Minimal Variation in Functional Connectivity in Relation to Daily Affect.

Reported associations between functional connectivity and affective disorder symptoms are minimally reproducible, which can partially be attributed to difficulty capturing highly variable clinical symptoms in cross-sectional study designs. "Dense sampling" protocols, where participants are sampled across multiple sessions, can overcome this limitation by studying associations between functional connectivity and variable clinical states. Here, we characterized effect sizes for the association between functional connectivity and time-varying positive and negative daily affect in a nonclinical cohort. Data were analyzed from 24 adults who attended four research visits, where participants self-reported daily affect using the PANAS-X questionnaire and completed 39 min of functional magnetic resonance imaging across three passive viewing conditions. We modeled positive and negative daily affect in relation to network-level functional connectivity, with hypotheses regarding within-network connectivity of the default mode, salience/cingulo-opercular, frontoparietal, dorsal attention, and visual networks and between-network connectivity of affective subcortical regions (amygdala and nucleus accumbens) with both default mode and salience/cingulo-opercular networks. Effect sizes for associations between affect and network-level functional connectivity were small and nonsignificant across analyses. We additionally report that functional connectivity variance is largely attributable to individual identity with small relative variance (<3%) accounted for by within-subject daily affect variation. These results support previous reports that functional connectivity is dominated by stable subject-specific connectivity patterns, while additionally suggesting relatively minimal influence of day-to-day affect. Researchers planning studies examining functional connectivity in relation to daily affect, or other varying stable states, should therefore anticipate small effect sizes and carefully consider power in study planning.