Keebler M&M Cookies (1.6Oz., 30 Ct.)

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Cohen J, Cohen P, West SG, Aiken LS. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Erlbaum, Mahwah, NJ; 2003. Kellogg gets out of cookie business by selling Keebler, Famous Amos brands". WXIN. April 1, 2019 . Retrieved October 13, 2019. Kashtan N, Alon U. Spontaneous evolution of modularity and network motifs. Proceedings of the National Academy of Sciences. 2005;102: 13773–13778.

Vas AK, Spence JS, Eschler B, Chapman SB. Sensitivity and Specificity of Abstraction using Gist Reasoning Measure in Adults with Traumatic Brain Injury. Journal of Applied Biobehavioral Research. 2016; in press. Characteristics of study participants are presented using means and percentages, depending on the measurement properties of the variables. We used logistic regression to assess the effects of the 2 interventions on our primary outcome: informed decision‐making at the 6‐month follow‐up. A separate regression model was performed at each follow‐up time point (i.e., 6‐week, 3‐month, and 6‐month). Each model controlled for informed decision‐making at baseline (0=did not meet criteria, 1=met criteria) and indicator variables for each intervention indexing assignment to the SMART program (0=no, 1=yes) and the DrugFactsBox group (0=no, 1=yes). We also included three two‐way interaction terms in each model. The first interaction term assessed whether the effects of the 2 interventions were dependent on one another. The other interaction terms assessed whether the effects of the interventions varied as a function of informed decision‐making at baseline. Interaction terms that were not statistically significant ( P<0.05) were dropped from the models and the models were re‐run to examine main effects.Elliot, Stuart (August 20, 2008). "Those Shelved Brands Start to Look Tempting". The New York Times. Vatansever D, Menon DK, Manktelow AE, Sahakian BJ, Stamatakis EA. Default Mode Dynamics for Global Functional Integration. Journal of Neuroscience. 2015;35: 15254–15262. pmid:26586814

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. The present study was based on the premise that interventions designed to educate patients about the risks and benefits associated with different therapeutic options require a 2‐pronged approach, including simplification of educational materials to convey the essential gist (i.e., “bottom‐line” meaning) and assistance to patients in developing the health literacy/numeracy skills needed to process complex information (e.g., scientific uncertainty concerning medication risks/benefits) to derive that gist ( 16, 17). Thus, we examined the effectiveness of 2 innovative communication strategies, including DrugFactsBoxes and the Strategic Memory Advanced Reasoning Training (SMART) program. DrugFactsBoxes were developed to enhance the usability of written consumer medication information (CMI), especially among individuals with limited health literacy/numeracy skills ( 18, 19, 20). The SMART program was developed to enhance patients' ability to understand and extract “bottom‐line” meaning (gist) from complex information, which we view as an essential health literacy skill ( 21, 22, 23, 24, 25, 26, 27). 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 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.Gallen CL, Turner GR, Adnan A, D'Esposito M. Reconfiguration of brain network architecture to support executive control in aging. Neurobiology of Aging. 2016;44: 42–52. pmid:27318132 Lustig C, Shah P, Seidler R, Reuter-Lorenz PA. Aging, Training, and the Brain: A Review and Future Directions. Neuropsychol Rev. 2009;19: 504–522. pmid:19876740 Medaglia JD, Lynall ME, Bassett DS. Cognitive Network Neuroscience. Journal of Cognitive Neuroscience. 2015;27: 1471–1491. pmid:25803596 American candy doesn't get much bigger than M&M's! Invented in 1941, today M&M's, the iconic melt in your mouth not in your hand sweets are America's top selling candy. But how well do you know M&M's? Have some fun with our M&M's trivia quiz in our blog - Are M&M's the best American Candy?.