Biomedical subjects

Lael J Schooler

Publications and source records attributed to Lael J Schooler.

4 recordsLinked to original sources

PubMed2006

Simple predictions fueled by capacity limitations: when are they successful?

Counterintuitively, Y. Kareev, I. Lieberman, and M. Lev (1997) found that a lower short-term memory capacity benefits performance on a correlation detection task. They assumed that people with low short-term memory capacity (low spans) perceived the correlations as more extreme because they relied on smaller samples, which are known to exaggerate correlations. The authors consider, as an alternative hypothesis, that low spans do not perceive exaggerated correlations but make simpler predictions. Modeling both hypotheses in ACT-R demonstrates that simpler predictions impair performance if the environment changes, whereas a more exaggerated perception of correlation is advantageous to detect a change. Congruent with differences in the way participants make predictions, 2 experiments revealed a low capacity advantage before the environment changes but a high capacity advantage afterward, although this pattern of results surprisingly only existed for men.

Adult↗

PubMed2006

Why you think milan is larger than modena: neural correlates of the recognition heuristic.

When ranking two alternatives by some criteria and only one of the alternatives is recognized, participants overwhelmingly adopt the strategy, termed the recognition heuristic (RH), of choosing the recognized alternative. Understanding the neural correlates underlying decisions that follow the RH could help determine whether people make judgments about the RH's applicability or simply choose the recognized alternative. We measured brain activity by using functional magnetic resonance imaging while participants indicated which of two cities they thought was larger (Experiment 1) or which city they recognized (Experiment 2). In Experiment 1, increased activation was observed within the anterior frontomedian cortex (aFMC), precuneus, and retrosplenial cortex when participants followed the RH compared to when they did not. Experiment 2 revealed that RH decisional processes cannot be reduced to recognition memory processes. As the aFMC has previously been associated with self-referential judgments, we conclude that RH decisional processes involve an assessment about the applicability of the RH.

Adult↗

PubMed2005

How forgetting aids heuristic inference.

Some theorists, ranging from W. James (1890) to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies on systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds.

Cognition↗

PubMed2005

Efficiently measuring recognition performance with sparse data.

We examine methods for measuring performance in signal-detection-like tasks when each participant provides only a few observations. Monte Carlo simulations demonstrate that standard statistical techniques applied to a d' analysis can lead to large numbers of Type I errors (incorrectly rejecting a hypothesis of no difference). Various statistical methods were compared in terms of their Type I and Type II error (incorrectly accepting a hypothesis of no difference) rates. Our conclusions are the same whether these two types of errors are weighted equally or Type I errors are weighted more heavily. The most promising method is to combine an aggregate d' measure with a percentile bootstrap confidence interval, a computer-intensive nonparametric method of statistical inference. Researchers who prefer statistical techniques more commonly used in psychology, such as a repeated measures t test, should use gamma (Goodman & Kruskal, 1954), since it performs slightly better than or nearly as well as d'. In general, when repeated measures t tests are used, gamma is more conservative than d': It makes more Type II errors, but its Type I error rate tends to be much closer to that of the traditional .05 alpha level. It is somewhat surprising that gamma performs as well as it does, given that the simulations that generated the hypothetical data conformed completely to the d' model. Analyses in which H--FA was used had the highest Type I error rates. Detailed simulation results can be downloaded from www.psychonomic.org/archive/Schooler-BRM-2004.zip.

Computer Simulation↗