ArticleBrain sciences2020
The Changes of qEEG Approximate Entropy during Test of Variables of Attention as a Predictor of Major Depressive Disorder.
Article in Brain sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 23 citations in OpenAlex.
- Differences in resting state and task-based EEG measures between patients with major depressive disorder and healthy controls.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Machine Learning Techniques Reveal Aberrated Multidimensional EEG Characteristics in Patients with Depression.Brain sciences · 2023Article
- Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression.Diagnostics (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
Evaluating brain function through biosignals remains challenging. Quantitative electroencephalography (qEEG) outcomes have emerged as a potential intermediate biomarker for diagnostic clarification in psychological disorders. The Test of Variables of Attention (TOVA) was combined with qEEG to evaluate biomarkers such as absolute power, relative power, cordance, and approximate entropy from covariance matrix images to predict major depressive disorder (MDD). EEG data from 18 healthy control and 18 MDD patients were monitored during the resting state and TOVA. TOVA was found to provide aspects for the evaluation of MDD beyond resting electroencephalography. The results showed that the prefrontal qEEG theta cordance of the control and MDD groups were significantly different. For comparison, the changes in qEEG approximate entropy (ApEn) patterns observed during TOVA provided features to distinguish between participants with or without MDD. Moreover, ApEn scores during TOVA were a strong predictor of MDD, and the ApEn scores correlated with the Beck Depression Inventory (BDI) scores. Between-group differences in ApEn were more significant for the testing state than for the resting state. Our results provide further understanding for MDD treatment selection and response prediction during TOVA.
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