Improved processing speed: online computer-based cognitive training in older adults

In an increasingly aging population, a number of adults are concerned about declines in their cognitive abilities. Online computer-based cognitive training programs have been proposed as an accessible means by which the elderly may improve their cognitive abilities; yet, more research is needed in order to assess the efficacy of these programs. In the current study, a commercially available 21-day online computer-based cognitive training intervention was administered to 34 individuals aged between 53 and 75 years. The intervention consisted of computerized training in reaction time, inspection time, short-term memory for words, executive function, visual spatial acuity, arithmetic, visual spatial memory, visual scanning/discrimination, and n-back working memory. An active solitaire control group was also included. Participants were tested at baseline, posttraining and at three-weeks follow-up using a battery of neuropsychological outcome measures. These consisted of simple reaction time, complex reaction time, digit forwards and backwards, spatial working memory, digit symbol substitution, RAVLT, and trail making. Significant improvement in simple reaction time and choice reaction time task was found in the cognitive training group both posttraining and at three-weeks follow-up. However, no significant improvements on the other cognitive tasks were found. The training program was found to be successful in achieving transfer of trained cognitive abilities in speed of processing to similar untrained tasks. © 2012 Copyright Taylor and Francis Group, LLC.

A parallel algorithm for calculation of determinants and minors using arbitrary precision arithmetic

We present a parallel algorithm for calculating determinants of matrices in arbitrary precision arithmetic on computer clusters. This algorithm limits data movements between the nodes and computes not only the determinant but also all the minors corresponding to a particular row or column at a little extra cost, and also the determinants and minors of all the leading principal submatrices at no extra cost. We implemented the algorithm in arbitrary precision arithmetic, suitable for very ill conditioned matrices, and empirically estimated the loss of precision. In our scenario the cost of computation is bigger than that of data movement. The algorithm was applied to studies of Riemann’s zeta function.