Executive function deficits in patients with the first episode of late-life depression before and after SSRI treatment: A pilot fMRI study.

BACKGROUND: Executive function deficits (EFD) in late-life depression (LLD) has been reported to be associated with antidepressant treatment resistance, increased disability, and poor quality of life. However, the underlying neutral mechanisms of EFD in patients with the first episode of LLD remains unclear. METHODS: A total of 27 patients with first-episode, drug-naive LLD and 27 non-depressed controls (NC) were recruited for the present research. Participants underwent the Trail Making Test, the 17-item Hamilton depression rating scale (HAMD-17) test, and task-state functional magnetic resonance imaging scans under the neutral Stroop task. LLD patients' executive functions, depressive symptoms, and brain activity were examined again after 6 months of antidepressant treatment. RESULTS: Of the 27 LLD patients, 16 cases completed 6-month follow-ups. Patients in the LLD baseline group spent more time on the Trail Making Test A test than those in the NC group (p < 0.05). In the presence of an incongruency between the word color and meaning, the accuracy rate of the neutral Stroop task in the LLD baseline group was lower, and the reaction time was greater than that in the NC group, with statistically significant difference (p < 0.05). The HAMD-17 score in the LLD follow-up group was significantly lower than that in the LLD baseline group (p < 0.05). More activated brain regions were present in the LLD baseline group than in the NC group when performing the neutral Stroop task. Compared with the LLD baseline group, abnormal activation of relevant brains in the cingulate-prefrontal-parietal network of LLD patients still existed in the LLD follow-up group. CONCLUSIONS: LLD patients engaged more brain areas than the NC group while performing the neutral Stroop task. Abnormal activation of the cingulate-prefrontal-parietal network could be a contributing factor to EFD in LLD. TRIAL REGISTRATION: ChiCTR, ChiCTR2100042370 (Date of registration: 21/01/2021). LIMITS: We didn't enroll enough first-episode, LLD patients, the robustness of the findings need to be confirmed by large sample clinical trials.

Repetitive Transcranial Magnetic Stimulation for Working Memory Deficits in Schizophrenia: A Systematic Review of Randomized Controlled Trials.

Working memory (WM) deficits are a significant component of neurocognitive impairment in individuals with schizophrenia (SCZ). Two previous meta-analyses, conducted on randomized controlled trials (RCTs), examined the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in addressing WM deficits in individuals diagnosed with SCZ. However, the conclusions drawn from these analyses were inconsistent. Additionally, the commonly used random effects (RE) models might underestimate statistical errors, attributing a significant portion of perceived heterogeneity between studies to variations in study quality. Therefore, this review utilized both RE and quality effects (QE) models to assess relevant RCTs comparing TMS with sham intervention in terms of clinical outcomes. A comprehensive literature search was conducted using PubMed and Scopus databases, resulting in the inclusion of 13 studies for data synthesis. Overall, regardless of whether the RE or QE model was used, eligible RCTs suggested that the TMS and sham groups exhibited comparable therapeutic effects after treatment. The current state of research regarding the use of rTMS as a treatment for WM deficits in patients with SCZ remains in its preliminary phase. Furthermore, concerning the mechanism of action, the activation of brain regions focused on the dorsolateral prefrontal cortex and alterations in gamma oscillations may hold significant relevance in the therapeutic application of rTMS for addressing WM impairments. Finally, we believe that the application of closed-loop neuromodulation may contribute to the optimization of rTMS for WM impairment in patients with SCZ.

Risk Factors of Alcohol Use Disorders Among Inpatients with Schizophrenia: An Institutional-Based Cross-sectional Survey.

Objective: This study aimed to elucidate the risk factors associated with alcohol use disorders (AUDs) among inpatients with schizophrenia at a specialized mental hospital in Baoding city, China. Methods: This cross-sectional survey comprised 301 comorbid patients. Three binary logistic regression models were used to investigate the factors linked to AUDs in patients with schizophrenia. Propensity score matching analysis was conducted to validate inconsistent variables identified by the regression models. Results: Significant differences were observed between the comorbid and non-comorbid groups concerning sex (P < .001), disposition (P = .049), smoking habits (P < .001), place of residence (P = .010), family relationships (P = .002), family history of mental disorders (P = .008), history of alcoholism (P = .003), onset latency (P = .005), impulsivity (P < .001), suicide or self-injury history (P < .001), and obvious aggressive behavior (P < .001) in univariate analyses. The area under the curve values for the three regression models were 0.83 (P < .001), 0.80 (P < .001), and 0.81 (P < .001), respectively. Binary logistic regression and propensity score matching analyses indicated that introverted disposition, smoking, acute onset, impulsivity, and suicide or self-injury history were independent risk factors associated with AUDs in inpatients with schizophrenia with an odds ratio of > 1. Conclusion: Introverted disposition, smoking, acute onset, impulsivity, and suicide or self-injury history were independently associated with the AUDs in inpatients with schizophrenia. Future studies should prioritize longitudinal studies to discern the evolving dynamics of potential confounding risk factors.

Prefrontal brain activity and self-injurious behavior in adolescents with major depressive disorder: A functional near-infrared spectroscopy (fNIRS) study.

In clinical practice, accurately identifying self-injurious behavior among adolescents with major depressive disorder (MDD) is crucial for individualized treatment. This study aimed to examine the differences in prefrontal cortex activation using the functional near-infrared spectroscopy (fNIRS) during the verbal fluency task (VFT) assessment of adolescents with MDD and self-harm (SH) compared with those without SH. A total of 60 eligible patients were included for final analysis, with the SH group containing 36 participants, and the Non-SH group containing 24 participants. We found that right middle frontal gyrus (rMFG) was more activated in the SH group than that in the Non-SH group during the VFT assessments (z = -3.591, p = 0.004, FDR correction). The z-scores of beta values of rMFG exhibited a good discriminatory power with the area under the curve (AUC) in distinguishing the two groups (AUC = 0.775, p < 0.001). These findings reveal that the fNIRS-VFT paradigm may be a useful tool for discovering neurobiological differences among adolescents with MDD.

Individualized prediction of cognitive test scores from functional brain connectome in patients with first-episode late-life depression.

BACKGROUND: In the realm of cognitive screening, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are widely utilized for detecting cognitive deficits in patients with late-life depression (LLD), However, the interindividual variability in neuroimaging biomarkers contributing to individual-specific symptom severity remains poorly understood. In this study, we used a connectome-based predictive model (CPM) approach on resting-state functional magnetic resonance imaging data from patients with LLD to establish individualized prediction models for the MoCA and the MMSE scores. METHODS: We recruited 135 individuals diagnosed with first-episode LLD for this research. Participants underwent the MMSE and MoCA tests, along with resting-state functional magnetic resonance imaging scans. Functional connectivity matrices derived from these scans were utilized in CPM models to predict MMSE or MoCA scores. Predictive precision was assessed by correlating predicted and observed scores, with the significance of prediction performance evaluated through a permutation test. RESULTS: The negative model of the CPM procedure demonstrated a significant capacity to predict MoCA scores (r = -0.309, p = 0.002). Similarly, the CPM procedure could predict MMSE scores (r = -0.236, p = 0.016). The predictive models for cognitive test scores in LLD primarily involved the visual network, somatomotor network, dorsal attention network, and ventral attention network. CONCLUSIONS: Brain functional connectivity emerges as a promising predictor of personalized cognitive test scores in LLD, suggesting that functional connectomes are potential neurobiological markers for cognitive performance in patients with LLD.