Spatial accuracy of grid cell firing correlates with the slope of the local field potential theta frequency vs. running speed relationship and integrates velocity signals over past time.

For analyzing time-dependent patch-clamp or patch-clamp fluorometry data of ion channels in terms of Markovian models, the superiority of Bayesian filtering with respect to traditional deterministic approaches is demonstrated enabling more reliable quantification of the parameters.

Single units in a deep convolutional neural network trained for image classification develop shape selectivity that is similar to that found in the primate visual cortex.

A computational model shows that it's possible to learn and replay extended temporal sequences in a network of spiking neurons with a modular architecture and a biologically realistic learning rule.

Revealing two distinct brain systems linked to obesity, this research illuminates the intricate relationship between obesity, brain microstructure and genetics with potential implications for treatment and prevention.

A mathematical modelling approach to understanding zebrafish stripe pattern formation exemplifies a biological rule-set sufficient to generate wild-type and a diverse range of mutant patterns.

A computational study quantifies how macroscopic grid-like representations may emerge in the human brain using different hypotheses and navigation patterns, indicating the need to further characterize properties of grid cells.

Integrated multi-scale, multi-tool approach to design novel 'evolution drugs' which can delay the emergence of antibiotic resistance by constraining bacterial evolutionary escape strategies.

Microbial cells optimally structure their proteomes in order to mutually maximize metabolism and translation, as established by an extensive comparison between data and a low-dimensional model of cellular physiology.