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The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation.

Krishnadas R, Kim J, McLean J, Batty GD, McLean JS, Millar K, Packard CJ, Cavanagh J - Front Hum Neurosci (2013)

Bottom Line: For example, the human brain has been found to have a modular architecture i.e., regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it.These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups.These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology.

View Article: PubMed Central - PubMed

Affiliation: Sackler Institute of Psychobiological Research, Institute of Health and Wellbeing, University of Glasgow, Gartnavel Royal Hospital Glasgow, UK.

ABSTRACT
Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large-scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e., regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure-modularity and gray nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer gray nodes-a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology.

No MeSH data available.


The distributions of correlation coefficients for both groups. The vertical red lines are the FDR threshold values for each group. Affluent: Least deprived; Deprived: Most deprived.
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Figure 7: The distributions of correlation coefficients for both groups. The vertical red lines are the FDR threshold values for each group. Affluent: Least deprived; Deprived: Most deprived.

Mentions: We conducted all analyses on binarised matrices derived from interregional correlations of cortical thickness. Initial examination of number of isolated modules showed that for a given correlation threshold, the least deprived group had greater number of isolated groups compared to the deprived group (Figure 4). The raw networks and FDR filtered networks are shown in Figures 5, 6. The distribution of the groups' correlation coefficients is shown in Figure 7. A direct comparison of the networks derived from the above populations, was not possible, as for a given correlation threshold, the sparsity (density) of the two networks were significantly different (Figure 8). In addition, the FDR procedure thresholded the two networks significantly differently. This method of thresholding resulted in different number of edges—k—(sparsity) in the networks of the two groups because of differences in their inter-regional cortical thickness correlations. We therefore compared the network structure derived from the groups to their corresponding random networks. The results of this analysis are shown in Figures 9, 10.


The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation.

Krishnadas R, Kim J, McLean J, Batty GD, McLean JS, Millar K, Packard CJ, Cavanagh J - Front Hum Neurosci (2013)

The distributions of correlation coefficients for both groups. The vertical red lines are the FDR threshold values for each group. Affluent: Least deprived; Deprived: Most deprived.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3824100&req=5

Figure 7: The distributions of correlation coefficients for both groups. The vertical red lines are the FDR threshold values for each group. Affluent: Least deprived; Deprived: Most deprived.
Mentions: We conducted all analyses on binarised matrices derived from interregional correlations of cortical thickness. Initial examination of number of isolated modules showed that for a given correlation threshold, the least deprived group had greater number of isolated groups compared to the deprived group (Figure 4). The raw networks and FDR filtered networks are shown in Figures 5, 6. The distribution of the groups' correlation coefficients is shown in Figure 7. A direct comparison of the networks derived from the above populations, was not possible, as for a given correlation threshold, the sparsity (density) of the two networks were significantly different (Figure 8). In addition, the FDR procedure thresholded the two networks significantly differently. This method of thresholding resulted in different number of edges—k—(sparsity) in the networks of the two groups because of differences in their inter-regional cortical thickness correlations. We therefore compared the network structure derived from the groups to their corresponding random networks. The results of this analysis are shown in Figures 9, 10.

Bottom Line: For example, the human brain has been found to have a modular architecture i.e., regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it.These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups.These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology.

View Article: PubMed Central - PubMed

Affiliation: Sackler Institute of Psychobiological Research, Institute of Health and Wellbeing, University of Glasgow, Gartnavel Royal Hospital Glasgow, UK.

ABSTRACT
Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large-scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e., regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure-modularity and gray nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer gray nodes-a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology.

No MeSH data available.