Multi-area recordings reveal how communication between two songbird brain areas conveys a top-down bias that adaptively modifies ongoing singing to support context-specific vocal learning.

Neural activity in the visual system is increased in different layers of the neocortex for bottom-up and top-down modulations.

Perceptual learning is specific because of the absence of bottom-up stimulation and top-down modulation at the untrained conditions.

Both bottom-up and top-down processing are involved in the occipital-temporal face network, with the top-down modulation more extensively engaged when available information is sparse in the face images.

Optogenetic and electrophysiological experiments show how a behaviorally relevant 'feedback' pathway from auditory cortex controls neural activity in the inferior colliculus, an auditory midbrain region important for processing complex time-varying sounds such as speech.

A new analysis algorithm (DISC) enables accurate analysis of data from high-throughput single-molecule paradigms and reveals a non-cooperative binding mechanism of cyclic nucleotide-binding domains from HCN ion channels.

Everyday soundscapes dynamically engage attention towards target sounds or salient ambient events, with both attentional forms engaging the same fronto-parietal network but in a push-pull competition for limited neural resources.

A computational model reveals how response properties of category-selective regions in the visual cortex reflect both bottom-up stimulus-driven signals and top-down attentional signals from the parietal cortex.

Computational simulations and mathematical derivations reveal why the response of neural populations to external modulation is sometimes reversed with respect to what intuition would lead to believe in cortical circuits with multiple types of inhibitory neurons.

A top-down circuit generating from the prelimbic cortex and projecting to the paraventricular nucleus of the thalamus mediates individual differences in cue-elicited responding by affecting subcortical dopamine-dependent incentive learning.