Human behaviour in a continuous decision making task adapts to the overall statistics of the sensory environment, and these adaptations are also reflected in changes in neural responses to incoming sensory evidence.

Motor signs of Parkinson’s disease such as tremor and bradykinesia are independently expressed and exhibit distinct signatures of neural activity that can independently decoded from subthalamic and cortical recordings using interpretable machine learning.

Mnemonic mechanisms of differentiation and integration within the medial temporal lobe occur concurrently during the learning of local and global environmental knowledge.

Six- to twelve-month old infants, who have little linguistic or object experience, classify objects by relying on a invariant representation of global shape known as the shape skeleton.

When a common error drives parallel implicit and explicit learning systems, increases in the explicit response will suppress implicit adaptation.

Visual input to prefrontal cortex preferentially targets neurons with both sensory and motor properties, and the synaptic efficacy of these inputs is facilitated by working memory.

During a sensorimotor perturbation, task outcome may serve as a gain on implicit adaptation or provide a distinct error signal for a second, independent implicit learning process.