Brain Imaging and Behavior

BackgroundTo understand the neurobiology underlying psychopathology, we need valid measurements of brain function. Group atlases for brain functional connectivity (FC) allow for efficient comparisons, but they fail to account for inter-individual variability in network topography, a problem that personalized methods address. We assess the validity and predictive utility of group and personalized approaches of quantifying FC by 1) comparing effect sizes of associations with clinical metrics; and 2) accounting for spatial features of brain networks when examining the association between FC and clinical metrics. Methods324 teens ages 13-16 participated. Personalized networks were estimated using a hierarchical Bayesian model. Effect size comparisons were done by comparing the correlations between FC and clinical metrics (depression, ruminative coping style, and sensitivity to punishment/reward) with Steiglers Z-test. We also conducted regressions, with clinical metrics as the dependent variables. Those models included FC and spatial features, together and alone. ResultsThe effect size comparisons did not survive FDR correction. However, exploratory permutation tests show that 1) the magnitude of the correlations with depression are larger on average for the intersection estimates of FC than the group estimates; and 2) the magnitude of the correlations with a ruminative coping style are larger on average for the intersection estimates of FC than the personalized estimate. The other comparisons conducted using permutation tests are not significant. Multiple regression analyses demonstrated that only spatial features of networks, not FC, are associated with sensitivity to reward. DiscussionThese results imply that the intersection estimates are more valid than the group estimates, and that the intersection estimates have greater predictive utility than personalized estimates. Further, spatial features of functions networks may be useful in and of themselves in certain contexts. Therefore, researchers in psychiatry should take into consideration functional network topography in order to gain a better understanding of the neurobiology underlying psychopathology.

IntroductionWe present here a methodology for morphometric analysis of the substantia nigra (SN), the ventral tegmental area (VTA), the dorsal raphe nucleus (DRN) and their respective structural brain circuits. MethodsOur analyses were based on multimodal T1-weighted MRI and diffusion MRI (dMRI) segmentation and tractography in 12 human subjects drawn from the Human Connectome Project (HCP) repository. ResultsWe were able to demonstrate strong connections of the SN, VTA and DRN with several brain regions, in particular the dorsolateral prefrontal cortex (DLPFC) and the cerebellum. More specifically, we created comprehensive visualizations of the SN and VTA dopaminergic as well as the DRN serotonergic structural circuits in the human brain, which, although preliminary, demonstrate the potential of multimodal neuroimaging to investigate these circuits quantitatively in clinical conditions. Finally, we created a pilot dataset for the most frequently observed structural connections, specifically those that were present more than 92% of the time among all subjects. Discussion This pilot morphometric report examines the structural circuits of the SN, VTA and DRN, which are critically involved in several biobehaviors and clinical conditions such as addiction, stress, Parkinsons disease (PD), schizophrenia, obsessive-compulsive disorder, post-traumatic stress disorder, attention deficit hyperactivity disorder, mood disorders, COVID-19 and long COVID. Importantly, the strong structural connectivity of the DLPFC and cerebellum with the SN, VTA and DRN is expected to be a potential target of noninvasive neuromodulation treatments in neuropsychiatry. Our findings demonstrate the potential of current clinical multimodal neuroimaging to delineate the dopaminergic (DA) and serotonergic (5-HT) circuits in the human brain in clinical conditions.

Self-referential processing is a fundamental cognitive function, and abnormalities in its neural implementation have been reported across a range of psychiatric disorders, leading to the proposal that such alterations may constitute a transdiagnostic neurobiological feature. Yet claiming transdiagnostic requires rigorous evidence. Here, we examined the evidence for such a hypothesis by conducting a systematic review and coordinate-based meta-analysis of psychiatric neuroimaging studies that employed self-referential tasks. The systematic review identified 36 neuroimaging studies across 9 broad categories of psychiatric disorders, suggesting that the neural aberrancy of self-referential processing is indeed of great interest across different diagnosis. Of these, 27 studies were eligible for the ALE meta-analysis. The ALE results revealed hypoactivation of the right precuneus in psychiatric groups relative to health controls, alongside hyperactivation of the right triangular part of the inferior frontal gyrus (IFGtri) during self-referential processing in psychiatric groups. Notably the precuneus and IFGtri are core nodes of the default mode network and the frontal-parietal control network, respectively, suggesting that aberrant self-referential processing across psychiatric disorders may be characterized by disrupted default mode network engagement accompanied by compensatory or maladaptive recruitment of control-related frontal regions. Together, our findings revealed a strong research interest in neural aberrancy of self-referential processing as a transdiagnostic feature. However, available evidence only provided preliminary evidence for such statement. To move forward, the field needs coordinated efforts to systematically accumulate data and collecting new datasets.

ObjectivesThis study examined whether bilingualism is associated with episodic memory (EM) and executive function (EF) in older Mandarin-speaking adults and whether associations differ by clinical diagnosis. Methods189 Mandarin-speaking older adults completed Mandarin-administered neuropsychological testing, brain MRI, and clinical diagnosis. English proficiency test was administered to determine whether they were bilinguals or monolinguals. Sensitivity analyses were conducted in an education-matched subgroup (16 years). ResultsBilingualism was associated with higher EF, with a significant bilingualism x diagnosis interaction indicating larger bilingual advantages among cognitively impaired participants. However, bilingualism was not associated with EM. Findings were preserved in education-matched analysis. ConclusionsResults support a domain-specific association between bilingualism and executive function in later life, consistent with cognitive maintenance mechanisms preferentially supporting executive processes rather than global protection.

BackgroundLarge-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics. MethodsCross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7{+/-}12.6 years) and 510 controls (33.3{+/-}12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications. ResultsBD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged. ConclusionsAs the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

BackgroundSchizophrenia is a severe neuropsychiatric disorder. Efforts to describe the underlying biology and establish diagnostic markers through non-invasive neuroimaging methods are ongoing, resulting in a range of theoretical brain-based frameworks. Prominent frameworks for aberrant schizophrenia-associated functional connectivity in resting-state functional magnetic resonance imaging (rsfMRI) include the dysconnectivity hypothesis, theory of cognitive dysmetria, and triple network theory. Although informative, prior work can be improved by increasing sample size, avoiding confirmation bias, and accounting for individual variability and the effects of medication and chronicity. MethodsWith these recommendations in mind, we employed a data-driven, whole-brain approach using a large multi-site rsfMRI dataset (N = 2,656; schizophrenia = 1,248). We used reference-guided independent component analysis (ICA) to generate subject-specific whole-brain functional network connectivity (FNC) and extract imaging markers of similarity to schizophrenia patterns. We modeled the relationship between medication dosage, age of onset, chronicity, symptom severity, and cognitive performance and FNC. ResultsOur analysis identified a reliable schizophrenia-FNC signature characterized by aberrantly stronger negative cerebellothalamic and positive thalamocortical connectivity, implicating sensory, motor, and associative cortical circuits. While medication and chronicity were significantly associated with these signatures, the core cerebellothalamic disruptions remained a robust marker of schizophrenia. ConclusionsThis work represents the largest schizophrenia-specific rsfMRI study to date, refines existing theoretical frameworks with a more nuanced map of how clinical variables interact with brain connectivity, and provides a high-fidelity template of schizophrenia-related connectivity. We have released this template as an open-source resource to facilitate reproducibility and accelerate the development of reliable rsfMRI-based schizophrenia biomarkers.

ObjectiveFinding indicators of early response to antidepressant treatment in EEG signals recorded from patients suffering from major depressive disorder. MethodsFunctional brain connectivity networks based on weighted imaginary coherence and weighted imaginary mean phase coherence were computed for 176 patients for 6 different EEG frequency bands. Cross-hemispheric connectivity (CH) and lateral asymmetry (LA) were estimated from these networks based on EEG signals recorded before the beginning of treatment (V is1) and one week after the start of the treatment (V is2). Repeated measures ANOVA was used to check for statistically significant changes in connectivity based on these measures at V is2 w.r.t. V is1. Post-hoc analysis was performed with multiple pairwise comparison tests to determine which group means were significantly different. ResultsIt was found that CHV is2 was significantly reduced w.r.t. CHV is1 in the {beta}1 [12.5 - 17.5 Hz] frequency band for the responders to treatment. Also, LAV is2 was significantly increased w.r.t. LAV is1 in the {beta}1 frequency band for the responders. No such significant changes were observed for the non-responders. Brain networks constructed using both weighted imaginary coherence and weighted imaginary mean phase coherence were found to exhibit these results. For the CH connectivity changes, binarized networks and for the LA connectivity changes, weighted networks were found to be more reliable. ConclusionsResponders were found to show a reduction in cross-hemispheric connectivity and an increase in lateral asymmetry, both in the {beta}1 band while no such change was observed for the non-responders. SignificanceDecrease in cross-hemispheric connectivity and increase in lateral asymmetry in the {beta}1 band may represent candidate neurophysiological indicators of early treatment response, but they require independent replication before any clinical application can be considered.

BackgroundExecutive functions are a key target of cognitive interventions for older adults due to their central role in daily functioning and maintaining a good quality of life. Piano training has been proposed as an ecologically valid method of improving cognition and brain structure in older adults. The primary aims of this study were to (i) evaluate the feasibility and acceptability of Piano Instruction for Adult Novices as an Online Cognitive Intervention (PIANO-Cog), a novel bespoke 8-week self-guided piano training programme for adults over 50 years of age, and (ii) assess the feasibility of conducting a fully-powered randomised controlled trial (RCT), including recruitment, retention, and adherence. Secondary aims explored effects of PIANO-Cog on executive functions and brain microstructure using advanced diffusion-weighted imaging (DWI). MethodThirty-three healthy music novices aged 51-80 years (M = 63.73, SD = 7.94) participated in a two-arm unblinded feasibility RCT. Participants were assigned by stratified allocation for age and sex to either (i) 8 weeks of PIANO-Cog, requiring 30 minutes of practice, 5 days per week, or (ii) a passive control group. Cognitive assessment and MRI scanning were conducted before and after the intervention using a strong-gradient (300mT/m) 3T Connectom scanner to acquire multi-shell DWI data with b-values ranging from 200 to 6,000 s/mm{superscript 2}. Grey and white matter microstructure were modelled with Soma And Neurite Density Imaging (SANDI) and Neurite Orientation Density and Dispersion Imaging (NODDI). ResultsAccording to predefined criteria, feasibility was established for recruitment (91.6%), retention (75%) and adherence (>100%) rates. Preliminary observations suggest that piano training compared with control was associated with improvements in verbal fluency and multiple changes in brain microstructure including increases in apparent soma size and radius and reductions in extracellular signal in frontal and temporal cortical regions, larger apparent neurite density in right inferior frontal gyrus and changes in neurite dispersion in left middle temporal and right precentral gyri. DiscussionThe results demonstrate that short-term remote piano training is a feasible cognitive intervention for healthy adults over 50. Preliminary evidence suggest that PIANO-Cog was associated cognitive improvements and changes in brain microstructure in executive, auditory and motor regions.

BackgroundThe relationship between neighborhood-level socioeconomic disadvantage and brain health is an emerging area of research with critical implications for public health and clinical practice, yet its influence on brain structure remains unclear. PurposeTo investigate the epidemiological association between neighborhood-level socioeconomic disadvantage [Area Deprivation Index (ADI)] and morphometric neuroimaging variables in a consecutive, non-disease enriched patient population. Materials and MethodsThis study, conducted at an academic medical center and associated community partners, used consecutive cross-sectional MRI neuroimaging data from 2,826 inpatient and outpatient individuals without radiological evidence of disease from January 2024 to June 2024. ADI, a geospatially determined index of neighborhood-level disadvantage, was calculated for each individual. Linear regressions tested the relationship between ADI and multiple morphometric variables: brain age gap (BAG; estimated - chronological BA), total brain tissue volume (TBV; total gray + white matter), five subcortical region volumes (hippocampus, thalamus, caudate, putamen, and nucleus accumbens) and four cortical region volumes [anterior cingulate cortex, posterior cingulate cortex, medial prefrontal cortex (MPFC), lateral PFC (LPFC)]. Volumetric measures were normalized to intracranial volume. Models controlled for age, sex, and total white matter hyperintensity volume (WMHV). Results2,826 individuals (mean age, 52.7 {+/-} 18.8 [standard deviation]; 1732 women) were evaluated. Residence in the 20% most disadvantaged neighborhoods was associated with a higher BAG ({beta}s > 2.12, Ps < .01) and decreased TBV ({beta}s < -5.12, Ps < .05). Additionally, increased WMHV was higher among those in the most disadvantaged neighborhoods (ts < - 2.50, Ps < .05) and associated with lower volume in most regions. Interaction models showed increased negative associations between WMHV and volumes of the caudate, nucleus accumbens, and lateral prefrontal cortex among those in the most disadvantaged neighborhoods. ConclusionsNeighborhood disadvantage is associated with adverse brain morphometry, including higher BAG, lower TBV, and amplified vascular-related regional volume loss. Key ResultsO_LIIn 2,826 adults (mean age, 53 years {+/-} 19; 1,732 women), residence in the most disadvantaged neighborhoods (national: 116/2,826, 4%; state: 129/2826, 5%) was associated with higher brain age gap at the national ({beta} = 2.12, 95% CI = 0.81 to 3.43, P = .001) and state levels ({beta} = 2.36; 95% CI = 1.10 to 3.61, P < .001). C_LIO_LITotal brain tissue volume was lower at the national ({beta} = -5.12, 95% CI = -10.13 to -0.11, P = .045) and state levels ({beta} = -6.13, 95% CI = -10.90 to -1.37, P = .011). C_LIO_LIWhite matter hyperintensity volume was higher in the most disadvantaged group (national: P = .013; state: P = .003) and demonstrated amplified associations with caudate, nucleus accumbens, and lateral prefrontal cortex volumes in the most disadvantaged group at the national and/or state levels (Ps < .05). C_LI

BackgroundAlzheimers disease (AD) patients are characterized by an early decline of episodic memory due to hippocampal damage. Nonetheless, besides the classical negative symptoms related to episodic memory deficits, i.e. failure to retrieve information, it has been shown that AD patients can also suffer from positives symptoms, i.e. confabulations. Some theoretical accounts have been proposed to explain the cognitive mechanisms underlying confabulation. Yet, even if most of these models have lead to some research trying to validate cognitive deficits in some cognitive domains, in particular executive functions, to our knowledge, none has yet tried to determine the specific cognitive profile of confabulatory patients. In the present study the main aim is to characterize the specific cognitive profile of confabulatory patients. Thus, given that AD patients cognitive profile is well known and documented, we compare mild to moderate AD patients with and without confabulations. Methods37 healthy control (HC) and 35 individuals with mild to moderate AD were recruited at the Pitie Salpetriere University Hospital. All participants were evaluated on Dalla Barbas Confabulation Battery to determine their tendency to produce provoked confabulations. Thus, among AD patients, we distinguish between those who produced confabulations in episodic memory questions, and those who did not. Accordingly 27 AD patients were considered free of confabulations (ADC-), and 8 as confabulators (ADC+) (none HC met the criteria). All participants were assessed on a comprehensive neuropsychological battery. ResultsStatistical analyses showed a significant difference between HC participants and the two groups of AD patients, in almost all cognitive domains assessed. However, when comparing the two AD groups, they did not show distinct profiles. Moreover, regarding the type of confabulations, ADC+ produced significantly more confabulations to the Episodic questions (both concerning past and future). ConclusionsBy not demonstrating cognitive differences between patients with and without confabulations, our results cast doubts on some confabulation models, which assume a unique and sufficient cognitive (e.g. executive) deficit underlying the onset of confabulations. HighlightsO_LIAlzheimers disease patients with or without confabulations do not have otherwise distinct cognitive profiles. C_LIO_LIThe emergence of a confabulatory syndrome does not seem to be the result of a necessary and sufficient executive deficit C_LIO_LIAlzheimers disease patients mainly produce episodic memory confabulations, which involve both the past and the future dimension. C_LI

BackgroundDepression is associated with social dysfunction, but the mechanisms linking affective symptoms to disrupted close relationships remain poorly understood. One possibility is that depression alters how people experience rewards shared with close others and how they interpret partners actions. It remains unclear whether neural sensitivity to shared reward predicts social valuation during more complex interactions such as reciprocated trust. MethodsIn this preregistered fMRI study, participants completed a reward-sharing task and a Trust Game with a close friend, a stranger, and a computer. We measured striatal shared reward sensitivity (SRS; friend > computer) and tested whether it related to subsequent investment behavior and brain responses to trust reciprocation. Depressive symptoms and perceived closeness were assessed via self-report. ResultsIn a final sample of n = 123, participants reporting more depressive symptoms invested more in their friend than in the computer. Striatal SRS predicted temporoparietal junction responses to reciprocated trust, but this association depended jointly on social closeness and depression -- with depression reversing the expected pattern among individuals reporting closer relationships. Striatal SRS was also inversely associated with connectivity between the default mode network and cerebellum during reciprocity. ConclusionsThese findings suggest that closeness calibrates the striatal SRS link to regional activity and network-level responses during social exchange, while depression alters how striatal SRS relates to regional activity, potentially disrupting how individuals interpret and respond to close others.

There is a predicted increase in older adults presenting with mild to severe cognitive impairment. Screening tools with high sensitivity are the first frontier in identifying a cognitive pathology; however, to ensure that they are measuring the intended concept or criterion, thorough psychometric procedures should be followed. In this study, convergent criterion validity of Riga Cognitive Screening Task was measured, using cortical thickness of regions of interest as the criterion. 106 older adults (Mage = 70.49, SD =8.08, 35.8% male) with varying levels of cognitive functioning were involved in the study. All participants underwent cognitive assessment with the screening task and a 3T MRI. Cortical thickness of selected temporal and parietal regions was used as a brain measure. Behavioural Partial Least Squares Correlation was conducted and one latent variable was extracted. The results confirmed that Riga Cognitive Screening Task shows good criterion validity, suggesting successful use for screening.

BackgroundMaternal mental health is an important contributor to child neurodevelopment. While there are multiple studies on prenatal exposure, early postnatal exposure has received little attention in neuroimaging research. Methods5-year-old children (n = 173) were recruited from the FinnBrain Birth Cohort study. Maternal distress was assessed using questionnaires on depressive and anxiety symptoms at 14, 24 and 34 gestational weeks and postnatally at 3, 6 and 24 months. T1-weighted structural images were processed using a voxel-based morphometry pipeline to map associations between maternal distress exposure and regional gray matter (GM) volumes, while accounting for potential confounders. ResultsWe found widespread associations between maternal distress symptoms and offspring brain morphology. Higher prenatal distress at 14 gestational weeks was positively associated with regional GM volume in the right superior parietal lobe and precuneus. In contrast, postnatal distress at 3 months was negatively associated with GM volumes in multiple motor regions, the left anterior insula, right superior frontal areas and supramarginal gyrus. Postnatal distress at 6 months demonstrated a positive relationship with GM volumes in the right calcarine and lingual gyri, while distress at 24 months was negatively associated with GM volumes in the left supramarginal and right superior frontal gyri. ConclusionsThis study provides support for hypotheses proposing that fetal and early life exposure to maternal distress can influence the structural development of the brain. Furthermore, it highlights the role of early postnatal period and calls for further research into this so far overlooked period and pathways that explain the associations.

Understanding the neurobiological basis of mental health disorders and their symptoms is a central goal of research in psychiatry. Yet, identifying robust brain-psychopathology associations with neuroimaging remains difficult, in part due to substantial heterogeneity within and comorbidity between diagnostic categories. Transdiagnostic latent factor models aim to address this structure by separating shared and unique symptom variance. This can potentially yield more reliable and neurobiologically-relevant dimensions of psychopathology. However, the extent to which latent factor models improve brain-psychopathology associations remains largely unclear. Using two large developmental cohorts, we compared transdiagnostic bifactor models, correlated factor models, and typical summary scores derived from the Child Behaviour Checklist (CBCL) in their reliability and multivariate associations with whole-brain structure (MRI) and function (resting-state fMRI). We found no consistent evidence that latent factors (bifactor or correlated factor models) strengthened reliability or brain-psychopathology associations, relative to summary scores. Whole-brain predictive models revealed broadly distributed neural signatures that were highly similar between corresponding factor and summary score constructs, with general psychopathology factors and total problem summary scores approaching numerical equivalence. Bifactor scores did, however, display more distinct neural signatures between general, internalising, and externalising dimensions than did summary or correlated factor scores. These results suggest that phenotypic modelling of psychopathology alone does not systematically strengthen the predictive utility of psychiatric neuroimaging, possibly reflecting fundamental limits on the amount of explainable symptom variance by brain features. While latent factor models may aid in distinguishing neural correlates between constructs, improving phenotypic assessment may be necessary for improvements to brain-psychopathology association strength.

An increasing number of studies are currently focusing on personality neuroscience, a term denoting the research aimed at neuroimaging correlates of inter-individual temperament and character variability. Among other methods, a graph theoretical analysis of the functional connectivity in resting-state functional magnetic resonance imaging data was applied in a study by Gao et al. (2013), reporting novel functional connectivity correlates of personality traits. The current paper presents a conceptual replication of the results of this study and discusses the related challenges, including an extension of the original statistical methods in order to illustrate the effect of the multiple comparison problem. Five personality dimensions were obtained using the revised Big Five Personality Inventory, including scores of Extraversion and Neuroticism covered in the original paper. Using a larger sample (84 subjects) with adequate statistical power (ranging from 0.75 to 0.95 across analyses), we failed to replicate any of the nine specific neuroimaging correlates of personality presented by Gao et al. While acknowledging differences in the experimental procedures, we discuss that the lack of replication might be caused by the relatively liberal control of false positives in the original study. Indeed, the original testing scheme leads to an expected count of about 10 false positive observations among all tests; applying this scheme to our data we observed a similar number of positive tests, albeit for different relations. No significant correlations were found in our data when standard family-wise error control was applied. These results illustrate the importance of combining exploration with independent validation, use of large datasets, as well as appropriate control of multiple comparison problem in order to prevent false alarms in research into neural substrates of personality differences. Importantly, our findings do not disprove the existence of a link between personality and the brains intrinsic functional architecture; but rather suggest that such a link might be even more subtle and elusive than previously reported.

BackgroundSchizophrenia is a highly heritable mental disorder associated with widespread anatomical alterations during neurodevelopment. Converging evidence suggests transcriptomic architecture underlying brain abnormalities in schizophrenia, while how individualized brain morphological deviations relate to gene expression levels remains unclear. MethodsTo investigate individual-level brain deviations and its transcriptomic signatures in schizophrenia, this study collected T1-weighted MRI data from 95 early-onset schizophrenia (EOS) patients and 99 typically developing (TD) controls. Normative modeling was used to measure individual deviations in cortical thickness and subcortical volume. Partial least squares regression was calculated to capture covarying patterns between structural deviations and whole-brain gene expression levels. Clustering analysis was performed on latent brain-gene covarying components, and the results were further functionally decoded through gene enrichment analyses. ResultsGroup-level comparisons suggested patients with EOS showed consistently decreased z-scores of cortical thickness in the frontal and temporal lobe regions, while increased inter-individual variability in the lingual gyrus. Clustering analysis of z-scores with transcriptomic signatures identified two distinct brain-gene covarying subtypes. Subtype 1 showed thickening cingulate gyrus, thinning occipital pole, and atrophic subcortical nuclei. Subtype 2 exhibited widespread cortical thinning across the frontal, parietal, temporal, and limbic regions, but enlarged subcortical nuclei. Genes underlying two subtypes were both enriched for neurodevelopmental diseases. However, subtype 1 was associated with synaptic transmission, and subtype 2 was related to cytoskeletal and neuronal connectivity. ConclusionThis study reveals individual-level anatomical deviations and transcriptomic heterogeneity in early-onset schizophrenia. The findings provide an individualized brain-gene coupling framework for understanding pathophysiology of schizophrenia during brain development.

BackgroundMild cognitive impairment (MCI) precedes Alzheimers disease (AD) in [~]40% of cases, with early language deficits distinguishing converters. This study develops a DTI radiomics model from language network gray matter to predict MCI to AD conversion and identify preclinical biomarkers. MethodsThis retrospective case-control study analyzed diffusion tensor imaging (DTI) data from 97 individuals with MCI (29 converters, 68 non-converters) from the Alzheimers Disease Neuroimaging Initiative (ADNI). Ethical approval and participant consent were obtained by ADNI. Radiomic features were extracted from fractional anisotropy (FA) and mean diffusivity (MD) maps within language network gray matter. A logistic regression model using eleven selected features performed classification. Performance was evaluated using area under the receiver operating characteristic curve (AUC). Radiomic-cognitive associations were analyzed using Pearson correlations; group differences were assessed with Fishers r-to-z transformation. ResultsThe model achieved cross-validation AUC = 0.84 and test AUC = 0.83. SHAP analysis identified two top predictors: lower right temporal pole original_glcm_Correlation_FA and higher right frontal orbital cortex original_glszm_SmallAreaHighGrayLevelEmphasis_FA. Right frontal orbital cortex original_glszm_SmallAreaHighGrayLevelEmphasis_FA correlated positively with ADAS-Q4 in non-converters (r = 0.27, p < 0.001) but negatively in converters (r = -0.48, p < 0.001). ConclusionsA DTI radiomics model achieved AUC = 0.83 for predicting MCI to AD conversion, with bilateral language network microstructural features showing group-specific cognitive associations, supporting their potential as early Alzheimers risk biomarkers. Key pointsO_LINew method identifies Alzheimers risk before significant cognitive decline occurs C_LIO_LIBrain language regions show detectable changes in future converters C_LIO_LITexture analysis reveals early disease signatures in brain tissue C_LI

BackgroundThe early diagnosis of Alzheimers disease (AD), a cause of progressive cognitive decline, remains challenging. Recent information-theoretic advances allow brain dynamics to be quantified in terms of how regions share and combine information. Integrated Information Decomposition ({Phi}ID) separates redundant (the same content present in multiple regions) from synergistic information (new content that emerges only when regions are considered together). Such information-dynamic measures may provide biomarkers relevant to AD risk and progression. MethodsHere we applied integrated information decomposition ({Phi}ID) to resting-state fMRI from the Alzheimers Disease Neuroimaging Initiative (ADNI), to test whether {Phi}ID measures are diagnostically sensitive and track cognition along the AD spectrum. For each region, we computed total synergy and redundancy and compared values across cognitively normal (CN), mild cognitive impairment (MCI), and AD groups. ResultsCompared to CN, AD patients showed a striking synergy reduction across the entire brain, in concert with widespread redundancy increases, particularly in the executive and default mode networks. Transitions from CN to AD included an intermediate MCI decrease in redundancy, possibly reflecting early disease compensation strategies. This AD informational shift from complex higher level information processing to more robust inefficient forms likely reflects a cognitive shift to simpler, less integrative cognitive processes. Indeed, when re-analysing the data according to a standard cognitive clinical test (the Montreal Cognitive Assessment), we found a synergy-redundancy shift in high versus low performers broadly very similar to the CN to AD shift. ConclusionAD shows a clear information-processing signature: reduced global synergy and increased redundancy, especially in the executive control network. These striking results provide powerful insights into the widespread information processing reconfiguration that occurs in AD, with clear changes already emerging at the earlier MCI stage. Further, these results provide a novel route to support early diagnosis and stratification.

Introduction. There is consistent evidence of a disadvantage in bilinguals' speech production compared to monolinguals in healthy individuals, but studies investigating this phenomenon in clinical populations such as Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) are scarce. Given that both clinical groups are characterized by wordfinding difficulties, understanding how bilingualism influences speech production in these populations is essential. Methods. Early and highly proficient Catalan-Spanish bilinguals (active bilinguals) were compared to Spanish-dominant speakers with low proficiency in Catalan (passive bilinguals) using a picture-naming task. The study included 58 older adults, 66 patients with AD, and 124 individuals with MCI. Reaction times, accuracy, and error types were collected in the naming task in each individual's dominant language. Results. First, active bilinguals demonstrated faster naming latencies than passive bilinguals, particularly for low-frequency words. Second, active bilinguals with MCI exhibited more naming errors than passive bilinguals with MCI, including a higher incidence of crosslanguage intrusions and anomia. Third, passive bilinguals with MCI and AD showed more semantic errors than active bilinguals. Discussion. These findings underscore the impact of second language use on naming performance in MCI and AD. Moreover, they provide insight into the potential mechanisms underlying lexical retrieval differences in bilinguals, including lexico-semantic processing and language control.

BackgroundThe brains glymphatic system plays a vital role in maintaining neural health. However, little is known about whether second language (L2) immersion can influence this clearance pathway. Methods50 high-proficiency L2 English speakers (mean age: 32.6 years; 78% female) were assessed for glymphatic function using three multimodal MRI markers: BOLD-CSF coupling strength (fMRI), choroid plexus ratio (structural MRI), and DTI-ALPS index (diffusion MRI). Analyses examined relationships between glymphatic markers and L2 immersion duration, age of acquisition (AOA), and active use environment, controlling for age, education, and sex. ResultsL2 immersion duration correlated significantly with better glymphatic function. Longer immersion related to better BOLD-CSF coupling strength (r = -0.315, p < 0.05) and decreased choroid plexus ratios (r = -0.39, p < 0.05), suggesting enhanced brain-CSF coordination and fewer pathological CSF production structures. Mediation analyses demonstrated that immersion influenced ALPS indirectly through effects on choroid plexus morphology and BOLD-CSF coupling. L2 AOA moderated the immersion-coupling relationship: individuals who began learning after age 9.53 showed stronger associations between immersion and BOLD-CSF coupling, though AOA did not moderate choroid plexus effects. As for L2 immersive active is associated with better glymphatic function, while L2 immersive passive and L2 non-immersive active are both unrelated. ConclusionsL2 immersion associates with better glymphatic system function through multiple pathways, including improved brain-CSF coordination, optimized choroid plexus structure, and increased perivascular flow. These findings provide novel neurobiological evidence that bilingual experience may confer neuroprotective benefits through brain waste clearance mechanisms.