BOLD time course similarity scales with genetic relatedness across the cortex. (A) Group differences in average BOLD time course similarity (indexed by ISC) show that BOLD time course similarity is greater among dyads who are more genetically related (51 MZ dyads, 34 DZ dyads, 690 UR dyads). (B) Group-average ISC values used to create the difference maps in A, plotted in order of average ISC across all subject pairs, show that group differences are most pronounced in parcels with medium to high ISC (shading = SEM).

BOLD time courses are heritable across the cortex. (A) Cortical surfaces show heritability of BOLD time courses parcellated using the Schaefer 400 atlas, controlling for age, gender, and head motion (mean h2 Day 1 / Day 2 = .064 ± .034/.068 ± .036). (B) Residuals after regressing parcel-level ISC from parcel-level heritability show that BOLD time courses in auditory cortices are less heritable than would be expected based on ISC, whereas the opposite is true for lateral prefrontal and temporo-occipito-parietal junction parcels.

BOLD time course heritability is greater in slower frequency bands, especially for more associative parcels. (A) Purple/yellow cortical surfaces (upper row) show unfiltered BOLD time course heritability (upper left is identical to Fig. 2A) as well as the heritability of BOLD time courses filtered with five frequency bands, with greater heritability in slower bands for Day 1 data. Red/blue cortical surfaces show BOLD time course heritability residuals after regressing out parcel- and frequency-level differences in ISC (lower left is identical to Fig. 2B), with greater residuals in slower frequencies and more associative parcels. (B) Scatter plot shows heritability averaged across the cortex for each frequency band (i.e., the averages of the upper row of surfaces in A; shading = jackknife SEM). (C) Scatter plot shows the difference in heritability between the slowest and fastest BOLD-sensitive frequency bands for each of the Schaefer 400 parcels plotted against parcel ranks from the Sydnor et al. sensorimotor-association hierarchy (higher = more associative). Least squares lines were added to highlight the positive relationships between average h2 and parcel ranks but note that these relationships were formally tested with Spearman correlations. (D–F) Same as A–C for Day 2 data.

Hyperalignment reduces BOLD time course heritability. (A) Cartoon illustrates the difference between shared cortical topographies and shared (topography-independent) information content. (B) Diagrams illustrate the inputs to response and connectivity hyperalignment (RHA and CHA, respectively) using the Schaefer 100 atlas. RHA topographies were learned using BOLD time course data from the other day’s movie-watching scans, while CHA topographies were learned from vertex-level FC profiles (i.e., correlations between one vertex’s BOLD time course and the average time course from each of the 99 other parcels) calculated from the other day’s resting state scans. (C) Vertex-level BOLD time course heritability is highest for data aligned via MSM (multimodal surface matching) and lower for data hyperaligned within 100 Schaefer atlas parcels using both response hyperalignment (RHA) and connectivity hyperalignment (CHA). (D) Differences between the MSM-only and hyperaligned heritability maps shown in (C) are distributed across the cortex but are most apparent in visual areas. (E) BOLD time course heritability decreases as a function of hyperalignment parcel size according to a power law (purple and orange lines); each dot corresponds to average cortex-wide heritability for data hyperaligned using one of the 10 Schaefer atlas resolutions (shading = jackknife SEM).

Controlling for neural timescales (NTs) reduces heritability of BOLD time courses. (A) Bar plots show average pairwise differences in cortex-wide NT across MZ, DZ, and unrelated dyads on both days of data collection, where only MZ and UR group means differed significantly on both days (MZ Day 1/Day 2 means = 0.15/0.15, UR = 0.24/0.27, FDR-corrected Pperm < .05). (B) Cortical surfaces show decreases in BOLD time course heritability after NTs calculated from the other day of data collection were included as covariates in the multidimensional heritability analyses for MSM-aligned and RHA-aligned (using the Schaefer 100 parcellation) data, most prominently in mid-level auditory and visual regions. These maps are thresholded at Δh2 = ±0.01 to aid comparisons of MSM- and RHA-aligned results. The maximum differences in h2 after controlling for NTs were −0.025 for MSM-aligned data and −0.007 for RHA-aligned data, respectively.

FC profile similarity scales with genetic relatedness across the cortex. (A) Group differences in average FC profile similarity show that FC profiles are more similar for dyads who are more genetically related (51 MZ dyads, 34 DZ dyads, 690 UR dyads). (B) Group-average FC profile similarity values used to create the difference maps in A, plotted in order of average FC profile similarity across all subject pairs (shading = SEM).

FC profiles are heritable across network combinations. Heatmaps show heritability of FC profiles for all unique within- and between-network combinations of the 17 Yeo networks after controlling for age, gender, and head motion. FC profiles during movie-watching (left column) were more heritable than resting state FC profiles (middle column) for more sensory-oriented networks (red rows in the right column).

Hyperalignment reduces FC profile heritability. (A) Heatmaps show decreased FC profile heritability for most combinations of 17 Yeo networks following RHA (left) and CHA (right) compared to the MSM-only baseline. (B) Scatter plots show that hyperalignment, especially with RHA, decreases FC profile heritability according to a power law function; each dot corresponds to average cortex-wide heritability for data hyperaligned using one of the 10 Schaefer atlas resolutions (or MSM-only alignment, shading = jackknife SEM).