Quantitative Electroencephalography for Objective and Differential Diagnosis of Depression: A Comprehensive Review
Ali Yadollahpour and
Hadi Nasrollahi
Global Journal of Health Science, 2016, vol. 8, issue 11, 249
Abstract:
Quantitative electroencephalography (QEEG) has been dramatically developed during recent years in cognitive neurosciences. It has shown significant potential in the diagnosis of cognitive neurological disorders as well as in the evaluation of treatment outcomes and response. Early diagnosis of depression, differential diagnosis, and assessing the treatment outcomes and response are currently the main research fields of QEEG in depression. Identifying reliable disorder-specific EEG-based biomarkers that have strong correlations with the depression specific cognitive functions is one of the major challenges in these fields. Such biomarkers not only allow early and cost-effective diagnosis of depression, but also may have differential diagnostic and predictive values for treatment response of a variety of treatments. This paper aims at a comprehensive review on the main principles of QEEG in developing biomarkers for MDD. The databases of PubMed (1985-2015), Web of Sciences (1985-2015), and Google Scholar (1980-2015) were searched using the set terms. The obtained results were screened for the title and abstract by two authors and they came to consensus whether the studies are related to the review. The main advantages of QEEG for mood disorders are also reviewed. In addition, different QEEG-based measures for objective diagnosis of MDD as well as for distinguishing depressed patients from healthy subjects are discussed.
Date: 2016
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.ccsenet.org/journal/index.php/gjhs/article/download/57054/31432 (application/pdf)
http://www.ccsenet.org/journal/index.php/gjhs/article/view/57054 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ibn:gjhsjl:v:8:y:2016:i:11:p:249
Access Statistics for this article
More articles in Global Journal of Health Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().