Neural correlates of somatosensory target detection are restricted to secondary somatosensory cortex, whereas activity in insular, cingulate, and motor regions reflects stimulus uncertainty and overt reports.
A well-trained deep learning neural network can outperform and can potentially assist expertly trained embryologists in selecting embryos based on their implantation potential, even amongst high-quality euploid blastocyst embryos.
The genomic architecture of allopatric species is a mosaic of many conserved genes and a few adaptive ones, reflecting balance between conservation of ancestral functions and evolution of new features.
Connectomic analysis identifies the complex circuits of a visual motion-sensing neuron that qualify them to generate direction-selective motion sensing signals using both Hassenstein-Reichardt and Barlow-Levick models.
A computational model shows that natural selection can cause populations to evolve a distinctive population-level phenotype: the ability to transition between collective states in response to the environment.