Aberrant EEG signal variability at a specific temporal scale in major depressive disorder.
OBJECTIVE
Signal variability is linked to irregularities in time series caused by intrinsic nonlinearities of the neural system and can be measured on variable temporal scales over short time series. By measuring refined complex multiscale permutation entropy (RCMPE) from resting-state electroencephalography (EEG) data, we investigated the presence of a specific range of time scales characterizing major depressive disorder (MDD).


METHOD
We used an EEG dataset acquired from 22 MDD patients and 22 healthy controls in the eyes-closed (EC) and eyes-open (EO) states available on the PRED + CT website. Signal variability in both the EC and EO states was compared between the two groups, and their relationship to depressive symptom severity was examined.


RESULTS
In the EC state, the RCMPE was higher in the MDD group than in the control group on a coarse temporal scale, approximately 20-32 ms, at almost all sensors. It also showed a negative correlation with depressive symptom severity on a fine temporal scale, approximately 2-26 ms, in the frontal, right temporal, and left parietal sensor areas in MDD. The EO state revealed a group difference but no relationship with depressive symptom severity.


CONCLUSION
Our results suggested that the diagnosis of MDD as a trait and the severity of depressive symptoms as a state are linked to EEG signal variability on the coarse temporal scale and the fine scale in the resting state, respectively.


SIGNIFICANCE
Signal variability reflects different characteristics of depression depending on the temporal scale.
['Yun|Seokho|S|', 'Jeong|Bumseok|B|']
D000293:Adolescent D000328:Adult D001921:Brain D001931:Brain Mapping D016208:Databases, Factual D003865:Depressive Disorder, Major D004569:Electroencephalography D005260:Female D006801:Humans D008297:Male D013997:Time Factors D055815:Young Adult
EEG Signal variability Depression Permutation entropy Biomarker