The Functional Connectivity Landscape of the Human Brain

Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.</p

Interacting with nature improves cognition and affect for individuals with depression

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150698/1/2012_Berman_et_al_Interacting_with_natures_improves_cognition.pd

The Functional Connectivity Landscape of the Human Brain

<div><p>Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.</p></div

Relationship between the Euclidean distance of parcels and the correlation between parcel timeseries for each fMRI study and for each condition and participant group.

<p>Relationship between the Euclidean distance of parcels and the correlation between parcel timeseries for each fMRI study and for each condition and participant group.</p

Details for the neuroimaging studies that were analyzed.

<p>Details for the neuroimaging studies that were analyzed.</p

For each study, a sampling distribution of correlations between changes in saliences and Euclidean distances was constructed using only independent pairs of nodes.

<p>For each study, a sampling distribution of correlations between changes in saliences and Euclidean distances was constructed using only independent pairs of nodes.</p

Changes in correlation between conditions of greatest difference in correlation plotted against Euclidean distance.

<p>Changes in correlation between conditions of greatest difference in correlation plotted against Euclidean distance.</p

PCA analysis of scatter plots displaying the relationship between correlation differences and Euclidean distance.

<p>The PCA analysis was used to determine if outlying points exhibited a different relationship with Euclidean distance than the majority of the points. Points that were in the upper or lower 5% in terms of displacement from the primary axis of variance are colored red and suggest that there is no systematic relationship between correlation differences and Euclidean distances for the outlying points. The red line represents the primary axis of variance.</p

3-dimensional histogram of correlation differences by Euclidean distance for each study.

<p>In the 3-dimensional histogram (top) the number of observations (i.e., density) is represented by color and height. In the 2-dimensional plot (bottom) density is represented by color only.</p