Late-onset depression: can EEG abnormalities help in clinical sub-typing?
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Updated: Oct 2, 2026

EEG Mu Rhythm in Typical and Atypical Development
Published on: April 9, 2014
Eishi Motomura1, Koji Inui, Shinji Nakase
1Department of Psychiatry, Mie University School of Medicine, Edobashi, Tsu, Mie 514-8507, Japan. motomura@clin.medic.mie-u.ac.jp
Background:
The purpose of this study was to determine the frequency of EEG abnormalities indicative of mild cerebrovascular dysfunction in patients with late-onset depression and to correlate these abnormalities with clinical features.
Methods:
The subjects, aged > or = 50 years, were 51 outpatients with major depression diagnosed according to DSM-IV criteria. They were living in the community and prospectively selected at their initial consultation for mostly mild-moderate depression. We also included 32 normal age-matched controls. We examined basic rhythms and temporal slow waves on EEG and determined the Hamilton Rating Scale for Depression (HAMD) as a scale for the severity of psychiatric symptoms.
Results:
Temporal slow waves were more common in depressed patients (47%) than in normal controls (22%). Depressed patients with temporal slow waves had significantly lower frequency of family history of mood disorders (P<0.05). There was no difference in the total score of HAMD between patients with and without temporal slow waves, however, each score of HAMD in patients with temporal slow waves showed a significantly lower score for "feeling of guilt" (P<0.01) and a significantly higher score for "general somatic symptoms" (P<0.01) and "hypochondriasis" (P<0.01).
Conclusions:
Our EEG study suggested that temporal slow waves, which were probably associated with subtle cerebrovascular lesions, might reflect vulnerability to late-onset depression. In addition, depressed patients with temporal slow waves could be classified as a subgroup of heterogeneous late-onset depression based on the clinical findings. These results must be interpreted within the limitations of the sample selection procedure.
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