Neuroscience

Researchers have discovered a surprising mathematical relationship in the brain’s representations of sensory information, with possible applications to AI research.

Beneath our awareness, the brain lets certain kinds of stimuli automatically capture our attention by lowering the priority of the rest.

A brain circuit that suppresses distracting sensory information holds important clues about attention and other cognitive processes.

Mathematicians and neuroscientists have created the first anatomically accurate model that explains how vision is possible.

Researchers found that elongating certain brain signals in rats improved their memory. The work revealed a new property to look out for in the hunt for “biomarkers” of learning.

To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes.

New experimental results simultaneously advance and challenge the theory that the brain’s network of neurons balances on the knife-edge between two phases.

Your expectations shape and quicken your perceptions. A new model that explains how that happens also suggests it’s time to update theories about sensory perception and decision making.

Two new studies show that the brain’s navigation system changes how it represents physical space to reflect personal experience.