Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (ß = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

Development of Peptide-Based Probes for Molecular Imaging of the Postsynaptic Density in the Brain.

The postsynaptic density (PSD) comprises numerous scaffolding proteins, receptors, and signaling molecules that coordinate synaptic transmission in the brain. Postsynaptic density protein 95 (PSD-95) is a master scaffold protein within the PSD and one of its most abundant proteins and therefore constitutes a very attractive biomarker of PSD function and its pathological changes. Here, we exploit a high-affinity inhibitor of PSD-95, AVLX-144, as a template for developing probes for molecular imaging of the PSD. AVLX-144-based probes were labeled with the radioisotopes fluorine-18 and tritium, as well as a fluorescent tag. Tracer binding showed saturable, displaceable, and uneven distribution in rat brain slices, proving effective in quantitative autoradiography and cell imaging studies. Notably, we observed diminished tracer binding in human post-mortem Parkinson's disease (PD) brain slices, suggesting postsynaptic impairment in PD. We thus offer a suite of translational probes for visualizing and understanding PSD-related pathologies.

Arterial Spin Labeling Magnetic Resonance Imaging for Acute Disorders of Consciousness in the Intensive Care Unit.

BACKGROUND: To investigate patients with disorders of consciousness (DoC) for residual awareness, guidelines recommend quantifying glucose brain metabolism using positron emission tomography. However, this is not feasible in the intensive care unit (ICU). Cerebral blood flow (CBF) assessed by arterial spin labeling magnetic resonance imaging (ASL-MRI) could serve as a proxy for brain metabolism and reflect consciousness levels in acute DoC. We hypothesized that ASL-MRI would show compromised CBF in coma and unresponsive wakefulness states (UWS) but relatively preserved CBF in minimally conscious states (MCS) or better. METHODS: We consecutively enrolled ICU patients with acute DoC and categorized them as being clinically unresponsive (i.e., coma or UWS [≤ UWS]) or low responsive (i.e., MCS or better [≥ MCS]). ASL-MRI was then acquired on 1.5 T or 3 T. Healthy controls were investigated with both 1.5 T and 3 T ASL-MRI. RESULTS: We obtained 84 ASL-MRI scans from 59 participants, comprising 36 scans from 35 patients (11 women [31.4%]; median age 56 years, range 18-82 years; 24 ≤ UWS patients, 12 ≥ MCS patients; 32 nontraumatic brain injuries) and 48 scans from 24 healthy controls (12 women [50%]; median age 50 years, range 21-77 years). In linear mixed-effects models of whole-brain cortical CBF, patients had 16.2 mL/100 g/min lower CBF than healthy controls (p = 0.0041). However, ASL-MRI was unable to discriminate between ≤ UWS and ≥ MCS patients (whole-brain cortical CBF: p = 0.33; best hemisphere cortical CBF: p = 0.41). Numerical differences of regional CBF in the thalamus, amygdala, and brainstem in the two patient groups were statistically nonsignificant. CONCLUSIONS: CBF measurement in ICU patients using ASL-MRI is feasible but cannot distinguish between the lower and the upper ends of the acute DoC spectrum. We suggest that pilot testing of diagnostic interventions at the extremes of this spectrum is a time-efficient approach in the continued quest to develop DoC neuroimaging markers in the ICU.

Rumination in patients with major depressive disorder before and after antidepressant treatment.

BACKGROUND: Rumination is a maladaptive response to distress characteristic of Major Depressive Disorder (MDD). It is unclear to what degree rumination is associated with depression severity prior to treatment and how it responds to antidepressant treatment. Therefore, we evaluated the association between rumination and depression severity in 92 untreated patients with MDD and explored the changes in rumination after initiation of antidepressant medication. METHOD: We measured rumination using the Rumination Response Scale (RRS) and depression severity with the Hamilton Depression Rating Scale (HDRS17 or HDRS6) before and after initiation of 12 weeks of antidepressant treatment. The association between RRS and pre-treatment HDRS17 was evaluated using a linear regression model. RRS at week 4, 8, and 12 across treatment response categories (remission vs. non-response) were evaluated using a mixed effect model. RESULTS: RRS was positively associated with depression severity prior to treatment at a trend level (p = 0.06). After initiation of treatment RRS decreased significantly (p < 0.0001) and remitters exhibited lower rumination compared to non-responders at week 4 (p = 0.03), 8 (p = 0.01), and 12 (p = 0.007). LIMITATIONS: The study had no placebo group. CONCLUSIONS: Although pre-treatment rumination did not significantly associate with depressive symptoms, rumination was closely connected to change in depressive symptoms. Tormented patients could be reassured that rumination symptoms may be alleviated over the course of antidepressant treatment.

Stable neural underpinnings of emotional cognition subgroups in patients newly diagnosed with bipolar disorder: A prospective fMRI study.

OBJECTIVES: This study aimed to investigate the neural underpinnings of emotional cognition subgroups in recently diagnosed patients with bipolar disorder (BD) and change over time over a 15-month follow-up period. METHODS: Patients and healthy controls (HC) underwent emotional and nonemotional cognitive assessments and functional magnetic resonance imaging (fMRI) at the baseline (BD n = 87; HC n = 65) and at 15-month follow-up (BD n = 44; HC n = 38). Neural activity during emotion reactivity and regulation in response to aversive pictures was assessed during fMRI. Patients were clustered into subgroups based on their emotional cognition and, with HC, were compared longitudinally on cognition and neural activity during emotion reactivity and regulation. RESULTS: Patients were optimally clustered into two subgroups: Subgroup 1 (n = 40, 46%) was characterized by heightened emotional reactivity in negative social scenarios, which persisted over time, but were otherwise cognitively intact. This subgroup exhibited stable left amygdala hyper-activity over time during emotion reactivity compared to subgroup 2. Subgroup 2 (n = 47, 54%) was characterized by global emotional cognitive impairments, including stable difficulties with emotion regulation over time. During emotion regulation across both time points, this group exhibited hypo-activity in the left dorsolateral prefrontal cortex. Additionally, patients in subgroup 2 had poorer nonemotional cognition, had more psychiatric hospital admissions and history of psychotic episodes than those in subgroup 1. CONCLUSIONS: Broad impairments in emotional cognition in approximately half of BD patients and associated nonemotional cognitive deficits may originate from insufficient recruitment of prefrontal resources, contributing to poorer clinical outcomes.

Assessment of cerebral drug occupancy in humans using a single PET-scan: A [11C]UCB-J PET study.

PURPOSE: Here, we evaluate a PET displacement model with a Single-step and Numerical solution in healthy individuals using the synaptic vesicle glycoprotein (SV2A) PET-tracer [11C]UCB-J and the anti-seizure medication levetiracetam (LEV). We aimed to (1) validate the displacement model by comparing the brain LEV-SV2A occupancy from a single PET scan with the occupancy derived from two PET scans and the Lassen plot and (2) determine the plasma LEV concentration-SV2A occupancy curve in healthy individuals. METHODS: Eleven healthy individuals (five females, mean age 35.5 [range: 25-47] years) underwent two 120-min [11C]UCB-J PET scans where an LEV dose (5-30 mg/kg) was administered intravenously halfway through the first PET scan to partially displace radioligand binding to SV2A. Five individuals were scanned twice on the same day; the remaining six were scanned once on two separate days, receiving two identical LEV doses. Arterial blood samples were acquired to determine the arterial input function and plasma LEV concentrations. Using the displacement model, the SV2A-LEV target engagement was calculated and compared with the Lassen plot method. The resulting data were fitted with a single-site binding model. RESULTS: SV2A occupancies and VND estimates derived from the displacement model were not significantly different from the Lassen plot (p = 0.55 and 0.13, respectively). The coefficient of variation was 14.6% vs. 17.3% for the Numerical and the Single-step solution in Bland-Altman comparisons with the Lassen plot. The average half maximal inhibitory concentration (IC50), as estimated from the area under the curve of the plasma LEV concentration, was 12.5 µg/mL (95% CI: 5-25) for the Single-Step solution, 11.8 µg/mL (95% CI: 4-25) for the Numerical solution, and 6.3 µg/mL (95% CI: 0.08-21) for the Lassen plot. Constraining Emax to 100% did not significantly improve model fits. CONCLUSION: Plasma LEV concentration vs. SV2A occupancy can be determined in humans using a single PET scan displacement model. The average concentration of the three computed IC50 values ranges between 6.3 and 12.5 µg/mL. The next step is to use the displacement model to evaluate LEV occupancy and corresponding plasma concentrations in relation to treatment efficacy. CLINICAL TRIAL REGISTRATION: NCT05450822. Retrospectively registered 5 July 2022 https://clinicaltrials.gov/ct2/results? term=NCT05450822&Search=Search.

Comorbid physical health burden of serious mental health disorders in 32 European countries.

BACKGROUND: Mental health disorders (MHDs) are associated with physical health disparities, but underlying excess risk and health burden have not yet been comprehensively assessed. OBJECTIVE: To assess the burden of comorbid physical health conditions (PHCs) across serious MHDs in Europe. METHODS: We estimated the relative prevalence risk of PHCs associated with alcohol use disorders (AUD), bipolar disorder (BD), depressive disorders (DD) and schizophrenia (SZ) across working-age populations of 32 European countries in 2019 based on a targeted literature review. Excess physical health burden was modelled using population-attributable fractions and country-level prevalence data. FINDINGS: We screened 10 960 studies, of which 41 were deemed eligible, with a total sample size of over 18 million persons. Relative prevalence of PHCs was reported in 54%, 20%, 15%, 5% and 7% of studies, respectively, for SZ, DD, BD, AUD or mixed. Significant relative risk estimates ranged from 1.44 to 3.66 for BD, from 1.43 to 2.21 for DD, from 0.81 to 1.97 for SZ and 3.31 for AUD. Excess physical health burden ranged between 27% and 67% of the total, corresponding to 84 million (AUD), 67 million (BD), 66 million (DD) and 5 million (SZ) PHC diagnoses in Europe. A 1% reduction in excess risk assuming causal inference could result in two million fewer PHCs across investigated MHDs. CONCLUSIONS: This is the first comprehensive study of the physical health burden of serious MHDs in Europe. The methods allow for updates, refinement and extension to other MHDs or geographical areas. CLINICAL IMPLICATIONS: The results indicate potential population health benefits achievable through more integrated mental and physical healthcare and prevention approaches.

Perivascular space diffusivity and brain microstructural measures are associated with circadian time and sleep quality.

The glymphatic system is centred around brain cerebrospinal fluid flow and is enhanced during sleep, and the synaptic homeostasis hypothesis proposes that sleep acts on brain microstructure by selective synaptic downscaling. While so far primarily studied in animals, we here examine in humans if brain diffusivity and microstructure is related to time of day, sleep quality and cognitive performance. We use diffusion weighted images from 916 young healthy individuals, aged between 22 and 37 years, collected as part of the Human Connectome Project to assess diffusion tensor image analysis along the perivascular space index, white matter fractional anisotropy, intra-neurite volume fraction and extra-neurite mean diffusivity. Next, we examine if these measures are associated with circadian time of acquisition, the Pittsburgh Sleep Quality Index (high scores correspond to low sleep quality) and age-adjusted cognitive function total composite score. Consistent with expectations, we find that diffusion tensor image analysis along the perivascular space index and orbitofrontal grey matter extra-neurite mean diffusivity are negatively and white matter fractional anisotropy positively correlated with circadian time. Further, we find that grey matter intra-neurite volume fraction correlates positively with Pittsburgh Sleep Quality Index, and that this correlation is driven by sleep duration. Finally, we find positive correlations between grey matter intra-neurite volume fraction and cognitive function total composite score, as well as negative interaction effects between cognitive function total composite score and Pittsburgh Sleep Quality Index on grey matter intra-neurite volume fraction. Our findings propose that perivascular flow is under circadian control and that sleep downregulates the intra-neurite volume in healthy adults with positive impact on cognitive function.

Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.

To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A receptors (5-HT2AR) show a particularly profound age-related decline and are also reduced in neurodegenerative disorders, such as Alzheimer's disease. This study investigates whether the decline in 5-HT2AR binding, measured in vivo using positron emission tomography (PET), can be used as a biomarker for brain aging. Specifically, we aim to (1) predict brain age using 5-HT2AR binding outcomes, (2) compare 5-HT2AR-based predictions of brain age to predictions based on gray matter (GM) volume, as determined with structural magnetic resonance imaging (MRI), and (3) investigate whether combining 5-HT2AR and GM volume data improves prediction. We used PET and MR images from 209 healthy individuals aged between 18 and 85 years (mean = 38, std = 18) and estimated 5-HT2AR binding and GM volume for 14 cortical and subcortical regions. Different machine learning algorithms were applied to predict chronological age based on 5-HT2AR binding, GM volume, and the combined measures. The mean absolute error (MAE) and a cross-validation approach were used for evaluation and model comparison. We find that both the cerebral 5-HT2AR binding (mean MAE = 6.63 years, std = 0.74 years) and GM volume (mean MAE = 6.95 years, std = 0.83 years) predict chronological age accurately. Combining the two measures improves the prediction further (mean MAE = 5.54 years, std = 0.68). In conclusion, 5-HT2AR binding measured using PET might be useful for improving the quantification of a biomarker for brain aging.

Characterizing the binding of TC-5619 and encenicline on the alpha7 nicotinic acetylcholine receptor using PET imaging in the pig.

The alpha7 nicotinic acetylcholine receptor (α7-nAChR) has has long been considered a promising therapeutic target for addressing cognitive impairments associated with a spectrum of neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, despite this potential, clinical trials employing α7-nAChR (partial) agonists such as TC-5619 and encenicline (EVP-6124) have fallen short in demonstrating sufficient efficacy. We here investigate the target engagement of TC-5619 and encenicline in the pig brain by use of the α7-nAChR radioligand 11C-NS14492 to characterize binding both with in vitro autoradiography and in vivo occupancy using positron emission tomography (PET). In vitro autoradiography demonstrates significant concentration-dependent binding of 11C-NS14492, and both TC-5619 and encenicline can block this binding. Of particular significance, our in vivo investigations demonstrate that TC-5619 achieves substantial α7-nAChR occupancy, effectively blocking approximately 40% of α7-nAChR binding, whereas encenicline exhibits more limited α7-nAChR occupancy. This study underscores the importance of preclinical PET imaging and target engagement analysis in informing clinical trial strategies, including dosing decisions.

Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder.

BACKGROUND: There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS: In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS: At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION: Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

Effects of erythropoietin on cognitive impairment and prefrontal cortex activity across affective disorders: A randomized, double-blinded, placebo-controlled trial.

BACKGROUND: Persistent cognitive impairment is frequent across bipolar disorder (BD) and major depressive disorder (MDD), highlighting an urgent need for pro-cognitive treatments. AIM: This study investigated effects of erythropoietin (EPO) on cognitive impairment and dorsal prefrontal cortex (dPFC) activity in affective disorders. METHODS: In this randomized, double-blinded, placebo-controlled trial, cognitively impaired patients with remitted BD or MDD received 1 weekly recombinant human EPO (40,000 IU/mL) or saline infusion for a 12-week period. Assessments were conducted at baseline, after 2 weeks of treatment (week 3), immediately after treatment (week 13) and at 6-months follow-up. Participants underwent functional MRI during performance on a n-back working memory (WM) task at baseline and week 3, and for a subgroup 6 weeks post-treatment (week 18). The primary outcome was a cognitive composite score at week 13, whereas secondary outcomes comprised sustained attention and functioning. WM-related dPFC activity was a tertiary outcome. RESULTS: Data were analysed for 101 of the 103 included patients (EPO, n = 58; saline, n = 43). There were no effects of EPO over saline on any cognitive or functional outcomes or on WM-related dPFC activity. CONCLUSIONS: The absence of treatment-related changes in cognition and neural activity was unexpected and contrasts with multiple previous preclinical and clinical studies. It is possible that the lack of effects resulted from a recent change in the manufacturing process for EPO. Nevertheless, the findings support the validity of dPFC target engagement as a biomarker model for pro-cognitive effects, according to which treatments that do not improve cognition should not modulate dPFC activity. TRIAL REGISTRATIONS: EudraCT no.: 2016-004023-24; ClinicalTrials.gov identifier: NCT03315897.

Functional brain responses to emotional faces after three to five weeks of intake of escitalopram in healthy individuals: a double-blind, placebo-controlled randomised study.

Short-term intake of selective serotonin reuptake inhibitors (SSRIs) modulates threat-related amygdala responses in healthy individuals. However, how SSRI intake over a clinically relevant time period modulates threat-related amygdala responses is less clear. In a semi-randomised, double-blind, placebo-controlled study of 64 healthy individuals (SSRI n = 32, placebo n = 32), we examined the effect of 3-5 weeks of SSRI escitalopram (20 mg daily) on brain response to angry, fearful and neutral faces using BOLD fMRI. Data was analysed using a whole-brain region-wise approach extracting standardised effects (i.e., Cohen's D). The study was conducted at the Copenhagen University Hospital. A priori, we hypothesised that SSRI would attenuate amygdala responses to angry and fearful faces but not to neutral ones. Whether SSRI modulates correlations between amygdala responses to emotional faces and negative mood states was also explored. Compared to placebo, 3-5 weeks of SSRI intake did not significantly affect the amygdala response to angry, fearful, or neutral faces (|Cohen's D|< 0.2, PFWER = 1). Whole-brain, region-wise analyses revealed significant differences in frontal (|Cohen's D|< 0.6, PFWER < .01) and occipital regions (|Cohen's D|< 0.5, PFWER < .01). SSRI did not modulate correlations between amygdala responses to emotional faces and negative mood states. Our findings indicate that a 3-5 week SSRI intake impacts cortical responses to emotional stimuli, an effect possibly involved in SSRI's therapeutic efficacy.Trial registration Clinical Trials NCT04239339.

Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines.

Objective. Most methods for partial volume correction (PVC) of positron emission tomography (PET) data employ anatomical segmentation of images into regions of interest. This approach is not optimal for exploratory functional imaging beyond regional hypotheses. Here, we describe a novel method for unbiased voxel-wise PVC.Approach.B-spline basis functions were combined with geometric transfer matrices to enable a method (bsGTM) that provides PVC or alternatively provides smoothing with minimal regional crosstalk. The efficacy of the proposed method was evaluated using Monte Carlo simulations, human PET data, and murine functional PET data.Main results.In simulations, bsGTM provided recovery of partial volume signal loss comparable to iterative deconvolution, while demonstrating superior resilience to noise. In a real murine PET dataset, bsGTM yielded much higher sensitivity for detecting amphetamine-induced reduction of [11C]raclopride binding potential. In human PET data, bsGTM smoothing enabled increased signal-to-noise ratios with less degradation of binding potentials relative to Gaussian convolution or non-local means.Significance.bsGTM offers improved performance for PVC relative to iterative deconvolution, the current method of choice for voxel-wise PVC, especially in the common PET regime of low signal-to-noise ratio. The new method provides an anatomically unbiased way to compensate partial volume errors in cases where anatomical segmentation is unavailable or of questionable relevance or accuracy.

CCH attack frequency reduction after psilocybin correlates with hypothalamic functional connectivity.

OBJECTIVE: To evaluate the feasibility and prophylactic effect of psilocybin as well as its effects on hypothalamic functional connectivity (FC) in patients with chronic cluster headache (CCH). BACKGROUND: CCH is an excruciating and difficult-to-treat disorder with incompletely understood pathophysiology, although hypothalamic dysfunction has been implicated. Psilocybin may have beneficial prophylactic effects, but clinical evidence is limited. METHODS: In this small open-label clinical trial, 10 patients with CCH were included and maintained headache diaries for 10 weeks. Patients received three doses of peroral psilocybin (0.14 mg/kg) on the first day of weeks five, six, and seven. The first 4 weeks served as baseline and the last 4 weeks as follow-up. Hypothalamic FC was determined using functional magnetic resonance imaging the day before the first psilocybin dose and 1 week after the last dose. RESULTS: The treatment was well tolerated. Attack frequency was reduced by mean (standard deviation) 31% (31) from baseline to follow-up (pFWER = 0.008). One patient experienced 21 weeks of complete remission. Changes in hypothalamic-diencephalic FC correlated negatively with a percent change in attack frequency (pFWER = 0.03, R = -0.81), implicating this neural pathway in treatment response. CONCLUSION: Our results indicate that psilocybin may have prophylactic potential and implicates the hypothalamus in possible treatment response. Further clinical studies are warranted.

Effect of immersive virtual reality-based cognitive remediation in patients with mood or psychosis spectrum disorders: study protocol for a randomized, controlled, double-blinded trial.

BACKGROUND: Cognitive impairments are prevalent across mood disorders and psychosis spectrum disorders, but there is a lack of real-life-like cognitive training programmes. Fully immersive virtual reality has the potential to ensure motivating and engaging cognitive training directly relevant to patients' daily lives. We will examine the effect of a 4-week, intensive virtual reality-based cognitive remediation programme involving daily life challenges on cognition and daily life functioning in patients with mood disorders or psychosis spectrum disorders and explore the neuronal underpinnings of potential treatment efficacy. METHODS: The trial has a randomized, controlled, double-blinded, parallel-group design. We will include 66 symptomatically stable outpatients with mood disorders or psychosis spectrum disorders aged 18-55 years with objective and subjective cognitive impairment. Assessments encompassing a virtual reality test of daily life cognitive skills, neuropsychological testing, measures of daily life functioning, symptom ratings, questionnaires on subjective cognitive complaints, and quality of life are carried out at baseline, after the end of 4 weeks of treatment and at a 3-month follow-up after treatment completion. Functional magnetic resonance imaging scans are performed at baseline and at the end of treatment. The primary outcome is a broad cognitive composite score comprising five subtasks on a novel ecologically valid virtual reality test of daily life cognitive functions. Two complete data sets for 54 patients will provide a power of 80% to detect a clinically relevant between-group difference in the primary outcome. Behavioural data will be analysed using linear mixed models in SPSS, while MRI data will be analysed with the FMRIB Expert Analysis Tool (FEAT). Treatment-related changes in neural activity from baseline to end of treatment will be investigated for the dorsal prefrontal cortex and hippocampus as the regions of interest. DISCUSSION: The results will provide insight into whether virtual reality-based cognitive remediation has beneficial effects on cognition and functioning in symptomatically stable patients with mood disorders or psychosis spectrum disorders, which can aid future treatment development. TRIAL REGISTRATION: ClinicalTrials.gov NCT06038955. Registered on September 15, 2023.

Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness.

BACKGROUND: In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, whereas multimodal data from acute DoC are scarce. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging (i.e. CONNECT-ME; ClinicalTrials.gov identifier: NCT02644265) investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations. METHODS: We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123). Favorable outcome was defined as a modified Rankin Scale score ≤ 3, a cerebral performance category score ≤ 2, and a Glasgow Outcome Scale Extended score ≥ 4. EEG features included visual grading, automated spectral categorization, and support vector machine consciousness classifier. fMRI features included functional connectivity measures from six resting-state networks. Random forest and support vector machine were applied to EEG and fMRI features to predict outcomes. Here, random forest results are presented as areas under the curve (AUC) of receiver operating characteristic curves or accuracy. Cox proportional regression with in-hospital death as a competing risk was used to assess independent clinical predictors of time to favorable outcome. RESULTS: Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77-0.82]) and 12-month (AUC 0.74 [95% CI 0.71-0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69-0.78) both alone and when combined with some EEG features (accuracies 0.73-0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02-1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04-3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40-5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12-5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41-15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46-4.19]). CONCLUSIONS: Our results indicate that EEG and fMRI features and readily available clinical data predict short-term outcome of patients with acute DoC and that EEG also predicts 12-month outcome after ICU discharge.

Comparable roles for serotonin in rats and humans for computations underlying flexible decision-making.

Serotonin is critical for adapting behavior flexibly to meet changing environmental demands. Cognitive flexibility is important for successful attainment of goals, as well as for social interactions, and is frequently impaired in neuropsychiatric disorders, including obsessive-compulsive disorder. However, a unifying mechanistic framework accounting for the role of serotonin in behavioral flexibility has remained elusive. Here, we demonstrate common effects of manipulating serotonin function across two species (rats and humans) on latent processes supporting choice behavior during probabilistic reversal learning, using computational modelling. The findings support a role of serotonin in behavioral flexibility and plasticity, indicated, respectively, by increases or decreases in choice repetition ('stickiness') or reinforcement learning rates following manipulations intended to increase or decrease serotonin function. More specifically, the rate at which expected value increased following reward and decreased following punishment (reward and punishment 'learning rates') was greatest after sub-chronic administration of the selective serotonin reuptake inhibitor (SSRI) citalopram (5 mg/kg for 7 days followed by 10 mg/kg twice a day for 5 days) in rats. Conversely, humans given a single dose of an SSRI (20 mg escitalopram), which can decrease post-synaptic serotonin signalling, and rats that received the neurotoxin 5,7-dihydroxytryptamine (5,7-DHT), which destroys forebrain serotonergic neurons, exhibited decreased reward learning rates. A basic perseverative tendency ('stickiness'), or choice repetition irrespective of the outcome produced, was likewise increased in rats after the 12-day SSRI regimen and decreased after single dose SSRI in humans and 5,7-DHT in rats. These common effects of serotonergic manipulations on rats and humans-identified via computational modelling-suggest an evolutionarily conserved role for serotonin in plasticity and behavioral flexibility and have clinical relevance transdiagnostically for neuropsychiatric disorders.

EEG abnormalities are not associated with poor antidepressant treatment outcome - A NeuroPharm study.

EEG brain abnormalities, such as slowing and isolated epileptiform discharges (IEDs), has previously been associated with non-response to antidepressant treatment with escitalopram and venlafaxine, suggesting a potential need for treatment with anticonvulsant property in some patients. The current study aims to replicate the reported association of EEG abnormality and treatment outcomes in an open-label trial of escitalopram for major depressive disorder (MDD) and explore its relationship to mood and cognition. Pretreatment, 6 min eyes-closed resting-state 256-channel EEG was recorded in 91 patients with MDD (age 18-57) who were treated with 10-20 mg escitalopram for 12 weeks; patients could switch to duloxetine after four weeks. A certified clinical neurophysiologist rated the EEGs. IED and EEG slowing was seen in 13.2%, and in 6.6% there were findings with unclear significance (i.e., Wicket spikes and theta activity). We saw no group-difference in remission or response rates after 8 and 12 weeks of treatment or switching to duloxetine. Patients with EEG abnormalities had higher pretreatment mood disturbances driven by greater anger (p=.039) and poorer verbal memory (p=.012). However, EEG abnormality was not associated with improved mood or verbal memory after treatment. Our findings should be interpreted in light of the rarity of EEG abnormalities and the sample size. While we cannot confirm that EEG abnormalities are associated with non-response to treatment, including escitalopram, abnormal EEG activity is associated with poor mood and verbal memory. The clinical utility of EEG abnormality in antidepressant treatment selection needs careful evaluation before deciding if useful for clinical implementation.

An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?

BACKGROUND: The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. MAIN BODY: This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF. CONCLUSION: Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.