Roman Moucek

Semantic framework for mapping object-oriented model to semantic web languages

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Event-related potential datasets based on a three-stimulus paradigm

BackgroundThe event-related potentials technique is widely used in cognitive neuroscience research. The P300 waveform has been explored in many research articles because of its wide applications, such as lie detection or brain-computer interfaces (BCI). However, very few datasets are publicly available. Therefore, most researchers use only their private datasets for their analysis. This leads to minimally comparable results, particularly in brain-computer research interfaces.Here we present electroencephalography/event-related potentials (EEG/ERP) data. The data were obtained from 20 healthy subjects and was acquired using an odd-ball hardware stimulator. The visual stimulation was based on a three-stimulus paradigm and included target, non-target and distracter stimuli. The data and collected metadata are shared in the EEG/ERP Portal.FindingsThe paper also describes the process and validation results of the presented data. The data were validated using two different methods. The first method evaluated the data by measuring the percentage of artifacts. The second method tested if the expectation of the experimental results was fulfilled (i.e., if the target trials contained the P300 component). The validation proved that most datasets were suitable for subsequent analysis.ConclusionsThe presented datasets together with their metadata provide researchers with an opportunity to study the P300 component from different perspectives. Furthermore, they can be used for BCI research.

Auditory ERPs in Children with Developmental Coordination Disorder

The present study aims to investigate and compare the auditory attention performance of children with developmental coordination disorder (DCD) and normally developing children (NDC) using cognitive evoked potentials (ERPs) in passive conditions. ERPs data showed that children with DCD have less ability to detect small physical differences between acoustic stimuli (no MMN response in DCD children) and have a reduced attentional engagement and stimulus evaluation of salient stimuli (a reduction of P3 amplitude in DCD children). The results of our study suggest that children with DCD do not only suffer from a visuospatial attention deficit as previous studies reported but also have auditory attention deficit.

Portal for research in electrophysiology — Data integration with neuroscience information framework

There is a problem with global search and data sharing. Our research group developed the EEG/ERP (electroencephalography, event-related potentials) portal; a system for storage and management of EEG/ERP resources - data, metadata, tools and materials related to EEG/ERP experiments. The EEG/ERP portal and existing solutions of data integration are presented. Authors registered the EEG/ERP portal as a source of neuroscience data and metadata within the world known project - Neuroscience Information Framework (NIF). Developed web services for harvesting EEG/ERP scenarios and experiments within NIF are presented.

EEG/ERP Portal -- Semantic Web Extension: Generating Ontology from Object Oriented Model

EEG/ERP domain is shortly introduced in this paper and system for storing and managing EEG/ERP experiments is presented. The system has been developed as a standalone web based portal. Authors’ plan to register this portal as a recognized data source requires providing domain ontology. Authors investigate transformation of data from the system (data in relational database) automatically. Several existing tools were tested and their integration and modification are presented.

Event-related potential data from a guess the number brain-computer interface experiment on school children

Guess the number is a simple P300-based brain-computer interface experiment. Its aim is to ask the measured participant to pick a number between 1 and 9. Then, he or she is exposed to corresponding visual stimuli and experimenters try to guess the number thought while they are observing event-related potential waveforms on-line. 250 school-age children participated in the experiments that were carried out in elementary and secondary schools in the Czech Republic. Electroencephalographic data from three EEG channels (Fz, Cz, Pz) and stimuli markers were stored. Additional metadata about the participants were collected (gender, age, laterality, the number thought by the participant, the guess of the experimenters, and various interesting additional information). Consequently, we offer the largest publicly available odd-ball paradigm collection of datasets to neuroscientific and brain-computer interface community.

Framework for automatic generation of graphical layout compatible with multiple platforms

Most data management systems include a database in the backend to store data and the associated metadata and a web-based user interface to access and modify the data/metadata. User interfaces are specifically tailored for representing a unique database structure and cannot be easily reused for other database structure. Furthermore the generated web-based layouts are often not compatible for other platform such as desktop applications or mobile devices. We are proposing here a general framework for designing a graphical layout compatible with different platforms including mobile devices and independent of the database structure. This framework is based on a model-driven approach using annotations of database entities that will be used to create desired layouts. A use case study is presented on a database designed for neuroscience experiments.

PROCESSING AND CATEGORIZATION OF CZECH WRITTEN DOCUMENTS USING NEURAL NETWORKS

The Kohonen Self-organizing Feature Map (SOM) has been developed for clustering input vectors and for projection of continuous high-dimensional signal to discrete low-dimensional space. The application area, where the map can be also used, is the processing of text documents. Within the project WEBSOM, some methods based on SOM have been developed. These methods are suitable either for text documents information retrieval or for organization of large document collections. All methods have been tested on collections of English and Finnish written documents. This article deals with the application of WEBSOM methods to Czech written documents collections. The basic principles of WEBSOM methods, transformation of text information into the real components feature vector and results of documents classification are described. The Carpenter-Grossberg ART-2 neural network, usually used for adaptive vector clustering, was also tested as a document categorization tool. The results achieved by using this network are also presented.

WEBSOM Method - Word Categories in Czech Written Documents

We applied well-known WEBSOM method (based on two layer architecture) to categorization of Czech written documents. Our research was focused on the syntactic and semantic relationship within word categories of word category map (WCM). The document classification system was tested on a subset of 100 documents (manual work was necessary) from the corpus of Czech News Agency documents. The result confirmed that WEBSOM method could be hardly evaluated because humans have problems with natural language semantics and determination of semantic domains from word categories.

Stress Dichotomy using Heart Rate and Tweet Sentiment

Automated detection of human stress from markers is very beneficial for the development of assistive technologies. Blood pressure, skin temperature, galvanic skin response or heart rate are typical physiological markers that help identify human stress. However, not only the human body itself but also the human mood expressed in short text messages can be a useful source of such information about stress. This paper focuses on detection of human stress using two different but synchronized sources of information, human heart rate and sentiment extracted from tweets. During the preliminary experiment lasting for two fifty-day periods, we obtained simultaneously 481 708 heart rate data samples from two wearables and sentiment from 2049 tweets. The tweet data contain a subjective sentiment evaluation that was recorded using positive and negative hashtags. A few states of stress were identified as the result of the data processing. The final discussion provides conclusions and recommendations for future research.