Autism spectrum disorder variation as a computational trade-off via dynamic range of neuronal population responses.

Individuals diagnosed with autism spectrum disorder (ASD) show neural and behavioral characteristics differing from the neurotypical population. This may stem from a computational principle that relates inference and computational dynamics to the dynamic range of neuronal population responses, reflecting the signal levels for which the system is responsive. In the present study, we showed that an increased dynamic range (IDR), indicating a gradual response of a neuronal population to changes in input, accounts for neural and behavioral variations in individuals diagnosed with ASD across diverse tasks.

Environmental susceptibility for all: A data-driven approach suggests individual differences in domain-general and domain-specific patterns of environmental susceptibility.

How we are influenced by our environment is a fundamental question in developmental science. Theories and empirical research have claimed that some individuals are susceptible to environmental influences and others are much less susceptible. The present study addressed four questions: (1) Is environmental susceptibility a continuous or categorical construct? (2) Is environmental susceptibility unidimensional (i.

Mind-bending geometry: Children's and adults' intuitions about linearity on spheres.

Humans appear to intuitively grasp definitions foundational to formal geometry, like definitions that describe points as infinitely small and lines as infinitely long. Nevertheless, previous studies exploring human's intuitive natural geometry have consistently focused on geometric principles in planar Euclidean contexts and thus may not comprehensively characterize humans' capacity for geometric reasoning. The present study explores whether children and adults can reason about linearity in spherical contexts.

Adaptive search space pruning in complex strategic problems.

People have limited computational resources, yet they make complex strategic decisions over enormous spaces of possibilities. How do people efficiently search spaces with combinatorially branching paths? Here, we study players' search strategies for a winning move in a "k-in-a-row" game. We find that players use scoring strategies to prune the search space and augment this pruning by a "shutter" heuristic that focuses the search on the paths emanating from their previous move.