Neonatal exposure to novel environment enhances hippocampal-dependent memory function during infancy and adulthood

Early life experience affects behavior and brain mechanisms. Handling rats during the first three weeks in life can slow age-related cognitive decline (as measured by a hippocampal-dependent spatial learning task) and reduce age-related hippocampal neuron loss. It is not clear, however, whether this early environmental influence on learning is selective for old age or is more general, affecting cognitive development during infancy and young adulthood as well. We briefly exposed neonatal rats to a novel non-home environment for 3 min daily during the first three weeks of life (as a component of the handling method). We found that this brief early environmental manipulation resulted in enhanced hippocampal-dependent learning immediately after weaning and that this learning enhancement persisted into adulthood. These results suggest that subtle early life events can affect cognitive development in all developmental stages and that changes in neural mechanisms other than neuron number are likely to mediate the learning enhancement at multiple developmental stages.     

Retrieval conditions and false recognition: testing the distinctiveness heuristic

High levels of false recognition are observed after people study lists of semantic associates that all converge on a nonpresented lure word. In previous experiments, we have found that orienting participants to encode distinctive information about study list items by presenting them as pictures as opposed to words produces marked reductions in false recognition. We have suggested that these reductions reflect the operation of a distinctiveness heuristic: Participants demand access to detailed pictorial information in order to support a positive recognition decision. The present experiments provide additional evidence on this point and allow us to distinguish between the distinctiveness heuristic account and an alternative account based on the impoverished encoding of relational information that occurs when one is studying pictures. In Experiment 1, even when only half of the items in a study list were presented as pictures, a general suppression of false recognition was observed that could be attributable to impoverished encoding of relational information. Experiment 2 provided a critical test of the distinctiveness heuristic account: We manipulated test instructions and found that differences in false recognition rates between picture and word encoding were attenuated in a retrieval condition that did not encourage reliance on a distinctiveness heuristic.     

Calculating and graphing within-subject confidence intervals for ANOVA

The psychological and statistical literature contains several proposals for calculating and plotting confidence intervals (CIs) for within-subjects (repeated measures) ANOVA designs. A key distinction is between intervals supporting inference about patterns of means (and differences between pairs of means, in particular) and those supporting inferences about individual means. In this report, it is argued that CIs for the former are best accomplished by adapting intervals proposed by Cousineau (Tutorials in Quantitative Methods for Psychology, 1, 42–45, 2005) and Morey (Tutorials in Quantitative Methods for Psychology, 4, 61–64, 2008) so that nonoverlapping CIs for individual means correspond to a confidence for their difference that does not include zero. CIs for the latter can be accomplished by fitting a multilevel model. In situations in which both types of inference are of interest, the use of a two-tiered CI is recommended. Free, open-source, cross-platform software for such interval estimates and plots (and for some common alternatives) is provided in the form of R functions for one-way within-subjects and two-way mixed ANOVA designs. These functions provide an easy-to-use solution to the difficult problem of calculating and displaying within-subjects CIs.     

Optimal sample sizes for precise interval estimation of Welch’s procedure under various allocation and cost considerations

Welch’s (Biometrika 29: 350–362, 1938) procedure has emerged as a robust alternative to the Student’s t test for comparing the means of two normal populations with unknown and possibly unequal variances. To facilitate the advocated statistical practice of confidence intervals and further improve the potential applicability of Welch’s procedure, in the present article, we consider exact approaches to optimize sample size determinations for precise interval estimation of the difference between two means under various allocation and cost considerations. The desired precision of a confidence interval is assessed with respect to the control of expected half-width, and to the assurance probability of interval half-width within a designated value. Furthermore, the design schemes in terms of participant allocation and cost constraints include (a) giving the ratio of group sizes, (b) specifying one sample size, (c) attaining maximum precision performance for a fixed cost, and (d) meeting a specified precision level for the least cost. The proposed methods provide useful alternatives to the conventional sample size procedures. Also, the developed programs expand the degree of generality for the existing statistical software packages and can be accessed at brm.psychonomic-journals.org/content/ supplemental.