7 research outputs found
Mapping the Human Brain in Frequency Band Analysis of Brain Cortex Electroencephalographic Activity for Selected Psychiatric Disorders
There are still no good quantitative methods to be applied in psychiatric diagnosis. The interview is still the main and most important tool in the psychiatrist work. This paper presents the results of electroencephalographic research with the subjects of a group of 30 patients with psychiatric disorders compared to the control group of healthy volunteers. All subjects were solving working memory task. The digit-span working memory task test was chosen as one of the most popular tasks given to subjects with cognitive dysfunctions, especially for the patients with panic disorders, depression (including the depressive phase of bipolar disorder), phobias, and schizophrenia. Having such cohort of patients some results for the subjects with insomnia and Asperger syndrome are also presented. The cortical activity of their brains was registered by the dense array EEG amplifier. Source localization using the photogrammetry station and the sLORETA algorithm was then performed in five EEG frequency bands. The most active Brodmann Areas are indicated. Methodology for mapping the brain and research protocol are presented. The first results indicate that the presented technique can be useful in finding psychiatric disorder neurophysiological biomarkers. The first attempts were made to associate hyperactivity of selected Brodmann Areas with particular disorders
Performance comparison of parallel fastICA algorithm in the PLGrid structures
During processing the EEG signal, the methods of cleaning it from artifacts play an important role. One of the most commonly used methods is ICA (independent component analysis) [1-3]. However, algorithms of this type are computationally expensive. Known implementations of ICA type algorithms rarely include the possibility of parallel computing and do not use the capabilities provided by the architecture itself. This paper presents a parallel implementation of the fastICA algorithm using the available libraries and extensions of the Intel processors (such as BLAS, MKL, Cilk Plus) and compares the execution time for two selected architectures in the PLGrid structure (Zeus and Prometheus)
Performance comparison of parallel fastICA algorithm in the PLGrid structures
During processing the EEG signal, the methods of cleaning it from artifacts play an important role. One of the most commonly used methods is ICA (independent component analysis) [1-3]. However, algorithms of this type are computationally expensive. Known implementations of ICA type algorithms rarely include the possibility of parallel computing and do not use the capabilities provided by the architecture itself. This paper presents a parallel implementation of the fastICA algorithm using the available libraries and extensions of the Intel processors (such as BLAS, MKL, Cilk Plus) and compares the execution time for two selected architectures in the PLGrid structure (Zeus and Prometheus)
New Protocol for Quantitative Analysis of Brain Cortex Electroencephalographic Activity in Patients With Psychiatric Disorders
The interview is still the main and most important tool in psychiatrist's work. The neuroimaging methods such as CT or MRI are widely used in other fields of medicine, for instance neurology. However, psychiatry lacks effective quantitative methods to support of diagnosis. A novel neuroinformatic approach to help clinical patients by means of electroencephalographic technology in order to build foundations for finding neurophysiological biomarkers of psychiatric disorders is proposed. A cohort of 30 right-handed patients (21 males, 9 females) with psychiatric disorders (mainly with panic and anxiety disorder, Asperger syndrome as well as with phobic anxiety disorders, schizophrenia, bipolar affective disorder, obsessive-compulsive disorder, nonorganic hypersomnia, and moderate depressive episode) were examined using the dense array EEG amplifier in the P300 experiment. The results were compared with the control group of 30 healthy, right-handed male volunteers. The quantitative analysis of cortical activity was conducted using the sLORETA source localization algorithm. The most active Brodmann Areas were pointed out and a new quantitative observable of electrical charge flowing through the selected Brodmann Area is proposed. The precise methodology and research protocol for collecting EEG data as well as the roadmap of future investigations in this area are presented. The essential result of this study is the idea proven by the initial results of our experiments that it is possible to determine quantitatively biomarkers of particular psychiatric disorders in order to support the process of diagnosis and hopefully choose most appropriate medical treatment later