Human tilt estimation in natural scenes is predicted by an image-computable Bayes optimal model that is grounded in the statistics of natural images and scenes.
Yeast cells can tune the modality of a nutrient response on physiological and evolutionary timescales by adapting the expression and sequence of a sensor protein.
Cell biological features are subject to stochastic forces of mutation and random genetic drift, which together cause lineages exposed to identical selection pressures to diverge, and mean phenotypes to deviate from expectations under optimizing selection.
A technique called meta3C provides an elegant and integrated approach to metagenomic analysis by allowing the de novo assembly, scaffolding and 3D characterization of unknown genomes from a complex mix of species
Yves Boubenec, Jennifer Lawlor ... Bernhard Englitz
Psychophysics experiments and EEG recordings reveal that people's performance in detecting unexpected changes in complex auditory scenes can be modeled as a process of sensory evidence accumulation.
Neural network modeling shows that hierarchical application of the simple computational principle of predicting future sensory input from its past can capture features of visual motion processing from the retina to the visual cortex.
In the processing of spoken narratives, bottom-up acoustic cues and top-down linguistic knowledge separately contribute to neural construction of linguistic units.
In scene-selective occipital cortex and within 200 ms of processing, visual inputs are sorted according to their typical spatial position within a scene.
The visual information walkers use for path selection during locomotion was revealed by analysis of a three-dimensional numerical representation of the natural terrain.
Hannes P Saal, Michael A Harvey, Sliman J Bensmaia
Signals from different tactile submodalities are integrated optimally to culminate in cortical responses whose rate and timing conveys stimulus information.
