Links between physical fitness and cardiovascular reactivity and recovery to psychological stressors: A meta-analysis.

A meta-analysis of published studies with adult human participants was conducted to evaluate whether physical fitness attenuates cardiovascular reactivity and improves recovery from acute psychological stressors. Thirty-three studies met selection criteria; 18 were included in recovery analyses. Effect sizes and moderator influences were calculated by using meta-analysis software. A fixed effects model was fit initially; however, between-studies heterogeneity could not be explained even after inclusion of moderators. Therefore, to account for residual heterogeneity, a random effects model was estimated. Under this model, fit individuals showed significantly attenuated heart rate and systolic blood pressure reactivity and a trend toward attenuated diastolic blood pressure reactivity. Fit individuals also showed faster heart rate recovery, but there were no significant differences in systolic blood pressure or diastolic blood pressure recovery. No significant moderators emerged. Results have important implications for elucidating mechanisms underlying effects of fitness on cardiovascular disease and suggest that fitness may be an important confound in studies of stress reactivity.     

Two ways of learning associations

How people learn chunks or associations between adjacent items in sequences was modelled. Two previously successful models of how people learn artificial grammars were contrasted: the CCN, a network version of the competitive chunker of Servan‐Schreiber and Anderson [J. Exp. Psychol.: Learn. Mem. Cogn. 16 (1990) 592], which produces local and compositionally‐structured chunk representations acquired incrementally; and the simple recurrent network (SRN) of Elman [Cogn. Sci. 14 (1990) 179], which acquires distributed representations through error correction. The models' susceptibility to two types of interference was determined: prediction conflicts, in which a given letter can predict two other letters that appear next with an unequal frequency; and retroactive interference, in which the prediction made by a letter changes in the second half of training. The predictions of the models were determined by exploring parameter space and seeing howdensely different regions of the space of possible experimental outcomes were populated by model outcomes. For both types of interference, human data fell squarely in regions characteristic of CCN performance but not characteristic of SRN performance.