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Our findings demonstrate that older adults with more modular brain networks at baseline showed greater improvements after cognitive training. Critically, this relationship was not present in a control group and remained significant when accounting for baseline performance on the cognitive measures that improved with training. These results are directly in line with our previous work demonstrating that TBI patients with higher brain network modularity at baseline exhibited greater improvements on executive function tasks after cognitive training [ 22]. We expand on these findings by demonstrating that the relationship between brain network modularity and training-related cognitive gains in healthy older adults was stronger for association cortex modules compared with sensory-motor modules. Together, these findings suggest that individuals with a more modular brain network organization measured during a task-free ‘resting-state’ prior to training are more likely to benefit from cognitive training.

Modular brain network organization is thought to support both specialized functions through communication within network modules and globally-integrated functions through communication between network modules [ 40]. Previous studies have provided support for the importance of this global network property by demonstrating that brain network modularity measured during a ‘resting-state’ is correlated with working memory capacity [ 41], predicts perception on a trial-by-trial basis [ 31], and is altered with varying task demands [ 42]. These studies suggest that modular network organization is related to both trait- and state-like aspects of cognition (e.g., working memory capacity and perceptual success, respectively). Here, we add to this previous work by showing that higher network modularity may represent an optimal brain organization for improving cognitive functioning with training. The benefits of highly modular networks have been previously demonstrated in both theoretical and empirical work. For example, computational models have shown that modular networks evolve in response to varying task goals and that this organization allows for rapid adaptation to new environments [ 43]. Further, individuals with higher general intelligence exhibit smaller changes in functional connectivity between a ‘resting-state’ and performance of a task, suggesting that high performing individuals have a more ‘optimal’ network organization at rest that supports more efficient changes in connectivity during task performance [ 44]. In the context of cognitive interventions, individuals with a more modular brain network organization may require less reconfiguration to achieve an ‘optimal’ state that allows for cognitive gains from training. Among patients with knowledge deficits, the SMART program may facilitate informed decision‐making by helping them develop the skills needed to understand and use complex information concerning medication risks/benefits. Depictions of within- (left) and between- (right) module connections for SMART subjects with low (top) and high (bottom) brain network modularity. The presence or absence of a connection was calculated for each connection density threshold (i.e., an adjacency matrix) for the top 2–10% of connections in 2% increments. For illustration purposes, we then averaged the adjacency matrices over thresholds for each subject, where edges represent the proportion of thresholds for which a connection was present between two regions (ranging from 0 to 1). Brain regions are colored according to their module assignments in Power et al. (2011) and are grouped into sensory-motor and association cortex modules as defined in Chan et al. (2014). The subject with high modularity has many connections within modules and fewer connections between modules compared to the subject with low modularity. Cerny, JoBe (May 11, 2015). "Icons of Advertising". Screen Magazine. Archived from the original on June 7, 2015 . Retrieved August 17, 2019.

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Coyle, John J.; Bardi, Edward J.; Langley, C. John (1996). "15". The management of business logistics (6thed.). Minneapolis/St. Paul: West Pub. Co. ISBN 9780314065070. OCLC 33280849. The inclusion criteria were clearly stated in terms of participants, intervention and outcomes. The search, covering a number of relevant sources, was likely to have reduced the risk of publication bias. Studies not written in English were excluded and this may have resulted in language bias. However, the authors' tests suggested that it was unlikely that missing studies would have significantly effected overall results. The methods of study selection and data extraction were aimed at reducing reviewer error or bias. Behzadi Y, Restom K, Liau J, Liu TT. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage. 2007;37: 90–101. pmid:17560126 Kashtan N, Alon U. Spontaneous evolution of modularity and network motifs. Proceedings of the National Academy of Sciences. 2005;102: 13773–13778.

Aging is associated with declines in various cognitive functions, such as attention, cognitive control, and memory [ 1]. There is emerging evidence that characterization of large-scale brain network properties provides an important framework for understanding such complex behaviors [ 2, 3]. Previous work has shown that brain networks exhibit a modular organization, such that they are comprised of sub-networks, or modules. The extent of segregation of brain network modules can be quantified with a modularity metric [ 4], where highly modular networks have many connections within modules and fewer connections to other modules. Previous studies examining changes in modularity with aging have shown that older adults have less modular structural and functional brain networks than young adults [ 5– 8], particularly in sub-networks thought to mediate ‘associative’ functions, such as the fronto-parietal control and dorsal and ventral attention modules, compared to those involved in sensory-motor processing [ 9].

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Stanley ML, Dagenbach D, Lyday RG, Burdette JH, Laurienti PJ. Changes in global and regional modularity associated with increasing working memory load. Frontiers in Human Neuroscience. 2014;8: 954. pmid:25520639 Enhancing patients' ability to understand and use information about medication risks and benefits to make informed decisions concerning treatment alternatives remains an important goal. Although more than half of the participants in our sample were college graduates, nearly two‐thirds (n=184) did not meet the criteria for informed decision‐making at baseline. In our full sample, neither of the interventions that were evaluated improved informed decision‐making, either alone or in combination. However, although not hypothesized a priori, our analyses revealed a statistically significant interaction between the SMART program and informed decision‐making at baseline. Specifically, the SMART program had a positive impact on informed decision‐making in the subset of participants who did not meet the criteria for informed decision‐making at baseline. This finding is consistent with previous research that has demonstrated benefits of the SMART program on performance on cognitive, neural, and functional measures immediately post‐training and 3–6 months post‐training ( 24, 27, 41, 42, 43).

Data Availability: The authors confirm that all data related to the findings reported here are fully available without restriction. As the data contain identifying human information, they are unsuitable for public deposition. The data will be stored at the Center for BrainHealth at UT Dallas and will be made available upon request to Scott Smith (Lead Systems Administrator at the Center for BrainHealth; [email protected]) or one of the authors. The animated Keebler Elves, led by "Ernest J. 'Ernie' Keebler", rank among the best-known characters from commercials. [ citation needed] Ernie is the head elf and the friendliest of the bunch. [27] The elves have appeared in countless television advertisements throughout the years (most of them animated at FilmFair), shown baking their unique products. [28] In the commercials, the Keebler tree logo is often turned into the tree in which the elves reside. Wen X, Zhang D, Liang B, Zhang R, Wang Z, Wang J, et al. Reconfiguration of the Brain Functional Network Associated with Visual Task Demands. PLoS ONE. 2015;10: e0132518. pmid:26146993 Medaglia JD, Lynall ME, Bassett DS. Cognitive Network Neuroscience. Journal of Cognitive Neuroscience. 2015;27: 1471–1491. pmid:25803596When comparing patients receiving dialysis with those not receiving dialysis with chronic kidney disease (glomerular filtration rate of less than 60ml/min/1.73m 2), the risk of death was similar for both groups (five studies; random-effects model). Cao W, Cao X, Hou C, Li T, Cheng Y, Jiang L, et al. Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks. Frontiers in Aging Neuroscience. 2016;8: 1–11.