Schemas allow efficient behavior in new situations, but reliance on them can impair flexibility when new demands conflict. Evidence implicates the orbitofrontal cortex (OFC) in deploying schemas in new situations. But how does this role affect learning of a conflicting schema? Here we addressed this question by recording or transiently inactivating OFC neurons in rats learning odor problems with identical external information but orthogonal rules governing reward. OFC representations adapted to track the underlying rules, and both performance and encoding were faster on subsequent than initial problems. Surprisingly, when the rule changed, persistent representation of the prior schema predicted faster acquisition of the new, and disrupting OFC activity during initial schema learning, later impaired acquisition of the second schema. Thus, rather than interfering with new learning, OFC neural activity was linked to improved acquisition by preserving accurate representations of the prior schema alongside the new one.
BACKGROUND:GM1 gangliosidosis, caused by biallelic variants in GLB1, results from deficiency of lysosomal β-galactosidase, which degrades GM1 ganglioside. This fatal neurodegenerative disease currently has no effective therapy. METHODS:In a phase 1-2, open-label, dose-escalation study, we assessed immunosuppression and a single intravenous infusion of adeno-associated virus serotype 9 (AAV9) encoding β-galactosidase in children with type II GM1 gangliosidosis with late-infantile or juvenile onset. The primary end point was safety. Secondary end points included changes from baseline in the cerebrospinal fluid (CSF) GM1 ganglioside concentration and β-galactosidase activity, clinical assessments (including the Clinical Global Impression-Improvement [CGI-I] score, assessed on a scale from 1 [very much improved] to 7 [very much worse]), and neuroimaging patterns. RESULTS:Nine participants were enrolled. Over a 3-year period, 124 adverse events occurred, 30 of which (8 gastrointestinal events, 21 laboratory abnormalities associated with inflammation, and 1 tachycardia event) were deemed by the investigator as being possibly, probably, or definitely related to the gene therapy. Five serious adverse events occurred, including vomiting that led to hospitalization in one participant, which was attributed to the gene therapy. Serum aspartate and alanine aminotransferase levels increased in all participants and returned to baseline levels by 18 months. In all participants, the CSF β-galactosidase level increased and CSF GM1 ganglioside level decreased. Expressive communication and gross motor scores appeared stable, but fine motor and receptive communication scores decreased. The median CGI-I score was 3 (indicating minimal improvement) at 2 years and 4 (indicating no change) at 3 years; in historical controls, scores have been shown to increase (indicating worsening) over time. Neuroimaging showed patterns consistent with reduced rates of cerebral atrophy and favorable changes in myelination as compared with baseline. CONCLUSIONS:In this study involving nine participants with type II GM1 gangliosidosis, a single infusion of AAV9 encoding β-galactosidase was associated with adverse events, including severe vomiting in one participant and elevated liver-enzyme levels in all participants. Secondary end-point results suggested improvements in biochemical markers and neuroimaging patterns and stable or reduced rates of developmental deterioration in some measures. (Funded by the National Human Genome Research Institute and others; ClinicalTrials.gov number, NCT03952637.).
Background Bipolar disorder (BD) is known to be highly heritable. Relatives of those with BD have been observed to experience a range of psychiatric symptoms, yet the extent to which particular symptoms reflect BD risk genes is largely unknown. To address this question, we are investigating the co-heritability of BD and nine dimensions of psychopathology in a family sample. Methods Affected probands and their family members enrolled in the Amish Mennonite Bipolar Genetics (AmBiGen) study completed the Symptom Checklist Questionnaire Revised (SCL-90-R), which measures 9 dimensions of psychopathology. Each participant was assigned a Best Estimate Final Diagnosis (BEFD) using one or more of the following: Diagnostic Interview for Genetics Studies (DIGS), Family Interview for Genetic Studies (FIGS), medical records, Mood Disorder Questionnaire, Past History Schedule, and SCL-90-R. Of the 501 participants, 224 were determined to be unaffected by any mental health disorder, 122 were determined to be affected with BP, and 155 were determined to be affected with one or more other mental health diagnoses. Participants’ genotypes were determined via SNP array genotyping. Polygenic risk scores (PRS) were calculated through published genome-wide association studies (GWAS) in independent samples. The heritability and co-heritability of psychopathological dimensions will be assessed through Sequential Oligogenic Linkage Analysis Routines (SOLAR) and the Genomic Relationship Matrix (GRM). The association between psychopathological dimensions and PRS for BP and various other psychiatric traits will also be assessed. Results Preliminary results indicate a broad range of psychopathology in this high-risk sample. Compared to healthy participants, those affected with BD or related disorders showed elevated scores for all dimensions of psychopathology, especially obsessive-compulsive traits, depression, and interpersonal sensitivity. It is expected that some of these dimensions will be co-heritable with BD or other disorders. PRS associations may align with co-heritability findings, while differences could reflect rare risk alleles. Discussion Since genetic risk for BD is expressed differently across individuals, some psychopathological dimensions could be more related to genetic risk for BD, while others may reflect distinct risk profiles, such as other genetic risk factors, comorbidity, and life experiences. Determining the phenotypes associated with genetic risk for BD in those with and without a BD diagnosis will give a clearer understanding of how genetic risk of BD is expressed among relatives and which symptoms may be most predictive of BD among high-risk individuals.
Background Mental health conditions contribute substantially to the global burden of disease, affecting quality of life and leading to increased health-care expenses and mortality. Accurate data on the prevalence and correlates of these disorders are crucial for policy making, advocacy, and improving population health, but there are notable gaps in the available data on the magnitude of mental health difficulties around the world. This study aims to identify and quantify the data gaps on mental disorders across the lifespan in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021. Methods We analysed the nationally representative data sources used by GBD 2021 on 11 mental health conditions, including neurodevelopmental disorders and neurodivergence, general psychiatric disorders, and substance-use disorders. Our analysis focused on the geographical origin of the data sources, the age groups and mental health conditions or neurodivergence covered, and temporal trends on the scientific production of data. Findings GBD 2021 identified 1241 unique nationally representative data sources for mental health conditions since 1950. Neurodevelopmental disorders and neurodivergence had the least coverage, with less than 13% of countries having prevalence data. Low-income countries had the largest data gap, with no data on neurodevelopmental disorders and neurodivergence, only 29% with any data on general psychiatric disorders, and 21% with data on substance-use disorders. The African and Western Pacific regions had the largest data gaps, and children were the least covered demographic: almost 90% of countries did not have any data for children. Most data (70-80% across disorders) were obtained before 2010. Interpretation Substantial gaps in prevalence data persist globally, particularly in children and in low-income countries. Despite increased scientific production in the 2000s, most mental disorders remain under-represented. Coordinated global efforts are required to enhance mental health data collection and address these gaps. Funding Coordena & ccedil;& atilde;o de Aperfei & ccedil;oamento de Pessoal de N & iacute;vel Superior-Brasil. Copyright (c) 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license.
Reservoir computers (RCs) are a class of recurrent neural networks that incorporate brain-inspired principles and provide an efficient alternative to deep learning. With fixed random internal connections and trained output weights, they simplify learning but remain sensitive to hyperparameters governing activation and connectivity. While various hyperparameters are commonly tuned, the relative balance between excitatory and inhibitory (E-I) signals-fundamental to brain function-is typically fixed in RCs. Here, we investigate tuning this balance and show that strong performance consistently arises in balanced or slightly over-inhibited regimes, not excitation-dominated ones. Further, we introduce a self-adapting mechanism that locally adjusts E-I balance to achieve target firing rates, reducing hyperparameter tuning costs and yielding up to 130% performance gains in memory capacity and time-series prediction. Incorporating heterogeneity in firing-rate targets further enhances robustness. These findings highlight dynamic adaptation as a promising design principle, improving RC performance while offering insights into neural computation.
