A scaffold for efficiency in the human brain

Abstract

The comprehensive relations between healthy adult human brain white matter (WM) microstructure and gray matter (GM) function, and their joint relations to cognitive performance, remain poorly understood. We investigated these associations in 27 younger and 28 older healthy adults by linking diffusion tensor imaging (DTI) with functional magnetic resonance imaging (fMRI) data collected during an n-back working memory task. We present a novel application of multivariate Partial Least Squares (PLS) analysis that permitted the simultaneous modeling of relations between WM integrity values from all major WM tracts and patterns of condition-related BOLD signal across all GM regions. Our results indicate that greater microstructural integrity of the major WM tracts was negatively related to condition-related blood oxygenation level-dependent (BOLD) signal in task-positive GM regions. This negative relationship suggests that better quality of structural connections allows for more efficient use of task-related GM processing resources. Individuals with more intact WM further showed greater BOLD signal increases in typical "task-negative" regions during fixation, and notably exhibited a balanced magnitude of BOLD response across task-positive and -negative states. Structure-function relations also predicted task performance, including accuracy and speed of responding. Finally, structure-function-behavior relations reflected individual differences over and above chronological age. Our findings provide evidence for the role of WM microstructure as a scaffold for the context-relevant utilization of GM regions.

Figure 1.

A, WM regions of interest. Superior corona radiata (SCR), superior longitudinal fasciculus (SLF), anterior and posterior limb of the internal capsule (ALIC and PLIC), external capsule (EC), fornix (FX), 5 regions of the corpus callosum [reg1, 2, 3, 4, 5 (Hofer and Frahm, 2006)], forceps major (fMAJ), forceps minor (fMIN), dorsal (dCING), and ventral cingulum (vCING), WM containing occipital portion of inferior longitudinal fasciculi and inferior fronto-occipital fasciculi (ILF/IFOF), ventral prefrontal part of uncinate (UNC_VPFC), WM containing uncinate and inferior fronto-occipital fasciculi (UNC_IFOF), medial temporal lobe WM (MTL), WM of the medial PFC (mPFC), WM of the temporal pole related to inferior longitudinal fasciculus (TEMP), and cerebral peduncles (CP). B, Histograms of region 2 of corpus callosum and global FA, mean RT, and mean accuracy in YA and OA. Note the overlapping distributions despite mean group differences.

Figure 2.

Multivariate relationships between WM integrity and BOLD signal. A, Spatial pattern where higher FA was related to less BOLD signal during task but more BOLD signal during fixation (blue-light blue). Only in one small cluster higher FA was related to higher BOLD signal at task and lower at fixation (red). Significant regions: bootstrap ratio >±3. PCC, Posterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; other labels are listed in Table 1. B, Correlation magnitudes (Pearson r) between FA in the 23 WM regions and BOLD signal during 1-, 2-, 3-back, and fixation (permuted p < 0.001, error bars represent bootstrapped 95% confidence intervals).

Figure 3.

Spatial differences and similarities between FA-BOLD and age group-BOLD multivariate models. A, Only FA-BOLD relations were predominant in the premotor, temporal, and visual regions, as well as in parts of DLPFC and thalamus (in blue). Age group-BOLD relations were robust in supramarginal, prefrontal, and parahippocampal regions (in red). FA-BOLD and age group-BOLD models overlapped in parietal, lateral prefrontal, posterior cingulate/precuneus, and visual regions (in green). The voxelwise spatial correlation of the first latent variables of the two models yielded Pearson r = 0.72, indicating that the two models shared only 52% spatial similarities. Labels are listed in Table 1. B, Correlation magnitudes (Pearson r) between age group and BOLD signal during 1-, 2-, 3-back, and fixation (permuted p < 0.001, error bars represent bootstrapped 95% confidence intervals).

Figure 4.

FA-BOLD relations for task-positive and task-negative BOLD signal. A, Mean-centered PLS revealed regions where BOLD signal increased on task (in red) or increased during fixation (in blue). Task-positive regions included the typical frontoparietal working memory network, as well as visual, anterior cingulate, and subcortical regions, while task-negative regions revealed typical default-mode network regions. Region abbreviations are listed in Table 1. B, FA-BOLD correlations within task-positive regions. C, FA-BOLD correlations within task-negative regions. D, Mean-centered brain scores showing differences from the mean of 1-, 2-, 3-back, and fixation (error bars represent bootstrapped 95% confidence intervals). E, Schematic representation of the differences in percent BOLD signal change between adults with higher and lower FA. The point estimates were calculated based on ± 1 SD global FA values given the slope and intercept from regression Models 1 and 2 in Table 1.

Figure 5.

Structure–function relations predict working memory performance. The scatterplots depict correlations of mean task brain scores for FA-BOLD relations to RT and accuracy across the three n-back conditions. Higher brain scores refer to higher FA and lower BOLD signal.