Table 3.

Summary of functional connectivity analysis findings in major depressive disorder.

Researchers	Aim	Material and methods	Results
Li et al. (2015)	Evaluation of the structure of functional brain networks in patients with depression and healthy individuals during emotion processing using graph theory	Traditional EEG (59 electrodes); coherence and graph theory analysis (clustering, path length) in delta–gamma bands. 16 patients with depression, 14 healthy subjects	Depressed patients show higher coherence and more randomized network topology, especially in the gamma band
Siegle et al. (2010)	Investigate differences in emotional processing by analyzing gamma EEG after negative words in healthy people, people with depression and people with schizophrenia	Task: identifying emotions in words during traditional EEG; gamma band analysis (35–45 Hz). 24 healthy subjects, 14 patients with depression, 15 patients with schizophrenia	Depressed individuals showed prolonged and increased gamma activity after negative stimuli.
Sun et al. (2020)	To identify effective EEG biomarkers for recognizing depression, with a focus on functional brain connectivity features.	Resting-state EEG data were collected from 24 MDD patients and 29 healthy controls using a 128-channel HydroCel Geodesic Sensor Net.	PLI outperformed linear and nonlinear features. The highest classification accuracy (82.31%) was achieved using ReliefF feature selection and logistic regression.
Lee et al. (2011)	To assess whether the strength of functional EEG connections can predict the response to depression treatment after 8 weeks of SSRI treatment.	3-minute resting EEG (eyes closed) recorded in 108 patients with MDD. Connectivity strengths in responders and non-responders compared after 8 weeks	Stronger frontotemporal connections in the delta/theta band were associated with a poorer response to treatment
Bares et al. (2008)	To assess whether the decrease in QEEG theta coherence in the prefrontal brain area after 1 week of venlafaxine treatment can predict the clinical response in treatment-resistant patients.	25 hospitalized patients with MDD, QEEG recorded at baseline and after 1 week of treatment	An early decrease in the theta coherence may be a useful marker for predicting the effectiveness of venlafaxine
Cook et al. (2002)	To assess whether changes in QEEG theta-correlation in the prefrontal cortex can predict the clinical response to treatment with fluoxetine or venlafaxine.	51 patients with unipolar depression; EEG recorded at 3 time points	Only drug-responders showed a significant decrease in prefrontal coherence after 48 hours and 7 days
Bares et al. (2015)	To assess the effectiveness of QEEG theta-correlation in the prefrontal cortex as a predictor of response to venlafaxine ER in patients with MDD.	50 patients with MDD; QEEG performed at baseline, after 1 and 4 weeks	A decrease in coherence in the first week occurred in all responders in both groups
Armitage (1995)	Summary of 10 years of research on the microarchitecture of sleep in the traditional EEG of patients with depression	Review of sleep EEG studies in people with depression (both in episode and remission), compared with other clinical and control groups	Reduced delta activity in early sleep, increased fast EEG (especially in the right hemisphere) and reduced interhemispheric coherence are observed