Brain Imaging and Behavior

Background: Large language models have been proposed to improve patient comprehension of radiology reports. However, whether they improve objective understanding remains unproven. Purpose: To evaluate the effect of appending an LLM-generated lay summary to brain MRI reports on objective and subjective patient comprehension in a randomized controlled trial. Materials and Methods: In this randomized controlled trial, 2,727 adult participants from the ComPaRe e-cohort were randomly assigned to interpret six standardized brain MRI reports for headache, presented either in their native format (control; n = 1,401) or appended with a lay summary generated by an open-weights LLM (Mistral Small 3.2) (intervention; n = 1,326). The primary outcome was objective comprehension, defined as the rate of correct classification of whether the report provided a probable explanation for the headache, with ground truth established by four-radiologist consensus. Secondary outcomes included satisfaction, subjective comprehension, anxiety, and willingness to contact a healthcare professional. Generalized estimating equations accounted for repeated within-participant observations. Results: A total of 2,727 participants (mean age, 52 years +/- 15; 75.2% women) were evaluated. Objective comprehension did not differ between arms (58.3% vs 59.4%; odds ratio (OR) 0.97; 95% CI: 0.90-1.06; P = .54). The intervention significantly improved overall satisfaction (64.9% vs 36.7%; OR 3.26; 95% CI: 2.93-3.64; P < .001) and subjective comprehension (50.3% vs 24.0%; OR 3.17; 95% CI: 2.82-3.56; P < .001). High anxiety was modestly reduced (25.1% vs 26.6%; OR 0.92; P = .037). The effect on objective comprehension varied by report type (P for interaction < .001): summaries improved comprehension of symptom-explaining reports (42.4% vs 37.4%; P < .001) but reduced it for normal reports (72.5% vs 76.6%; P = .001). Conclusion: LLM-generated lay summaries appended to brain MRI reports improved patient satisfaction and subjective comprehension but did not improve objective comprehension, indicating a gap between perceived and actual understanding that should be addressed before clinical integration.

Background: Neuroimaging studies implicate network alterations in functional motor disorder (FND-motor), yet white matter remains poorly characterized. Objectives: To characterize white matter microstructure in FND-motor relative to healthy (HCs) and psychiatric (PCs) controls and examine symptom associations. Methods: Fifty individuals with FND-motor, 50 age- and sex-matched HCs, and 50 PCs matched on age, sex, depression, anxiety, and post-traumatic stress disorder severity underwent multi-shell diffusion MRI. Voxel-based analyses examined whole-brain white matter using diffusion tensor imaging (fractional anisotropy [FA], mean diffusivity [MD]) and neurite orientation dispersion and density imaging (NODDI) (neurite density index [NDI], orientation dispersion index, and free water fraction [FWF]) metrics. Cross-metric convergence was characterized using atlas-based tract overlap analyses and probabilistic tractography. Associations with FND symptoms and transdiagnostic physical symptoms were also evaluated. Results: Compared with HCs, FND-motor showed higher FA/NDI and lower MD/FWF, predominantly in the middle cerebellar peduncle. Compared with PCs, differences were limited to lower MD/FWF, involving the corpus callosum, middle cerebellar peduncle, and left inferior longitudinal fasciculus. Greater FND symptom severity was associated with a lower FA/NDI and higher MD/FWF in the corpus callosum and right-lateralized association and projection pathways, whereas greater transdiagnostic physical symptom burden across FND-motor and PCs was associated with higher FA and lower MD/FWF in the middle cerebellar peduncle. Conclusions: This study provides a comprehensive multi-metric diffusion-weighted characterization of white matter microstructure in FND-motor relative to both HCs and PCs - highlighting cortico-cerebellar connections via the middle cerebellar peduncle as distinct in FND-motor and associated transdiagnostically with physical symptom burden.

BackgroundSocial dysfunction is a major source of disability in schizophrenia, yet the neural mechanisms that contribute to impaired social understanding remain poorly understood. Converging evidence points to the role of the default mode network (DMN) in integrating social information over time to construct interpretations of social behaviors. Here, we tested the hypothesis that individuals with schizophrenia show reduced stimulus-driven coordination between brain regions within the DMN during free viewing of naturalistic social stimuli. MethodsA sample of 124 adults (schizophrenia: n=63; healthy controls: n=61) viewed naturalistic video clips during fMRI. Inter-subject functional connectivity (ISFC) was computed within the two groups. Group differences were identified via permutation testing. We also explored group differences in other brain networks to examine whether effects were specific to the DMN. ResultsIndividuals with schizophrenia showed weaker stimulus-driven coupling within the DMN compared to healthy controls, specifically between areas such as the parahippocampal gyrus, precuneus, and medial prefrontal cortex. Group differences in ISFC were specific to the DMN. Furthermore, no between-group differences emerged for within-participant functional connectivity in the DMN, suggesting that the observed effects reflect reduced stimulus-driven coordination among DMN regions when processing social stimuli rather than a more general decline in DMN connectivity. ConclusionsSchizophrenia is characterized by impaired coordination within the DMN as it dynamically integrates social information over time, which could contribute to difficulties in constructing coherent interpretations of real-world social situations. These findings suggest that disrupted stimulus-driven network coordination might underlie social cognitive impairments in schizophrenia, highlighting the value of naturalistic paradigms for revealing network-level dysfunction under conditions that closely approximate real-world experience.

Post-traumatic stress disorder (PTSD) has been associated with impairments in cognitive function, including working memory, and may involve altered glutamatergic regulation in the prefrontal cortex. In this study, we used 7T functional magnetic resonance spectroscopy (fMRS) to examine dorsolateral prefrontal cortex (DLPFC) glutamate during working memory in individuals with PTSD, trauma exposure without PTSD (TE), and no trauma exposure (NT). Eighty participants (27 PTSD, 27 TE, 26 NT) underwent baseline MRS followed by fMRS during a letter n-back task. A linear mixed-effects model was used to evaluate glutamate concentrations across baseline, 0-back, 1-back, 2-back, and post-task fixation conditions. Behavioral performance was assessed using repeated-measures ANOVA for percentage correct, reaction time, and the discrimination index (d) across the 0-back, 1-back, and 2-back conditions. Glutamate differed significantly by group, condition, and the group x condition interaction. Individuals with PTSD exhibited lower glutamate than NT at baseline and during the 0-back, 1-back, and 2-back conditions. TE participants also showed lower glutamate than NT during the 1-back and 2-back conditions. Within-group analyses showed higher glutamate during the 0-back, 1-back, and 2-back conditions than at baseline in the NT group, whereas these baseline-to-task differences were limited in the PTSD and TE groups. Accuracy decreased and reaction time increased with increasing working memory load, and discrimination (d) was lower in PTSD than NT. These findings demonstrate altered DLPFC glutamate dynamics during working memory in PTSD and trauma-exposed individuals. Functional MRS provides complementary information beyond resting-state MRS by characterizing glutamatergic responses during cognitive engagement and may improve our understanding of neurochemical alterations associated with trauma and PTSD.

BackgroundSelf-compassion has shown to be an effective emotion regulation strategy, but its neural mechanisms remain understudied in adolescents with depression who suffer from social exclusion. This study employed event-related potentials to investigate the psychophysiological mechanisms underlying impaired self-compassion in adolescents with depression during social exclusion. MethodsThirty-seven adolescents with major depressive disorder (age = 16.46 {+/-} 2.02) and thirty-two demographically matched healthy controls (age = 16.54 {+/-} 2.29) completed a social exclusion scenario imagination task. This task presented participants with social exclusion scenarios, asking them to imagine themselves as the excluded individual and subsequently rate their negative emotions. The regulation session required participants to use self-compassionate statements to regulate their emotional responses while imagining and rate how much self-compassion they have engaged in; the non-regulation required them not to use those statements and rate their negative emotions immediately following imagination. EEG signals were recorded during the task, and the late positive potential (LPP) was analyzed to examine the neural responses associated with self-compassion regulation following social exclusion. ResultsCompared with the non-regulation condition, both groups showed less negative emotion during the self-compassion regulation condition. Adolescents with depression exhibited significantly lower self-compassion ratings than healthy controls, and showed a significantly smaller decrease in negative emotions. Higher self-compassion ratings were correlated with greater emotion regulation effect, particularly in adolescents with depression. Furthermore, LPP amplitudes were significantly higher in adolescents with depression than in healthy controls during both regulation and non-regulation conditions. ConclusionsAdolescents with depression were characterized by impairment in using self-compassion to downregulate negative emotions when confronted with social exclusion. LPP amplitudes were consistently elevated in adolescents with depression, underscoring their potential as a critical focus for psychophysiologically-informed therapies.

Reading comprehension is a complex cognitive task that involves dynamic interactions between the brain and external information. Previous studies on reading development primarily focused on localized or static brain activities. However, it remains an enigma how brain state dynamics evolve with development underlying reading comprehension. This study aims to address this issue by combining functional magnetic resonance imaging (fMRI) with Hidden Markov Model (HMM) to explore brain state dynamics. A total of 35 typically developing children and 31 adults were scanned while reading a story. Our results demonstrated a tripartite brain state organization, characterized respectively by high activities in the visual (State #1), language (State #2), and default mode network (DMN, State #3) regions. Children exhibited significantly longer dwell time in the DMN state (State #3) compared to adults, along with a higher probability of transitioning from the language state (State #2) to the DMN state (State #3). In addition, adults exhibited greater flexibility in state transitions during reading comprehension. Finally, the alignment between the dynamic states of children and the average states of adults was a significant positive predictor of their reading comprehension performance. This study provides a novel, intuitive perspective on how brain state dynamics evolve during the development of reading comprehension.

BACKGROUND AND PURPOSENeighborhood-level socioeconomic disadvantage is associated with adverse brain morphometry, yet whether these associations differ by biological sex remain opaque. Here, we investigated sex-specific associations between the area deprivation index and brain morphometry derived from routine clinical MRI in a real-world clinical population. MATERIALS AND METHODSIntracranial volume-normalized regional brain volumes were extracted from T1-weighted MRI examinations performed in 2,863 consecutive clinical patients (median age 54 years [IQR 38-68]; 61.2% female) at a single academic medical center and associated community partners using an automated atlas-based segmentation pipeline. Exploratory factor analysis was applied to 131 regional brain volumes to identify latent neuroanatomical morphometric networks. Sex-stratified linear regression models examined associations between area deprivation index national percentile rank and each factor score, adjusting for age, with correction for multiple comparisons. RESULTSFactor analysis identified five neuroanatomical morphometric networks: cerebellar (ML1), frontal/executive (ML2), subcortical-ventricular (ML3), medial temporal/limbic (ML4), and posterior cortical/visual (ML5). In male patients (n = 1,112), linear regressions revealed that greater neighborhood-level socioeconomic disadvantage was significantly associated with lower factor scores on the cerebellar ({beta} = -0.006, 95% CI [-0.009, -0.003], P < .001), medial temporal/limbic ({beta} = -0.004, 95% CI [-0.007, -0.001], P = .01), and frontal/executive ({beta} = -0.004, 95% CI [-0.007, -0.0004], P = .04) networks. No significant associations were observed in female patients (all Ps [&ge;] .61). CONCLUSIONSIn a real-world clinical population, neighborhood-level socioeconomic disadvantage was associated with lower regional brain volumes across cerebellar, frontal/executive, and medial temporal/limbic neuroanatomical morphometric networks in male but not female patients. These findings suggest that the neuroanatomical correlates of neighborhood disadvantage may be sex-specific, and that sex-stratified analyses may be necessary to fully characterize the relationship between the social exposome and brain morphometry in clinical neuroimaging research.

Laboratory stress tasks are widely used to assess individual differences in acute stress reactivity, yet it remains unclear how these responses correspond to stress experienced in everyday life. Here, we combined the Montreal imaging stress task (MIST) with ecological momentary assessment (EMA) over three months to assess acute and everyday stress in 67 healthy women. Greater within-person variability in everyday stress, but not average stress levels, were associated with stronger overall stress-related brain responses (b = 0.73, p = .039), with a whole-brain association particularly evident in the bilateral caudate (rROI = .32, pcluster.FWE < .001). Greater everyday stress variability was also associated with stronger stress-related functional connectivity between the ventromedial prefrontal cortex (vmPFC) and parietal and posterior medial regions (pcluster.FWE < .001). We conclude that acute neural stress responses relate more closely to fluctuations in perceived stress than to how stressed an individual feels on average. This suggests that laboratory stress tasks capture acute stress responsivity that is distinct from average stress exposure, highlighting the importance of considering what these tasks measure when interpreting individual differences in acute stress responses.

Introduction The superior longitudinal fasciculus (SLF) is a major association fiber bundle implicated in cognition, visuospatial attention, language, and motor control, and its impairment is linked to several neurological and neuropsychiatric disorders. This proof-of-concept study was performed with three main objectives in healthy adults. First, to fuse whole brain spectroscopic (WBSI) and diffusion MRI (dMRI) derived parametric maps along the SLF I and II segments to quantify their spatial concordance, second, to evaluate regional metabolite concentrations and microstructural properties along these trajectories and finally, to determine the relationships between the WBSI and dMRI parameters within these segments. Methods Ten healthy adults (4F, 6M; mean age 31.4 {+/-} 7.53 years) underwent 3T MRI including multi-shell high angular resolution diffusion imaging and WBSI. After preprocessing and non-linear co-registration, WBSI-derived white matter metabolite maps and neurite orientation dispersion and density imaging (NODDI) / diffusion tensor imaging (DTI) derived parametric maps were spatially aligned and projected along the centroid of reconstructed SLF I and II segments divided into 20 discrete, anatomically contiguous sections. Results A strong spatial alignment between WBSI and dMRI imaging modalities was confirmed by mutual information and Pearson's correlation analyses. Intra-subject repeatability, as assessed from a single participant scanned three times, demonstrated high tract reconstruction reliability (mean Dice similarity coefficients >0.79; track density-weighted Dice >0.97) and acceptable intra-subject coefficients of variation. Inter-subject coefficients of variation were within acceptable ranges ({approx}3-17%) for most parameters, with free water fraction (fiso) exhibiting relatively higher variability. Single and multivariate regression analyses revealed significant associations between WBSI and dMRI tract profiles: choline/creatine (Cho/Cr) and choline/ N-acetyl aspartate (Cho/NAA) ratios showed positive linear associations with intra-cellular volume fraction (ficvf) and fractional anisotropy (FA), and negative associations with mean diffusivity (MD) along bilateral SLF I, with ficvf and MD identified as the strongest combined predictors of metabolite ratios. Conclusion Co-localization/fusion of WBSI and NODDI/DTI data into one framework offers a reliable, user-independent way for mapping regional metabolite and microstructural alterations along the path of SLF. Moving forward, this image processing pipeline has the potential to enhance diagnosis and clinical assessment of neurological disorders linked to SLF damage.

Background Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a poorly understood, debilitating multisystem condition. Converging evidence implicates impaired cellular bioenergetics, neuroinflammation and defective neurovascular coupling that may manifest as "virtual hypoxia" only under physiological stress. Methods We performed a single-session multimodal 3T MRI study combining brain volumetry, arterial spin labelling (ASL) and multivoxel proton magnetic resonance spectroscopy under normoxia and two controlled hypoxic challenges (oxygen saturation 87 {+/-} 3%) in 26 ME/CFS patients and 27 age- and sex-matched healthy controls. Results After intracranial-volume normalization, patients showed a reduced brainstem volume (1.46 0.14 vs. 1.55 {+/-} 0.18 % of eTIV; p = 0.013, FDR-p = 0.039), whereas deep grey matter and whole-brain parenchymal fraction did not differ between groups. Whole-brain cerebral blood flow (CBF) rose under hypoxia in both groups (controls +4.8 {+/-} 13.0%, patients +3.7 {+/-} 11.7%), with greater initial inter-individual variability in patients (patient-to-control variance ratio up to 6.94; FDR-p = 0.001). Thalamic lactate-to-creatine (Lac/tCr) ratios increased with hypoxia in controls (FDR-p = 0.028) but were already elevated at normoxia in patients (0.171 vs. 0.135; FDR-p = 0.021) and did not rise further (FDR-p = 0.38). In exploratory analyses, patients showed exaggerated inverse coupling between thalamic total N-acetylaspartate (tNAA/tCr) and white-matter CBF. Conclusions These findings provide in vivo evidence of impaired neuro-metabolic and vascular adaptive capacity in ME/CFS, supporting the virtual hypoxia hypothesis and highlighting candidate imaging markers for stratification that warrant validation.

Background: Acute cortisol responses to psychosocial stress vary substantially across individuals, yet how this variability is reflected in post-stress resting-state functional connectivity (rsFC) remains unclear. Although prior work has linked stress-related endocrine responses to brain connectivity, studies have been limited by small samples, region-of-interest approaches, or a sole focus on group-level analyses. Here, we investigated whether acute cortisol increase is associated with, and can be predicted from, whole-brain post-stress rsFC. Methods: We analyzed 339 healthy participants from two ScanSTRESS datasets using complementary inferential and predictive approaches. First, we used the Network-Based Statistic (NBS) to identify connected rsFC networks associated with acute cortisol increase, controlling for age, site, and sex/hormonal status. Second, we predicted participants' acute cortisol increase from their connectivity patterns using NBS-Predict and Connectome-Based Predictive Modeling (CPM). Together, we examined the cortisol-rsFC relationship at the population and individual levels. Results: Greater cortisol responses were associated with lower post-stress rsFC within a significant distributed network comprising 258 connections among 78 regions, centered on thalamic nuclei and pallidal regions and extending to default-mode, limbic, orbitofrontal, and cerebellar regions. Sex-stratified analyses revealed a significant negative association only in females, but formal sex-difference contrasts were not significant. NBS-Predict and CPM yielded modest but significant out-of-sample prediction, with predictive networks converging on subcortical and posterior cingulate regions. Conclusions: Post-stress rsFC carries convergent inferential and predictive information about individual HPA-axis reactivity. Stronger cortisol responses were characterized by reduced connectivity within a distributed subcortical-cingulate network, supporting a network-level perspective on neural-endocrine coupling following acute stress.

Introduction: Functional Neurological Disorder (FND) affects women approximately three times more often than men. This disparity has largely been attributed to higher trauma prevalence and diagnostic bias, while the potential contribution of hormonal influences has received little attention. Methods: An online questionnaire was distributed through FND clinics in thirteen countries, assessing self-reported symptom change across five hormonal events: hormonal contraception, pregnancy, the menstrual cycle, menopause, and gender-affirming hormone therapy. Eligible participants were cisgender women with a diagnosis of FND, or gender minority individuals (transgender or non-binary). Perceived symptom change was rated on a five-point scale ranging from large improvement to large worsening. Results: Among 262 respondents (96% female; mean age 39 years), several hormonal contexts were associated with self-reported symptom changes. Overall, hormonal contraception and pregnancy were frequently associated with worsening of motor and cognitive symptoms, and menopause with worsening across all symptom domains. Menstrual cycle analysis revealed a phase-dependent pattern: worsening was most frequently reported during menstruation and the luteal phase, whereas improvement was most frequent during the follicular phase. Reported changes were not uniform, with a substantial proportion of participants describing no change or improvement. Conclusion: Self-reported FND symptom severity appears to vary with hormonal context, with motor and cognitive symptoms most consistently affected. Given the retrospective, self-report design, these findings are hypothesis-generating and support prospective research into the role of hormonal transitions in FND.

BackgroundIndividuals with early psychosis (EP) have elevated risk for suicide, the leading cause of death in the first five years following diagnosis. Non-suicidal self-injury (NSSI) significantly predicts suicidal behavior, yet studies of self-injury often exclude participants with psychosis. We investigated effective connectivity in emotion regulation and reward network regions among participants with lifetime history of NSSI or suicide attempt (SA) with and without EP. MethodsResting-state fMRI data were acquired for 23 individuals with EP and 34 non-clinical controls (NCC). We estimated effective connectivity models for regions implicated in the self-injury literature: middle cingulate cortex (MCC), posterior cingulate cortex (PCC), caudate, putamen, posterior superior temporal gyrus (STG), orbitofrontal cortex (OFC), and insula. There were 3 models characterizing different groupings: diagnosis (NCC vs. EP); NSSI (present[+], n=21 vs. absent[-], n=36); and SA (present[+], n=21 vs. absent[-], n=36). ResultsEP was associated with increased STG to PCC and insula to putamen connectivity. NSSI+ (n=7 NCC, 14 EP) had increased PCC to insula lagged connectivity and increased contemporaneous bilateral putamen activity, relative to NSSI- (n=27 NCC, 9 EP). NSSI was positively correlated with lagged insula to putamen activity (p=0.016). SA and NSSI were associated with reduced PCC to caudate connectivity. ConclusionNSSI is associated with increased connectivity within emotion regulation regions and disrupted connectivity between emotion regulation and reward networks modulated by the STG and striatum. Findings are consistent with broader self-injury literature, supporting the utility of using similar interventions from other disorders to address self-injury within EP.

Lesion Network Mapping (LNM) is a framework used for identifying symptom-related brain circuits by projecting lesion locations onto a normative connectome. Recent methodological investigations have raised concerns about the biological interpretation and specificity of the circuits derived using this method, with published LNM maps often showing high similarity across clinically unrelated conditions. Specificity testing has subsequently been put forward as the decisive step to ensure specificity to the symptom in question, accompanied by the argument that this step was not evaluated in the original methodological investigation. Yet, sensitivity testing, specificity testing, case-control LNM, permutation of group labels, and symptom-based LNM involve related operations on connectivity matrix C. We expand on specificity testing in LNM, clarify its relationship to other LNM steps and variants, and examine the persistent repetition among LNM specificity networks across studies. These considerations advance our understanding of the disease-specificity limitation of LNM and encourage the development of new methodological approaches for identifying brain circuits underlying psychiatric and neurological disorders.

1.IntroductionUnderstanding mid-term test-retest reliability and within-subject variability is important for interpreting changes observed in longitudinal and intervention studies. The reliability of resting-state functional magnetic resonance imaging (rs-fMRI) is known to vary across measures and brain regions. However, how reliability differs across functional networks and connectivity-and amplitude-based measures, and whether multi-echo acquisition and processing modify these patterns, remain incompletely characterized. MethodsTwenty-two healthy volunteers underwent two rs-fMRI sessions 15.7 {+/-} 4.0 days apart on a Compact 3T scanner. Multi-echo, middle-echo, and independently acquired single-echo datasets were compared, with multi-echo independent component analysis additionally evaluated as a denoising approach. Functional connectivity (FC) and three amplitude-based measures were evaluated using the Schaefer 400 parcellation. Reliability was systematically assessed using intraclass correlation coefficient (ICC), within-subject standard deviation (wSD), and systematic bias at edge or regional, and network levels. ResultsAcquisition-dependent differences in reliability were generally modest. Multi-echo acquisition and processing increased functional connectivity strength and the magnitude of amplitude-based measures and improved inferior cortical coverage, but these enhancements did not consistently translate into substantially higher ICC or lower wSD. In contrast, reliability showed clear network-dependent differences. FC reliability varied markedly across network pairs and was not explained by connectivity strength alone; pairs involving the default mode and control networks generally showed more favorable profiles than several somatomotor and visual network pairs. Fractional amplitude of low-frequency fluctuations (fALFF) also showed network-dependent reliability, with the most favorable regional reproducibility observed in the default mode and control networks and lower reproducibility in the somatomotor and visual networks. ConclusionThese findings provide practical mid-term reliability benchmarks for rs-fMRI on a Compact 3T scanner and show that measurement stability varies more clearly across measures and functional networks than across acquisition approaches. Key pointsO_LIMid-term test-retest reliability varied more clearly across resting-state measures and functional networks than across acquisition and processing approaches. C_LIO_LIMulti-echo acquisition and processing enhanced functional connectivity strength, amplitude-based signal magnitude, and inferior cortical coverage but did not consistently improve reliability. C_LIO_LIFunctional connectivity strength and fractional amplitude of low-frequency fluctuations showed distinct network-specific reliability profiles, with more favorable reproducibility in default mode and control networks than in several somatomotor and visual networks. C_LI

BackgroundHigh-frequency heart-rate variability (HF-HRV) is a downstream marker of cortico-autonomic regulation linked to executive function. A recent proposal suggests it indexes regulatory processes because it is both a product of and contributor to neural organization within the prefrontal cortex. The oscillatory phase of HF-HRV has been reported to modulate fronto-central EEG amplitude at rest, and this coupling is attenuated in individuals with schizophrenia relative to healthy controls. We evaluated this brain-body correspondence in relation to anxiety symptomatology, which is likewise associated with autonomic dysregulation. MethodsConcurrent EEG and electrocardiography (ECG) were recorded in 22 nonclinical adults at rest and during a mental arithmetic task. Participants rated anxiety severity using the Generalized Anxiety Disorder 7-item scale (GAD-7). We evaluated between-person associations between anxiety severity and HF-HRV-EEG coupling, as well as within-person differences in coupling between rest and mental arithmetic. ResultsAnxiety symptomatology was associated with decreased resting-state phase-amplitude coupling between HF-HRV phase and fronto-central theta amplitude, independent of EEG and HRV covariates. Relative to rest, HF-HRV-theta coupling increased during a cognitive task, independent of condition-related changes in EEG, HR, or respiration. Anxiety severity moderated the task-evoked changes in heart-brain coupling such that more anxious individuals exhibited larger condition-related differences. Simple-slope analyses indicated anxietys effect on coupling at rest was absent when engaged in a task. ConclusionsHF-HRV-theta phase-amplitude coupling captured anxiety-related and state-dependent variance not evident in conventional cardiac or neural indices. This coupling may index a state-sensitive component of cortico-autonomic regulation, although its putative functional role requires direct testing.

BackgroundPsychedelics have been proposed to enhance empathy and social connectedness, but it remains unclear whether these effects reflect global increases in empathic ability, whether they persist beyond the acute drug state, and whether they contribute to later psychological outcomes. MethodsIn a randomized, double-blind, placebo-controlled, parallel-group study, healthy participants received psilocybin (0.17 mg/kg) or placebo. Three dissociable components of empathy were assessed using the Multifaceted Empathy Test at baseline, during the acute drug state, and 7 days later: cognitive empathy (accuracy of emotion identification), emotional arousal (affective activation in response to anothers emotional state) and empathic concern (other-oriented compassion toward the depicted person. Persisting positive psychological effects were assessed at follow-up. Circulating oxytocin was measured, and spectral dynamic causal modeling was applied to resting-state fMRI data acquired during the acute drug state to examine effective connectivity within an empathy-relevant network. ResultsCompared with placebo, psilocybin acutely reduced cognitive empathy selectively for positive stimuli, while increasing emotional arousal for positive stimuli and empathic concern across valences. These empathy-related effects did not persist 7 days later. However, acute increases in empathic concern mediated later positive psychological changes, including improved attitudes about life and self, mood, and relationships. Psilocybin also increased circulating oxytocin compared to baseline, but oxytocin changes were not associated with empathy changes. Effective-connectivity analyses showed that empathic responding under psilocybin was associated with altered directional coupling among superior temporal and parahippocampal regions. ConclusionsPsilocybin does not simply enhance empathy, rather it impairs the identification of positive emotional states while heightening affective engagement and concern. Although these effects do not persist, acute empathic concern may contribute to later positive psychological change.

Background: Choroid plexus (CP) volume is an emerging magnetic resonance imaging (MRI) biomarker in various disorders of the central nervous system (CNS). However, clinical translation is hindered by methodological heterogeneity and inconsistent anatomical coverage. Double inversion recovery (DIR) - a sequence providing dual-tissue suppression - is a promising candidate to improve CP segmentation. Methods: The dataset included 93 scans across healthy subjects and individuals with multiple sclerosis (MS), divided into a training set (n = 63), an internal test set (n = 20), and an external test set (n = 10). First, relative CP signal intensity and tissue contrast ratios on DIR were compared against fluid-attenuated inversion recovery (FLAIR) and T1-weighted (T1w) sequences (pre- and post-contrast). Reproducibility of manual CP segmentations was assessed via intraclass correlation coefficients (ICCs). Subsequently, we developed a 3D nnU-Net model for CP segmentation based on manually labeled DIR masks. Model performance was evaluated against manual segmentation using spatial overlap and volumetric error metrics. Finally, we compared our DIR-based model against three publicly available T1w- or FLAIR-based tools by assessing slice-wise volume distributions and voxel-wise density maps. Results: DIR demonstrated the highest CP signal intensity and most consistent tissue contrast among evaluated MRI sequences (p < 0.001). Intra- and inter-rater agreement for manual CP segmentations was robust (ICC = 0.92 and 0.83, respectively). The trained nnU-Net achieved high internal accuracy (Dice = 0.82) independent of scanner, diagnosis, or absolute CP volume, and generalized well to the external test set (Dice = 0.75). Compared to public T1w- and FLAIR-based models, DIR-based approaches (nnU-Net and manual) yielded significantly larger CP volumes (p < 0.01). Axial volume distribution analysis attributed this difference to a distinct bimodal profile in DIR segmentations, more fully capturing the CP inside the temporal horn of the lateral ventricle (p < 0.001 against T1w- and FLAIR-based models). Conclusions: By leveraging the superior tissue contrast of DIR, our nnU-Net model achieves highly accurate CP segmentation that generalizes across scanners and captures the inferior extent of the C-shaped structure often missed by conventional models. This may improve standardization of CP volumetry and allow for more reliable studies in CNS disorders.

Background Alcohol use disorder (AUD) is highly prevalent in schizophrenia, yet the neurobiological basis of this vulnerability remains poorly understood. Neurodevelopmental models suggest that pre-existing brain dysconnectivity may increase vulnerability to AUD. We therefore tested whether schizophrenia-like neurodevelopmental pathology alters how alcohol-related experience is incorporated into large-scale brain networks. Methods Resting-state functional connectivity was assessed in male Sprague-Dawley rats (n = 18-21/group) with neonatal ventral hippocampal lesions (NVHL), a neurodevelopmental model of schizophrenia, and sham-operated controls, with or without voluntary adolescent alcohol exposure. Functional connectivity was assessed using seed-to-voxel and seed-to-seed analyses within a cortico-striato-limbic network. We additionally examined whether individual alcohol intake during adolescence predicted adult functional connectivity according to neurodevelopmental status. Results NVHL and adolescent alcohol exposure independently produced predominantly hypoconnected cortico-striato-limbic networks. However, alcohol exposure did not exacerbate NVHL-associated dysconnectivity but instead induced a distinct network reorganization characterized by functional hyperconnectivity. Although alcohol intake was comparable between groups, dose-dependent relationships between adolescent alcohol consumption and adult functional connectivity were observed in sham animals but were absent or markedly attenuated in NVHL rats. These effects were primarily centered on prelimbic cortex connectivity with the amygdala, hippocampus, and dorsal striatum, highlighting this circuitry as a major locus of altered experience-dependent remodeling. Conclusions These findings suggest that vulnerability to AUD associated with schizophrenia-like neurodevelopment may arise less from additive network dysfunction than from an altered capacity of large-scale brain networks for experience-dependent functional remodeling. Schizophrenia-like neurodevelopmental pathology may therefore change how alcohol-related experience is translated into persistent brain network organization.

Background: Brain banks usually provide small tissue blocks fixed by immersion in neutral-buffered formalin (NBF). While still underexploited for research, gross anatomy laboratories could provide full brains fixed by perfusion with solutions better suited for gross anatomy dissection. However, the chemicals in these solutions might have a different impact on histology protocols for cell quantification than in NBF-fixed brains. The main goal of this study is to compare the effects on the number and size of labeled neurons of the primary motor cortex (PMC) of mouse brains fixed with three different solutions: (1) NBF, typical of brain banks, (2) a saturated salt solution (SSS), and (3) an alcohol-formaldehyde solution (AFS), both used in human anatomy laboratories. Methods: 27 C57BL/6J mouse brains were perfused with the NBF (N=9), SSS (N=9) or AFS (N=9), then cut in 40-m slices and processed with immunohistochemistry to target neurons. Various quantitative variables were assessed manually and automatically on photomicrographs of 3 regions of interest (ROIs) of the PMC per specimen, namely the total and individual neuronal profile areas, number and diameters. The effects of the three fixatives on these variables were compared using ANOVA or Kruskal-Wallis, depending on the distribution. For measures on individual cells, a generalized linear mixed model was applied. Dice coefficients and correlations were applied to evaluate the agreement of the manual and automatic methods. Results: There was no significant difference between the brains fixed by the three fixatives for the total and individual cell areas, the total cell count and the cell diameters. The values obtained from manual and automatic measures had an overall good agreement (Dice coefficients > 0.79). Conclusion: It was found that the SSS and AFS had similar impacts on the quantitative variables in the tissue as the NBF. These results are promising for neuroscientists interested in using brains from anatomy laboratories for quantitative research on neurons from the PMC.