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objective. depression is a severe mental disorder. however, the neural mechanisms underlying affective interference (difficulties in directing attention away from negative distractors) in depression patients are still not well-understood. in particular, the connections between brain regions remain unclear. using the emotional face-word stroop task, we aimed to reveal the altered electroencephalography (eeg) functional connectivity in patients with depression, using concepts from event-related potentials (erps) and time series clustering. approach. in this study, the eeg signals of ten healthy participants and ten depression patients were collected from a 64-sensor cap. subsequently, eeg signals were segmented into temporal windows corresponding to the erps. for each duration, the dynamic time warping algorithm was used to calculate the similarities between eeg signals from different electrodes, and differences of these similarities were compared between the groups. finally, hierarchical clustering was used to identify functionally connected regions and examine changes in depression. main results. it was observed that during the time interval of 400–600 ms (n450 components), depression patients had more long-range connections than did healthy control patients and exhibited abnormal functional connectivity via the superior and middle frontal gyrus, specifically, the dorsolateral prefrontal cortex (dl-pfc, brodmann's area 8 and 9), which is related to the control and resolution of affective interference. moreover, the functionally connected region of depression patients was much larger than that of healthy participants, which is caused by brain resource reorganization. significance. these findings thus provide new insights into the neural mechanisms of depression and further identify the dl-pfc and connections between certain electrodes as quantitative indicators of depression.