Expectation mismatch: differences between self-generated and cue-induced expectations.

Expectation of upcoming stimuli and tasks can lead to improved performance, if the anticipated situation occurs, while expectation mismatch can lead to less efficient processing. Researchers have used methodological approaches that rely on either self-generated expectations (predictions) or cue-induced expectations to investigate expectation mismatch effects. Differentiating these two types of expectations for different contents of expectation such as stimuli, responses, task sets and conflict level, we review evidence suggesting that self-generated expectations lead to larger facilitating effects and conflict effects on the behavioral and neural level - as compared to cue-based expectations. On a methodological level, we suggest that self-generated as compared to cue-induced expectations allow for a higher amount of experimental control in many experimental designs on expectation effects. On a theoretical level, we argue for qualitative differences in how cues vs. self-generated expectations influence performance. While self-generated expectations might generally involve representing the expected event in the focus of attention in working memory, cues might only lead to such representations under supportive circumstances (i.e., cue of high validity and attended).

The role of inhibition in the regulation of sequential action.

We investigated the regulation of sequential action using a new paradigm. Participants learned a sequence of seven stimulus categories and then monitored for them during successive displays. All displays were instances of these categories, presented in pseudorandom order. On each trial, participants monitored for an instance of Category 1, pressed a key on a computer keyboard, then monitored for an instance of Category 2, pressed a key on the keyboard, and so on for all seven categories. Thus, a perfect trial contained exactly seven responses. Intrusion errors were classified as a function of ordinal distance from the current serial position (n). Fewer intrusion errors were made at near serial positions than at far ones, suggesting a gradient of lateral inhibition. In addition, more intrusions were made on n + 1 categories than n - 1 categories, suggesting greater availability of intended than completed goals. In accord with current models of sequential action, the results indicate lateral and self-inhibition as important mechanisms in regulation of sequential action.

Long-term effects of aerobic exercise on psychological outcomes.

BACKGROUND: Although the literature on increased physical fitness and psychological outcomes has grown large, a number of methodological limitations remain unaddressed. The present study was designed to address a number of these limitations while examining the short- and long-term psychological effects following completion of a 12-week aerobic fitness program using bicycle ergometry (and confirmed increases in fitness). METHOD: Following completion of a 12-week aerobic fitness program (and through 12 months of follow-up), 82 adult participants completed the Beck Depression Inventory, Profile of Mood States, State-Trait Anxiety Inventory, and the Tennessee Self-Concept Scale. Physiological measures used to assess changes in aerobic fitness were maximal work load, submaximal heart rate at a standard work load, predicted maximum oxygen uptake, and resting heart rate. RESULTS: Exercise participants experienced a positive fitness change and psychological improvement over the initial 12-week program compared to a control group. At 1 year follow-up, physiological and psychological benefits remained significantly improved from baseline. CONCLUSIONS: Overall, results indicate that exercise-induced increases in aerobic fitness have beneficial short-term and long-term effects on psychological outcomes. We postulate that participants in the exercise group did not increase the amount of weekly exercise they performed over the 12-month follow-up period and thus the maintenance of the psychological improvements occurred concurrent with equal or lesser amounts of exercise.

Composition during serial learning: a serial position effect.

Composition is a computational learning mechanism that merges serially performed elementary processes into hierarchically organized knowledge structures. The main goals of this research were to explore (a) the role of serial position in composition and (b) the relation between degree of composition and explicit serial recall in serial learning. In 3 experiments, Ss performed a rule-based serial reaction time task in which they had to categorize a sequence of 12 stimuli shown simultaneously on a video monitor. A procedure based on the comparison of reaction times to random sequences and a repeating sequence identified a serial position effect of composition that was, however, moderated by Ss' explicit, postexperimental recall of the repeating sequence. A production-system-based computational model of composition is described that qualitatively reproduces the empirical findings. Implications for the mechanisms governing serial learning are discussed.

Effects of presentation rate and individual differences in short-term memory capacity on an indirect measure of serial learning.

In three experiments, we studied the relation between degree of implicit learning and two aspects of short-term memory: (1) the activation level of the to-be-learned information, and (2) individual differences in short-term memory capacity. In all the experiments, we used the Nissen and Bullemer (1987) serial reaction time paradigm or a modification thereof. The effects of activation level were assessed by experimentally manipulating the rate of presentation. Individual differences in short-term memory capacity were assessed via traditional span measures. The experiments demonstrated that the rate of presentation reliably affected an indirect measure of learning (i.e., response time) under both incidental and intentional task instructions and under both single-task and dual-task conditions. Short-term memory span was reliably related to the indirect measure of learning only in some experimental conditions. The findings represent important constraints for models of implicit serial learning and are discussed within a general framework for understanding implicit learning and memory.

Simple and complex mental subtraction: strategy choice and speed-of-processing differences in younger and older adults.

Thirty-six younger adults (10 male, 26 female; ages 18 to 38 years) and 36 older adults (14 male, 22 female; ages 61 to 80 years) completed simple and complex paper-and-pencil subtraction tests and solved a series of simple and complex computer-presented subtraction problems. For the computer task, strategies and solution times were recorded on a trial-by-trial basis. Older Ss used a developmentally more mature mix of problem-solving strategies to solve both simple and complex subtraction problems. Analyses of component scores derived from the solution times suggest that the older Ss are slower at number encoding and number production but faster at executing the borrow procedure. In contrast, groups did not appear to differ in the speed of subtraction fact retrieval. Results from a computational simulation are consistent with the interpretation that older adults' advantage for strategy choices and for the speed of executing the borrow procedure might result from more practice solving subtraction problems.

Effects of practice on component processes in complex mental addition.

Two experiments examined the effects of task practice on the speed of executing the component processes underlying the mental solution of complex addition problems. Componential analyses of Ss' response times in Experiment 1 demonstrated that the component process of carrying was reliably affected by amount of task practice. In contrast, the component processes of encoding single digits and of retrieving correct columnar answers from long-term memory appeared not to have been affected by amount of task practice. Computational feasibility checks indicated that the specificity of the practice effects could be explained by 2 distinct learning mechanisms: strengthening and composition. Results of Experiments 2A and 2B favor a composition explanation. We conclude that the differential practice effects in Experiment 1 are probably due to differential composition of component processes underlying complex mental addition.