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.

Cerebellar functional regions follow a gradual organization, which progresses from primary (motor) to transmodal (Default Mode Network) regions, and a secondary axis extends from task-unfocused to task-focused processing.

Mere exposure to scenes with statistical contingencies in the visual or haptic modality alone allows participants to decompose scenes into object-like multimodal representations.

Default mode network and visual cortex are connected via two parallel pathways that differentially respond to the processing of visual scenes and semantic information about objects, reflecting domain-specific organisation.

A computational model shows that it's possible to learn and replay extended temporal sequences in a network of spiking neurons with a modular architecture and a biologically realistic learning rule.

Anatomical projections from sensory, motor, and association cortex to the cerebellum are precisely mapped, including cortical-precerebellar connections and terminal organization, providing insight into how the cerebellum may utilize cortical information.

Neural populations in PPC dynamically represent motor-like and then sensory-like aspects of brain–computer interface finger movements with a representational structure that matches able-bodied individuals.

THINGS-data reflects three large-scale neuroimaging and behavioral datasets of object processing in humans, comprising densely sampled functional MRI and magnetoencephalographic recordings, as well as 4.70 million similarity judgments in response to thousands of photographic images for up to 1854 objects.

Electrophysiology identifies a population of fan-shaped body neurons that encode airflow in two directions relative to the fly midline and whose silencing disrupts proper orientation to airflow.

Classical theoretical approaches to studying the cerebellar cortex are generalized to a broader set of learning tasks, revealing that the optimal value for the sparsity of granule cell activity is task-dependent.