Machine-learning algorithms tuned to detecting cancer DNA in the blood could pave the way for personalized cancer care.

An algorithm trained to move through a virtual environment spontaneously generated patterns of activity found in so-called grid neurons.

A map of neural networks in the striatum of the mouse brain reveals clues about psychiatric and movement disorders.

Software that can separate signals from noise brings neuroscientists a step closer to understanding neurons’ patterns of communication.

A new microscopy program requires no fluorescent markers to identify cell type, nuclei, and other characteristics.

Scientists are beginning to unravel the mechanisms behind the therapeutic effects of psychedelic drugs.

Understanding how hallucinogenic drugs affect different neural networks could shed light on their therapeutic potential.

The UCLA neurobiologist uses computational modeling, in vitro electrophysiology, and human psychophysics experiments to explore how neurons and the brain as a whole perceive and respond to time.