Dysfunctional brain networks have been found in patients with major depressive disorder (MDD). In this study, to verify this in a more straightforward way, we investigated the intrinsic organization of brain networks in MDD by leveraging the resting-state functional near-infrared spectroscopy (rs-fNIRS). Thirty-four MDD patients (24 females, 38.41 ± 13.14 years old) and thirty healthy controls (22 females, 34.43 ± 5.03 years old) underwent a 10 min rest while their brain activity was recorded via fNIRS. The results showed that MDD patients and healthy controls exhibited similar resting-state functional connectivity. Moreover, the depression group showed lower small-world Lambda (1.12 ± 0.04 vs. 1.16 ± 0.10, p = 0.04) but higher global efficiency (0.51 ± 0.03 vs. 0.48 ± 0.05, p = 0.03) than the control group. Importantly, MDD patients, as opposed to healthy controls, showed a significantly lower nodal local efficiency at the left middle occipital gyrus (0.56 ± 0.36 vs. 0.81 ± 0.20, p_FDR < 0.05), which predicted the level of depression in MDD (r = 0.45, p = 0.01, R² = 0.15). In sum, we found a more integrated brain network in MDD patients with a lower nodal local efficiency at the occipital hub, which could predict depressive symptoms.

Background: The effectiveness of medication combined with smartphone-delivered cognitive behavioral therapy for insomnia (CBT-I) has been well verified, but there are few studies on the sequence of remission of insomnia symptoms. This study aims to understand the sequence of symptom improvement and the factors influencing the treatment effectiveness in patients with insomnia. Methods: Smartphone-delivered CBT, as a form of Online CBT, allows for training through mobile devices at any time and place. We utilized the Good Sleep 365 app to conduct a survey, involving 2820 patients who met the baseline inclusion criteria. These patients were assessed using a general demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI) to evaluate general demographic information and insomnia symptoms, and subsequently underwent CBT training using the Good Sleep 365 app. A total of 1179 patients completed follow-ups at 4 weeks, 8 weeks, 16 weeks, and 24 weeks. Results: At 4 weeks and 8 weeks, the descending order of the reduction rates of PSQI components (excluding component 6: use of sleeping medication) was: sleep latency, subjective sleep quality, sleep efficiency, sleep disturbance, sleep maintenance, and daytime dysfunction. At 16 weeks and 24 weeks, the descending order was subjective sleep quality, sleep latency, sleep efficiency, daytime dysfunction, sleep maintenance, and sleep disturbance. There were significant differences in the reduction rates of PSQI components (excluding component 6: use of sleeping medication) both at the same follow-up times and at different follow-up times (all P< 0.05). Multivariable logistic regression analysis showed that patients older than 30 years and those with a college degree or above had better treatment outcomes, whereas those with a disease duration of more than three years had worse outcomes. Conclusion: The sequence of symptom improvement in patients with insomnia changes over time, and age, educational level, and duration of disease are factors influencing treatment outcomes.