Dynamic functional network connectivity reveals unique and overlapping profiles of insula subdivisions

Abstract

The human insular cortex consists of functionally diverse subdivisions that engage during tasks ranging from interoception to cognitive control. The multiplicity of functions subserved by insular subdivisions calls for a nuanced investigation of their functional connectivity profiles. Four insula subdivisions (dorsal anterior, dAI; ventral, VI; posterior, PI; middle, MI) derived using a data-driven approach were subjected to static- and dynamic functional network connectivity (s-FNC and d-FNC) analyses. Static-FNC analyses replicated previous work demonstrating a cognition-emotion-interoception division of the insula, where the dAI is functionally connected to frontal areas, the VI to limbic areas, and the PI and MI to sensorimotor areas. Dynamic-FNC analyses consisted of k-means clustering of sliding windows to identify variable insula connectivity states. The d-FNC analysis revealed that the most frequently occurring dynamic state mirrored the cognition-emotion-interoception division observed from the s-FNC analysis, with less frequently occurring states showing overlapping and unique subdivision connectivity profiles. In two of the states, all subdivisions exhibited largely overlapping profiles, consisting of subcortical, sensory, motor, and frontal connections. Two other states showed the dAI exhibited a unique connectivity profile compared with other insula subdivisions. Additionally, the dAI exhibited the most variable functional connections across the s-FNC and d-FNC analyses, and was the only subdivision to exhibit dynamic functional connections with regions of the default mode network. These results highlight how a d-FNC approach can capture functional dynamics masked by s-FNC approaches, and reveal dynamic functional connections enabling the functional flexibility of the insula across time. Hum Brain Mapp 37:1770-1787, 2016. © 2016 Wiley Periodicals, Inc.

Keywords: default mode network; dynamic functional network connectivity; flexibility; insular cortex; limbic system; resting state fMRI; salience network.

Figure 1

Schematic of analysis steps. (A) high‐model group ICA (100 components) creates a functional parcellation of the brain resulting in 52 non‐noise components. (B) Subject‐specific time courses from the group ICA are then used to calculate functional connections. The static analysis entails computing correlations across the entire duration of the rsfMRI scan. The dynamic analysis utilized 45 second tapered‐sliding windows slid in 1TR to acquire 237 correlation matrices for each subject (one per window). Connections between each insula subdivision and all other ICs were then extracted for data anaylysis. (C) A concatenated data matrix consisting of all insula subdivision correlations x each window for each subject (237 windows x 31 subjects) was subjected to k‐means clustering using values 2–20 that identified the optimal k as 5 using the elbow criterion. K‐means clustering using a value of k = 5 then assigned each window to dynamic state k regardless of subject assignment. Subject‐specific medians were then back‐reconstructed for each state k before they were averaged together to produce the final five dynamic insula states. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 2

Top: Static functional connectivity correlation matrix for IC pairs. Bottom: ICs grouped according to brain systems. IC labels for the correlation matrix denote bilateral activation unless specified by L (left) or R (right). STG, superior temporal gyrus; MTG, medial temporal gyrus; IFG, inferior frontal gyrus; CG, central gyrus; SMA, supplementary motor area; OCC, occipital; CC, calcarine cortex; FG, fusiform gyrus; ACC, anterior cingulate; OBF, orbitofrontal cortex; DLPFC, dorsal lateral pre‐frontal cortex; AG, angular gyrus; MPFC, medial pre‐frontal cortex; DMN, default mode network. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 3

Plots of significant positive connections between insula subdivisions and other ICs. The maximum intensity values from each IC were used to designate the surface plot areas. The connections of the static analysis and State 3 from the dynamic analysis are in accord with the cognition‐emotion‐tripartite framework of insula function; the dorsal anterior insula (dAI) has connections with frontal areas, the middle and posterior (MI and PI) insula subdivisions have connections with sensorimotor areas, and the ventral insula (VI) has connections with the nucleus accumbens and hippocampus/amygdala ICs. State 1 is generally represented by similar connections across subdivisions with subcortical, frontal, sensorimotor, salience, and visual ICs. State 4 is similar to State 1 but with less frontal and sensorimotor connections and virtually no visual connections. States 2 and 5 show that the MI and PI have similar connections while the VI has less sensorimotor connections and the dAI diverges from other subdivisions to have connections with frontal (State 5) and default mode (States 2 and 5) ICs. Percent values refer to the frequency of state occurrence while n refers to the number of subjects that enter into that state. CEN, central executive network; DMN, default mode network; CB cerebellum. Figure created using BrainNet Viewer (https://www.nitrc.org/projects/bnv/). [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 4

Polar plot showing functional connections of insula subdivisions in the static functional connectivity analysis (s‐FNC). Labels on the outer edges of the polar plots are grouped in the same way as Figure 1, with different brain systems represented by different color fonts. The “*” placed along the radiating axes represents a significant difference among insula subdivisions for that specific brain area. Significant positive correlations can be seen between the dorsal anterior insula (dAI) and frontal ICs, the VI with the hippocampus/amygdala and the nucleus accumbens, and the posterior/middle insula with sensorimotor ICs (Figure 3). Polar plot labels use the same abbreviations as in Figure 2. The scale of the polar plot (−0.7 to 0.7) represents the size of the fisher‐z transformed correlations. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 5

Polar plots representing functional connections of insula subdivisions for the whole insula d‐FNC analysis. Labels on the outer edges of the polar plots are grouped in the same way as Figure 1, with different brain systems represented by different color fonts. The “*” placed along the radiating axes represents a significant difference among insula subdivisions for that specific brain area. Notably, State 1 shows the most convergence among insula subdivision connections (less significant differences among subdivision connections) while State 5 shows the most divergence among insula subdivision connections (more significant differences among insula subdivision connections). Dorsal anterior insula = dAI. Polar plot labels use the same abbreviations as Figure 2. The scale of the polar plot (−0.5 to 0.5) represents the size of the fisher z transformed correlations. Percent values refer to the frequency of state occurrence while n refers to the number of subjects that enter into that state. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 6

Correlations between static and dynamic insula profiles. The top matrix shows the overall correlations calculated using all insula states and show that State 3 has the largest correlation with the static analysis. The bottom matrices show that the dAI has the lowest correlations between the static and dynamic analyses, and also the lowest correlations among dynamic states. This shows that the dAI has more variable connections than the other insula subdivisions. S1, dynamic state 1; s2, dynamic state 2; s3, dynamic state 3, etc. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]