Dynamic functional network connectivity in Huntington's disease and its associations with motor and cognitive measures

Abstract

Dynamic functional network connectivity (dFNC) is an expansion of traditional, static FNC that measures connectivity variation among brain networks throughout scan duration. We used a large resting-state fMRI (rs-fMRI) sample from the PREDICT-HD study (N = 183 Huntington disease gene mutation carriers [HDgmc] and N = 78 healthy control [HC] participants) to examine whole-brain dFNC and its associations with CAG repeat length as well as the product of scaled CAG length and age, a variable representing disease burden. We also tested for relationships between functional connectivity and motor and cognitive measurements. Group independent component analysis was applied to rs-fMRI data to obtain whole-brain resting state networks. FNC was defined as the correlation between RSN time-courses. Dynamic FNC behavior was captured using a sliding time window approach, and FNC results from each window were assigned to four clusters representing FNC states, using a k-means clustering algorithm. HDgmc individuals spent significantly more time in State-1 (the state with the weakest FNC pattern) compared to HC. However, overall HC individuals showed more FNC dynamism than HDgmc. Significant associations between FNC states and genetic and clinical variables were also identified. In FNC State-4 (the one that most resembled static FNC), HDgmc exhibited significantly decreased connectivity between the putamen and medial prefrontal cortex compared to HC, and this was significantly associated with cognitive performance. In FNC State-1, disease burden in HDgmc participants was significantly associated with connectivity between the postcentral gyrus and posterior cingulate cortex, as well as between the inferior occipital gyrus and posterior parietal cortex.

Keywords: Huntington's disease; dynamic functional network connectivity; group independent component analysis; resting-state fMRI.

Figure 1

(a) Spatial maps of the 46 independent components identified as RSNs, grouped into eight domains based on their anatomical and functional properties: auditory (AUD), cerebellar (CB), cognitive control (CC), default mode network (DMN), salience (SAL), subcortical (SC), sensorimotor, and visual (VIS). For each domain, all spatial maps are overlaid on a standard template and shown with a specific color. (b) Static functional network connectivity matrix, showing all pairwise correlations between the selected 46 RSN time‐courses averaged across subjects. Positive correlations are in the yellow to red range, whereas negative correlations are light to dark blue. Color bar correlation values range from −0.8 (dark blue) to 0.8 (dark red) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

States 1–4 FNC matrices with the number of windowed FNC in each state and corresponding percentage listed in brackets. Positive correlations are in the yellow to red range, whereas negative correlations are light to dark blue [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Significant group differences in connectivity between RSNs from the subcortical (SC) and default mode network (DMN) domains. In the left figure, the blue line shows significant negative associations between the group and the functional connectivity between putamen (IC13) and medial prefrontal cortex (IC73) in State‐4 (right figure) marked with a black star. Results are displayed as—sign(t)*log10(p value) and include only the p values that survived FDR correction [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

Positive association between the FNC pair putamen (IC13) and medial prefrontal cortex (IC73), which showed significant group effects, and the cognitive measure SDMT raw score (beta = 5.559, p value = 0.044) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

Bar plots displaying mean dwell times in States 1–4 for HC (blue) and HDgmc (magenta) participants. Two t‐test results showed a significant difference in mean dwell time between the HC and HDgmc groups in State‐1, t value = −2.7865 and corrected p value = 0.0058 from Table 4 [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 6

Significant CAP effects on connectivity between RSNs from the sensorimotor (SM), default mode network (DMN), visual (VIS), and cognitive control (CC) domains. In the left figure, yellow curves show significant positive associations between CAP and the functional connectivity between [1] postcentral gyrus (IC36) and posterior cingulate cortex (IC 90); and [2] inferior occipital gyrus (IC76) and posterior parietal cortex (IC99) in State‐1 (right figure) marked with black stars. Results are displayed as—sign(t)*log10(p value), and only p values that survived FDR correction are presented [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 7

Negative (blue lines) and positive (red lines) associations between the CAP‐associated FNC pair inferior occipital gyrus (IC76) and posterior parietal cortex (IC99) and the cognitive measures SDMT raw score (beta = −9.9266, p value = 0.008), Stroop color total (beta = −12.771, p value = 0.015), Stroop interference (beta = −9.3478, p value = 0.013), and TMTB time (beta = 23.742, p value = 0.024) [Color figure can be viewed at http://wileyonlinelibrary.com]