Slower is not always better: Response-time evidence clarifies the limited role of miserly information processing in the Cognitive Reflection Test

We report a study examining the role of `cognitive miserliness' as a determinant of poor performance on the standard three-item Cognitive Reflection Test (CRT). The cognitive miserliness hypothesis proposes that people often respond incorrectly on CRT items because of an unwillingness to go beyond default, heuristic processing and invest time and effort in analytic, reflective processing. Our analysis (N = 391) focused on people's response times to CRT items to determine whether predicted associations are evident between miserly thinking and the generation of incorrect, intuitive answers. Evidence indicated only a weak correlation between CRT response times and accuracy. Item-level analyses also failed to demonstrate predicted response time differences between correct analytic and incorrect intuitive answers for two of the three CRT items. We question whether participants who give incorrect intuitive answers on the CRT can legitimately be termed cognitive misers and whether the three CRT items measure the same general construct

Spatially constrained adaptive rewiring in cortical networks creates spatially modular small world architectures

A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture