Working memory is a mental storage system that keeps task-relevant information accessible for a brief span of time, and it is strikingly limited. Its limits differ substantially across people but are assumed to be fixed for a given person. Here we show that there is substantial variability in the quality of working memory representations within an individual. This variability can be explained neither by fluctuations in attention or arousal over time, nor by uneven distribution of a limited mental commodity. Variability of this sort is inconsistent with the assumptions of the standard cognitive models of working memory capacity, including both slot- and resource-based models, and so we propose a new framework for understanding the limitations of working memory: a stochastic process of degradation that plays out independently across memories.

The MemToolbox is a collection of MATLAB functions for modeling visual working memory. In support of its goal to provide a full suite of data analysis tools, the toolbox includes implementations of popular models of visual working memory, real and simulated data sets, Bayesian and maximum likelihood estimation procedures for fitting models to data, visualizations of data and fit, validation routines, model comparison metrics, and experiment scripts. The MemToolbox is released under the permissive BSD license and is available at http://memtoolbox.org.

Over the last ten years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgments of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries, and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods, correlate and rotate the dimension reduction solution.

Loud bangs, bright flashes, and intense shocks capture attention, but other changes--even those of similar magnitude--can go unnoticed. Demonstrations of change blindness have shown that observers fail to detect substantial alterations to a scene when distracted by an irrelevant flash, or when the alterations happen gradually [1-5]. Here, we show that objects changing in hue, luminance, size, or shape appear to stop changing when they move. This motion-induced failure to detect change, silencing, persists even though the observer attends to the objects, knows that they are changing, and can make veridical judgments about their current state. Silencing demonstrates the tight coupling of motion and object appearance.