Deep Learning Artificial Intelligence tools can be developed to accurately identify cell divisions during development and wound repair of epithelial tissue.

A Bayesian model of phase angles illustrates a novel approach to the analysis of phase coherence in frequency-tagged experiments.

Across individuals of a mouse population, brain regions volumes scaled to accommodate the same amount of cells, but left hemisphere cortical regions were denser than right, and several regions of the limbic system were more pronounced in either sex.

The numerous reports in support of action-value representation in the striatum are based on statistical analyses that are subject to two critical confounds and, thus, this long-held belief of striatal action-value representation should be retested using different experiments and analyses.

Environmental heterogeneity can dramatically reduce the efficacy of selection and alter the neutral evolutionary dynamics in microbial range expansions.

Measures of visuocortical activity during aversive generalization learning revealed sharpened representations of facial identity, reflecting inhibitory interactions between neuronal populations that represent facial features associated with threat versus safety.

The dynamics of neural responses during visual perception are best explained by a joint feedforward and recurrent architecture, which both maintains and broadcasts input features over time.

DNA fingerprinting by portable nanopore sequencing is a novel re-identification method with applications in (clinical) laboratories and biobanks.

Node of Ranvier length is similar at successive nodes along single myelinated CNS axons, but differs between axons, and could potentially be tuned to adjust the conduction velocity of each axon.

Single cell RNA sequencing reveals that mouse embryonic stem cells can be differentiated into the same terminal motor neuron state via distinct differentiation paths, one of which includes a surprising intermediate state not found in embryos.