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Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults (N = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, espe

Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults (N = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, espe

Better-performing younger adults typically express greater brain signal variability relative to older, poorer performers. Mechanisms for age and performance-graded differences in brain dynamics have, however, not yet been uncovered. Given the age-related decline of the dopamine (DA) system in normal cognitive aging, DA neuromodulation is one plausible mechanism. Hence, agents that boost systemic DA [such as d-amphetamine (AMPH)] may help to restore deficient signal variability levels. Furthermore, despite the standard practice of counterbalancing drug session order (AMPH first vs. placebo first), it remains understudied how AMPH may interact with practice effects, possibly influencing whether DA up-regulation is functional. We examined the effects of AMPH on functional-MRI-based blood oxygen level-dependent (BOLD) signal variability (SDBOLD) in younger and older adults during a working memory task (letter n-back). Older adults expressed lower brain signal variability at placebo, but met or exceeded young adult SDBOLD levels in the presence of AMPH. Drug session order greatly moderated change-change relations between AMPH-driven SDBOLD and reaction time means (RTmean) and SDs (RTSD). Older adults who received AMPH in the first session tended to improve in RTmean and RTSD when SDBOLD was boosted on AMPH, whereas younger and older adults who received AMPH in the second session showed either a performance improvement when SDBOLD decreased (for RTmean) or no effect at all (for RTSD). The present findings support the hypothesis that age differences in brain signal variability reflect aging-induced changes in dopaminergic neuromodulation. The observed interactions among AMPH, age, and session order highlight the state-and practice-dependent neurochemical basis of human brain dynamics.

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., AuthorCount:8;Funding Agencies:Max Planck Society-University College London Initiative for Computational Psychiatry and Ageing Research (ICPAR); Swedish Research Council; Swedish Brain Power, an Alexander von Humboldt Research Award; Jochnick Foundation

Executive functions that are dependent upon the frontal-parietal network decline considerably during the course of normal aging. To delineate neuroanatomical correlates of age-related executive impairment, we investigated the relation between cortical thickness and executive functioning in 73 younger (20-32 years) and 56 older (60-71 years) healthy adults. Executive functioning was assessed using the Wisconsin Card Sorting Test (WCST). Cortical thickness was measured at each location of the cortical mantle using surface-based segmentation procedures on high-resolution T1-weighted magnetic resonance images. For regions involved in WCST performance, such as the lateral prefrontal and parietal cortices, we found that thicker cortex was related to higher accuracy. Follow-up ROI-based analyses revealed that these associations were stronger in older than in younger adults. Moreover, among older adults, high and low performers differed in cortical thickness within regions generally linked to WCST performance. Our results indicate that the structural cortical correlates of executive functioning largely overlap with previously identified functional patterns. We conclude that structural preservation of relevant brain regions is associated with higher levels of executive performance in old age, and underscore the need to consider the heterogeneity of brain aging in relation to cognitive functioning.