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.
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Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. As morphometric studies have shown widespread structural damage in TLE, this condition is often referred to as a ...system disorder with disrupted structural networks. Studies based on univariate statistical comparisons can only indirectly test such hypothesis. Graph theory provides a new approach to formally analyze large-scale networks. Using graph-theoretical analysis of magnetic resonance imaging-based cortical thickness correlations, we investigated the structural basis of the organization of such networks in 122 TLE patients and 47 age- and sex-matched healthy controls. Networks in patients and controls were characterized by a short path length between anatomical regions and a high degree of clustering, suggestive of a small-world topology. However, compared with controls, patients showed increased path length and clustering, altered distribution of network hubs, and higher vulnerability to targeted attacks, suggesting a reorganization of cortical thickness correlation networks. Longitudinal analysis demonstrated that network alterations intensify over time. Bootstrap simulations showed high reproducibility of network parameters across random subsamplings, indicating that altered network topology in TLE is a consistent finding. Increased network disruption was associated with unfavorable postoperative seizure outcome, implying adverse effects of epileptogenesis on large-scale network organization.
An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the ...human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.
Neuroimaging studies in autism spectrum disorders (ASDs) have provided inconsistent evidence of cortical abnormality. This is probably due to the small sample sizes used in most studies, and ...important differences in sample characteristics, particularly age, as well as to the heterogeneity of the disorder. To address these issues, we assessed abnormalities in ASD within the Autism Brain Imaging Data Exchange data set, which comprises data from approximately 1100 individuals (~6-55 years). A subset of these data that met stringent quality control and inclusion criteria (560 male subjects; 266 ASD; age = 6-35 years) were used to compute age-specific differences in cortical thickness in ASD and the relationship of any such differences to symptom severity of ASD. Our results show widespread increased cortical thickness in ASD, primarily left lateralized, from 6 years onwards, with differences diminishing during adulthood. The severity of symptoms related to social affect and communication correlated with these cortical abnormalities. These results are consistent with the conjecture that developmental patterns of cortical thickness abnormalities reflect delayed cortical maturation and highlight the dynamic nature of morphological abnormalities in ASD.
Brain Connectivity Gong, Gaolang; He, Yong; Evans, Alan C.
The Neuroscientist (Baltimore, Md.),
10/2011, Volume:
17, Issue:
5
Journal Article
Peer reviewed
It has been well known that gender plays a critical role in the anatomy and function of the human brain, as well as human behaviors. Recent neuroimaging studies have demonstrated gender effects on ...not only focal brain areas but also the connectivity between areas. Specifically, structural MRI and diffusion MRI data have revealed substantial gender differences in white matter–based anatomical connectivity. Structural MRI data further demonstrated gender differences in the connectivity revealed by morphometric correlation among brain areas. Functional connectivity derived from functional neuroimaging (e.g., functional MRI and PET) data is also modulated by gender. Moreover, male and female human brains display differences in the network topology that represents the organizational patterns of brain connectivity across the entire brain. In this review, the authors summarize recent findings in the multimodal brain connectivity/network research with gender, focusing on large-scale data sets derived from modern neuroimaging techniques. The literature provides convergent evidence for a substantial gender difference in brain connectivity within the human brain that possibly underlies gender-related cognitive differences. Therefore, it should be mandatory to take gender into account when designing experiments or interpreting results of brain connectivity/network in health and disease. Future studies will likely be conducted to explore the interdependence between gender-related brain connectivity/network and the gender-specific nature of brain diseases as well as to investigate gender-related characteristics of multimodal brain connectivity/network in the normal brain.
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Knowing the maturational schedule of typical brain development is critical to our ability to identify deviations from it; such deviations have been related to cognitive performance and even ...developmental disorders. Chronological age can be predicted from brain images with considerable accuracy, but with limited spatial specificity, particularly in the case of the cerebral cortex. Methods using multi-modal data have shown the greatest accuracy, but have made limited use of cortical measures. Methods using complex measures derived from voxels throughout the brain have also shown great accuracy, but are difficult to interpret in terms of cortical development. Measures based on cortical surfaces have yielded less accurate predictions, suggesting that perhaps cortical maturation is less strongly related to chronological age than is maturation of deep white matter or subcortical structures. We question this suggestion. We show that a simple metric based on the white/gray contrast at the inner border of the cortex is a good predictor of chronological age. We demonstrate this in two large datasets: the NIH Pediatric Data, with 832 scans of typically developing children, adolescents, and young adults; and the Pediatric Imaging, Neurocognition, and Genetics data, with 760 scans of individuals in a similar age-range. Further, our usage of an elastic net penalized linear regression model reveals the brain regions which contribute most to age-prediction. Moreover, we show that the residuals of age-prediction based on this white/gray contrast metric are not merely random errors, but are strongly related to IQ, suggesting that this metric is sensitive to aspects of brain development that reflect cognitive performance.
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The characterization of the topological architecture of complex networks underlying the structural and functional organization of the brain is a basic challenge in neuroscience. However, direct ...evidence for anatomical connectivity networks in the human brain remains scarce. Here, we utilized diffusion tensor imaging deterministic tractography to construct a macroscale anatomical network capturing the underlying common connectivity pattern of human cerebral cortex in a large sample of subjects (80 young adults) and further quantitatively analyzed its topological properties with graph theoretical approaches. The cerebral cortex was divided into 78 cortical regions, each representing a network node, and 2 cortical regions were considered connected if the probability of fiber connections exceeded a statistical criterion. The topological parameters of the established cortical network (binarized) resemble that of a "small-world" architecture characterized by an exponentially truncated power-law distribution. These characteristics imply high resilience to localized damage. Furthermore, this cortical network was characterized by major hub regions in association cortices that were connected by bridge connections following long-range white matter pathways. Our results are compatible with previous structural and functional brain networks studies and provide insight into the organizational principles of human brain anatomical networks that underlie functional states.
Cortical thickness correlation across individuals has been observed. So far, it remains unclear to what extent such a correlation in thickness is a reflection of underlying fiber connection. Here we ...explicitly compared the patterns of cortical thickness correlation and diffusion-based fiber connection across the entire cerebral cortex, in 95 normal adults. Interregional thickness correlations were extracted by using computational neuroanatomy algorithms based on structural MRI, and diffusion connections were detected by using diffusion probabilistic tractography. Approximately 35–40% of thickness correlations showed convergent diffusion connections across the cerebral cortex. Intriguingly, the observed convergences between thickness correlation and diffusion connection are mostly focused on the positive thickness correlations, while almost all of the negative correlations (>90%) did not have a matched diffusion connection, suggesting different mechanisms behind the positive and negative thickness correlations, the latter not being mediated by a direct fiber pathway. Furthermore, graph theoretic analysis reveals that the thickness correlation network has a more randomized overall topology, whereas the nodal characteristics of cortical regions in these two networks are statistically correlated. These findings indicate that thickness correlations partly reflect underlying fiber connections but they contains exclusive information, and therefore should not be simply taken as a proxy measure for fiber connections.
► Thickness correlation and fiber connection are compared across the cerebral cortex. ► Positive thickness correlations show substantial convergence with fiber connections. ► Negative thickness correlations show substantial divergence with fiber connections. ► The thickness correlation network has a more randomized overall topology.
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Neuroanatomical differences attributable to aging and gender have been well documented, and these differences may be associated with differences in behaviors and cognitive performance. However, ...little is known about the dynamic organization of anatomical connectivity within the cerebral cortex, which may underlie population differences in brain function. In this study, we investigated age and sex effects on the anatomical connectivity patterns of 95 normal subjects ranging in age from 19 to 85 years. Using the connectivity probability derived from diffusion magnetic resonance imaging tractography, we characterized the cerebral cortex as a weighted network of connected regions. This approach captures the underlying organization of anatomical connectivity for each subject at a regional level. Advanced graph theoretical analysis revealed that the resulting cortical networks exhibited "small-world" character (i.e., efficient information transfer both at local and global scale). In particular, the precuneus and posterior cingulate gyrus were consistently observed as centrally connected regions, independent of age and sex. Additional analysis revealed a reduction in overall cortical connectivity with age. There were also changes in the underlying network organization that resulted in decreased local efficiency, and also a shift of regional efficiency from the parietal and occipital to frontal and temporal neocortex in older brains. In addition, women showed greater overall cortical connectivity and the underlying organization of their cortical networks was more efficient, both locally and globally. There were also distributed regional differences in efficiency between sexes. Our results provide new insights into the substrates that underlie behavioral and cognitive differences in aging and sex.
Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure–function relationships in the human brain. While these microstructurally defined ...maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure–function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure–function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the “central tendency” of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.
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