Large-scale brain networks underlying domain-specific memory, intelligence, and academic performance
Academic performance relies, in part, on memory and intelligence. These phenomena have been studied at length, but little is known about the role of brain connectivity in integrating memory and intelligence to support academic success. Even less is known about if and how these relationships vary between sexes. Here, we take a targeted approach to investigate brain networks underlying domain-specific memory, general intelligence, and academic performance, and how these measures differ among female versus male students in a historically male-dominated domain. We focused on the hippocampus, default mode, and central executive networks, which support internally- and externally-oriented processes underlying memory and task performance. 
Data were collected from 107 undergraduate students (47 female) following the completion of their first college-level physics course. Behavioral data included IQ and final course grade. 3T MR data included structural images and fMRI data collected while participants performed a novel memory retrieval task, with general and physics-specific conditions. Following preprocessing, connectivity matrices were calculated per condition, using networks meta-analytically delineated by Laird et al. (2011). We compared between-network connectivity for the default mode network (DMN), left and right central executive networks (lCEN, rCEN) and hippocampus (Hc) across conditions for the whole sample and separately for each sex, between conditions across sex, and with respect to individual differences in behavioral measures.
Overall, students answered more slowly and less accurately during physics versus general retrieval conditions, differences reflected by decreased rCEN-DMN and rCEN-lCEN connectivity (p<0.01; Figure 1, lower triangle). Male students responded more quickly than female students during both physics and general retrieval (p<0.05), but only more accurately during physics retrieval (p<0.01). There were no sex differences in general retrieval accuracy. Only Hc-lCEN connectivity differed between male and female students (p<0.05; Fig. 1, upper triangle), during physics retrieval. Within sex, female students demonstrated greater Hc-DMN connectivity during physics versus general retrieval (p<0.01) and male students demonstrated greater rCEN-DMN and rCEN-lCEN (p < 0.01) connectivity during general versus physics retrieval, likely driving these relationships in the whole sample (Fig. 1, upper triangle). While male students had significantly higher IQs (p<0.01) and IQ was significantly correlated with reaction time and accuracy across conditions (p<0.01), we found no relationship between IQ and course grade. Across the sample, there were no significant relationships between brain connectivity and course grade. When separated by sex, local efficiency within the lCEN was negatively correlated with grade (r = -0.356, p<0.01) in male, but not female students. Exploratory, whole-brain analyses revealed a more strongly connected subgraph during general versus physics retrieval, in which DMN, lCEN, rCEN, and a motor execution network showed high centrality (Figure 2), but no significant relationships between brain organization and IQ.
Behavioral differences between general and physics-specific memory were linked with differences in CEN and DMN connectivity, distinguishing processes by domain. The consistently stronger inter-network connectivity during general memory processing compared to physics-specific memory may reflect a Hebbian-like phenomenon, such that older (e.g., general) knowledge retrieval relies on a more strongly connected neural network than students’ newer (e.g., physics) knowledge retrieval. However, female students showed greater coordination between the Hc and DMN, suggesting a reliance on autobiographical memories may facilitate domain-specific recall. Lastly, while performance on the physics retrieval task was predictive of course grade, no underlying neural contribution was detected.