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Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. Objective: We investigated whether there are consistent changes in effective resting-state connectivity. Methods: This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. Results: Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. Conclusions: A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.

The clinical effect of electroconvulsive therapy (ECT) is mediated by eliciting a generalized seizure, which is achieved by applying electrical current to the head via scalp electrodes. The anatomy of the head influences the distribution of current flow in each brain region. Here, we investigated whether individual differences in simulated local electrical field strength are associated with ECT efficacy. We modeled the electric field of 67 depressed patients receiving ECT. Patient’s T1 magnetic resonance images were segmented, conductivities were assigned to each tissue and the finite element method was used to solve for the electric field induced by the electrodes. We investigated the correlation between modelled electric field and ECT outcome using voxel-wise general linear models. The difference between bilateral (BL) and right unilateral (RUL) electrode placement was striking. Even within electrode configuration, there was substantial variability between patients. For the modeled BL placement, stronger electric field strengths appeared in the left hemisphere and part of the right temporal lobe. Importantly, a stronger electric field in the temporal lobes was associated with less optimal ECT response in patients treated with BL-ECT. No significant differences in electric field distributions were found between responders and non-responders to RUL-ECT. These results suggest that overstimulation of the temporal lobes during BL stimulation has negative consequences on treatment outcome. If replicated, individualized pre-ECT computer-modelled electric field distributions may inform the development of patient-specific ECT protocols.

Background: Deep brain stimulation (DBS) is a new treatment option for patients with therapy-resistant obsessive–compulsive disorder (OCD). Approximately 60% of patients benefit from DBS, which might be improved if a biomarker could identify patients who are likely to respond. Therefore, we evaluated the use of preoperative structural magnetic resonance imaging (MRI) in predicting treatment outcome for OCD patients on the group- and individual-level. Methods: In this retrospective study, we analyzed preoperative MRI data of a large cohort of patients who received DBS for OCD (n = 57). We used voxel-based morphometry to investigate whether grey matter (GM) or white matter (WM) volume surrounding the DBS electrode (nucleus accumbens (NAc), anterior thalamic radiation), and whole-brain GM/WM volume were associated with OCD severity and response status at 12-month follow-up. In addition, we performed machine learning analyses to predict treatment outcome at an individual-level and evaluated its performance using cross-validation. Results: Larger preoperative left NAc volume was associated with lower OCD severity at 12-month follow-up (pFWE

Randomized controlled trials have shown efficacy of trauma-focused psychotherapies in youth with posttraumatic stress disorder (PTSD). However, response varies considerably among individuals. Currently, no biomarkers are available to assist clinicians in identifying youth who are most likely to benefit from treatment. In this study, we investigated whether resting-state functional magnetic resonance imaging (rs-fMRI) could distinguish between responders and non-responders on the group- and individual patient level. Pre-treatment rs-fMRI was recorded in 40 youth (ages 8–17 years) with (partial) PTSD before trauma-focused psychotherapy. Change in symptom severity from pre- to post-treatment was assessed using the Clinician-Administered PTSD scale for Children and Adolescents to divide participants into responders (≥30% symptom reduction) and non-responders. Functional networks were identified using meta-independent component analysis. Group-differences within- and between-network connectivity between responders and non-responders were tested using permutation testing. Individual predictions were made using multivariate, cross-validated support vector machine classification. A network centered on the bilateral superior temporal gyrus predicted treatment response for individual patients with 76% accuracy (pFWE = 0.02, 87% sensitivity, 65% specificity, area-under-receiver-operator-curve of 0.82). Functional connectivity between the frontoparietal and sensorimotor network was significantly stronger in non-responders (t = 5.35, pFWE = 0.01) on the group-level. Within-network connectivity was not significantly different between groups. This study provides proof-of-concept evidence for the feasibility to predict trauma-focused psychotherapy response in youth with PTSD at an individual-level. Future studies are required to test if larger cohorts could increase accuracy and to test further generalizability of the prediction models.

Background: Gamma-hydroxybutyric acid (GHB) is a recreational drug associated with increasing numbers of GHB-dependent patients and emergency attendances often related to GHB-induced comas. Working memory (WM) deficits have been reported in association with GHB use, and animal studies have shown that GHB induces oxidative stress in vulnerable WM-related brain areas such as the dorsolateral prefrontal cortex (DLPFC). However, the effects of chronic GHB use and multiple GHB-induced comas on WM-related brain function in humans remains unknown. Methods: We recruited 27 GHB users with ≥4 GHB-induced comas (GHB-Coma), 27 GHB users who never experienced GHB-induced coma (GHB-NoComa), and 27 polydrug users who never used GHB (No-GHB). Participants performed an n-back WM task during functional magnetic resonance imaging (fMRI) to probe DLPFC functioning. Results: The GHB-Coma group had lower premorbid IQ (p = .006) than the GHB-NoComa group despite comparable age and education level. There were also group differences in the use of other drugs than GHB. Therefore, all group comparisons were adjusted for IQ and drug use other than GHB. Compared with the GHB-NoComa and the No-GHB groups, the GHB-Coma group showed increased activity in the right DLPFC (pSVC = 0.028) and increased functional connectivity of the right DLPFC with a cluster comprising the left anterior cingulate and medial frontal gyrus (pFWE = 0.003). No significant fMRI differences were observed between the GHB-NoComa and No-GHB groups. Due to technical problems, no behavioural data were collected. Discussion: These results suggest that multiple GHB-induced comas, but not GHB-use per se, are associated with alterations in WM-related brain function. Public awareness campaigns are required to minimize the potential adverse effects induced by GHB recreational use, and especially GHB-induced comas, even if no immediate side effects are experienced. Keywords: Functional magnetic resonance imaging (fMRI), Functional connectivity, Drug addiction, Gamma-Hydroxybutyric acid (GHB) abuse, GHB-induced coma, Working memory

Background: Deep brain stimulation (DBS) is an innovative treatment for treatment-refractory depression. DBS is usually targeted at specific anatomical landmarks, with patients responding to DBS in approximately 50% of cases. Attention has recently shifted to white matter tracts to explain DBS response, with initial open-label trials targeting white matter tracts yielding much higher response rates (>70%). Objective/Hypothesis: Our aim was to associate distance to individual white matter tracts around the stimulation target in the ventral anterior limb of the internal capsule to treatment response. Methods: We performed diffusion magnetic resonance tractography of the superolateral branch of the medial forebrain bundle and the anterior thalamic radiation in fourteen patients that participated in our randomized clinical trial. We combined the tract reconstructions with the postoperative images to identify the DBS leads and estimated the distance between tracts and leads, which we subsequently associated with treatment response. Results: Stimulation closer to both tracts was significantly correlated to a larger symptom decrease (r = 0.61, p = 0.02), suggesting that stimulation more proximal to the tracts was beneficial. Biophysical modelling indicated that 37.5% of tracts were even outside the volume of activated tissue. There was no difference in lead placement with respect to anatomical landmarks, which could mean that differences in treatment response were driven by individual differences in white matter anatomy. Conclusions: Our results suggest that deep brain stimulation of the ventral anterior limb of the internal capsule could benefit from targeting white matter bundles. We recommend acquiring diffusion magnetic resonance data for each individual patient.

Given the restricted total scanning time for clinical neuroimaging, it is unclear whether clinical diffusion MRI protocols would benefit more from higher spatial resolution or higher angular resolution. In this work, we investigated the relative benefit of improving spatial or angular resolution in diffusion MRI to separate two parallel running white matter tracts that are targets for deep brain stimulation: the anterior thalamic radiation and the supero-lateral branch of the medial forebrain bundle. Both these tracts are situated in the ventral anterior limb of the internal capsule, and recent studies suggest that targeting a specific tract could improve treatment efficacy. Therefore, we scanned 19 healthy volunteers at 3T and 7T according to three diffusion MRI protocols with respectively standard clinical settings, increased spatial resolution of 1.4 mm, and increased angular resolution (64 additional gradient directions at b = 2200s/mm2). We performed probabilistic tractography for all protocols and quantified the separability of both tracts. The higher spatial resolution protocol improved separability by 41% with respect to the clinical standard, presumably due to decreased partial voluming. The higher angular resolution protocol resulted in increased apparent tract volumes and overlap, which is disadvantageous for application in precise treatment planning. We thus recommend to increase the spatial resolution for deep brain stimulation planning to 1.4 mm while maintaining angular resolution. This recommendation complements the general advice to aim for high angular resolution to resolve crossing fibers, confirming that the specific application and anatomical considerations are leading in clinical diffusion MRI protocol optimization. Keywords: Diffusion MRI, Tractography, Deep brain stimulation, Internal capsule, Angular and spatial resolution