Multivariate analyses of human electrophysiological recordings revealed that the brain represents unexpected visual stimuli with greater fidelity than expected stimuli which arose independently of simple habituation arising from repetition.
Hybrid brain network models predict neurophysiological processes that link structural and functional empirical data across scales and modalities in order to better understand neural information processing and its relation to brain function.
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.
Direct measure of neural and hemodynamic activity in the developing human brain shows that the insula is a major source of transient bursting events that are critical for cortical maturation.
Non-REM sleep is essential in the restoration of initial motor memory trace and gradual reorganization of newly-learned information underlying human procedural memory consolidation.
The P300, an electroencephalography (EEG) component known to be evoked by surprising events, predicts learning in a bidirectional manner that depends critically on the surrounding statistical context.
State anxiety alters the dynamics of beta oscillations during reward-dependent motor learning, thereby impairing proper updating of motor predictions when learning in unstable environments.