Filters are commonly used to reduce noise and improve data quality. Filter theory is part of a
scientist's training, yet the impact of filters on interpreting data is not always fully appreciated …

After having been in routine use for about half a century, neonatal EEG is currently facing
unprecedented challenges in assessing and monitoring brain function during intensive care …

Abstract Recording infraslow brain signals (< 0.1 Hz) with microelectrodes is severely
hampered by current microelectrode materials, primarily due to limitations resulting from …

In vivo electronic monitoring systems are promising technology to obtain biosignals with
high spatiotemporal resolution and sensitivity. Here we demonstrate the fabrication of a …

Electric Vehicles (EVs) are increasing in numbers at a rapid rate. In this phase change of the
automobile sector for charging the electrical vehicles is one major barrier. Also, due to the …

This is the final paper in a Comments and Controversies series dedicated to “The
identification of interacting networks in the brain using fMRI: Model selection, causality and …

Graphene active sensors have demonstrated promising capabilities for the detection of
electrophysiological signals in the brain. Their functional properties, together with their …

Abstract Electroencephalography (EEG), magnetoencephalography (MEG) and related
techniques are prone to glitches, slow drift, steps, etc., that contaminate the data and …

The existence of the electrical activity of the brain (ie the electroencephalogram or EEG) was
discovered more than a century ago by Caton. After the demonstration that the EEG could be …

This study explores the possibility of noninvasively inducing long‐term changes in human
corticomotor excitability by means of a brain–computer interface, which enables users to …