Critical Evaluation of Auditory Event-Related Potential Deficits in Schizophrenia: Evidence From Large-Scale Single-Subject Pattern Classification.
Event-related potential (ERP) deficits associated with auditory oddball and click-conditioning paradigms are among the most consistent findings in schizophrenia and are discussed as potential biomarkers. However, it is unclear to what extend these ERP deficits distinguish between schizophrenia patie...
| Publicado en: | Schizophrenia Bulletin Vol. 40; no. 5; pp. 1062 - 1072 |
|---|---|
| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Sep2014
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=97548468&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 97548468 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 05867614 2CZ jtl: Schizophrenia Bulletin issn: 05867614 maglogo: N pubinfo: dt: Sep2014 vid: 40 iid: 5 pid: 622 pub: Oxford University Press / USA artinfo: ui: 97548468 103990159 103990159 10.1093/schbul/sbt151 97548468 ppf: 1062 ppct: 10 formats: tig: atl: Critical Evaluation of Auditory Event-Related Potential Deficits in Schizophrenia: Evidence From Large-Scale Single-Subject Pattern Classification. aug: au: Neuhaus, Andres H. Popescu, Florin C. Rentzsch, Johannes Gallinat, Jürgen affil: Department of Psychiatry and Psychotherapy, Charité University Medicine Berlin , Berlin , Germany ; sug: subj: Evoked Potentials, Auditory Schizophrenia Classification Human Analysis of Variance Repeated Measures Female Male Psychological Tests Adult Electroencephalography Data Analysis Software T-Tests ROC Curve P-Value Adult: 19-44 years Female Male ab: Event-related potential (ERP) deficits associated with auditory oddball and click-conditioning paradigms are among the most consistent findings in schizophrenia and are discussed as potential biomarkers. However, it is unclear to what extend these ERP deficits distinguish between schizophrenia patients and healthy controls on a single-subject level, which is of high importance for potential translation to clinical routine. Here, we investigated 144 schizophrenia patients and 144 matched controls with an auditory click-conditioning/oddball paradigm. P50 and N1 gating ratios as well as target-locked N1 and P3 components were submitted to conventional general linear models and to explorative machine learning algorithms. Repeated-measures ANOVAs revealed significant between-group differences for the oddball-locked N1 and P3 components but not for any gating measure. Machine learning-assisted analysis achieved 77.7% balanced classification accuracy using a combination of target-locked N1 and P3 amplitudes as classifiers. The superiority of machine learning over repeated-measures analysis for classifying schizophrenia patients was in the range of about 10% as quantified by receiver operating characteristics. For the first time, our study provides large-scale single-subject classification data on auditory click-conditioning and oddball paradigms in schizophrenia. Although our study exemplifies how automated inference may substantially improve classification accuracy, our data also show that the investigated ERP measures show comparably poor discriminatory properties in single subjects, thus illustrating the need to establish either new analytical approaches for these paradigms or other paradigms to investigate the disorder. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|