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Background: ¹³ C magnetic resonance spectroscopy (MRS), combined with ¹³ C‐labeled substrate infusion, offers a nonionizing, minimally invasive method for assessing fluxes through the main cerebral energy metabolism pathways. However, its human application at 7T has not been fully established, especially within the frontal lobe, where alterations are linked to various neurological and psychiatric disorders. Purpose: To explore the feasibility of the interleaved ¹ H / ¹³ C MRS protocol for quantification of cerebral glucose uptake and downstream metabolism at 7T, and to estimate the tricarboxylic acid ( TCA ) cycle flux ( V _TCA ) for validation. Study Type: Prospective. Population: Three healthy volunteers (Two females and one male). Field Strength/Sequence: 7T; single voxel spectroscopy: ACE‐STEAM (indirect ¹ H‐[ ¹³ C]) and ISIS‐DEPT (direct ¹³ C‐[ ¹ H]). Assessment: ACE‐STEAM and ISIS‐DEPT were applied to acquire the time‐resolved spectra in the frontal lobe. ¹³ C‐labeled glucose, glutamate, and glutamine fractional enrichment time courses were quantified to estimate V _TCA through the one‐compartment model. Statistical Tests: The relative estimated fitting uncertainties (EFUs) were reported for the processed spectra. Nonlinear least squares minimization was used for flux fitting of ¹³ C traces. Uncertainty of the estimated metabolic fluxes was evaluated using Monte Carlo simulations. Results: [1‐ ¹³ C]‐glucose (GlcC1) was detected within 6 min on ¹³ C MR spectra, followed by ¹³ C‐labeled GluH4 and GlnH4, and then GlxH3 can be quantified on ¹ H MR spectra. End‐of‐infusion mean enrichments were 17% (GluH4), 13% (GlnH4), and 7% (GlxH3). Brain glucose concentration ranged 1.86–2.94 mM, with 61% of the mean enrichment in C1. Group‐average V _TCA was 0.66 ± 0.07 μmol/g/min ( n = 3). Data Conclusion: This interleaved ¹ H/ ¹³ C MRS protocol, combined with ¹³ C‐labeled glucose infusion, enables minimally invasive quantification of cerebral metabolic fluxes. As a proof‐of‐concept feasibility study in a small healthy volunteer cohort, it may provide a useful framework for investigating neuropsychiatric and neurodegenerative diseases at 7T. Evidence Level: 1. Technical Efficacy: Stage 1.

Schizophrenia presents with several partially independent symptom dimensions, including positive symptoms, negative symptoms, and cognitive impairment; yet no neuroimaging framework has provided individual-level markers of symptom severity that remain anatomically interpretable. Here, we present an interpretable AI-based framework that addresses this gap by mapping high-dimensional resting-state rs-fMRI dynamics onto a low-dimensional latent manifold using self-supervised contrastive learning with a new attribution method to localize the highest decodable regions. Applied to two independent schizophrenia-spectrum cohorts, the label-free latent space supports individual-level prediction across clinical features of the disorder, including symptom severity and cognitive function. The attribution maps identify a disease-specific pathological footprint concentrated in prefrontal, posterior cerebellar and temporal areas that diverge from the manifold organization observed in healthy controls, which was dominated by auditory, limbic, and ventral-striatal circuits. These results establish an interpretable latent space framework for characterizing the distributed neural substrates of schizophrenia symptoms at the level of the individual patient, and provide an anatomically grounded route toward precision decoding of symptom severity.

Neurology and psychiatry have operated as separate disciplines for over a century, yet this division reflects historical and institutional developments rather than the underlying biology of the brain. Contemporary neuroscience shows that brain and mental health disorders share genetic susceptibilities, inflammatory and metabolic pathways, environmental and social risk factors, and clinical features that cross diagnostic boundaries. Cognitive, emotional, sensory, and motor symptoms regularly appear across both neurological and psychiatric populations, and conditions such as seizures, psychosis, mood disorders, cognitive disorders, and sleep disorders are common to both. A brain health framework addresses this reality by treating the brain as a single biological organ whose function emerges from the interplay between genome and exposome – including stress, trauma, social context, existential meaning, pollution, and physical health – and which underlies perception, behaviour, cognition, emotion, resilience, and vulnerability. Translating this perspective into practice requires coordinated action across domains. Clinically, collaborative models such as joint neurology–psychiatry consultations and shared outpatient pathways can be implemented within existing resources to improve diagnostic clarity and continuity of care. In training, a more harmonised curriculum with shared foundations in neurobiology, joint seminars, and cross-rotations would equip clinicians with a common language while preserving specialist depth, and support the emerging fields of preventive neurology and preventive psychiatry. In research, organising studies around shared mechanisms and symptom dimensions, and launching joint funding calls, would enhance translational relevance and reduce duplication. To realise this vision, sustained leadership from European professional bodies is essential to establish collaboration as a shared professional standard.

Apathy is a leading driver of functional disability in schizophrenia, yet effective mechanism-based therapies are lacking. We evaluated whether cerebellum–ventral tegmental area functional connectivity (CB-VTA FC) meets the criteria for clinical translation as a therapeutic neuromodulation target. Using resting-state fMRI in three independent repeated-imaging cohorts (healthy controls, early psychosis or chronic schizophrenia patients, minutes–months inter-scan intervals), CB-VTA FC was always stable and individual-specific (stability r =0.52–0.69; differential identifiability Δ r =0.21–0.35; all p n =99; r LL=0.36, p =2.65·10⁻L; chronic schizophrenia, Lobules VIIB/VIIIA: n =87 scans [65 patients]; t LL=4.06, p =1.1·10⁻L). In a meta-analysis of 39 randomized controlled transcranial magnetic stimulation trials ( n =1,624; 867 active), connectivity of neighboring areas to stimulation site predicted negative symptoms improvement. CB-VTA FC thus emerges as a stable, individual-specific, and symptom-related therapeutically relevant circuit, constituting a mechanism-informed precision neuromodulation target in schizophrenia, ready for prospective clinical trials. One-sentence summary: Cerebellum-ventral tegmental area functional connectivity is stable over time, differs across subjects, and its intensity is associated with the severity of apathy in schizophrenia.

Summary: Background: Brain disorders are leading contributors to increasing disability and spending worldwide. In 2022 the Swiss Brain Health Plan (SBHP) was launched to promote brain health and prevent brain disorders. To guide the implementation of the SBHP, we performed a detailed analysis of the health and economic burden of brain disorders in Switzerland. Methods: We analyzed Global Burden of Disease 2023 disability-adjusted life years (DALYs) and Institute for Health Metrics and Evaluation (IHME) cause-specific health-care spending estimates for Switzerland. DALYs were quantified for 1990 – 2023. Spending was analyzed for 2000 – 2019 across six types of care. We examined age and sex patterns, spending distribution, and international comparisons with six other countries (Germany, France, Denmark, Norway, Italy, Singapore). To assess short- and longer-term association between burden and spending estimates, we fitted panel regression models with disorder and year fixed effects under one-year and five-year lag specifications. Findings: Both disease burden and spending were highly concentrated in a small number of conditions in Switzerland. In 2023, ten brain disorders accounted for 82·9% of Switzerland’s total DALY burden. In 2019, ten brain disorders accounted for 86·0% of all direct brain-health spending, with dementia alone comprising 29·5% of total expenditures. Among seven analyzed comparator countries, Switzerland had the highest per-capita brain-health spending and the highest spending per DALY. In fixed-effects panel models that accounted for spending persistence, lagged DALYs were not statistically associated with subsequent spending. Suicide prevention and addiction showed significant lower-than-expected health-sector spending (self-harm: β = -0·23; drug use disorders: β = -0·08 to -0·18 across lag models). Interpretation: Brain disorders generate a large burden in Switzerland. Within the IHME estimates, the burden–spending relationship over time appears limited. The implementation of the SBHP will refer to the current data and call for a burden-informed financing to guide strategic cross-sectorial allocation and prevention investments. Research in context: Evidence before this study: We drew on evidence from the Global Burden of Disease (GBD) 2023 estimates on neurological and mental health conditions, and on cause-specific health-care spending data from the Institute for Health Metrics and Evaluation for Switzerland and selected high-income countries. These sources show that brain disorders are major contributors to disability and premature mortality, and that Switzerland is among the world’s highest spenders per capita on health care. Prior work has described the costs of individual brain disorders and drivers of health expenditure growth; however, it has often treated burden and spending as partly separate domains, leaving the country-level link between cause-specific disability-adjusted life-years (DALYs) and cause-specific spending, over time and in either direction, poorly characterized. Added value of this study: To our knowledge, this is the first study in a single country to systematically link cause-specific DALYs and cause-specific direct health-care spending for brain disorders and to examine their longitudinal and bi-directional associations. Using harmonized GBD 2023 estimates and IHME 2019 cause-specific health spending data, we quantify the health and economic burden of 23 brain disorders in Switzerland across age, sex, care setting, and time, and benchmark patterns against six other high-income countries. By applying panel regression models with disorder and year fixed effects, we assess whether modeled spending shows any association with prior modeled burden once spending persistence is accounted for, and identify conditions with higher or lower spending relative to burden. Implications of all the available evidence: Switzerland bears a major burden of brain disorders and devotes substantial resources to their care, yet within the modeled estimates, spending does not consistently correspond to burden over time. Disorders with long-standing multisectoral programs tended to show lower spending-to-burden ratios, suggesting that coordinated action beyond the health sector may reduce downstream health-sector demand. For Switzerland and similar health systems, these findings support national brain-health strategies that strengthen life-course prevention and early intervention, and that integrate financing with burden data to inform priority setting and periodic reassessment of resource allocation.

Positive and negative schizotypy reflect distinct patterns of subclinical traits in the general population associated with neurodevelopmental and schizophrenia-spectrum pathologies. Yet, a comprehensive characterization of the unique and shared neuroanatomical signatures of these schizotypy dimensions is lacking. Leveraging 3D brain MRI data from 2730 unmedicated healthy individuals, we identified neuroanatomical profiles of positive and negative schizotypy and systematically compared them with disorder-specific, microarchitectural, neurotransmitter-level, and connectome measures. Positive and negative schizotypy were associated with distinct cortical signatures, of predominantly thinner frontal and thicker paralimbic cortical areas, respectively. These cortical signatures of positive and negative schizotypy were differentially linked to brain-wide cortical patterns of schizophrenia-spectrum (clinical high-risk for psychosis, schizophrenia) and neurodevelopmental conditions (ADHD, autism spectrum disorder and 22q11.2 deletion syndrome). Additionally, the positive and negative schizotypy-related cortical profiles mapped onto different local attributes of gene expression, cortical myelination, D1, and histamine receptor distributions. Network models further showed that positive and negative schizotypy cortical signatures were spatially associated with cortical hubs, suggesting that highly interconnected regions are more vulnerable to the morphological differences associated with both schizotypy dimensions. Finally, predominantly sensorimotor-to-association and paralimbic areas emerged as epicenters with connectivity profiles significantly linked to the schizotypy-related cortical patterns. Collectively, this study identified cortical signatures of positive and negative schizotypy traits that are embedded along multiple scales of cortical organization and neuropsychiatric pathologies. Our work yields novel insights into how neurobiology and brain architecture may guide neuroanatomical vulnerability and resilience to psychopathology in the general population.

Background: Brain disorders are leading contributors to disability worldwide, yet it is unclear whether health-care spending reflects their burden. In 2022 the Swiss Brain Health Plan (SBHP) was launched to promote brain health and prevent brain disorders. The implementation of the SBHP includes a detailed analysis of the burden of brain disorders.Methods: We analyzed Global Burden of Disease 2021 disability-adjusted life years (DALYs) and Institute for Health Metrics and Evaluation (IHME) cause-specific health-care spending estimates for Switzerland. DALYs were quantified for 1990 – 2021 with projections to 2050. Spending was analyzed for 2000 – 2019 across six types of care. We examined age and sex patterns, spending distribution, and international comparisons with six other countries (Germany, France, Denmark, Norway, Italy, Singapore). To assess short- and longer-term association between burden and spending estimates, we fitted panel regression models with disorder and year fixed effects under one-year and five-year lag specifications.Findings: Both disease burden and spending were highly concentrated in a small number of conditions in Switzerland. In 2021, ten brain disorders accounted for 82·9% of Switzerland’s total DALY burden. In 2019, ten brain disorders accounted for 86·0% of all direct brain-health spending, with dementia alone comprising 29·5% of total expenditures. Switzerland had the highest per-capita brain-health spending and the highest spending per DALY among the seven analyzed countries. In fixed-effects panel models that accounted for spending persistence, lagged DALYs were not statistically associated with subsequent spending. Suicide prevention and addiction showed lower-than-expected health-sector spending (self-harm: β = -0·20; drug use disorders: β = -0·08 to -0·17 across lag models).Interpretation: Brain disorders generate a large burden in Switzerland. Within the IHME estimates, the burden–spending relationship over time appears limited. The implementation of the SBHP will refer to the current data and call for a burden-informed financing to guide strategic allocation and prevention investments.

Global population aging and increased chronic stress due to numerous mass disasters including those related to pandemics, climate change, war, displacement, and political unrest all challenge our collective resilience, with a growing burden of late-life neuropsychiatric and neurodegenerative disorders placing unprecedented demands on health and social systems worldwide. With these considerations in mind, understanding and promoting brain health is becoming a priority for the prevention of neuropsychiatric disorders across the lifespan. Brain health represents a dynamic balance of neural, cognitive, and emotional processes that determine resilience to neuropsychiatric illness. In later life, this balance becomes particularly critical as neurobiological and psychosocial stressors converge to shape trajectories of neuropsychiatric and neurodegenerative disorders. This review synthesizes current evidence on the determinants of brain health in aging, emphasizing resilience as a modifiable pathway linking neuropsychiatric illness risk and prevention. We integrate insights from neuroscience, lifestyle medicine, geroscience, and social determinants of health to emphasize the value of a whole-person, life-course approach. Particular attention is given to the interplay between stress physiology, interoceptive regulation, emotional resilience, and cognitive and brain reserve across the aging continuum. Emerging frameworks including brain clocks, precision biomarkers, digital phenotyping, and artificial intelligence, are considered as tools for risk stratification, early detection, and personalized intervention. By linking resilience mechanisms to measurable biological indices, we argue for the integration of neurobiological, psychological, behavioral, and sociocultural domains to inform next-generation strategies in neuropsychopharmacology, prevention science, and the promotion of healthy brain aging.

Negative, positive, and cognitive symptoms of schizophrenia relate to disruptions in partially distinct brain circuits. Although promising, transcranial magnetic stimulation (TMS) strategies across and within symptom domains remain to be established due to TMS protocol heterogeneity. For this, we combined standard meta-analysis with electric field (E-field) modeling to identify stimulation sites where E-field strength was associated most significantly with clinical improvement. Standard meta-analysis of randomized, sham-controlled studies in 4283 patients demonstrated the benefit of TMS across symptom domains, regardless of target or protocol. TMS significantly improved negative and cognitive symptoms with high-frequency stimulation applied to the left prefrontal cortex, whereas positive symptoms improved with low-frequency TMS applied to the left temporoparietal cortex. In-depth examination of these results with E-field modeling identified stimulation of the left dorsomedial prefrontal cortex (L-DMPFC), left orbitofrontal cortex (L-OFC), and left cerebellar crus II and right lobule IX to be significantly associated with improvement across all symptom domains. Greater overlap of studies’ stimulation targets with L-DMPFC and L-OFC related to improved outcomes. For negative symptoms, E-field distribution in L-DMPFC and L-OFC related most significantly to clinical improvement. Greater proximity to L-DMPFC stimulation site indicated better outcomes, with trend-level significance for L-OFC. In the cognitive domain, E-field distribution in the left dorsolateral prefrontal cortex was related to clinical improvement. Finally, the strongest E-field association with clinical improvement was found in the right cerebellar lobules VIIIA, VIIIB, and IX for positive symptoms. These results support symptom-general and symptom-specific TMS approaches for distinct therapeutic goals towards personalized neuromodulation in schizophrenia.