Decoding auditory working memory content from intracranial high frequency activity in humans

How the human brain maintains information in working memory (WM), a process critical for all our goal-directed function, has been debated for decades. Classic neurophysiological models, which argue that WM is maintained via persistent content-specific “delay activity”, have been challenged by alternative ideas suggesting a combination of dynamic activity patterns and activity-silent mechanisms. Here, making use of human intracranial stereo-EEG (sEEG) recordings and machine learning techniques, we tested understudied auditory WM in multiple cortical and subcortical brain areas. Neuronal activity was quantified as broadband high frequency activity (HFA, 70-190 Hz), which has been shown to be highly correlated with multiunit activity of neuron populations. Our multivariate pattern analysis (MVPA) results, validated via robust non- parametric permutation testing, show that information can be decoded from multiple brain areas including frontal and auditory areas as well as hippocampus. However, the recording sites with high decoding accuracies were not accompanied by statistically significant increases in HFA power. In contrast, HFA power was reduced relative to the pre-trial period in many in frontal, auditory cortex, and hippocampal sEEG recording sites. These results are in line with the hypothesis that WM maintenance can be supported by highly dynamic activity silent processes, rather than via persistent activity only. ### Competing Interest Statement The authors have declared no competing interest.