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Infrastructure for Electrophysiology Research

JEŽEK, P., MOUČEK, R., NOVOTNÝ, J., PAPEŽ, V., ŘONDÍK, T. Infrastructure for Electrophysiology Research. Washington, 2014.
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Operation of electrophysiological laboratory, design and performance of electrophysiological experiments, collection, storage, management and sharing of experimental data and metadata, analysis and interpretation of these data/metadata, and final publication of results are time consuming activities. These activities need to be well organized and supported by a suitable infrastructure to increase work efficiency of researchers. The EEG/ERP Portal (EEGBase) is a web-based portal that enables community researchers to store, manage, share, download and search data and metadata from electrophysiological experiments. The internal data and metadata model progressively reflects the outcomes of the INCF Task Force on standards for sharing of electrophysiology data and the outcomes of the group developing Ontology for describing Experimental Neurophysiology (OEN). As a follow-up to EEGBase, a project of a personal electronic health record system using semantic web resources is being developed. Within the system we are expanding into new bio data domains (e.g. ECG, sleep data) and looks for non-trivial consequences across them. The system is based on openEHR archetypes. Whereas measured subjects are different (in general), a workflow for EEG/ERP signal processing is nearly identical for the same protocol. To be able to process a lot of electrophysiological data according to given workflows, Biosignal Processor is being developed. It is a solution for batch processing of electrophysiological data which allows to process and analyze them automatically. The hardware stimulator is a universal portable device providing a subset of often used software stimulation functions. By default, visual and simple audio stimuli for P300 experiments and VEP-based BCIs are supported. The device can also track reaction time separately or during stimulation.

Initiatives and projects for collaboration in neuroinformatics

MOUČEK, R., JEŽEK, P., MAUTNER, P. Initiatives and projects for collaboration in neuroinformatics. Olomouc, 2014.
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Sharing of electrophysiology data, related metadata, processing methods and workflows is one of the crucial tasks in neuroinformatics. International Neuroinformatics Coordinating Facility (INCF) develops and maintains computational infrastructure for neuroscientists and INCF Programs address infrastructural issues of high importance to the neuroscience community. The INCF program ?Standard for data sharing ? Electrophysiology Task Force? deals with collection of requirements for developing the data format that could be accepted and widely shared within the community. To enable collaboration through the sharing of neuroscience data, INCF also introduced the INCF Dataspace that associates data sources in a distributed system based on iRods solution. The Czech National Node for Neuroinformatics (CNNN) is currently focused on two main topics. The first one deals with higher reliability of interactions of human subjects, artificial systems and their alliances. Theoretical knowledge is applied in transportation area; relations between the components of the EEG alpha rhythmus and attention levels of relevant subjects are investigated. The Node also continues in building of complex hardware and software infrastructure for research in electrophysiology. A catalog server connected to INCF Dataspace and a node server for EEG/ERP domain were established. The EEG/ERP Portal (EEGBase) is a web-based system that enables researchers to store, manage, share, and process data and metadata from EEG/ERP experiments. The portal was registered as a neuroscience resource within the Neuroscience Information Framework (NIF). Off-line and mobile versions of the portal are also available. A programmable hardware stimulator that allows users to create various experiments and use the combined stimulation (acoustic and visual) was designed and developed. The stimulator is portable and can be connected to conventional equipment.

Developmental coordination disorder in children – experimental work and data annotation

MOUČEK, R., MAUTNER, P., BRŮHA, P., VAŘEKA, L., ČEPIČKA, L., HOLEČKOVÁ, I. Developmental coordination disorder in children ? experimental work and data annotation. Leiden, 2014.
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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 to make a step towards 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. The experimental protocol is based on auditory stimulation using the stimuli representing animals and their sounds: bleating goat (80% probability of occurrence), barking dog (5%), meowing cat (5%), meowing dog (5%), and barking cat (5%); 600 stimuli are used in total during the experimental session. The tested subjects were children of younger school age from elementary schools in Pilsen. All experiments were performed in a sound and electrically shielded booth placed in an electrophysiology lab. EEG/ERP activity was recorded using standard 10-20 international system with the reference electrode placed above the nose. The data were collected and annotated respecting the current outcomes of INCF Program on Standards for Data Sharing, Task Force on Electrophysiology and the group developing the Ontology for Experimental Neurophysiology (OEN, https://github.com/G-Node/OEN). The data with metadata will be stored in the EEGbase database (http://eegdatabase.kiv.zcu.cz/) after several conceptual and technological changes (deployment of noSQL database, changes in the user interface) in this web application.

Describing neurophysiology data and metadata with OEN, the Ontology for Experimental Neurophysiology

FRANC, Y. L., BANDROWSKI, A., BRŮHA, P., PAPEŽ, V., GREWE, J., MOUČEK, R., TRIPATHY, S. J., WACHTLER, T. Describing neurophysiology data and metadata with OEN, the Ontology for Experimental Neurophysiology. Leiden, 2014.
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OEN (the Ontology for Experimental Neurophysiology) has been developed to support the community in accurate and unambiguous description of both raw data and the associated metadata.

P3 Component Detection Using HHT Improvement of EMD with Additional Stopping Criteria

PROKOP, T., MOUČEK, R. P3 Component Detection Using HHT Improvement of EMD with Additional Stopping Criteria. In Brain Informatics and Health. Heidelberg: Springer, 2014. s. 100-110. ISBN: 978-3-319-09890-6 , ISSN: 0302-9743
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This paper describes improvement of the Hilbert-Huang transform (HHT) for detection of ERP components in the EEG signal. Time-frequency domain methods, such as the wavelet transform or matching pursuit, are commonly for this task. We used a modified Hilbert-Huang transform that allows the processing of quasi-stationary signals such as EEG. The essential part of the HHT is an Empirical Mode Decomposition (EMD) that decomposes signal into intrinsic mode functions (IMFs). We designed additional stopping criteria for better selection of IMFs in the EMD. These IMFs positively affect later computed instantaneous attributes and increase classification success. We tested the influence of additional stopping criteria on classification reliability using the real EEG data acquired in our laboratory. Our results demonstrated that we were able to detect the P3 component by using the HHT with additional stopping criteria more successfully than by using the original implementation of modified HHT, continuous wavelet transform and matching pursuit.

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