fMRI evidence for distinct hierarchical alterations in intrinsic neural timescales for different positive symptoms of schizophrenia support hierarchical perceptual-inference models of psychosis and suggest local increases in excitation-inhibition ratio.

Hierarchical transformations of visual representations, saccade-related activity, and sensorimotor associations occur in parallel at the juncture of visual and parietal cortex.

Invasive electrophysiological recording measures neuronal transmembrane current timescales across human cortex, which lengthens from sensory to association regions, follows variations in ion channel expressions, and alters with behavior and aging.

The selective effect of local inhibition on diffuse patterns of brain connectivity can be accounted for by an intrinsic hierarchical ordering of cortical timescales.

Neural computations necessary for efficient control of saccades capture the phenomenon of saccadic suppression, which suggests that neural resources are shared for perception and control.

The ongoing stream of information that comes in through our senses is segmented into distinct neural states at each level of the cortical hierarchy, which underpins our experience of distinct events.

An anatomically constrained computational model of the macaque cortical network demonstrates the emergence of large-scale distributed patterns of mnemonic activity sustained by long-range cortico-cortical interactions.

Distortion and elimination of limb visual feedback affects low-level stretch reflex control, indicating the involvement of a high-level and multimodal representation of the limb state in orchestrating hierarchical sensorimotor control.

Learning to reach in the sensorimotor loop, and the required neural dynamics, can be potentially explained by simple principles.

A novel machine learning approach improves quantitative comparisons of mouse and human brains using spatial transcriptomics data sets.