A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC).

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

Childhood adversity, stress reactivity, and structural brain measures in stress-related/neurodevelopmental disorders, and their comorbidity: A large transdiagnostic cross-sectional study.

Childhood adversity (CA), including childhood adverse life events, increases the risk for development of psychiatric disorders later in life. Both CA and psychiatric disorders are associated with structural brain changes and dysfunctional hypothalamic-pituitary-adrenal-axis. However, many studies investigated single diagnostic and single regions of interest of the brain, and did not take stress reactivity into account. We investigated associations of CA and cortisol levels with gray matter volume and cortical thickness, in a whole-brain manner. Primary analysis constituted of a transdiagnostic approach, followed by a moderation analysis to investigate the influence of diagnosis. Patients with stress-related and/or neurodevelopmental disorders and matched healthy controls underwent an magnetic resonance imaging scan, next to assessing hair cortisol levels and CA/life events. CA was reported by 62-72% of the patients versus 33% of the controls. Primary transdiagnostic linear regression analyses revealed that CA was not associated with gray matter volume, while childhood life events were associated with lower right thalamic volume. Hair cortisol was not associated with any lobe volume. None of the associations were moderated by diagnosis. In conclusion, CA is a risk factor that needs to be taken into account when investigating psychiatric disorders. Yet the relationship with structural brain changes and stress reactivity is less clear than postulated on the basis of more seed-based studies.

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting. METHODS: Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier. RESULTS: Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC). CONCLUSIONS: These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression.

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Structural Changes in Depressed Patients Directly After Treatment With Electroconvulsive Therapy and 3 Months Later.

OBJECTIVES: It is assumed that neuroplasticity plays a central role in the effect of electroconvulsive therapy (ECT) on patients with major depressive disorder. We carried out an explorative study to map out the extent in which gray matter volume changes could be found directly after ECT treatment and after follow-up. METHODS: Initially, 12 patients with treatment-resistant depression were recruited from the Radboud Medical Center. Magnetic resonance imaging scans were conducted at the following 3 time points: before ECT (n = 12), after ECT (n = 10), and at 3-month follow-up (n = 8). Subcortical volume, hippocampal subfield volume, and cortical thickness were analyzed using FreeSurfer. RESULTS: The extensive, generalized changes in gray matter volume are largely transient after treatment with ECT, with the noted exceptions being a sustained increase in volume of the right amygdala and a part of the left cornu ammonis. Post hoc testing revealed no significant correlation with clinical response. DISCUSSION: Our results suggest that the neuroplastic effects of ECT may not be mediators of clinical response and could be transient epiphenomena.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Age-related change in cortical thickness in adolescents at clinical high risk for psychosis: a longitudinal study.

Progression to psychosis has been associated with increased cortical thinning in the frontal, temporal and parietal lobes in individuals at clinical high risk for the disorder (CHR-P). The timing and spatial extent of these changes are thought to be influenced by age. However, most evidence so far stems from adult samples. Longitudinal studies are essential to understanding the neuroanatomical changes associated to transition to psychosis during adolescence, and their relationship with age. We conducted a longitudinal, multisite study including adolescents at CHR-P and healthy controls (HC), aged 10-17 years. Structural images were acquired at baseline and at 18-month follow-up. Images were processed with the longitudinal pipeline in FreeSurfer. We used a longitudinal two-stage model to compute the regional cortical thickness (CT) change, and analyze between-group differences controlling for age, sex and scan, and corrected for multiple comparisons. Linear regression was used to study the effect of age at baseline. A total of 103 individuals (49 CHR-P and 54 HC) were included in the analysis. During follow-up, the 13 CHR-P participants who transitioned to psychosis exhibited greater CT decrease over time in the right parietal cortex compared to those who did not transition to psychosis and to HC. Age at baseline correlated with longitudinal changes in CT, with younger individuals showing greater cortical thinning in this region. The emergence of psychosis during early adolescence may have an impact on typical neuromaturational processes. This study provides new insights on the cortical changes taking place prior to illness onset.

Challenging the negative learning bias hypothesis of depression: reversal learning in a naturalistic psychiatric sample.

BACKGROUND: Classic theories posit that depression is driven by a negative learning bias. Most studies supporting this proposition used small and selected samples, excluding patients with comorbidities. However, comorbidity between psychiatric disorders occurs in up to 70% of the population. Therefore, the generalizability of the negative bias hypothesis to a naturalistic psychiatric sample as well as the specificity of the bias to depression, remain unclear. In the present study, we tested the negative learning bias hypothesis in a large naturalistic sample of psychiatric patients, including depression, anxiety, addiction, attention-deficit/hyperactivity disorder, and/or autism. First, we assessed whether the negative bias hypothesis of depression generalized to a heterogeneous (and hence more naturalistic) depression sample compared with controls. Second, we assessed whether negative bias extends to other psychiatric disorders. Third, we adopted a dimensional approach, by using symptom severity as a way to assess associations across the sample. METHODS: We administered a probabilistic reversal learning task to 217 patients and 81 healthy controls. According to the negative bias hypothesis, participants with depression should exhibit enhanced learning and flexibility based on punishment v. reward. We combined analyses of traditional measures with more sensitive computational modeling. RESULTS: In contrast to previous findings, this sample of depressed patients with psychiatric comorbidities did not show a negative learning bias. CONCLUSIONS: These results speak against the generalizability of the negative learning bias hypothesis to depressed patients with comorbidities. This study highlights the importance of investigating unselected samples of psychiatric patients, which represent the vast majority of the psychiatric population.

rTMS combined with CBT as a next step in antidepressant non-responders: a study protocol for a randomized comparison with current antidepressant treatment approaches.

BACKGROUND: Major depressive disorder (MDD) is one of the most common psychiatric disorders, however, current treatment options are insufficiently effective for about 35% of patients, resulting in treatment-resistant depression (TRD). Repetitive transcranial magnetic stimulation (rTMS) is a form of non-invasive neuromodulation that is effective in treating TRD. Not much is known about the comparative efficacy of rTMS and other treatments and their timing within the treatment algorithm, making it difficult for the treating physician to establish when rTMS is best offered as a treatment option. This study aims to investigate the (cost-)effectiveness of rTMS (in combination with cognitive behavioral therapy (CBT) and continued antidepressant medication), compared to the next step in the treatment algorithm. This will be done in a sample of patients with treatment resistant non-psychotic unipolar depression. METHODS: In this pragmatic multicenter randomized controlled trial 132 patients with MDD are randomized to either rTMS or the next pharmacological step within the current treatment protocol (a switch to a tricyclic antidepressant or augmentation with lithium or a second-generation antipsychotic). Both groups also receive CBT. The trial consists of 8 weeks of unblinded treatment followed by follow-up of the cohort at four and 6 months. A subgroup of patients (n = 92) will have an extended follow-up at nine and 12 months to assess effect decay or retention. We expect that rTMS is more (cost-)effective than medication in reducing depressive symptoms in patients with TRD. We will also explore the effects of both treatments on symptoms associated with depression, e.g. anhedonia and rumination, as well as the effect of expectations regarding the treatments on its effectiveness. DISCUSSION: The present trial aims to inform clinical decision making about whether rTMS should be considered as a treatment option in patients with TRD. The results may improve treatment outcomes in patients with TRD and may facilitate adoption of rTMS in the treatment algorithm for depression and its implementation in clinical practice. TRIAL REGISTRATION: This trial is registered within the Netherlands Trial Register (code: NL7628 , date: March 29th 2019).

The Role of Perseverative Cognition for Both Mental and Somatic Disorders in a Naturalistic Psychiatric Patient Sample.

OBJECTIVE: Perseverative cognition (PC) is the repeated or long-term activation of the cognitive representation of psychological stressors and is associated with prolonged stress including somatic and mental consequences. Hence, PC might represent a cognitive process linking mental and somatic pathology, but current research on this link is limited by investigating healthy samples, markers of somatic disease, and single disorders. The present study explored the importance of PC for different mental and somatic disorders in psychiatric patients. METHODS: Data from 260 naturalistic psychiatric outpatients were used. Psychiatric diagnoses were based on structured clinical interviews. Somatic diseases were assessed using a well-validated questionnaire and were clustered into (cardio)vascular and immune/endocrine diseases. PC was operationalized using the Perseverative Thinking Questionnaire (PTQ). RESULTS: Multiple regression complemented with relative importance analyses showed that the PTQ total and subscale scores were associated with the presence of mood disorders, addiction, and anxiety. Unexpectedly, no relatively important associations were found between the PTQ and autism spectrum disorder, attention-deficit/hyperactivity disorder, or somatic disease. CONCLUSIONS: Our data complement previous work linking PC to stress-related mental disorders but question its immediate role in neurodevelopmental and somatic disorders. Targeting PC in the treatment of mood disorders and perhaps also in addiction seems promising.

Longitudinal effects of rTMS on neuroplasticity in chronic treatment-resistant depression.

Major depressive disorder (MDD) is amongst the most prevalent of psychiatric disorders. Unfortunately, a third of patients will not respond to conventional treatments and suffer from treatment-resistant depression (TRD). Repetitive transcranial magnetic stimulation (rTMS) has been proven effective in treating TRD. The research suggests that rTMS acts via neuroplastic effects on the brain, which can be measured by changes in hippocampal and amygdala volume as well as cortical thickness. This sham-controlled study investigates longitudinal effects of rTMS on the volumes of the hippocampus and amygdala and cortical thickness in patients with chronic TRD. 31 patients received 20 sessions of high-frequency rTMS (N = 15) or sham treatment (N = 16) over the left dorsolateral prefrontal cortex during 4 consecutive weeks. Using structural magnetic resonance imaging, we investigated longitudinal treatment effects on hippocampus and amygdala volume as well as thickness of the paralimbic cortex. We found no clinical differences between the active and sham rTMS group. Longitudinal changes in hippocampal and amygdala volume did not differ significantly, although males showed a significant decrease in left amygdala volume, irrespective of treatment group. Changes in cortical thickness of the paralimbic cortex differed significantly between the active and sham groups. Most notably, the increase in cortical thickness of the isthmus of the left cingulate gyrus was greater in the active as compared to the sham rTMS group. Our data suggest that rTMS can induce neuroplastic changes, particularly in cortical thickness, independent of treatment response. We also found longitudinal changes in amygdala volume in males. For clinical effects to follow these neuroplastic effects, more intensive rTMS treatment might be needed in chronically depressed patients.Trial registration number: ISRCTN 15535800, registered on 29-06-2017.

Inflammation, Hippocampal Volume, and Therapeutic Outcome following Electroconvulsive Therapy in Depressive Patients: A Pilot Study.

INTRODUCTION: Electroconvulsive therapy (ECT) influences the concentration of peripheral inflammatory markers, such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). In which way this immune effect contributes to the impact of ECT on the central nervous system in depression remains unknown. OBJECTIVE: The aim of this study was to examine whether the hippocampal volumetric increase in depressed patients treated with ECT is related to changes in peripheral IL-6 and TNF-α levels. METHODS: IL-6 and TNF-α plasma levels were measured in 62 patients 1 week before and after an acute course of ECT. Hippocampal volumes were analyzed in a magnetic resonance imaging (MRI) subsample of 13 patients at the same time points. RESULTS: A significant decrease in IL-6 levels was observed in the total sample and a significant increase in hippocampal volume in the MRI subsample. The reduction of peripheral IL-6 correlated with an increase in total hippocampal volume. A more limited decrease of TNF-α correlated with a more limited increase of both the total and left hippocampus volumes. CONCLUSION: This pilot study is the first to highlight the link between peripheral immune changes and hippocampal volume increase following ECT. Further research is required to conclude whether ECT indeed exerts its central effect on the brain via changes of peripheral inflammatory markers.

Decreased Cognitive Functioning After Electroconvulsive Therapy Is Related to Increased Hippocampal Volume: Exploring the Role of Brain Plasticity.

OBJECTIVE: Electroconvulsive therapy (ECT) is still the most effective treatment of severe and therapy-refractory major depressive disorder. Cognitive side effects are the major disadvantage of ECT. Cognitive deficits are generally temporary in nature and may be mediated by the hippocampus. Recent studies have shown a temporary increase in hippocampal volume and a temporary decrease in cognitive functioning post-ECT compared with pre-ECT. This study investigates whether these volumetric changes are related to changes in cognitive functioning after ECT. METHODS: Nineteen medication-free patients with treatment-resistant major depressive disorder underwent a whole-brain magnetic resonance imaging scan and a neuropsychological examination (including the Rey auditory verbal learning task, Wechsler Memory Scale Visual Reproduction, fluency, Trail Making Task) within 1 week before and within 1 week after the course of ECT. Electroconvulsive therapy was administered twice a week bitemporally with a brief pulse. A matched healthy control group (n = 18) received the same neuropsychological examination and at a similar interval to that of the patients. RESULTS: Hippocampal volumes increased significantly from pretreatment to posttreatment in patients. Mean performance on cognitive tasks declined, or remained stable, whereas performance in controls generally improved because of retesting effects. The increase in hippocampal volume was related to changes in cognitive performance, indicating that this increase co-occurred with a decrease in cognitive functioning. CONCLUSIONS: Our findings tentatively suggest that the temporal increase in hippocampal volume after treatment, which may result from neurotrophic processes and is thought to be crucial for the antidepressive effect, is also related to the temporary cognitive side effects of ECT.

rTMS as a Next Step in Antidepressant Nonresponders: A Randomized Comparison With Current Antidepressant Treatment Approaches.

OBJECTIVE: Although repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, little is known about the comparative effectiveness of rTMS and other treatment options, such as antidepressants. In this multicenter randomized controlled trial, rTMS was compared with the next pharmacological treatment step in patients with treatment-resistant depression. METHODS: Patients with unipolar nonpsychotic depression (N=89) with an inadequate response to at least two treatment trials were randomized to treatment with rTMS or to a switch of antidepressants, both in combination with psychotherapy. Treatment duration was 8 weeks and consisted of either 25 high-frequency rTMS sessions to the left dorsolateral prefrontal cortex or a switch of antidepressant medication following the Dutch treatment algorithm. The primary outcome was change in depression severity based on the Hamilton Depression Rating Scale (HAM-D). Secondary outcomes were response and remission rates as well as change in symptom dimensions (anhedonia, anxiety, sleep, rumination, and cognitive reactivity). Finally, expectations regarding treatment were assessed. RESULTS: rTMS resulted in a significantly larger reduction in depressive symptoms than medication, which was also reflected in higher response (37.5% vs. 14.6%) and remission (27.1% vs. 4.9%) rates. A larger decrease in symptoms of anxiety and anhedonia was observed after rTMS compared with a switch in antidepressants, and no difference from the medication group was seen for symptom reductions in rumination, cognitive reactivity, and sleep disorders. Expectations regarding treatment correlated with changes in HAM-D scores. CONCLUSIONS: In a sample of patients with moderately treatment-resistant depression, rTMS was more effective in reducing depressive symptoms than a switch of antidepressant medication. In addition, the findings suggest that the choice of treatment may be guided by specific symptom dimensions.

The gut-microbiome in adult Attention-deficit/hyperactivity disorder - A Meta-analysis.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition that persists into adulthood in the majority of individuals. While the gut-microbiome seems to be relevant for ADHD, the few publications on gut-microbial alterations in ADHD are inconsistent, in the investigated phenotypes, sequencing method/region, preprocessing, statistical approaches, and findings. To identify gut-microbiome alterations in adult ADHD, robust across studies and statistical approaches, we harmonized bioinformatic pipelines and analyses of raw 16S rRNA sequencing data from four adult ADHD case-control studies (NADHD=312, NNoADHD=305). We investigated diversity and differential abundance of selected genera (logistic regression and ANOVA-like Differential Expression tool), corrected for age and sex, and meta-analyzed the study results. Converging results were investigated for association with hyperactive/impulsive and inattentive symptoms across all participants. Beta diversity was associated with ADHD diagnosis but showed significant heterogeneity between cohorts, despite harmonized analyses. Several genera were robustly associated with adult ADHD; e.g., Ruminococcus_torques_group (LogOdds=0.17, pfdr=4.42 × 10-2), which was more abundant in adults with ADHD, and Eubacterium_xylanophilum_group (LogOdds= -0.12, pfdr=6.9 × 10-3), which was less abundant in ADHD. Ruminococcus_torques_group was further associated with hyperactivity/impulsivity symptoms and Eisenbergiella with inattention and hyperactivity/impulsivity (pfdr<0.05). The literature points towards a role of these genera in inflammatory processes. Irreproducible results in the field of gut-microbiota research, due to between study heterogeneity and small sample sizes, stress the need for meta-analytic approaches and large sample sizes. While we robustly identified genera associated with adult ADHD, that might overall be considered beneficial or risk-conferring, functional studies are needed to shed light on these properties.

Dissecting task-based fMRI activity using normative modelling: an application to the Emotional Face Matching Task.

Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N = 7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals' transdiagnostic functioning. Taken together, we demonstrate that normative modelling of fMRI task-activation can be used to illustrate the influence of different task choices and map replicable individual differences, and we encourage its application to other neuroimaging tasks in future studies.

Pre-treatment predictors of cognitive side-effects after treatment with electroconvulsive therapy in patients with depression: A multicenter study.

BACKGROUND: Electroconvulsive therapy (ECT) is a highly effective treatment for major depressive episodes (MDE). However, ECT-induced cognitive side-effects remain a concern. Identification of pre-treatment predictors that contribute to these side-effects remain unclear. We examined cognitive performance and individual cognitive profiles over time (up to six months) following ECT and investigated possible pre-treatment clinical and demographic predictors of cognitive decline shortly after ECT. METHODS: 634 patients with MDE from five sites were included with recruitment periods between 2001 and 2020. Linear mixed models were used to examine how cognitive performance, assessed with an extensive neuropsychological test battery, evolved over time following ECT. Next, possible pre-treatment predictors of cognitive side-effects directly after ECT were examined using linear regression. RESULTS: Directly after ECT, only verbal fluency (animal and letter; p < 0.0001; Cohen's d: -0.25 and -0.29 respectively) and verbal recall (p < 0.0001; Cohen's d: -0.26) significantly declined. However, during three and six months of follow-up, cognitive performance across all domains significantly improved, even outperforming baseline levels. No other pre-treatment factor than a younger age predicted a larger deterioration in cognitive performance shortly after ECT. LIMITATIONS: There was a substantial amount of missing data especially at 6 months follow-up. CONCLUSIONS: Our findings show that verbal fluency and memory retention are temporarily affected immediately after ECT. Younger patients may be more susceptible to experiencing these acute cognitive side-effects, which seems to be mostly due to a more intact cognitive functioning prior to ECT. These findings could contribute to decision-making regarding treatment selection, psychoeducation, and guidance during an ECT course.

Autistic and non-autistic individuals show the same amygdala activity during emotional face processing.

BACKGROUND: Autistic and non-autistic individuals often differ in how they perceive and show emotions, especially in their ability and inclination to infer other people's feelings from subtle cues like facial expressions. Prominent theories of autism have suggested that these differences stem from alterations in amygdala functioning and that amygdala hypoactivation causes problems with emotion recognition. Thus far, however, empirical investigations of this hypothesis have yielded mixed results and largely relied on relatively small samples. METHODS: In a sample of 72 autistic and 79 non-autistic participants, we conducted a study in which we used the Hariri paradigm to test whether amygdala activation during emotional face processing is altered in autism spectrum disorder, and whether common mental disorders like depression, ADHD or anxiety disorders influence any potential alterations in activation patterns. RESULTS: We found no evidence for differences in amygdala activation, neither when comparing autistic and non-autistic participants, nor when taking into account mental disorders or the overall level of functional impairment. LIMITATIONS: Because we used one basic emotion processing task in a Dutch sample, results might not generalise to other tasks and other populations. CONCLUSIONS: Our results challenge the view that autistic and non-autistic processing of emotional faces in the amygdala is vastly different and call for a more nuanced view of differences between non-autistic and autistic emotion processing.

The sensitivity of the Mini-Mental State Examination to detect objective cognitive side-effects induced by electroconvulsive therapy, results from the Dutch ECT Consortium.

BACKGROUND: Monitoring cognitive side-effects following electroconvulsive therapy (ECT) is crucial for balancing side-effects and clinical effectiveness. Unfortunately, evidence-based guidelines on cognitive testing following ECT are lacking. A frequently used test in global ECT practice is the Mini Mental State Examination (MMSE). We examined the change of the MMSE and its performance in identifying a decline in predefined neuropsychological measures sensitive to ECT-induced cognitive changes: verbal recall and verbal fluency. METHODS: The mean MMSE scores pre- and one week post-ECT were compared using a Wilcoxon signed-rank test. The Reliable Change Index was calculated for all cognitive measures to indicate whether an individual's change score from pre- to post-ECT is considered statistically significant. The sensitivity and specificity of the MMSE were calculated. RESULTS: 426 patients with depression from five sites were included from the Dutch ECT Consortium. The mean MMSE increased significantly from 26.2 (SD=3.9) pre-ECT to 26.8 (SD=3.8) post-ECT (p=0.002). 36 patients (8.5%) showed a significant decline in MMSE score post-ECT. The sensitivity of the MMSE in identifying patients who experienced a significant decline in verbal recall or verbal fluency ranged from 3.6% to 11.1%. The specificity of the MMSE in identifying patients who did not experience a significant decline in verbal recall or verbal fluency ranged from 95.6% to 96.6%. CONCLUSIONS: Given the very low sensitivity of the MMSE, we propose reconsidering the prominence of the MMSE in ECT practice and cognitive monitoring guidelines, advocating for a more comprehensive approach to assess ECT-induced cognitive changes.