A novel analysis of neural activity recorded in monkeys performing a “brain-machine interface” task reveals that a mismatch between motor effectors and the brains’ internal models of those effectors can explain a substantial portion of movement errors.

The rhythmicity in upper-limb tracking movements and associated population dynamics in primary motor cortex is explained by a feedback controller incorporating optimal state estimation.

Evidence of an interaction between expected reward size and visual cortical microstimulation indicates that expected reward can affect sensory representations.

Visual information (optic flow) can be used to discount self-generated rotations and aid in the accurate representation of heading.

Neurons in the amygdala, a brain system usually associated with emotion, track progress during sequential reward-directed choices according to an internal plan in Rhesus macaques.

Electrode recordings and optogenetics reveal that the cerebellum can modulate its response to error signals from the brainstem during motor learning.

To establish a trade-off between the speed and accuracy of a decision, neurons in lateral intraparietal cortex combine evidence bearing on the decision with a signal that incorporates the cost of time into the decision-making process.

Recent advances in technology now make it possible to carry out biomedical research on animals living in the wild, or captive animals living in naturalistic conditions.

A combination of invasive and non-invasive techniques has allowed researchers to take a closer look at the two major neural pathways that connect the amygdala and the prefrontal cortex.

Gamma-band synchronization behavior in area V1 was predicted by weakly coupled oscillator principles.