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Pleasure and motivation are important factors for goal-directed behavior and well-being in both animals and humans. Intact hedonic capacity requires an undisturbed interplay between a number of different brain regions and transmitter systems. Concordantly, dysfunction of networks encoding for reward have been shown in depression and other psychiatric disorders. The development of technological possibilities to investigate connectivity on a functional level in humans and to directly influence networks in animals using optogenetics among other techniques has provided new important insights in this field of research.In this review, we aim to provide an overview on the neurobiological substrates of anhedonia on a network level. For this purpose, definition of anhedonia and the involved reward components are described first, then current data on reward networks in healthy individuals and in depressed patients are summarized, and the roles of different neurotransmitter systems involved in reward processing are specified. Based on this information, the impact of different therapeutic approaches on reward processing is described with a particular focus on deep brain stimulation (DBS) as a possibility for a direct modulation of human brain structures in vivo.Overall, results of current studies emphasize the importance of anhedonia in psychiatric disorders and the relevance of targeting this phenotype for a successful psychiatric treatment. However, more data incorporating these results for the refinement of methodological approaches are needed to be able to develop individually tailored therapeutic concepts based on both clinical and neurobiological profiles of patients.

Treatment outcomes for major depressive disorder (MDD) need to be improved. Presently, no clinically relevant tools have been established for stratifying subgroups or predicting outcomes. This literature review sought to investigate factors closely linked to outcome and summarize existing and novel strategies for improvement. The results show that early recognition and treatment are crucial, as duration of untreated depression correlates with worse outcomes. Early improvement is associated with response and remission, while comorbidities prolong course of illness. Potential biomarkers have been explored, including hippocampal volumes, neuronal activity of the anterior cingulate cortex, and levels of brain-derived neurotrophic factor (BDNF) and central and peripheral inflammatory markers (e.g., translocator protein (TSPO), interleukin-6 (IL-6), C-reactive protein (CRP), tumor necrosis factor alpha (TNFα)). However, their integration into routine clinical care has not yet been fully elucidated, and more research is needed in this regard. Genetic findings suggest that testing for CYP450 isoenzyme activity may improve treatment outcomes. Strategies such as managing risk factors, improving clinical trial methodology, and designing structured step-by-step treatments are also beneficial. Finally, drawing on existing guidelines, we outline a sequential treatment optimization paradigm for selecting first-, second-, and third-line treatments for acute and chronically ill patients. Well-established treatments such as electroconvulsive therapy (ECT) are clinically relevant for treatment-resistant populations, and novel transcranial stimulation methods such as theta-burst stimulation (TBS) and magnetic seizure therapy (MST) have shown promising results. Novel rapid-acting antidepressants, such as ketamine, may also constitute a paradigm shift in treatment optimization for MDD.

The ability to solve cognitive tasks depends upon adaptive changes in the organization of whole-brain functional networks. However, the link between task-induced network reconfigurations and their underlying energy demands is poorly understood. We address this by multimodal network analyses integrating functional and molecular neuroimaging acquired concurrently during a complex cognitive task. Task engagement elicited a marked increase in the association between glucose consumption and functional brain network reorganization. This convergence between metabolic and neural processes was specific to feedforward connections linking the visual and dorsal attention networks, in accordance with task requirements of visuo-spatial reasoning. Further increases in cognitive load above initial task engagement did not affect the relationship between metabolism and network reorganization but only modulated existing interactions. Our findings show how the upregulation of key computational mechanisms to support cognitive performance unveils the complex, interdependent changes in neural metabolism and neuro-vascular responses.

Background:Many patients with obsessive-compulsive disorder do not respond adequately to serotonin reuptake inhibitors. Augmentation with antipsychotic drugs can be beneficial in this regard. However, since new relevant randomized controlled trials evaluating new antipsychotics were conducted, a recalculation of the effect sizes appears necessary.Methods:We meta-analyzed all double-blind, randomized, placebo-controlled trials comparing augmentation of serotonin reuptake inhibitors with antipsychotics to placebo supplementation in treatment-resistant obsessive-compulsive disorder. The primary outcome was mean change in the Yale-Brown Obsessive–Compulsive Scale total score. Secondary outcomes were obsessions, compulsions, response rates, and attrition rates. The data collection process was conducted independently by 2 authors. Hedges’s g and risks ratios were calculated as effect sizes. In preplanned meta-regressions, subgroup analyses, and sensitivity analyses, we examined the robustness of the results and explored reasons for potential heterogeneity.Results:Altogether, 14 double-blind, randomized, placebo-controlled trials (n=491) investigating quetiapine (N=4, n=142), risperidone (N=4, n=132), aripiprazole (N=2, n=79), olanzapine (N=2, n=70), paliperidone (N=1, n=34), and haloperidol (N=1, n=34) were incorporated. Augmentation with antipsychotics was significantly more efficacious than placebo in Yale-Brown Obsessive–Compulsive Scale total reduction (N=14, n=478; Hedges’s g=-0.64, 95% CI: -0.87 to -0.41; P=<.01). Aripiprazole (Hedges’s g=-1.35), haloperidol (Hedges’s g=-0.82), and risperidone (Hedges’s g=-0.59) significantly outperformed placebo. Antipsychotics were superior to placebo in treating obsessions, compulsions, and achieving response. There was no between-group difference concerning all-cause discontinuation. The nonsignificant meta-regressions suggest no influence of the antipsychotic dose or baseline symptom severity on the meta-analytic results.Conclusions:According to our findings, antipsychotic augmentation of serotonin reuptake inhibitors can be regarded as an evidence-based measure in treatment-resistant obsessive-compulsive disorder.

Social anxiety disorder patients suffer from excessive anxious responses in social interaction leading to avoidance behavior and social impairment. Although the amygdala has a central role in perception and processing of threatening cues, little is known about the involved networks and corresponding dysfunctions in social anxiety. Therefore, this study aims to investigate the functional connectivity network of the amygdala in patients with social anxiety disorder and to identify regions that might influence amygdalar reactivity via modulatory pathways. Ten patients with anxiety disorders (social and/or panic) and 27 healthy controls underwent a facial emotion processing task as well as 6-min functional MRI at resting state. Individual voxel-wise functional connectivity maps were calculated using the amygdala as seed region. Group comparisons were done by random-effects analysis in SPM. Patients exhibited an amygdala hyperactivation during the emotional task and decreased functional coupling of the left amygdala with the medial orbitofrontal cortex and the posterior cingulate cortex/precuneus. The strength of this functional connectivity showed a negative association with the severity of state anxiety. In addition, an exploratory analysis revealed further reduced functional connectivity and a marked functional separation between the medial orbitofrontal and anterior cingulate cortices in the patient group. Our results suggest alterations within the amygdalar functional connectivity network in social anxiety disorder. Combined with the amygdalar hyperactivation our findings corroborate the proposed dysfunction of the fronto-amygdalar inhibition in anxiety disorders and indicate a modulatory influence of the anterior and posterior cingulate cortices on threat perception and processing. ►Resting state functional connectivity of amygdala in social anxiety disorder. ►Reduced amygdala connectivity with orbitofrontal and posterior cingulate cortices. ►Decreased coupling between orbitofrontal and anterior cingulate cortices.

Introduction: Although post-COVID-19 syndrome (PCS) with cognitive impairment is increasingly encountered in primary care, evidence-based recommendations for its appropriate management are lacking. Methods: A systematic literature search evaluating the diagnosis and treatment of cognitive impairment associated with PCS was conducted. Practical recommendations for the management of PCS-associated cognitive impairment in primary care are summarized, based on an evaluation of pharmacological plausibility and clinical applications. Results: Currently, the pathology of cognitive impairment associated with PCS remains unclear with no high-quality data to support targeted interventions. Existing treatment approaches are directed towards symptom relief where counseling on the chronicity of the disease and regular reassessments at 4- to 8-week intervals is considered reasonable. Patients should be informed and encouraged to adopt a healthy lifestyle that centers around balanced nutrition and appropriate physical activities. They may also benefit from the intake of vitamins, micronutrients, and probiotics. The administration of Ginkgo biloba extract could offer a safe and potentially beneficial treatment option. Other non-pharmacological measures include physiotherapy, digitally supported cognitive training, and, if indicated, ergotherapy or speech therapy. In most patients, symptoms improve within 8 weeks. If serious, ambiguous, or when new symptoms occur, specialized diagnostic measures such as comprehensive neurocognitive testing or neuroimaging should be initiated. Very few patients would require inpatient rehabilitation. Conclusion: PCS with cognitive impairment is a debilitating condition that could affect daily functioning and reduce work productivity. Management in primary care should adopt a multidisciplinary approach, centering around physical, cognitive, and pharmacological therapies.

Electroconvulsive therapy (ECT) is the treatment of choice for severe mental illness including treatment-resistant depression (TRD). Increases in volume of the hippocampus and amygdala following ECT have consistently been reported.AimsTo investigate neuroplastic changes after ECT in specific hippocampal subfields and amygdala nuclei using high-resolution structural magnetic resonance imaging (MRI) (trial registration: clinicaltrials.gov - NCT02379767). MRI scans were carried out in 14 patients (11 women, 46.9 years (s.d. = 8.1)) with unipolar TRD twice before and once after a series of right unilateral ECT in a pre-post study design. Volumes of subcortical structures, including subfields of the hippocampus and amygdala, and cortical thickness were extracted using FreeSurfer. The effect of ECT was tested using repeated-measures ANOVA. Correlations of imaging and clinical parameters were explored. Increases in volume of the right hippocampus by 139.4 mm3 (s.d. = 34.9), right amygdala by 82.3 mm3 (s.d. = 43.9) and right putamen by 73.9 mm3 (s.d. = 77.0) were observed. These changes were localised in the basal and lateral nuclei, and the corticoamygdaloid transition area of the amygdala, the hippocampal-amygdaloid transition area and the granule cell and molecular layer of the dentate gyrus. Cortical thickness increased in the temporal, parietal and insular cortices of the right hemisphere. Following ECT structural changes were observed in hippocampal subfields and amygdala nuclei that are specifically implicated in the pathophysiology of depression and stress-related disorders and retain a high potential for neuroplasticity in adulthood.Declaration of interestS.K. has received grants/research support, consulting fees and/or honoraria within the past 3 years from Angelini, AOP Orphan Pharmaceuticals AG, AstraZeneca, Celegne GmbH, Eli Lilly, Janssen-Cilag Pharma GmbH, KRKA-Pharma, Lundbeck A/S, Neuraxpharm, Pfizer, Pierre Fabre, Schwabe and Servier. R.L. received travel grants and/or conference speaker honoraria from Shire, AstraZeneca, Lundbeck A/S, Dr. Willmar Schwabe GmbH, Orphan Pharmaceuticals AG, Janssen-Cilag Pharma GmbH, and Roche Austria GmbH.

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl-11C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. •Comprehensive mRNA expression atlases in MNI and surface space for each gene.•Gaussian process regression corrects bias from non-uniform distribution of samples.•Improved correlation with PET data shown for the serotonin 1A receptor.•Models of spatial dependence vary across brain structures for each gene.•High spatially structured variability indicates relevant topology of transcription.

Neural plasticity is a complex process dependent on neurochemical underpinnings. Next to the glutamatergic system which contributes to memory formation via long-term potentiation (LTP) and long-term depression (LTD), the main inhibitory neurotransmitter, GABA is crucially involved in neuroplastic processes. Hence, we investigated changes in glutamate and GABA levels in the brain in healthy participants performing an associative learning paradigm. Twenty healthy participants (10 female, 25 ± 5 years) underwent paired multi-voxel magnetic resonance spectroscopy imaging before and after completing 21 days of a facial associative learning paradigm in a longitudinal study design. Changes of GABA and glutamate were compared to retrieval success in the hippocampus, insula and thalamus. No changes in GABA and glutamate concentration were found after 21 days of associative learning. However, baseline hippocampal GABA levels were significantly correlated with initial retrieval success (pcor = 0.013, r = 0.690). In contrast to the thalamus and insula (pcor>0.1), higher baseline GABA levels in the hippocampus were associated with better retrieval performance in an associative learning paradigm. Therefore, our findings support the importance of hippocampal GABA levels in memory formation in the human brain in vivo. ∙Hippocampal GABA levels correlate with retrieval performance.∙No changes of GABA and glutamate levels after three weeks of associative learning.∙Baseline glutamate levels show no correlations with retrieval success.∙High GABA levels in the hippocampus show positive effects on retrieval performance.

Background: As many patients with unipolar depression do not respond sufficiently to initial antidepressant monotherapy, a dose increase of the current administered antidepressant (dose escalation, high-dose treatment) is frequently carried out as next treatment measure. Methods: We conducted a meta-analysis which included all double-blind randomized controlled trials (RCTs) comparing a dose increase of antidepressants directly to continuation of standard-dose treatment in unipolar depressive patients who were non- responders to standard-dose pharmacotherapy. A mean change in the Hamilton Rating Scale for Depression (HAM-D) total score was the primary outcome. Secondary outcomes were response rates and discontinuation rates due to any reason, inefficacy, and adverse effects. Hedges g and risk ratios were calculated as effect sizes. Results: Seven double-blind RCTs (8 study arms) representing 1,208 participants were included. Fluoxetine (N [number of studies] = 2, n [number of patients] = 448), sertraline (N = 2, n = 272), paroxetine (N = 2, n = 146), duloxetine (N = 1, n = 255), and maprotiline (N = 1, n = 87) were investigated. Dose escalation was not more efficacious in HAM-D total score reduction than maintaining standard-dose treatment, neither for the pooled antidepressant group (N = 7, n = 999; Hedges g = -0.04, 95% CI: -0.20 to 0.12; p = 0.63) nor the individual antidepressants. No differences could be determined for response rates, all-cause discontinuation, and drop-outs due to inefficacy. Significantly more patients in the dose escalation group dropped out due to adverse effects than in the standard-dose continuation group. The metaregressions indicate no influence of baseline symptom severity or amounts of dose increments on effect sizes. Conclusions: According to our meta-analytic findings, dose escalation after initial non-response to standard-dose pharmacotherapy cannot be regarded as general evidence-based treatment option in unipolar depression.