![Dynamic functional network connectivity analysis. (A) Three resulting connectivity states as well as their across-group frequencies. The first state was characterized by a highly positive intra-domain connectivity in all of the domains [sensorimotor (SMN), subcortical (SC), cerebellar, (CB)] and highly negative inter-domain connectivity. It was the state resembling the static connectivity matrix the most, measured in Manhattan distance. The second and most frequent state featured comparably lower connectivity within the sensorimotor domain, particularly between the ventral precentral component and the paracentral lobule to further sensorimotor components. Inter-domain connectivity was mostly neutral. The third state comprised positive intra-domain connectivity, negative inter-domain connectivity between both the sensorimotor and subcortical domains to the cerebellar domain and no connectivity between the sensorimotor and subcortical domains. (B) Elbow criterion. Trajectory of the cluster validity index with increasing numbers of clusters, i.e. k in k-means clustering (top) and cluster distributions for a given number of clusters (bottom). The cluster validity index was computed as the ratio between the within-cluster distance to between-cluster distance. As the steepness of the decline in the clustering validity index decreased markedly after three and four clusters, yet the four-cluster solution included a state with a frequency of <10%, k = 3 combined the lowest cluster validity index and most well-balanced solution. This choice was additionally enforced by the highest silhouette measure for k = 3 (see Supplementary material). (C) Connectivity states separately for each of the three subgroups. Please note that some subjects only entered one or two of the defined three connectivity states, resulting in varying numbers of subjects within a specific state (cf., stated absolute numbers of subjects entering the state as well as the percentage of the entire subgroup). Connectivity state frequencies did not differ significantly between subgroups.](https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/brain/143/5/10.1093_brain_awaa101/1/awaa101f4.jpeg?Expires=1749766742&Signature=CYdwjc4yB9S6Kr9E70SfGgte728Jf3A-pgU5MwqEcL-oC4fOhjTwBOD8bjEo7jHeZ~FqZHE8gjXpjNQSvcO1ZLMLVH45ZJIKM-9kvUoaLTHxpb2y9sREolLIt3tCsLNIgFdPzaScBe3hobAXbUYAaPIPAJGuTKYEvcARlPCQOQl-ELB7iXA2yxWTQbK9HgNjWbH4IWsM1QogDMs~-~Hhvl9CbjDFgTv5Xnmt0Om1yivPWpbBZkeA9R5ipluW~zB4EwNjiWCSyTAM6VvO38-qN-JfR~cNK8eBlxbLtQsh39d13wQfXfUioAG9UmwGDhL46T2VpdAbWEDLVO51B4cMtw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA)
Dynamic functional network connectivity analysis. (A) Three resulting connectivity states as well as their across-group frequencies. The first state was characterized by a highly positive intra-domain connectivity in all of the domains [sensorimotor (SMN), subcortical (SC), cerebellar, (CB)] and highly negative inter-domain connectivity. It was the state resembling the static connectivity matrix the most, measured in Manhattan distance. The second and most frequent state featured comparably lower connectivity within the sensorimotor domain, particularly between the ventral precentral component and the paracentral lobule to further sensorimotor components. Inter-domain connectivity was mostly neutral. The third state comprised positive intra-domain connectivity, negative inter-domain connectivity between both the sensorimotor and subcortical domains to the cerebellar domain and no connectivity between the sensorimotor and subcortical domains. (B) Elbow criterion. Trajectory of the cluster validity index with increasing numbers of clusters, i.e. k in k-means clustering (top) and cluster distributions for a given number of clusters (bottom). The cluster validity index was computed as the ratio between the within-cluster distance to between-cluster distance. As the steepness of the decline in the clustering validity index decreased markedly after three and four clusters, yet the four-cluster solution included a state with a frequency of <10%, k = 3 combined the lowest cluster validity index and most well-balanced solution. This choice was additionally enforced by the highest silhouette measure for k = 3 (see Supplementary material). (C) Connectivity states separately for each of the three subgroups. Please note that some subjects only entered one or two of the defined three connectivity states, resulting in varying numbers of subjects within a specific state (cf., stated absolute numbers of subjects entering the state as well as the percentage of the entire subgroup). Connectivity state frequencies did not differ significantly between subgroups.
