

Whole-brain functional networks in cognitively normal, mild cognitive impairment, and Alzheimer's disease

The conceptual significance of understanding functional brain alterations and cognitive deficits associated with Alzheimer's disease (AD) process has been widely established. However, the whole-brain functional networks of AD and its prodromal stage, mild cognitive impairment (MCI), are not well clarified yet. In this study, we compared the characteristics of the whole-brain functional networks among cognitively normal (CN), MCI, and AD individuals by applying graph theoretical analyses to [(18)F] fluorodeoxyglucose positron emission tomography (FDG-PET) data. Ninety-four CN elderly, 183 with MCI, and 216 with AD underwent clinical evaluation and FDG-PET scan. The overall small-world property as seen in the CN whole-brain network was preserved in MCI and AD. In contrast, individual parameters of the network were altered with the following patterns of changes: local clustering of networks was lower in both MCI and AD compared to CN, while path length was not different among the three groups. Then, MCI had a lower level of local clustering than AD. Subgroup analyses for AD also revealed that very mild AD had lower local clustering and shorter path length compared to mild AD. Regarding the local properties of the whole-brain networks, MCI and AD had significantly decreased normalized betweenness centrality in several hubs regionally associated with the default mode network compared to CN. Our results suggest that the functional integration in whole-brain network progressively declines due to the AD process. On the other hand, functional relatedness between neighboring brain regions may not gradually decrease, but be the most severely altered in MCI stage and gradually re-increase in clinical AD stages.

Hierarchical alteration of brain structural and functional networks in female migraine sufferers

BACKGROUND

Little is known about the changes of brain structural and functional connectivity networks underlying the pathophysiology in migraine. We aimed to investigate how the cortical network reorganization is altered by frequent cortical overstimulation associated with migraine.

METHODOLOGY/PRINCIPAL FINDINGS

Gray matter volumes and resting-state functional magnetic resonance imaging signal correlations were employed to construct structural and functional networks between brain regions in 43 female patients with migraine (PM) and 43 gender-matched healthy controls (HC) by using graph theory-based approaches. Compared with the HC group, the patients showed abnormal global topology in both structural and functional networks, characterized by higher mean clustering coefficients without significant change in the shortest absolute path length, which indicated that the PM lost optimal topological organization in their cortical networks. Brain hubs related to pain-processing revealed abnormal nodal centrality in both structural and functional networks, including the precentral gyrus, orbital part of the inferior frontal gyrus, parahippocampal gyrus, anterior cingulate gyrus, thalamus, temporal pole of the middle temporal gyrus and the inferior parietal gyrus. Negative correlations were found between migraine duration and regions with abnormal centrality. Furthermore, the dysfunctional connections in patients' cortical networks formed into a connected component and three dysregulated modules were identified involving pain-related information processing and motion-processing visual networks.

CONCLUSIONS

Our results may reflect brain alteration dynamics resulting from migraine and suggest that long-term and high-frequency headache attacks may cause both structural and functional connectivity network reorganization. The disrupted information exchange between brain areas in migraine may be reshaped into a hierarchical modular structure progressively.

Interhemispheric temporal lobe connectivity predicts language impairment in adolescents born preterm

Although language difficulties are common in children born prematurely, robust neuroanatomical correlates of these impairments remain to be established. This study investigated whether the greater prevalence of language problems in preterm (versus term-born) children might reflect injury to major intra- or interhemispheric white matter pathways connecting frontal and temporal language regions. To investigate this, we performed a comprehensive assessment of language and academic abilities in a group of adolescents born prematurely, some of whom had evidence of brain injury at birth (n = 50, mean age: 16 years, mean gestational age: 27 weeks) and compared them to a term-born control group (n = 30). Detailed structural magnetic resonance imaging and diffusion-tractography analyses of intrahemispheric and interhemispheric white matter bundles were performed. Analysis of intrahemispheric pathways included the arcuate fasciculus (dorsal language pathway) and uncinate fasciculus/extreme capsule (ventral language pathway). Analysis of interhemispheric pathways (in particular, connections between the temporal lobes) included the two major commissural bundles: the corpus callosum and anterior commissure. We found language impairment in 38% of adolescents born preterm. Language impairment was not related to abnormalities of the arcuate fasciculus (or its subsegments), but was associated with bilateral volume reductions in the ventral language pathway. However, the most significant volume reduction was detected in the posterior corpus callosum (splenium), which contains interhemispheric connections between the occipital, parietal and temporal lobes. Diffusion tractography showed that of the three groups of interhemispheric fibres within the splenium, only those connecting the temporal lobes were reduced. Crucially, we found that language impairment was only detectable if the anterior commissure (a second temporal lobe commissural pathway) was also small. Regression analyses showed that a combination of anatomical measures of temporal interhemispheric connectivity (through the splenium of the corpus callosum and anterior commissure) explained 57% of the variance in language abilities. This supports recent theories emphasizing the importance of interhemispheric connections for language, particularly in the developing brain.

Magnetic resonance methods in fetal neurology

Fetal magnetic resonance imaging (MRI) has become an established clinical adjunct for the in-vivo evaluation of human brain development. Normal fetal brain maturation can be studied with MRI from the 18th week of gestation to term and relies primarily on T2-weighted sequences. Recently diffusion-weighted sequences have gained importance in the structural assessment of the fetal brain. Diffusion-weighted imaging provides quantitative information about water motion and tissue microstructure and has applications for both developmental and destructive brain processes. Advanced magnetic resonance techniques, such as spectroscopy, might be used to demonstrate metabolites that are involved in brain maturation, though their development is still in the early stages. Using fetal MRI in addition to prenatal ultrasound, morphological, metabolic, and functional assessment of the fetus can be achieved. The latter is not only based on observation of fetal movements as an indirect sign of activity of the fetal brain but also on direct visualization of fetal brain activity, adding a new component to fetal neurology. This article provides an overview of the MRI methods used for fetal neurologic evaluation, focusing on normal and abnormal early brain development.

Brain development during the preschool years

The preschool years represent a time of expansive mental growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its "blossoming" nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond.

Brain SCALE: brain structure and cognition: an adolescent longitudinal twin study into the genetic etiology of individual differences

From childhood into adolescence, the child's brain undergoes considerable changes in both structure and function. Twin studies are of great value to explore to what extent genetic and environmental factors explain individual differences in brain development and cognition. In The Netherlands, we initiated a longitudinal study in which twins, their siblings and their parents are assessed at three year intervals. The participants were recruited from The Netherlands Twin Register (NTR) and at baseline consisted of 112 families, with 9-year-old twins and an older sibling. Three years later, 89 families returned for follow-up assessment. Data collection included psychometric IQ tests, a comprehensive neuropsychological testing protocol, and parental and self-ratings of behavioral and emotional problems. Physical maturation was measured through assessment of Tanner stages. Hormonal levels (cortisol, luteinizing hormone, follicle-stimulating hormone, testosterone, and estrogens) were assessed in urine and saliva. Brain scans were acquired using 1.5 Tesla Magnetic Resonance Imaging (MRI), which provided volumetric measures and measures of cortical thickness. Buccal swabs were collected for DNA isolation for future candidate gene and genome-wide analysis studies. This article gives an overview of the study and the main findings. Participants will return for a third assessment when the twins are around 16 years old. Longitudinal twin-sibling studies that map brain development and cognitive function at well-defined ages aid in the understanding of genetic influences on normative brain development.

Weighted phase lag index and graph analysis: preliminary investigation of functional connectivity during resting state in children

Resting state functional connectivity of MEG data was studied in 29 children (9-10 years old). The weighted phase lag index (WPLI) was employed for estimating connectivity and compared to coherence. To further evaluate the network structure, a graph analysis based on WPLI was used to determine clustering coefficient (C) and betweenness centrality (BC) as local coefficients as well as the characteristic path length (L) as a parameter for global interconnectedness. The network's modular structure was also calculated to estimate functional segregation. A seed region was identified in the central occipital area based on the power distribution at the sensor level in the alpha band. WPLI reveals a specific connectivity map different from power and coherence. BC and modularity show a strong level of connectedness in the occipital area between lateral and central sensors. C shows different isolated areas of occipital sensors. Globally, a network with the shortest L is detected in the alpha band, consistently with the local results. Our results are in agreement with findings in adults, indicating a similar functional network in children at this age in the alpha band. The integrated use of WPLI and graph analysis can help to gain a better description of resting state networks.

Overcoming residual interference in mental set switching: neural correlates and developmental trajectory

Mental set switching is a key facet of executive control measured behaviorally through reaction time or accuracy (i.e., 'switch costs') when shifting among task types. One of several experimentally dissociable influences on switch costs is 'task set inertia', conceptualized as the residual interference conferred when a previous stimulus-response tendency interferes with subsequent stimulus processing on a new task. Task set inertia is thought to represent the passive decay of the previous stimulus-response set from working memory, and its effects decrease with increased interstimulus interval. Closely spaced trials confer high task set inertia, while sparsely spaced trials confer low task set inertia. This functional magnetic resonance imaging (fMRI) study characterized, for the first time, two opposing brain systems engaged to resolve task set inertia: 1) a frontoparietal 'cortical control' network for overcoming high task set inertia interference and 2) a subcortical-motor network more active during trials with low task set inertia. These networks were distinct from brain regions showing general switching effects (i.e., switch>non-switch) and from other previously characterized interference effects. Moreover, there were ongoing maturational effects throughout adolescence for the brain regions engaged to overcome high task set inertia not seen for generalized switching effects. These novel findings represent a new avenue of exploration of cognitive set switching neural function.

Default mode network connectivity in children with a history of preschool onset depression

BACKGROUND

Atypical Default Mode Network (DMN) functional connectivity has been previously reported in depressed adults. However, there is relatively little data informing the developmental nature of this phenomenon. The current case-control study examined the DMN in a unique prospective sample of school-age children with a previous history of preschool depression.

METHODS

DMN functional connectivity was assessed using resting state functional connectivity magnetic resonance imaging data and the posterior cingulate (PCC) as a seed region of interest. Thirty-nine medication naïve school age children (21 with a history of preschool depression and 18 healthy peers) and their families who were ascertained as preschoolers and prospectively assessed over at least 4 annual waves as part of a federally funded study of preschool depression were included.

RESULTS

  Decreased connectivity between the PCC and regions within the middle temporal gyrus (MTG), inferior parietal lobule, and cerebellum was found in children with known depression during the preschool period. Increased connectivity between the PCC and regions within the subgenual and anterior cingulate cortices and anterior MTG bilaterally was also found in these children. Additionally, a clinically relevant 'brain-behavior' relationship between atypical functional connectivity of the PCC and disruptions in emotion regulation was identified.

CONCLUSIONS

To our knowledge, this is the first study to examine the DMN in children known to have experienced the onset of a clinically significant depressive syndrome during preschool. Results suggest that a history of preschool depression is associated with atypical DMN connectivity. However, longitudinal studies are needed to clarify whether the current findings of atypical DMN connectivity are a precursor or a consequence of preschool depression.

A brief history of the resting state: the Washington University perspective

We present a history of the concepts and developments that have led us to focus on the resting state as an object of study. We then discuss resting state research performed in our laboratory since 2005 with an emphasis on papers of particular interest.

The development of hub architecture in the human functional brain network

Functional hubs are brain regions that play a crucial role in facilitating communication among parallel, distributed brain networks. The developmental emergence and stability of hubs, however, is not well understood. The current study used measures of network topology drawn from graph theory to investigate the development of functional hubs in 99 participants, 10-20 years of age. We found that hub architecture was evident in late childhood and was stable from adolescence to early adulthood. Connectivity between hub and non-hub ("spoke") regions, however, changed with development. From childhood to adolescence, the strength of connections between frontal hubs and cortical and subcortical spoke regions increased. From adolescence to adulthood, hub-spoke connections with frontal hubs were stable, whereas connectivity between cerebellar hubs and cortical spoke regions increased. Our findings suggest that a developmentally stable functional hub architecture provides the foundation of information flow in the brain, whereas connections between hubs and spokes continue to develop, possibly supporting mature cognitive function.

The organization of the human striatum estimated by intrinsic functional connectivity

The striatum is connected to the cerebral cortex through multiple anatomical loops that process sensory, limbic, and heteromodal information. Tract-tracing studies in the monkey reveal that these corticostriatal connections form stereotyped patterns in the striatum. Here the organization of the striatum was explored in the human with resting-state functional connectivity MRI (fcMRI). Data from 1,000 subjects were registered with nonlinear deformation of the striatum in combination with surface-based alignment of the cerebral cortex. fcMRI maps derived from seed regions placed in the foot and tongue representations of the motor cortex yielded the expected inverted somatotopy in the putamen. fcMRI maps derived from the supplementary motor area were located medially to the primary motor representation, also consistent with anatomical studies. The topography of the complete striatum was estimated and replicated by assigning each voxel in the striatum to its most strongly correlated cortical network in two independent groups of 500 subjects. The results revealed at least five cortical zones in the striatum linked to sensorimotor, premotor, limbic, and two association networks with a topography globally consistent with monkey anatomical studies. The majority of the human striatum was coupled to cortical association networks. Examining these association networks further revealed details that fractionated the five major networks. The resulting estimates of striatal organization provide a reference for exploring how the striatum contributes to processing motor, limbic, and heteromodal information through multiple large-scale corticostriatal circuits.

Developmental changes in organization of structural brain networks

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

Abnormal modular organization of functional networks in cognitively impaired children with frontal lobe epilepsy

Many children with frontal lobe epilepsy (FLE) have significant cognitive comorbidity, for which the underlying mechanism has not yet been unraveled, but is likely related to disturbed cerebral network integrity. Using resting-state fMRI, we investigated whether cerebral network characteristics are associated with epilepsy and cognitive comorbidity. We included 37 children with FLE and 41 healthy age-matched controls. Cognitive performance was determined by means of a computerized visual searching task. A connectivity matrix for 82 cortical and subcortical brain regions was generated for each subject by calculating the inter-regional correlation of the fMRI time signals. From the connectivity matrix, graph metrics were calculated and the anatomical configuration of aberrant connections and modular organization was investigated. Both patients and controls displayed efficiently organized networks. However, FLE patients displayed a higher modularity, implying that subnetworks are less interconnected. Impaired cognition was associated with higher modularity scores and abnormal modular organization of the brain, which was mainly expressed as a decrease in long-range and an increase in interhemispheric connectivity in patients. We showed that network modularity analysis provides a sensitive marker for cognitive impairment in FLE and suggest that abnormally interconnected functional subnetworks of the brain might underlie the cognitive problems in children with FLE.

The cognitive neuroscience of ageing

The availability of neuroimaging technology has spurred a marked increase in the human cognitive neuroscience literature, including the study of cognitive ageing. Although there is a growing consensus that the ageing brain retains considerable plasticity of function, currently measured primarily by means of functional MRI, it is less clear how age differences in brain activity relate to cognitive performance. The field is also hampered by the complexity of the ageing process itself and the large number of factors that are influenced by age. In this Review, current trends and unresolved issues in the cognitive neuroscience of ageing are discussed.

MR connectomics: a conceptual framework for studying the developing brain

THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.

Social brain development in williams syndrome: the current status and directions for future research

Williams syndrome (WS) is a neurodevelopmental condition that occurs as a result of a contiguous deletion of ∼26–28 genes on chromosome 7q11.23. WS is often associated with a distinctive social phenotype characterized by an increased affinity toward processing faces, reduced sensitivity to fear related social stimuli and a reduced ability to form concrete social relationships. Understanding the biological mechanisms that underlie the social phenotype in WS may elucidate genetic and neural factors influencing the typical development of the social brain. In this article, we review available studies investigating the social phenotype of WS throughout development and neuroimaging studies investigating brain structure and function as related to social and emotional functioning in this condition. This review makes an important contribution by highlighting several neuro-behavioral mechanisms that may be a cause or a consequence of atypical social development in WS. In particular, we discuss how distinctive social behaviors in WS may be associated with alterations or delays in the cortical representation of faces, connectivity within the ventral stream, structure and function of the amygdala and how long- and short-range connections develop within the brain. We integrate research on typical brain development and from existing behavioral and neuroimaging research on WS. We conclude with a discussion of how genetic and environmental factors might interact to influence social brain development in WS and how future neuroimaging and behavioral research can further elucidate social brain development in WS. Lastly, we describe how ongoing studies may translate to improved social developmental outcomes for individuals with WS.

Neural correlates of establishing, maintaining, and switching brain states

Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance.

The brain's default network and its adaptive role in internal mentation

During the many idle moments that comprise daily life, the human brain increases its activity across a set of midline and lateral cortical brain regions known as the "default network." Despite the robustness with which the brain defaults to this pattern of activity, surprisingly little is known about the network's precise anatomical organization and adaptive functions. To provide insight into these questions, this article synthesizes recent literature from structural and functional imaging with a growing behavioral literature on mind wandering. Results characterize the default network as a set of interacting hubs and subsystems that play an important role in "internal mentation"-the introspective and adaptive mental activities in which humans spontaneously and deliberately engage in every day.

A case of frontal neuropsychological and neuroimaging signs following multiple primary-blast exposure

Blast-related traumatic brain injury (TBI) from the Afghanistan and Iraq wars represents a significant medical concern for troops and veterans. To better understand the consequences of primary-blast injury in humans, we present a case of a Marine exposed to multiple primary blasts during his 14-year military career. The neuropsychological profile of this formerly high-functioning veteran suggested primarily executive dysfunction. Diffusion-tensor imaging revealed white-matter pathology in long fiber tracks compared with a composite fractional-anisotropy template derived from a veteran reference control group without TBI. This study supports the existence of primary blast-induced neurotrauma in humans and introduces a neuroimaging technique with potential to discriminate multiple-blast TBI.

Cortical dynamics of human scalp EEG origins in a visually guided motor execution

The EEG mu rhythm is often used as an index of activation in the sensorimotor cortex. However, the blur caused by volume conduction makes it difficult to identify the exact origin of the EEG rhythm in the brain using only the human scalp EEG. In this study, simultaneous fMRI and EEG measurements were performed during a visually guided motor execution task in order to investigate whether the mu rhythm in the scalp EEG is an indication of the activity in the sensorimotor cortex. In addition, a new method was proposed for reconstruction of the cortical EEG activity through the fusion of fMRI and EEG data. A suppression of mu rhythm appeared around the lateral central electrode sites, just above the sensorimotor cortex, in association with the activity in that region. During a visually guided motor execution task, the alpha rhythms at the occipital electrode sites and the alpha rhythm at the central electrode sites also showed a correlation with the fMRI signal in the occipital and the supplementary motor cortices, respectively. This method allows the investigation of the scalp EEG origin with the spatial precision of fMRI, while retaining dynamic properties of the cortex with the temporal precision of EEG.

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI

A number of previous studies have examined music-related plasticity in terms of multi-sensory and motor integration but little is known about the functional and effective connectivity patterns of spontaneous intrinsic activity in these systems during the resting state in musicians. Using functional connectivity and Granger causal analysis, functional and effective connectivity among the motor and multi-sensory (visual, auditory and somatosensory) cortices were evaluated using resting-state functional magnetic resonance imaging (fMRI) in musicians and non-musicians. The results revealed that functional connectivity was significantly increased in the motor and multi-sensory cortices of musicians. Moreover, the Granger causality results demonstrated a significant increase outflow-inflow degree in the auditory cortex with the strongest causal outflow pattern of effective connectivity being found in musicians. These resting state fMRI findings indicate enhanced functional integration among the lower-level perceptual and motor networks in musicians, and may reflect functional consolidation (plasticity) resulting from long-term musical training, involving both multi-sensory and motor functional integration.

Emergence of stable functional networks in long-term human electroencephalography

Functional connectivity networks have become a central focus in neuroscience because they reveal key higher-dimensional features of normal and abnormal nervous system physiology. Functional networks reflect activity-based coupling between brain regions that may be constrained by relatively static anatomical connections, yet these networks appear to support tremendously dynamic behaviors. Within this growing field, the stability and temporal characteristics of functional connectivity brain networks have not been well characterized. We evaluated the temporal stability of spontaneous functional connectivity networks derived from multi-day scalp encephalogram (EEG) recordings in five healthy human subjects. Topological stability and graph characteristics of networks derived from averaged data epochs ranging from 1 s to multiple hours across different states of consciousness were compared. We show that, although functional networks are highly variable on the order of seconds, stable network templates emerge after as little as ∼100 s of recording and persist across different states and frequency bands (albeit with slightly different characteristics in different states and frequencies). Within these network templates, the most common edges are markedly consistent, constituting a network "core." Although average network topologies persist across time, measures of global network connectivity, density and clustering coefficient, are state and frequency specific, with sparsest but most highly clustered networks seen during sleep and in the gamma frequency band. These findings support the notion that a core functional organization underlies spontaneous cortical processing and may provide a reference template on which unstable, transient, and rapidly adaptive long-range assemblies are overlaid in a frequency-dependent manner.

Reorganization of Brain Networks in Aging and Age-related Diseases

Aging is associated with reorganization of brain in both structure and function. In recent years, graph theoretical analysis of brain organization has drawn increasing attention, and reorganization of brain in aging has been investigated in terms of connectivity and networks in topology such as modular organization, global and local efficiency, and small-worldness. Beyond studying on abnormity in local brain regions, connectivity quantifies alternations of correlation between two regions that may be spatially far separated, and graph theoretical analysis of brain network examines the complex interactions among multiple regions. This article reviewed complex brain networks of human in normal aging or with age-related diseases such as stroke and Alzheimer's disease after a technical introduction of brain networks and graph theoretical analysis. We further discussed the relationship between the functional and the structural brain networks of subjects in aging or with age-related diseases. Finally, we proposed several interesting topics for future research in this field.

Neurobiological circuits regulating attention, cognitive control, motivation, and emotion: disruptions in neurodevelopmental psychiatric disorders

OBJECTIVE

This article aims to review basic and clinical studies outlining the roles of prefrontal cortical (PFC) networks in the behavior and cognitive functions that are compromised in childhood neurodevelopmental disorders and how these map into the neuroimaging evidence of circuit abnormalities in these disorders.

METHOD

Studies of animals, normally developing children, and patients with neurodevelopmental disorders were reviewed, with focus on neuroimaging studies.

RESULTS

The PFC provides "top-down" regulation of attention, inhibition/cognitive control, motivation, and emotion through connections with posterior cortical and subcortical structures. Dorsolateral and inferior PFC regulate attention and cognitive/inhibitory control, whereas orbital and ventromedial structures regulate motivation and affect. PFC circuitries are very sensitive to their neurochemical environment, and small changes in the underlying neurotransmitter systems, e.g. by medications, can produce large effects on mediated function. Neuroimaging studies of children with neurodevelopmental disorders show altered brain structure and function in distinctive circuits respecting this organization. Children with attention-deficit/hyperactivity disorder show prominent abnormalities in the inferior PFC and its connections to striatal, cerebellar, and parietal regions, whereas children with conduct disorder show alterations in the paralimbic system, comprising ventromedial, lateral orbitofrontal, and superior temporal cortices together with specific underlying limbic regions, regulating motivation and emotion control. Children with major depressive disorder show alterations in ventral orbital and limbic activity, particularly in the left hemisphere, mediating emotions. Finally, children with obsessive-compulsive disorder appear to have a dysregulation in orbito-fronto-striatal inhibitory control pathways, but also deficits in dorsolateral fronto-parietal systems of attention.

CONCLUSIONS

Altogether, there is a good correspondence between anatomical circuitry mediating compromised functions and patterns of brain structure and function changes in children with neuropsychiatric disorders. Medications may optimize the neurochemical environment in PFC and associated circuitries, and improve structure and function.

Correspondence between structure and function in the human brain at rest

To further understanding of basic and complex cognitive functions, previous connectome research has identified functional and structural connections of the human brain. Functional connectivity is often measured by using resting-state functional magnetic resonance imaging (rs-fMRI) and is generally interpreted as an indirect measure of neuronal activity. Gray matter (GM) primarily consists of neuronal and glia cell bodies; therefore, it is surprising that the majority of connectome research has excluded GM measures. Therefore, we propose that by exploring where GM corresponds to function would aid in the understanding of both structural and functional connectivity and in turn the human connectome. A cohort of 603 healthy participants underwent structural and functional scanning on the same 3 T scanner at the Mind Research Network. To investigate the spatial correspondence between structure and function, spatial independent component analysis (ICA) was applied separately to both GM density (GMD) maps and to rs-fMRI data. ICA of GM delineates structural components based on the covariation of GMD regions among subjects. For the rs-fMRI data, ICA identified spatial patterns with common temporal features. These decomposed structural and functional components were then compared by spatial correlation. Basal ganglia components exhibited the highest structural to resting-state functional spatial correlation (r = 0.59). Cortical components generally show correspondence between a single structural component and several resting-state functional components. We also studied relationships between the weights of different structural components and identified the precuneus as a hub in GMD structural network correlations. In addition, we analyzed relationships between component weights, age, and gender; concluding that age has a significant effect on structural components.

Functional immaturity of cortico-basal ganglia networks in Gilles de la Tourette syndrome

Gilles de la Tourette syndrome is a clinically heterogeneous disorder with poor known pathophysiology. Recent neuropathological and structural neuroimaging data pointed to the dysfunction of cortico-basal ganglia networks. Nonetheless, it is not clear how these structural changes alter the functional activity of the brain and lead to heterogeneous clinical expressions of the syndrome. The objective of this study was to evaluate global integrative state and organization of functional connections of sensori-motor, associative and limbic cortico-basal ganglia networks, which are likely involved in tics and behavioural expressions of Gilles de la Tourette syndrome. We also tested the hypothesis that specific regions and networks contribute to different symptoms. Data were acquired on 59 adult patients and 27 gender- and age-matched controls using a 3T magnetic resonance imaging scanner. Cortico-basal ganglia networks were constructed from 91 regions of interest. Functional connectivity was quantified using global integration and graph theory measures. We found a stronger functional integration (more interactions among anatomical regions) and a global functional disorganization of cortico-basal ganglia networks in patients with Gilles de la Tourette syndrome compared with controls. All networks were characterized by a shorter path length, a higher number of and stronger functional connections among the regions and by a loss of pivotal regions of information transfer (hubs). The functional abnormalities correlated to tic severity in all cortico-basal ganglia networks, namely in premotor, sensori-motor, parietal and cingulate cortices and medial thalamus. Tic complexity was correlated to functional abnormalities in sensori-motor and associative networks, namely in insula and putamen. Severity of obsessive-compulsive disorder was correlated with functional abnormalities in associative and limbic networks, namely in orbito-frontal and prefrontal dorsolateral cortices. The results suggest that the pattern of functional changes in cortico-basal ganglia networks in patients could reflect a defect in brain maturation. They also support the hypothesis that distinct regions of cortico-basal ganglia networks contribute to the clinical heterogeneity of this syndrome.

Graph-based network analysis in schizophrenia

Over the last few years, many studies have been published using modern network analysis of the brain. Researchers and practical doctors alike should understand this method and its results on the brain evaluation at rest, during activation and in brain disease. The studies are noninvasive and usually performed with elecroencephalographic, magnetoencephalographic, magnetic resonance imaging and diffusion tensor imaging brain recordings. Different tools for analysis have been developed, although the methods are in their early stages. The results of these analyses are of special value. Studies of these tools in schizophrenia are important because widespread and local network disturbances can be evaluated by assessing integration, segregation and several structural and functional properties. With the help of network analyses, the main findings in schizophrenia are lower optimum network organization, less efficiently wired networks, less local clustering, less hierarchical organization and signs of disconnection. There are only about twenty five relevant papers on the subject today. Only a few years of study of these methods have produced interesting results and it appears promising that the development of these methods will present important knowledge for both the preclinical signs of schizophrenia and the methods’ therapeutic effects.