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Electroencephalography (EEG) is a method for monitoring electrical activity in the brain. It uses electrodes placed on or below the scalp to record activity with coarse spatial but high temporal resolution. EEG can be used in cognitive research or to diagnose conditions such as epilepsy and sleep disorders.
Whether connectivity in white matter detected by functional MRI relates to underlying electrophysiological synchronization is unclear. Here, the authors show that blood-oxygenation-level-dependent (BOLD) functional connectivity and intracranial stereotactic-electroencephalography (SEEG) connectivity are correlated across a wide range of frequency bands.
Using machine learning, Zhang et al. identify EEG signature to predict psychotherapy outcomes in PTSD, paving the way towards the development of scalable biomarkers.
A fast and accurate time–frequency analysis is challenging for many applications, especially in the current big data era. A recent work introduces a fast continuous wavelet transform that effectively boosts the analysis speed without sacrificing the resolution of the result.
