Multimodal multilayer network centrality relates to executive functioning.

Executive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one 'network of networks.' We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.

BrainAge of patients with severe late-life depression referred for electroconvulsive therapy.

BACKGROUND: Severe depression is associated with accelerated brain aging. BrainAge gap, the difference between predicted and observed BrainAge, was investigated in patients with late-life depression (LLD). We aimed to examine BrainAge gap in LLD and its associations with clinical characteristics indexing LLD chronicity, current severity, prior to electroconvulsive therapy (ECT) and ECT outcome. METHODS: Data was analyzed from the Mood Disorders in Elderly treated with Electroconvulsive Therapy (MODECT) study. A previously established BrainAge algorithm (BrainAge R by James Cole, (https://github.com/james-cole/brainageR)) was applied to pre-ECT T1-weighted structural MRI-scans of 42 patients who underwent ECT. RESULTS: A BrainAge gap of 1.8 years (SD = 5.5) was observed, Cohen's d = 0.3. No significant associations between BrainAge gap, number of previous episodes, current episode duration, age of onset, depression severity, psychotic symptoms or ECT outcome were observed. LIMITATIONS: Limited sample size. CONCLUSIONS: Our initial findings suggest an older BrainAge than chronological age in patients with severe LLD referred for ECT, however with high degree of variability and direction of the gap. No associations were found with clinical measures. Larger samples are needed to better understand brain aging and to evaluate the usability of BrainAge gap as potential biomarker of prognosis an treatment-response in LLD. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02667353.

Remission Rates Following Electroconvulsive Therapy and Relation to Index Episode Duration in Patients With Psychotic Versus Nonpsychotic Late-Life Depression.

Objective: Electroconvulsive therapy (ECT) is a safe and effective treatment, especially in psychotic late-life depression (LLD). However, it is not yet clear whether the greater efficacy seen in psychotic LLD is because of a shorter index episode duration. The first aim of this study was to substantiate the superior ECT remission rates in patients with psychotic LLD, as compared to patients with nonpsychotic LLD, and a second aim was to investigate whether this association is independent of the index duration.Methods: 186 patients with LLD treated with ECT were included in the study: 76 from the Valerius cohort (data collection from 2001 to 2006) and 110 from the Mood Disorders Treated with Electroconvulsive Therapy (MODECT) cohort (data collection from 2011 to 2013). The Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate depression severity, with remission defined as 2 consecutive MADRS scores < 10. Diagnosis of depression was based on DSM-IV (Valerius) and DSM-IV-TR (MODECT) criteria. A stepwise logistic regression model was built to assess the association between psychotic symptoms, index duration, and remission.Results: Patients with psychotic LLD showed significantly higher remission rates compared to patients with nonpsychotic LLD (68.9% vs 51.0%), independent of index duration, additionally corrected for age, sex, and baseline depression severity (OR = 2.10 [95% CI, 1.07-4.10], P = .03).Conclusions: Patients with psychotic LLD treated with ECT show higher remission rates compared to patients with nonpsychotic LLD. The high remission rates in patients with psychotic LLD are not explained by a shorter index duration. Future studies focusing on neurobiological differences in psychotic versus nonpsychotic depression may indicate why this subtype of depression is very responsive to ECT.Trial Registration: ClinicalTrials.gov identifier: NCT02667353.

Which residual symptoms predict relapse after successful electroconvulsive therapy for late-life depression?

The risk of relapse following successful acute-phase treatment of late-life depression (LLD), including electroconvulsive therapy (ECT), is substantial. In order to improve reliable prediction of individuals' risk of relapse, we assessed the association between individual residual symptoms following a successful acute course of ECT for LLD and relapse at six-month follow-up. This prospective cohort study was part of the MODECT study, which included 110 patients aged 55 years and older with major depressive disorder. Participants who showed response to the index ECT course were monitored for relapse for six months. We used multivariable stepwise logistic regression models to assess the association between the scores on the 10 individual Montgomery-Åsberg Depression Rating Scale (MADRS) items at the end of the acute ECT course and relapse at six-month follow-up. Of the 80 responders with available six-month follow-up data (58.75% of which had psychotic features at baseline), 36.25% had relapsed. Higher scores on the MADRS items 'reduced sleep' (odds ratio (OR) = 2.03, 95% confidence interval (CI) = 1.11-3.69, p = 0.0214) and 'lassitude' (OR = 1.62, 95% CI = 1.00-2.62, p = 0.0497) at the end of the acute ECT course were significantly associated with increased risk of relapse at six-month follow-up. In conclusion, some residual depressive symptoms, including sleep disturbance and lassitude, may help better identify patients vulnerable to relapse following a successful acute course of ECT for LLD. If these findings can be replicated, studies assessing interventions that target specific residual symptoms may further reduce post-ECT depressive relapse rates.

Long-term Outcome Following Electroconvulsive Therapy for Late-Life Depression: Five-Year Follow-up Data From the MODECT Study.

OBJECTIVE: Electroconvulsive therapy (ECT) is the most effective treatment for late-life depression (LLD). Research addressing long-term outcome following an acute course of ECT for LLD is limited. We aimed to describe relapse, cognitive impairment and survival 5 years after a treatment with ECT for severe LLD, and assess the association of clinical characteristics with all three outcome measures. METHODS: This cohort study was part of the Mood Disorders in Elderly treated with ECT (MODECT) study, which included patients aged 55 years and older with major depressive disorder. Data regarding clinical course, cognitive impairment and mortality were collected 5 years after the index ECT course. We used multivariable Cox proportional hazards models and logistic regression models to assess the association of clinical characteristics with relapse and survival, and cognitive impairment, respectively. RESULTS: We studied 110 patients with a mean age of 72.9 years. 67.1% of patients who showed response at the end of the index ECT course relapsed, and the included clinical characteristics were not significantly associated with the risk of relapse. 38.8% of patients with available data showed cognitive impairment at five-year follow-up. 27.5% were deceased; higher age and a higher number of previous psychiatric admissions were significantly associated with increased risk of mortality. CONCLUSIONS: Five-year outcome after a course of ECT for severe LLD seems to be in line with long-term outcome following other acute treatments for severe LLD in terms of relapse, cognitive impairment and survival. Additional studies aimed at improving long-term outcome in severe LLD are warranted.

Transient Cognitive Impairment and White Matter Hyperintensities in Severely Depressed Older Patients Treated With Electroconvulsive Therapy.

BACKGROUND: Although electroconvulsive therapy (ECT) is a safe and effective treatment for patients with severe late life depression (LLD), transient cognitive impairment can be a reason to discontinue the treatment. The aim of the current study was to evaluate the association between structural brain characteristics and general cognitive function during and after ECT. METHODS: A total of 80 patients with LLD from the prospective naturalistic follow-up Mood Disorders in Elderly treated with Electroconvulsive Therapy study were examined. Magnetic resonance imaging scans were acquired before ECT. Overall brain morphology (white and grey matter) was evaluated using visual rating scales. Cognitive functioning before, during, and after ECT was measured using the Mini Mental State Examination (MMSE). A linear mixed-model analysis was performed to analyze the association between structural brain alterations and cognitive functioning over time. RESULTS: Patients with moderate to severe white matter hyperintensities (WMH) showed significantly lower MMSE scores than patients without severe WMH (F(1,75.54) = 5.42, p = 0.02) before, during, and post-ECT, however their trajectory of cognitive functioning was similar as no time × WMH interaction effect was observed (F(4,65.85) = 1.9, p = 0.25). Transient cognitive impairment was not associated with medial temporal or global cortical atrophy (MTA, GCA). CONCLUSION: All patients showed a significant drop in cognitive functioning during ECT, which however recovered above baseline levels post-ECT and remained stable until at least 6 months post-ECT, independently of severity of WMH, GCA, or MTA. Therefore, clinicians should not be reluctant to start or continue ECT in patients with severe structural brain alterations.

Psychotic late-life depression less likely to relapse after electroconvulsive therapy.

BACKGROUND: A substantial number of patients with late-life depression (LLD) that remitted after ECT experience relapse. Identifying risk factors for relapse may guide clinical management to devote attention to those at increased risk. Therefore the current study aims to evaluate which baseline clinical characteristics are related to relapse within six months after successful ECT in patients with severe LLD. METHODS: 110 patients with LLD from the prospective naturalistic follow-up Mood Disorders in Elderly treated with Electro-Convulsive Therapy (MODECT) study were included. A total of 73 patients (66.4%) remitted after ECT, six patients had missing information on relapse, rendering to a total sample size of 67 patients. Relapse within six months after ECT was defined as a Montgomery Åsberg Depression Scale (MADRS)-score > 15, readmission or restart of ECT. Logistic regression analyses were conducted to examine the association between baseline clinical characteristics and relapse. RESULTS: A total of 22 patients (32.8%) experienced a relapse. Patients with psychotic depression were less likely to relapse (odds ratio = 0.32, p = .047), corrected for prior admissions; 76.9% of patients with psychotic depression remained remitted. LIMITATIONS: Due to its naturalistic design, no firm conclusions can be drawn on the effect of post-ECT treatment. CONCLUSIONS: Patients with psychotic depression had a lower risk to experience relapse after successful ECT. This result strengthens the hypothesis that psychotic depression might be a specific depression subtype with a favorable ECT outcome up to six months after ECT.

Resting-state network topology and planning ability in healthy adults.

Functional magnetic resonance imaging (fMRI) studies have been used extensively to investigate the brain areas that are recruited during the Tower of London (ToL) task. Nevertheless, little research has been devoted to study the neural correlates of the ToL task using a network approach. Here we investigated the association between functional connectivity and network topology during resting-state fMRI and ToL task performance, that was performed outside the scanner. Sixty-two (62) healthy subjects (21-74 years) underwent eyes-closed rsfMRI and performed the task on a laptop. We studied global (whole-brain) and within subnetwork resting-state topology as well as functional connectivity between subnetworks, with a focus on the default-mode, fronto-parietal and dorsal and ventral attention networks. Efficiency and clustering coefficient were calculated to measure network integration and segregation, respectively, at both the global and subnetwork level. Our main finding was that higher global efficiency was associated with slower performance (ß = 0.22, Pbca = 0.04) and this association seemed mainly driven by inter-individual differences in default-mode network connectivity. The reported results were independent of age, sex, education-level and motion. Although this finding is contrary to earlier findings on general cognition, we tentatively hypothesize that the reported association may indicate that individuals with a more integrated brain during the resting-state are less able to further increase network efficiency when transitioning from a rest to task state, leading to slower responses. This study also adds to a growing body of literature supporting a central role for the default-mode network in individual differences in cognitive performance.