Dataset Information

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.

ABSTRACT: Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

SUBMITTER: Duarte-Carvajalino JM

PROVIDER: S-EPMC3551467 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.

Duarte-Carvajalino Julio M JM Jahanshad Neda N Lenglet Christophe C McMahon Katie L KL de Zubicaray Greig I GI Martin Nicholas G NG Wright Margaret J MJ Thompson Paul M PM Sapiro Guillermo G

NeuroImage 20111112 4

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain ...[more]

PMID: 22108644

Similar Datasets

Project description:IntroductionSuccessful inhibition of distracting emotions is important for preserving well-being and daily functioning. There is conflicting evidence regarding the impact of healthy aging on emotional inhibition, and possible age-related alterations in the neuronal underpinnings of emotional interference processing are unexplored.MethodsThirty younger (mean age 26 years; 15 women) and 30 older (mean age 71 years; 13 women) healthy adults performed a face-word emotional Stroop task while undergoing functional magnetic resonance imaging of the brain. A resting-state scan was acquired for calculating the amplitude of low-frequency fluctuations as an estimate of vascular reactivity. Comparisons of brain activation during the task were assessed in a whole-brain, voxel-wise analysis, contrasting congruent, and incongruent conditions. The canonical regions of the frontoparietal, salience, dorsal attention, and default mode networks were used as seed regions for assessing functional connectivity within and between large-scale brain networks. Task performance was evaluated using response accuracy and response time.ResultsThe older adults had longer response times and lower task accuracy than the younger adults, but the emotional interference effect was not significantly different between the groups. Whole-brain analysis revealed no significant age-related differences in brain activation patterns. Rescaling the data for estimated variability in vascular reactivity did not affect the results. In older adults, there was relatively stronger functional connectivity with the default mode network, the sensorimotor network, and the dorsal attention network for the frontoparietal and salience network seeds during the task. Conversely, younger adults had relatively stronger connections within and between the frontoparietal and salience networks.ConclusionIn this first fMRI study of emotional Stroop interference in older and younger adults, we found that the emotional interference effect was unchanged in healthy aging and replicated the finding from non-emotional task studies that older adults have greater between-network and less within-network connectivity compared to younger adults.

Project description:Spatial navigation involves multiple cognitive processes including multisensory integration, visuospatial coding, memory, and decision-making. These functions are mediated by the interplay of cerebral structures that can be broadly separated into a posterior network (subserving visual and spatial processing) and an anterior network (dedicated to memory and navigation planning). Within these networks, areas such as the hippocampus (HC) are known to be affected by aging and to be associated with cognitive decline and navigation impairments. However, age-related changes in brain connectivity within the spatial navigation network remain to be investigated. For this purpose, we performed a neuroimaging study combining functional and structural connectivity analyses between cerebral regions involved in spatial navigation. Nineteen young (μ = 27 years, σ = 4.3; 10 F) and 22 older (μ = 73 years, σ = 4.1; 10 F) participants were examined in this study. Our analyses focused on the parahippocampal place area (PPA), the retrosplenial cortex (RSC), the occipital place area (OPA), and the projections into the visual cortex of central and peripheral visual fields, delineated from independent functional localizers. In addition, we segmented the HC and the medial prefrontal cortex (mPFC) from anatomical images. Our results show an age-related decrease in functional connectivity between low-visual areas and the HC, associated with an increase in functional connectivity between OPA and PPA in older participants compared to young subjects. Concerning the structural connectivity, we found age-related differences in white matter integrity within the navigation brain network, with the exception of the OPA. The OPA is known to be involved in egocentric navigation, as opposed to allocentric strategies which are more related to the hippocampal region. The increase in functional connectivity between the OPA and PPA may thus reflect a compensatory mechanism for the age-related alterations around the HC, favoring the use of the preserved structural network mediating egocentric navigation. Overall, these findings on age-related differences of functional and structural connectivity may help to elucidate the cerebral bases of spatial navigation deficits in healthy and pathological aging.

Project description:ObjectiveThe study aimed to find the difference in functional network topology on interictal electroencephalographic (EEG) between patients with drug-resistant epilepsy (DRE) and healthy people.MethodsWe retrospectively analyzed the medical records as well as EEG data of ten patients with DRE and recruited five sex-age-matched healthy controls (HC group). Each participant remained awake while undergoing video-electroencephalography (vEEG) monitoring. After excluding data that contained abnormal discharges, we screened EEG segments that were free of artifacts and put them together into 20-min segments. The screened data was bandpass filtered to different frequency bands (delta, theta, alpha, beta, and gamma). The weighted phase lag index (wPLI) and the network properties were calculated to evaluate changes in the topology of the functional network. Finally, the results were statistically analyzed, and the false discovery rate (FDR) was used to correct for differences after multiple comparisons.ResultsIn the full frequency band (0.5-45 Hz), the functional connectivity in the DRE group during the interictal period was significantly lower than that in the HC group (p < 0.05). Compared to the HC group, in the full frequency band, the DRE group exhibited significantly decreased clustering coefficient (CC), node degree (D), and global efficiency (GE), while the characteristic path length (CPL) significantly increased (p < 0.05). In the sub-frequency bands, the functional connectivity of the DRE group was significantly lower than that of the HC group in the delta band but higher in the alpha, beta, and gamma bands (p < 0.05). The statistical results of network properties revealed that in the delta band, the DRE group had significantly decreased values for D, CC, and GE, but in the alpha, beta, and gamma bands, these values were significantly increased (p < 0.05). Additionally, the CPL of the DRE group significantly increased in the delta and theta bands but significantly decreased in the alpha, beta, and gamma bands (p < 0.05).ConclusionThe topology structure of the functional network in DRE patients was significantly changed compared with healthy people, which was reflected in different frequency bands. It provided a theoretical basis for understanding the pathological network alterations of DRE.

Dataset Information

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.

Publications

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets