Table 2 Network Based Statistics (NBS) for testing component-level associations between functional connectivity and individual characteristics (n = 64).

Variables	Association	Statistics	Component threshold
			p < 0.01		p < 0.005		p < 0.001
			Size	(p_NBS)	Size	(p_NBS)	Size	(p_NBS)
Age	−	Extent	86	(0.011)	28	(0.031)	4	(0.083)
Age		Intensity	35.9	(0.011)	8.0	(0.057)	2.1	(0.044)
Years of education	+	Extent	19	(0.229)	8	(0.228)	1	(0.628)
Years of education		Intensity	4.7	(0.331)	0.9	(0.590)	0.0	(0.625)
Social network size	+	Extent	12	(0.347)	8	(0.225)	6	(0.042)
Social network size		Intensity	9.4	(0.156)	6.7	(0.081)	2.5	(0.037)
Social network embeddedness (continuous)	+	Extent	48	(0.051)	32	(0.024)	9	(0.017)
Social network embeddedness (continuous)		Intensity	24.7	(0.030)	14.5	(0.020)	3.7	(0.016)
Social network embeddedness (low = 0, high = 1)	+	Extent	73	(0.016)	47	(0.010)	12	(0.010)
Social network embeddedness (low = 0, high = 1)		Intensity	36.6	(0.011)	20.9	(0.010)	3.8	(0.017)

Note: From each set of ROI-pairs selected by pair-level tests with three different thresholds of p < 0.01, p < 0.005, and p < 0.001, NBS detects the largest ROI-component based on the extent (the number of ROI-pairs) or intensity (the extent weighted by the strength of associations), and calculates p-values (p_NBS) from the rate of cases where empirical brain networks have larger extent or intensity than 5,000 simulated networks. All the analyses were performed with covariates of gender, MMSE score, age, years of education, social network size, and social network embeddedness. The continuous form of social network embeddedness was used when testing the hypotheses for other major predictors.

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