Publikation:

Statistical discrimination of controls, schizophrenics, depressives and alcoholics using local magnetoencephalographic frequency-related variables

Lade...
Vorschaubild

Dateien

Fehr_et_al._Biomed._01.pdf
Fehr_et_al._Biomed._01.pdfGröße: 111.41 KBDownloads: 264

Datum

2001

Autor:innen

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Biomedizinische Technik. 2001, 46(Suppl. 2), pp. 242-244. Available under: doi: 10.1515/bmte.2001.46.s2.242

Zusammenfassung

Atypically enhanced activity in the delta and theta EEG frequency bands has frequently been reported for schizophrenic patients, while alpha activity is often attenuated in these patients [2,9,10,12]. MEG and EEG data provide an advanced approach to analyze complex brain functioning and to examine differences between different psychiatric patient groups due to their brain activity. Past analyses using different physiological parameters to discriminate a psychiatric patient group from controls reached statistical correct classification rates of at maximum 80 percent. Results usually shifted to chance when adding a third group to the analysis. Winterer (2000) [13], for example, could discriminate between schizophrenic patients and controls with a correct classification rate of 77 percent when using delta power, signal power at Cz and power values of the high alpha range as variables in a discriminant analysis. Including a group of depressive patients in the analysis reduced the correct classification rate to 50 percent. Gallhofer (1991) [5] used 50 topographical frequency-related EEG-parameters in a discriminant analysis with schizophrenic and depressive patients and controls. He classified 49 out of the 50 subjects correctly.
Strategies that try to describe the physiological substrate of psychiatric diseases with only a few parameters possibly over-simplify the nature of the phenomenon [see also 5]. More complex strategies are possibly more adequate to describe complex phenomena such like psychiatric diseases.
The present study examined to what extent delta-, theta and alpha-band-related source space activity can separate controls, schizophrenics, depressives and alcoholics by discriminant analysis. The analyses are meant as a first step towards an evaluation of a set of physiological parameters that could possibly be representative of certain psychiatric gross groups. In order to explore possible methods sensitive to these physiological parameters, different strategies of MEG source space analysis and statistical procedures were performed on data obtained during three different mental modalities (rest, mental calculation and mental imagery).
Enhancement in focal [1] as well as in multiple [4] slow wave activity has been reported for schizophrenic patients. A reduction of alpha activity has been reported for schizophrenic [10,12] and alcohol [3] patients as well. For the analysis of focal sources we performed the dipole density method that has been shown as a valid tool in the vicinity of the detection of pathological attributed slow wave activity for example around tumors [8] or lesions [11]. Multiple source activity in the slow wave and alpha range was detected by the minimum-norm method [6,7].

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
150 Psychologie

Schlagwörter

MEG

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690FEHR, Thorsten, Christian WIENBRUCH, Stephan MORATTI, Brigitte ROCKSTROH, Thomas ELBERT, 2001. Statistical discrimination of controls, schizophrenics, depressives and alcoholics using local magnetoencephalographic frequency-related variables. In: Biomedizinische Technik. 2001, 46(Suppl. 2), pp. 242-244. Available under: doi: 10.1515/bmte.2001.46.s2.242
BibTex
@article{Fehr2001Stati-11156,
  year={2001},
  doi={10.1515/bmte.2001.46.s2.242},
  title={Statistical discrimination of controls, schizophrenics, depressives and alcoholics using local magnetoencephalographic frequency-related variables},
  number={Suppl. 2},
  volume={46},
  journal={Biomedizinische Technik},
  pages={242--244},
  author={Fehr, Thorsten and Wienbruch, Christian and Moratti, Stephan and Rockstroh, Brigitte and Elbert, Thomas}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/11156">
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:issued>2001</dcterms:issued>
    <dcterms:abstract xml:lang="eng">Atypically enhanced activity in the delta and theta EEG frequency bands has frequently been reported for schizophrenic patients, while alpha activity is often attenuated in these patients [2,9,10,12]. MEG and EEG data provide an advanced approach to analyze complex brain functioning and to examine differences between different psychiatric patient groups due to their brain activity. Past analyses using different physiological parameters to discriminate a psychiatric patient group from controls reached statistical correct classification rates of at maximum 80 percent. Results usually shifted to chance when adding a third group to the analysis. Winterer (2000) [13], for example, could discriminate between schizophrenic patients and controls with a correct classification rate of 77 percent when using delta power, signal power at Cz and power values of the high alpha range as variables in a discriminant analysis. Including a group of depressive patients in the analysis reduced the correct classification rate to 50 percent. Gallhofer (1991) [5] used 50 topographical frequency-related EEG-parameters in a discriminant analysis with schizophrenic and depressive patients and controls. He classified 49 out of the 50 subjects correctly.&lt;br /&gt;Strategies that try to describe the physiological substrate of psychiatric diseases with only a few parameters possibly over-simplify the nature of the phenomenon [see also 5]. More complex strategies are possibly more adequate to describe complex phenomena such like psychiatric diseases.&lt;br /&gt;The present study examined to what extent delta-, theta and alpha-band-related source space activity can separate controls, schizophrenics, depressives and alcoholics by discriminant analysis. The analyses are meant as a first step towards an evaluation of a set of physiological parameters that could possibly be representative of certain psychiatric gross groups. In order to explore possible methods sensitive to these physiological parameters, different strategies of MEG source space analysis and statistical procedures were performed on data obtained during three different mental modalities (rest, mental calculation and mental imagery).&lt;br /&gt;Enhancement in focal [1] as well as in multiple [4] slow wave activity has been reported for schizophrenic patients. A reduction of alpha activity has been reported for schizophrenic [10,12] and alcohol [3] patients as well. For the analysis of focal sources we performed the dipole density method that has been shown as a valid tool in the vicinity of the detection of pathological attributed slow wave activity for example around tumors [8] or lesions [11]. Multiple source activity in the slow wave and alpha range was detected by the minimum-norm method [6,7].</dcterms:abstract>
    <dc:creator>Wienbruch, Christian</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Elbert, Thomas</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Fehr, Thorsten</dc:contributor>
    <dc:contributor>Rockstroh, Brigitte</dc:contributor>
    <dc:creator>Moratti, Stephan</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:25:59Z</dc:date>
    <dc:format>application/pdf</dc:format>
    <dc:contributor>Wienbruch, Christian</dc:contributor>
    <dcterms:title>Statistical discrimination of controls, schizophrenics, depressives and alcoholics using local magnetoencephalographic frequency-related variables</dcterms:title>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:25:59Z</dcterms:available>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/11156"/>
    <dc:creator>Fehr, Thorsten</dc:creator>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/11156/1/Fehr_et_al._Biomed._01.pdf"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:creator>Rockstroh, Brigitte</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <dc:contributor>Moratti, Stephan</dc:contributor>
    <dc:contributor>Elbert, Thomas</dc:contributor>
    <dcterms:bibliographicCitation>Biomedizinische Technik ; 46 (2001), Suppl. 2. - S. 242-244</dcterms:bibliographicCitation>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/11156/1/Fehr_et_al._Biomed._01.pdf"/>
    <dc:language>eng</dc:language>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen