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… collaboration and mentorship of early-career researchers will live on in SURFiN, Picchini Schaffer says.

Krishna Shenoy set out to develop workable prosthetics for profoundly paralyzed people. Along the way, he helped usher in a novel framework for deciphering neural activity.

A recent wave of research is using pharmacology to test new hypotheses of neural coding and cognition.

The ability to record neural activity from populations of single cells in the human brain is expanding. What will these efforts reveal about neural dynamics?

Flexible electrodes offer an alternative approach to silicon probes for high-density recordings. Both methods face challenges in how to best process data.

Neuroscientists are uncovering patterns of neuron population activity during different movements and in new places, but why these dynamics exist is still a mystery

Three new methods to identify hidden structure in neural activity.

New research suggests that under certain conditions, localizing neural activity to specific cells is unnecessary.

A new method for analyzing neural dynamics reveals that two regions involved in movement exhibit different patterns of activity, suggesting they perform different computations.

The brain represents different contexts by confining neural activity to parallel landscapes.

By analyzing neural activity in real time, scientists can almost instantaneously predict the likelihood that an animal will make a certain choice or change its mind.

Insights into how dopamine directs learning and new techniques for imaging and tracing cells were just some of the advances described at the third annual gathering of the …

How many cells do neuroscientists need to monitor to get an accurate picture of what the brain is doing?

New insights into how the brain makes decisions, recognizes novel objects and controls attention were among many areas discussed at the second annual gathering of the Simons Collaboration …

A new understanding of how motor neurons fire should lead to a dramatic increase in performance of brain-machine interfaces