Cognitive impairment measured by event-related potentials during early and late postoperative period following intravenous or inhalation anaesthesia.

Objective: This study investigated modification in cognitive function following inhalation (IA) and total intravenous (TIVA) anaesthesia measured using auditory ERPs (Event Related Potentials).

Methods: Auditory ERPs examination with N1, P3a and P3b component registration was carried out one day before surgery (D-1) and on the first (D+1), sixth (D+6) and 42nd (D+42) days after surgery. Results were compared between two anaesthetic groups.

Stacked Autoencoders for the P300 Component Detection.

Novel neural network training methods (commonly referred to as deep learning) have emerged in recent years. Using a combination of unsupervised pre-training and subsequent fine-tuning, deep neural networks have become one of the most reliable classification methods. Since deep neural networks are especially powerful for high-dimensional and non-linear feature vectors, electroencephalography (EEG) and event-related potentials (ERPs) are one of the promising applications.

Developmental coordination disorder in children - experimental work and data annotation.

Background: Developmental coordination disorder (DCD) is described as a motor skill disorder characterized by a marked impairment in the development of motor coordination abilities that significantly interferes with performance of daily activities and/or academic achievement. Since some electrophysiological studies suggest differences between children with/without motor development problems, we prepared an experimental protocol and performed electrophysiological experiments with the aim of making a step toward a possible diagnosis of this disorder using the event-related potentials (ERP) technique. The second aim is to properly annotate the obtained raw data with relevant metadata and promote their long-term sustainability.

Software and hardware infrastructure for research in electrophysiology.

As in other areas of experimental science, operation of electrophysiological laboratory, design and performance of electrophysiological experiments, collection, storage and sharing of experimental data and metadata, analysis and interpretation of these data, and publication of results are time consuming activities. If these activities are well organized and supported by a suitable infrastructure, work efficiency of researchers increases significantly. This article deals with the main concepts, design, and development of software and hardware infrastructure for research in electrophysiology.