Integrating decades of small-scale experiments with human gene expression data provides a systems-level view of the coordinated molecular processes triggered by spinal cord injury, and their relationship to recovery.

New computer algorithms have allowed people with paralysis to achieve the highest reported typing performance using a brain-computer interface.

State anxiety alters the dynamics of beta oscillations during reward-dependent motor learning, thereby impairing proper updating of motor predictions when learning in unstable environments.

Neural ensemble activity in the human motor cortex contains dynamical structure that is independent of movement parameters and is not well-explained by current models.

Increasing microstimulation frequency in some regions of the human somatosensory cortex decreased the perceived intensity and evoked specific percepts, providing insight into cortical organization and sensory feedback approaches for brain–computer interfaces.

The response from discrete stages of the early auditory pathway can be measured by subtle manipulations to long-form natural speech stimuli paired with deconvolution analysis of electroencephalography data.

A model with a mixture of three different decision strategies is developed to characterize several atypical behavioral patterns of individuals with depression and anxiety in an uncertain reward environment.