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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.
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.
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.
Catherine Dulac is overturning preconceptions about “male” and “female” instincts and opening new avenues to treating postpartum depression.
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