Differential resting-state EEG patterns associated with comorbid depression in Internet addiction

Area of Science:

• Neuroscience
• Psychiatry
• Digital Health

Background:

• Internet addiction is increasingly recognized as a significant mental health concern.
• Comorbidity with depression is common, yet neurobiological distinctions remain unclear.

Purpose of the Study:

• To identify neurobiological markers differentiating Internet addiction (IA) from IA with comorbid depression.
• To compare resting-state quantitative electroencephalography (QEEG) patterns.

Main Methods:

• Recruited 35 IA patients and 34 healthy controls.
• Divided IA patients into groups with (N=18) and without (N=17) depression.
• Recorded resting-state, eye-closed QEEG and analyzed brainwave power.

Main Results:

• IA without depression showed decreased absolute delta and beta power.
• IA with depression exhibited increased relative theta and decreased relative alpha power.
• Observed neurophysiological changes were independent of clinical variables.

Conclusions:

• Resting-state QEEG patterns differ between IA patients and healthy controls.
• Distinct QEEG signatures exist for IA alone versus IA with depression.
• Decreased absolute delta and beta power may serve as neurobiological markers for IA.