Neurons

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.

When animals move through 3D spaces, the neat system of grid cell activity they use for navigating on flat surfaces gets more disorderly. That has implications for some ideas about memory and other processes.

Computational neuroscientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the complexity of single brain cells.

A temporal pattern of activity observed in human brains may explain how we can learn so quickly.

Mitochondria appear to communicate and cooperate with one another, both within and between cells. Biologists are only just beginning to understand how and why.

Eve Marder’s research into the plasticity and resilience of nervous systems finds universal principles guiding life’s responses to stress.

Advances in brain-computer interface technology are impressive, but we’re not close to anything resembling mind control.

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.

While the study of the SARS-CoV-2 virus was the most urgent priority, biologists also learned more about how brains process information, how to define individuality and why sleep deprivation kills.