Niels Trusbak Haumann

This study finds that interoceptive ability is positively linked to singing expertise and musical competence, with professional singers showing higher interoceptive accuracy and non-singers with higher interoception performing better in singing accuracy.

The paper measures cortical evoked potentials to naturalistic music in cochlear implant users, finding that experience correlates with P2 amplitude and perceived musical quality.

The paper investigates brain mechanisms for predicting and error processing in music, finding distinct neural regions for local acoustic and cognitive priors, with enhanced involvement in musicians.

The paper investigates how predictive processes in the brain respond to high uncertainty in musical contexts using MMN and behavioral experiments, finding robust MMN responses in atonal music but better behavioral performance in tonal contexts.

This paper introduces a machine-learning pipeline for analysing MEG data to detect beat-related oscillatory power modulation, showing clearer patterns than traditional methods.

The paper investigates rapid brain mechanisms for encoding and predicting complex temporal sound sequences using MEG data from 68 participants.

This study examines the effect of COMT Val158Met polymorphism on neural responses to deviant auditory stimuli using MEG in healthy participants.

This paper validates Spike-density Component Analysis (SCA) for isolating neural components in children's auditory ERPs, showing superior accuracy with SCA-HSAC over other methods.

This paper introduces a theory of stochastic spike timing and a method called SCA to accurately isolate neural sources in MEG/EEG data, outperforming PCA and ICA in separating overlapping brain signals.