Parker L. Kotlarz

The paper characterizes the auditory cortex's function through dynamic coactivation patterns identified in fMRI data, showing consistency between resting-state and task conditions.

The paper maps individual auditory cortex subareas using functional network analysis and fMRI, showing high intraindividual reproducibility and meaningful interindividual variability.

The paper decodes auditory working memory content from EEG aftereffects of auditory-cortical TMS using multivariate pattern analysis.

This study uses multilayer network analysis to examine functional connectivity across cortical depths in resting-state 7T fMRI, finding that superficial layers dominate information transfer while deeper layers drive clustering, particularly in frontotemporal and limbic regions.

This study uses intracranial EEG and machine learning to show dynamic, activity-silent mechanisms maintain auditory working memory in humans.

The paper compares auditory and visual aspects of multisensory working memory using bimodally matched stimuli and finds auditory matching is more accurate than visual in certain conditions.