Reconfiguration of the Brain Functional Network Associated with Visual Task Demands

<div><p>Neuroimaging studies have demonstrated that the topological properties of resting-state brain functional networks are modulated through task performances. However, the reconfiguration of functional networks associated with distinct degrees of task demands is not well understood. In the present study, we acquired fMRI data from 18 healthy adult volunteers during resting-state (RS) and two visual tasks (i.e., visual stimulus watching, VSW; and visual stimulus decision, VSD). Subsequently, we constructed the functional brain networks associated with these three conditions and analyzed the changes in the topological properties (e.g., network efficiency, wiring-cost, modularity, and robustness) among them. Although the small-world attributes were preserved qualitatively across the functional networks of the three conditions, changes in the topological properties were also observed. Compared with the resting-state, the functional networks associated with the visual tasks exhibited significantly increased network efficiency and wiring-cost, but decreased modularity and network robustness. The changes in the task-related topological properties were modulated according to the task complexity (i.e., from RS to VSW and VSD). Moreover, at the regional level, we observed that the increased nodal efficiencies in the visual and working memory regions were positively associated with the increase in task complexity. Together, these results suggest that the increased efficiency of the functional brain network and higher wiring-cost were observed to afford the demands of visual tasks. These observations provide further insights into the mechanisms underlying the reconfiguration of the brain network during task performance.</p></div

Validation analyses of the effects of task complexity on the global parameters derived from the binary networks in different brain templates (the AAL90 and Fun268 templates) and the weighted network in the Fun160 template.

<p>Note: The validation of the nodal analysis was not performed due to the incompatibility across different brain templates. The bold text represents the consistent results compared with the main findings.—represents non-applicability because the corresponding result of ANOVA is not significant (<i>p</i> > 0.05). ↑ represents RS < VSW, VSW < VSD, and RS < VSD, respectively; ↓ represents the contrary. <i>C</i>_p, clustering coefficient; <i>L</i>_p, characteristic path length; <i>E</i>_loc, local efficiency; <i>E</i>_glob, global efficiency; <i>σ</i>, small-worldness; <i>K</i>, average degree; <i>D</i>_p, physical distance; <i>Q</i>, modularity; <i>R</i>, robustness. RS: resting-state, VSW: visual stimulus watching task, VSD: visual stimulus decision task.</p><p>^a 0.01 ≤ <i>p</i><0.05</p><p>^b<i>p</i><0.01</p><p>^ns, Nonsignificant (<i>p</i>>0.05)</p><p>Validation analyses of the effects of task complexity on the global parameters derived from the binary networks in different brain templates (the AAL90 and Fun268 templates) and the weighted network in the Fun160 template.</p

The small-world parameters and efficiency of brain functional networks.

<p>(A) The functional networks of all cognitive conditions showed a higher clustering coefficient (<i>C</i>_p) and approximately equal characteristic path length (<i>L</i>_p) compared with the matched random networks (top panel), resulting in normalized <i>C</i>_p > 1 and normalized <i>L</i>_p ≈ 1 (bottom panel). (B) Functional networks exhibited higher local efficiency (<i>E</i>_loc) but approximately identical global efficiency (<i>E</i>_glob) of parallel information transmission compared with matched random networks (top panel), resulting in normalized <i>E</i>_loc > 1 and normalized <i>E</i>_glob ≈ 1 (bottom panel). RS: resting-state, VSW: visual stimulus watching task, VSD: visual stimulus decision task.</p

Costs, modularity, and robustness of brain functional networks across all subjects in the three cognitive conditions.

<p>Box-plots show the median, interquartile range, and range for the wiring-cost. (A) Average degree <i>K</i> and physical distance <i>D</i>_p; (B) the modularity <i>Q</i>; and (C) the robustness <i>R</i>. Each horizontal line and the associated number indicate the <i>p</i>-value of a post-hoc paired <i>t</i>-test (two-tailed). ‘ns’ presents the <i>p</i>-value > 0.05. RS: resting-state, VSW: visual stimulus watching task, VSD: visual stimulus decision task.</p

Surface visualization of the brain regions exhibiting significant between-state differences in nodal efficiency for the three comparisons, VSW-RS, VSD-VSW, and VSD-RS.

<p>The node size is proportional to the relative significance of each between-state comparison (two-tailed paired <i>t</i>-test, <i>p</i> < 0.05, FDR correction). The node colors indicate the node belonging to the six different modules according to the brain template [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132518#pone.0132518.ref035" target="_blank">35</a>]. Uniformly, we detected significantly increased nodal efficiency between each of the three comparisons, VSW-RS, VSD-VSW, and VSD-RS. RS: resting-state, VSW: visual stimulus watching task, VSD: visual stimulus decision task. LH (RH), left (right) hemisphere.</p

Global parameters of brain functional networks across all subjects in the three cognitive conditions.

<p>(Top row) Within-subject effects of task complexity on the clustering coefficient <i>C</i>_p, characteristic path length <i>L</i>_p, local efficiency <i>E</i>_loc, global efficiency <i>E</i>_glob. (Bottom row) Box-plots show the median, interquartile range, and range for each parameter in each condition. Each horizontal line and the associated number indicate the <i>p</i>-value of a post-hoc paired <i>t</i>-test (two-tailed). RS: resting-state, VSW: visual stimulus watching task, VSD: visual stimulus decision task.</p

Mean global parameters of brain functional networks for the three cognitive conditions (RS: resting-state; VSW: visual stimulus watching task; VSD: visual stimulus decision task).

<p>Note: Global parameters across all three conditions were calculated for each subject and averaged as group means. <i>C</i>_p, clustering coefficient; <i>L</i>_p, characteristic path length; <i>E</i>_loc, local efficiency; <i>E</i>_glob, global efficiency; <i>σ</i>, small-worldness; <i>K</i>, average degree; <i>D</i>_p, physical distance; <i>Q</i>, modularity; <i>R</i>, robustness. The range of σ indicated that the functional network for each subject exhibits small-world attributes in each of the three cognitive conditions (σ > 1).</p><p>Mean global parameters of brain functional networks for the three cognitive conditions (RS: resting-state; VSW: visual stimulus watching task; VSD: visual stimulus decision task).</p

Disrupted Topological Organization in Whole-Brain Functional Networks of Heroin-Dependent Individuals: A Resting-State fMRI Study

<div><p>Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.</p></div

Demographic information for the heroin-dependent individuals (HDIs) and the normal controls (NCs) in the present study.

<p> The duration of heroin usage means the period from the time of their initial heroin use to the time of their seeking medical attention.</p><p>^a Fisher's exact test.</p><p><i>t</i>-test.^b Two sample </p

The connected subnetwork showing decreased functional connections in the heroin-dependent individuals (HDIs) compared to the normal controls (NCs).

<p>(a) Visualization of decreased functional connections related to heroin addiction using BrainNet Viewer (<a href="http://www.nitrc.org/projects/bnv/" target="_blank">http://www.nitrc.org/projects/bnv/</a>). The width of the line indicates the <i>t</i>-value of the connection comparisons between the two groups. A single, connected subnetwork containing 19 nodes and 19 connections was determined using the network-based statistic (NBS) method. (b) Scatter plot of the integrated clustering coefficient, , against the mean functional connectivity of this connected subnetwork averaged over all subjects. (c) Same as (b) but for the integrated normalized clustering coefficient, . (d) Same as (b) but for integrated small-worldness, . The abbreviations of the regions are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082715#pone.0082715.s003" target="_blank">Table S2</a>.</p