This study investigated whether childhood white matter organization in those with and without ADHD predicted the emergence of internalizing problems in adolescence. Further, we aimed to determine whether (i) this longitudinal effect was mediated by motor skill level, and/or (ii) white matter organization in children with ADHD mediated the expected relationship between motor skill level and internalizing problems in adolescence. Participants were 40 children with ADHD and 36 typically developing (TD) controls aged between 8 and 13 years, who were followed-up during adolescence (12-18 years). All underwent diffusion MRI at Time 1, and assessment of motor competence using the Movement ABC-2 (MABC-2). At Time 2, internalizing problems (i.e., 'depression', 'anxiety', and 'somatization') were measured using the parent- and self-report Behavior Assessment System for Children (BASC). Following pre-processing of diffusion MRI scans, fixel based analysis was conducted and fibre cross-section (FC) extracted. TractSeg was then used to delineate the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF) and the uncinate fasciculus (UC). Results showed that childhood FC within the UF was a significant predictor of parent and child-rated depression scores in adolescence. Further, childhood FC of the bilaterial ILF was a significant predictor of parent report depression scores in adolescence. These effects were stable for those with and without ADHD, and no group differences in FC were observed in those white matter regions found to be associated with adolescent depressive symptoms. We failed to find evidence that motor ability mediated the relationship between white matter organization of the UF of ILF and depressive symptoms. When childhood motor ability was considered as a predictor of adolescent depressive scores (an effect that was significant for parent reported effects), this effect was mediated by childhood FC of the UF. This work suggests that low motor skill in children with and without ADHD may provide a developmental marker for emotional and behavioral dysregulation in adolescence, with this effect partly explained by childhood white matter organization within fronto-limbic circuitry.
Lesion-symptom mapping is widely used to identify causal relationships between brain structures and behaviour, and has played a central role in neuropsychologically informed network models of cognition. However, even recent approaches remain constrained by a one-to-one mapping framework, which oversimplifies the complex relationships between network-level damage and cognitive deficits. In addition, the non-orthogonality of cortical and white matter damage makes it difficult to disentangle their distinct contributions. Here, we used graph-based multilayer network analysis to address these limitations and evaluate clinical relevance. Using neuroanatomical and longitudinal neuropsychological data from 252 patients who underwent awake neurosurgery for low-grade glioma, we constructed interactive, three-layer networks for each hemisphere. Layer 1 comprised neuropsychological tasks (NT), layer 2 structural disconnections (SD), and layer 3 cortical damage (CD). Nodes represented tasks, white matter tracts, and cortical parcels, respectively, whereas within-layer edges captured correlations in performance or co-occurring damage patterns. Multilayer community detection identified domain- and hemisphere-specific brain-behaviour motifs linking executive, language, and spatial functions to distinct combinations of cortical and white matter disruption, a pattern confirmed by two spatial embedding approaches. Centrality analyses revealed a continuum of mapping relationships, ranging from one-to-one to one-to-many associations, indicating that tasks such as verbal fluency are better explained by multiple disconnection mechanisms. Additional analyses uncovered many-to-one and many-to-many relationships and highlighted tracts and cortical regions with domain-general relevance. Together, these findings support a neurobiologically grounded, network-oriented account of how structural brain damage gives rise to cognitive deficits, with implications for clinical care.
Objectives Parkinson's disease (PD) involves large-scale network disruptions, yet functional connectivity (FC) alterations specific to distinct primary motor cortex (M1) subregions and their subcortical targets remain poorly characterized. We aimed to investigate subregion-specific resting-state FC alterations in PD and their clinical associations. Methods Resting-state fMRI data from 37 PD patients and 37 matched healthy controls were analyzed. Seed-to-voxel and expanded ROI-to-ROI analyses (incorporating subcortical nuclei) mapped FC patterns of two M1 subregions: inter-effector and effector-specific. A System Segregation index quantitatively assessed large-scale network boundaries. Results PD patients exhibited local intra-M1 hyperconnectivity and subsystem-specific cortico-subcortical hyperconnectivity, particularly involving the putamen and thalamus for the effector-specific region. Seed-to-voxel analyses revealed divergent long-range dysconnectivity: the inter-effector region showed hypoconnectivity with sensorimotor and limbic areas, whereas the effector-specific region exhibited sensorimotor hypoconnectivity and a pathological loss of anti-correlation with cerebellar and frontoparietal networks. Quantitative evaluation confirmed a significant collapse in the System Segregation index, validating network boundary breakdown. Clinically, inter-effector hypoconnectivity to the right Rolandic operculum correlated with freezing of gait severity, while aberrant effector-specific-cerebellar positive FC correlated with tremor severity. Conclusions This study delineates a multilayered network pathology in PD, involving local hyperconnectivity, cortico-subcortical desegregation, and quantitatively verified impairment of large-scale network segregation. These subregion-specific alterations, particularly maladaptive cortico-cerebellar and cortico-striatal coupling, reframe PD as a disorder of network dedifferentiation, highlighting M1 subcircuits as targets for symptom-specific neuromodulation.
Background Glymphatic dysfunction is thought to underlie neurodegenerative dementia; however, its interplay with dopaminergic degeneration and concurrent amyloid-β (Aβ) pathology in Parkinson's disease (PD) remains unresolved. This study aimed to evaluate MRI-based glymphatic metrics (the diffusion tensor image analysis along the perivascular space [DTI-ALPS] index and choroid plexus volume [CPV]) and their associations with dopaminergic degeneration, Aβ burden, and cognitive impairment (CI) in PD. Methods 79 PD patients (48 with CI (PD-CI), and 31 cognitive normal (PD-N)) and 28 age-, gender-matched normal controls (NC) were included. Dopaminergic degeneration was measured by dopamine transporter (DAT) availability using 11C-CFT-PET in PD. Additionally, 46 out of 79 PD patients conducted 18F-Florbetapir-PET for quantifying global Aβ burden (Centiloid values) and regional Aβ burden (voxel-wise regression analysis). Results PD-CI showed a significantly reduced DTI-ALPS index (1.31 ± 0.12 vs. 1.40 ± 0.12, p = 0.014; and 1.41 ± 0.12, p = 0.004) and enlarged CPV (1.43 ± 0.31 vs. 1.07 ± 0.18; and 1.14 ± 0.24; p < 0.001 respectively) compared to NC and PD-N. Both the DTI-ALPS index and CPV were significantly correlated with age and caudate DAT availability (CAU_DAT), but not correlated with DAT availability in anterior / posterior putamen, Centiloid values or regional Aβ burden. Further mediation analyses indicated that CAU_DAT mediated the associations between glymphatic metrics and CI after adjustment for covariates, as assessed by the DTI-ALPS index (p = 0.026) and CPV (p = 0.042). Conclusions The caudate dopaminergic degeneration corelates with MRI-based glymphatic metrics and cognitive deterioration in PD.
INTRODUCTION:Post-stroke motor recovery relies on rebalancing of network connectivity, yet objective biomarkers for longitudinal monitoring remain limited. The delta/alpha ratio (DAR) is an established quantitative electroencephalography (qEEG) index of pathological slow-wave activity associated with stroke outcomes; the theta/alpha ratio (TAR) is a related but less-established measure. In this exploratory analysis, we investigated whether these biomarkers can serve as longitudinal treatment-response markers during neurorehabilitation, using electromagnetic network targeting field (ENTF) stimulation. PATIENTS AND METHODS:We conducted a longitudinal analysis of 21 subacute ischemic stroke patients from a double-blind, sham-controlled randomized trial. Participants received either active ENTF stimulation or sham treatment over 15 sessions spanning 2 months. Resting-state EEG was recorded from 8 scalp electrodes. DAR and TAR were computed per session. Linear mixed-effects models (LMM) assessed session-by-treatment interactions. Secondary exploratory analyses examined coherence-based functional connectivity. RESULTS:LMM analysis revealed significant session-by-treatment interactions for both DAR (β = -0.29, p = 0.016) and TAR (β = -0.034, p < 0.001). The active group was associated with steeper biomarker declines in DAR and TAR than sham. Secondary connectivity analyses showed no robust effects. DISCUSSION:In this analysis, DAR and TAR showed treatment-associated longitudinal changes, and were associated with functional improvement trajectories, consistent with their behavior as candidate treatment-response markers. CONCLUSION:These exploratory findings are consistent with DAR and TAR behaving as longitudinal treatment-response markers in post-stroke rehabilitation. The results are hypothesis-generating and require confirmation in a trial with pre-specified endpoints.
BACKGROUND:Non-invasive brain stimulation (NIBS) has emerged as a promising approach to enhance neuroplasticity and functional recovery after stroke. However, substantial inter-individual variability in treatment response limits its clinical translation. The lack of objective neuroimaging biomarkers that capture stimulation-induced brain reorganization remains a critical barrier to personalized neuromodulation. OBJECTIVE:To synthesize current evidence on electroencephalography (EEG)- and functional magnetic resonance imaging (fMRI)-based biomarkers of NIBS-induced neuroplasticity in post-stroke populations and to present a unified neuroimaging framework for predicting treatment response and guiding individualized stimulation strategies. METHODS:This review provides a comprehensive and integrative synthesis of studies investigating neuroimaging correlates of NIBS, focusing on EEG and fMRI modalities. Evidence is organized within a unified neuroimaging framework spanning multiple levels of neural organization, including cortical excitability, oscillatory dynamics, and large-scale functional connectivity. Multimodal and computational approaches, such as EEG-fMRI integration and electric field modeling, are also considered to highlight emerging analytical frameworks. RESULTS:Converging evidence indicates that NIBS induces measurable changes across multiple neural scales. EEG-based metrics, including oscillatory activity, TMS-evoked potentials, and interhemispheric balance indices, reflect modulation of cortical excitability and network dynamics. fMRI findings demonstrate alterations in regional activation and functional connectivity, particularly within motor and association networks. Multimodal approaches further improve the characterization of stimulation-induced reorganization and enhance the prediction of functional recovery. CONCLUSIONS:Neuroimaging biomarkers derived from EEG and fMRI provide critical insight into the mechanisms and variability of NIBS-induced neuroplasticity. Integrating these biomarkers into a unified framework enables stratification of patients and supports the development of precision neuromodulation strategies in stroke rehabilitation. Future research should prioritize large-scale validation and the implementation of biomarker-driven, adaptive stimulation paradigms.
Bipolar disorder (BD) follows a neuro-progressive trajectory, yet current clinical staging models lack robust biological markers. Based on recent evidence, we hypothesized that BD stages are associated with alterations in the functional architecture of the Triple Network Model. We analyzed resting-state fMRI data from 123 individuals spanning five clinically defined BD stages. Using a hierarchical approach, we investigated how functional connectivity features characterize these stages, transitioning from coarse- to fine-grained analyses in both clinical classification (binary early-versus-late grouping to five-stage discrimination) and connectivity metrics (mean and standard deviation of connectivity to topological dynamic features). First, low-level functional connectivity features, combined with gene expression data, discriminated early- from late-stage illness, reaching higher performance than unimodal approaches. Next, evaluating the full staging spectrum revealed a non-linear trajectory in whole-brain connection density, which was lower at each successive stage from 0 to 3 but unexpectedly higher at stage 4. Network topology analysis contextualized this finding, revealing a reorganization of functional hubs in the final stage. Specifically, three hubs within the Salience Network exhibited decreased centrality despite the overall increase in connection density. This shift corresponded to a loss of temporal synchronization between these hubs and default-mode hubs, an axis of communication mediated by the salience network that is known to be important in healthy subjects and disrupted in psychiatric disorders. Overall, our findings suggest that late-stage BD is characterized by a subtle but significant reorganization of brain architecture, accompanied by alterations in the dynamics of the salience network which loses its coordinating role.
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating chronic disease characterized by physical and mental fatigue, post-exertional malaise, muscle pain, headaches, and unrefreshing sleep. Fatigability refers to a reduction of muscular force over time despite willed effort and has a central and a peripheral component. We studied whether fatigability in ME/CFS is related to central or peripheral mechanisms.We recruited fifteen patients with ME/CFS and nineteen age- and sex-matched healthy volunteers (with seven females in each group). Participants performed a fatiguing grip force task, requiring them to maintain 50% of their maximum voluntary force during alternating 30 s blocks of grip and rest. We simultaneously recorded grip force, forearm muscle activity with electromyography, and brain activity with electroencephalography and functional magnetic resonance imaging. Fatigue onset was based on grip force performance and was set individually for each participant.ME/CFS patients generated the same level of maximum voluntary force than healthy volunteers but developed fatigue much earlier. Healthy volunteers increased their muscle and brain activity from the beginning of the task until the onset of fatigue. Specifically, muscle activity shifted from high to low frequencies and brain activity increased steadily in cortical and subcortical areas. Then, muscle and brain activity declined slowly. In contrast, in ME/CFS, the muscles and brain activity only showed minimal fluctuations across all the task blocks.The earlier onset of fatigue in ME/CFS is related to central mechanisms, as their brain did not increase its output to drive muscle activity like healthy volunteers did.While this is a small sample study, and caution should be taken regarding the generalizability of the results, the earlier onset of fatigue in ME/CFS was observed to be related to central mechanisms. The brain in ME/CFS participants did not increase its output to drive muscle activity like healthy volunteers did.
Children with autism spectrum disorder (ASD) often exhibit language deficits, yet the influence of varying language deficits on global white matter networks remains underexplored.In this study, diffusion-weighted imaging data were collected from a cohort of Chinese children with ASD (n = 67, 54 boys) and typically developing (TD) children (n = 36, 23 boys) aged 20 to 93 months. K-means clustering divided the ASD sample into higher language (ASD-HL, n = 29) and lower language (ASD-LL, n = 38) subgroups. We examined topological properties of brain networks and compared global and nodal characteristics across ASD subgroups and TD children. Relationships between autism symptom severity, language abilities, and brain network characteristics were also assessed.The ASD-LL subgroup showed reduced global efficiency (Eg), fewer hubs, decreased fiber connectivity, and fewer inter-hemispheric connections, compared to both ASD-HL and TD groups. Decreased Eg was associated with more severe autism symptoms in the ASD-LL subgroup, but not in the ASD-HL subgroup. Moderation analysis revealed that language ability significantly moderated the link between symptom severity and Eg: higher symptom severity was significantly associated with lower Eg in children with lower language ability, but not in those with higher language ability.These findings suggest that language deficits contribute to alterations in white matter networks and may modulate the impact of autism symptoms on brain structural inefficiency in children with ASD. This study underscores the importance of targeting language skills in interventions and using language ability as a key stratification factor in ASD research.
OBJECTIVES:Microvascular remodeling and blood-brain barrier dysfunction (BBBD) are increasingly recognized as contributors to epilepsy. However, commonly used vascular imaging markers are often state-dependent and lack spatial specificity. We aimed to (1) validate plasma volume fraction (vₚ) derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a sensitive marker of microvascular changes; (2) characterize the vₚ alterations in patients with drug-resistant epilepsy (DRE); and (3) assess the spatial relationship between vₚ abnormalities and BBBD. METHODS:We analyzed DCE-MRI images from 49 people with epilepsy (PWE) and 68 healthy controls across two sites. vₚ and BBB permeability were quantified using BBBdetect software. Voxel-wise vₚ was estimated using the extended Tofts model, and BBBD was quantified using slope-based permeability mapping. Both measures were summarized using modified z-scores, with suprathreshold abnormality defined as modified z-score > 2. We performed region-wise and lobe-wise analyses restricted to gray matter and trained supervised classifiers to distinguish PWE from controls using regional z-vₚ and z-BBBD features. RESULTS:Compared with controls, PWE showed increased voxel-wise and region-wise vₚ abnormality burden, with a non-uniform spatial pattern that includes prominent fronto-temporal elevations and frequent involvement of limbic regions. BBBD was common and spatially diffuse. Restricting analysis to regions with co-occurring suprathreshold vₚ and BBBD reduced spatial diffuseness relative to BBBD alone. Multivariate classification achieved encouraging test performance using vascular and barrier features (balanced accuracy = 0.81), with feature importance suggesting complementary contributions from vₚ and BBBD. CONCLUSION:vₚ is a sensitive DCE-MRI-derived marker of microvascular abnormalities in DRE. Integrating vₚ with BBBD enhances the spatial specificity of abnormality patterns and shows encouraging concordance with the clinically suspected epileptogenic territories, warranting prospective validation against clinical reference standards.
Objective: To investigate the clinical efficacy of Individualized Theta Frequency High-Definition Transcranial Alternating Current Stimulation (ITF HD-tACS) and 5 Hz HD-tACS for patients with Post-stroke Cognitive Impairment (PSCI), and to clarify the potential neurophysiological mechanisms through electroencephalogram (EEG) analysis.Methods: In this single-blinded, randomized controlled trial, 34 PSCI patients meeting the inclusion criteria were randomly allocated to three groups: the individualized theta frequency group (ITF group), the 5 Hz group, or the sham stimulation group (sham group). The intervention delivered a 1 mA (peak-to-peak) current at the corresponding frequency (ITF or 5 Hz) to the left dorsolateral prefrontal cortex (DLPFC) for 10 consecutive days. We collected scale assessments and 5-min closed-eye resting-state electroencephalogram (EEG) data at two time points: baseline (T0) and the 10th day of intervention, which is after intervention initiation(T1). The assessments included the Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Digit Span Test (DST), Digit Symbol Coding Test (DSCT), Hamilton Depression Scale-17 item (HAMD-17), and Modified Barthel Index (MBI).Results: Behavioral results indicated that the ITF group showed the greatest change amplitude in MoCA scores (T1-T0), which was significantly different from that of the sham group (p = 0.002). Both the ITF group and the 5 Hz group demonstrated substantial improvements in orientation sub-scale scores, AVLT immediate recall, and short-delay recall (all p < 0.05). Compared with the sham group, both the ITF and 5 Hz groups exhibited an increased relative Power Spectral Density (PSD) of the theta band and a decreased relative PSD of the gamma band in the frontal region. There were significant differences in ΔPSD between each stimulation group and the sham group. Moreover, a significant positive correlation was found between frontal theta-band ΔPSD and ΔMoCA in the ITF group(p = 0.017).Conclusion: Theta-tACS is a promising treatment for PSCI patients. ITF-tACS may mediate cognitive improvement by modulating frontal theta oscillations. Due to its significant brain responsiveness, this approach points to an important direction for future individualized neuromodulation.Trial registration: This trial was retrospectively registered in the Chinese Clinical Trial Registry, registration number ChiCTR2600121224.
Advanced brain imaging studies have been scarcely reported in neurodevelopmental encephalopathies. In this study we assess structural brain alterations in three rare neurogenetic disorders primarily affecting glutamatergic neurotransmission, aiming to identify shared and disease-specific neuroanatomical patterns and their clinical correlations. A cohort of patients with SYNGAP1 (n = 19), GRIN gene family (n = 19), and STXBP1 (n = 10) mutations underwent magnetic resonance imaging. Advanced segmentation tools were used to extract regional brain volumes. Volumetric differences between patient and age-matched normative reference templates were assessed using parametric and non-parametric tests, depending on data distribution, and ANCOVA was used to adjust between covariates. Associations with clinical symptoms were evaluated using the appropriate correlation tests. In our cohort, we found that patients exhibited statistically significant and consistent shared differences in brain tissue volumes compared to age-matched templates, including larger volumes in the basal ganglia, thalamus, ventricles, and certain cortical regions, alongside reductions in total white matter, cerebellar, and limbic structures (amygdala and parahippocampal gyrus). Clinically, ventricular enlargement correlated positively with the severity of intellectual disability, language impairment, and motor dysfunction, while total intracranial volume showed negative correlations with these same domains. Distinctive trends included supplementary motor cortex enlargement and cerebellar volume deficit in STXBP1, while amygdala volume deficit was most prominent in SYNGAP1 and GRINpathies. In conclusion, the study suggests the presence of shared and disease-specific brain alterations in SYNGAP1, GRINpathies, and STXBP1 disorders. Overall, brain volumetry may represent a useful exploratory tool, contributing to a more detailed characterization of these diseases while offering insights beyond conventional radiological assessment.
Purpose Data-driven intensity normalization has emerged as an alternative to proportional scaling (PS) and reference-region methods in brain [18F]FDG PET. However, no consensus exists for autoimmune encephalitis (AE), whose variable metabolic patterns and lack of a reliable disease-free reference region complicate normalization. We compared three methods; PS, iterative PS (iPS), and pons-based reference-region (RR) normalization, in patients with definite AE (n = 29, 42 ± 20 years) and healthy controls (HC; n = 53, 46 ± 15 y/o) examined with brain [18F]FDG PET at diagnosis. Methods Three sets of normalized [18F]FDG PET images (2 MBq/kg, Biograph mCT Flow PET/CT system, Siemens Healthcare) were generated using: (1) PS with an eroded AAL grey-matter mask; (2) iPS, applying PS then excluding voxels deviating from controls (SPM12, F-contrast p < 0.01 uncorrected) to create a subject-specific mask; and (3) RR, normalizing to mean pons uptake. Effects were assessed through voxel-based AE vs. HC comparisons in SPM12. Two limbic AE cases were analyzed longitudinally. Results PS and iPS revealed basal ganglia and mesiotemporal hypermetabolism in AE vs. HC that RR failed to detect (p < 0.05 FWE corrected). All methods identified cortical hypometabolism, slightly more extensive with RR. PS and iPS yielded broadly similar results. Follow-up showed that iPS and PS better captured initial abnormalities than RR. Conclusion PS and iterative PS may provide more robust normalization than RR in AE. As interest in neuroinflammatory disorders grows, standardized normalization protocols are needed to ensure consistency across studies.
Progressive supranuclear palsy (PSP) shows a characteristic but incompletely defined pattern of neurodegeneration, in part because prior imaging studies have been limited by small and heterogeneous cohorts. Here, we consolidated evidence for PSP-related gray matter (GM) loss using a coordinate-based meta-analysis and interpreted the resulting atrophy pattern in a network and molecular framework to infer disease-relevant mechanisms. We conducted an Anatomical Likelihood Estimation (ALE) meta-analysis of whole-brain morphometry studies investigating atrophy in PSP, followed by functional decoding to evaluate the functions recruiting the atrophied regions and meta-analytic connectivity to delineate co-activation-based connectivity profiles. Finally, we explored potential neurochemical underpinnings by correlating the atrophy map with PET-derived neurotransmitter density distributions. ALE meta-analysis identified clusters of robust gray matter (GM) atrophy in PSP in the bilateral thalamus & midbrain, left anterior-dorsal insula as well as bilateral caudate nucleus. These regions were shown to be functionally associated with language, body perception, somatosensation and emotion processing. Connectivity analyses indicated coupling with fronto-insular salience-network circuitry and with key subcortical nodes, consistent with a distributed systems-level disturbance. At the molecular level, PSP-related atrophy aligned with higher densities of dopaminergic, serotonergic, and-most prominently-cholinergic markers, suggesting multi-transmitter-system vulnerability with a critical role of the cholinergic architecture. Together, these findings identify an interconnected set of cortical-subcortical targets in PSP whose functional and molecular profiles map onto core clinical features, supporting a network-based view of PSP neurodegeneration beyond isolated local atrophy with critical roles of the insula and the cholinergic system.
Aim: Despite the intimate link between cerebral blood flow (CBF) alterations and Parkinson's disease (PD) pathogenesis and cognitive decline, the precise pathophysiological mechanisms driving this relationship remain elusive. This study seeks to correlate changes in CBF with regional gene expression to advance mechanistic understanding of the disease. Methods: CBF group differences were first determined from ASL data in 53 PD and 40 healthy controls (HC) and subsequently correlated with cognitive scores (Dataset 1). A coordinate-based meta-analysis of published literature provided a second set of CBF differences (Dataset 2). Transcriptomic data from the Allen Human Brain Atlas were then correlated with hemodynamic patterns derived from each dataset to identify genes associated with CBF alterations across two independent datasets. The statistically significant genes from each cohort were intersected to obtain a common gene set, which subsequently underwent functional annotation and cell-type enrichment analysis. Finally, cross-modal spatial correlation was employed to investigate CBF changes associated with neurotransmitters. Results: In dataset 1, PD showed decreased CBF in frontal and occipital regions, but increased CBF in limbic and parietal areas. CBF variations in the hippocampus, parahippocampal gyrus, and postcentral gyrus correlated with cognitive scores (MMSE/MoCA). Dataset 2 revealed frontal region and angular gyri hypoperfusion. Integration with transcriptomic data identified an overlapping gene set, enriched in synaptic structure, plasticity, and energy metabolism pathways. Cellular enrichment showed predominant expression in excitatory/inhibitory neurons, microglia, and oligodendrocyte precursor cells. Neurotransmitter association analysis linked CBF alterations to the norepinephrine transporter (NET). Conclusion: By integrating transcriptomic and neuroimaging findings, this study suggests that CBF alterations may be linked to specific genes and biological processes in PD.
BACKGROUND:Cardiac- and respiration-driven vascular pulsations influence cerebrospinal fluid (CSF) oscillations and neurofluid dynamics and are considered relevant for perivascular fluid transport and brain homeostasis. In atrial fibrillation (AF), irregular cardiac rhythm alters cerebral hemodynamics and may affect CSF flow dynamics. This exploratory pre-post pilot study investigated physiological changes in CSF and blood flow dynamics following AF intervention. METHODS:This pilot study included 7 patients with AF, using a 3 T MRI system. To capture CSF and blood flow, real-time phase-contrast flow MRI was employed in the aqueduct, the internal carotid artery, the jugular vein and the sagittal sinus. T1-weighted MRI and fast T1 mapping characterized the tissue anatomy and integrity and EPI diffusion assessed fluid motion along the perivascular space. Artefact-free STEAM diffusion described whole-brain CSF dynamics. Physiological data were recorded simultaneously during MRI. RESULTS:Before intervention, AF patients exhibited reduced CSF flow and irregular CSF oscillatory patterns. After intervention, CSF dynamics shifted toward more periodic, cardiac-dominated oscillatory patterns, with increased CSF flow volume, consistent with altered neurofluid dynamics following restoration of sinus rhythm. Blood flow in the internal carotid artery, jugular vein, and sagittal sinus similarly shifted toward sinus rhythmic patterns, while DTI-ALPS, quantitative T1 measures, brain volume, ventricular size, and white matter integrity remained unchanged. CONCLUSION:Within-subject comparisons indicated that restoration of sinus rhythm was accompanied by measurable alterations in CSF and blood flow dynamics.
Background Traumatic brain injury (TBI) in the chronic stage (≥ 3 months post-injury) is associated with long-term symptoms and secondary conditions, which have been linked to persistent white matter alterations. Although these changes can be detected using diffusion magnetic resonance imaging (dMRI), it remains unclear whether the findings are consistently reported in the chronic phase of injury. This review aims to summarise and quantify differences in diffusion metrics between individuals with chronic non-sports/non-combat-related TBI and controls. Methods This review followed PRISMA guidelines. Database searches were conducted in MEDLINE, Embase, PsycINFO, and Scopus to identify studies examining dMRI metric changes in chronic TBI. Fractional anisotropy (FA) and mean diffusivity (MD) values were extracted to compute the standardised mean difference for individual fibre pathways. Meta-regression was performed to investigate the effect of clinical-demographic and imaging variables on FA effect sizes. Results Twenty-seven studies were included in the meta-analysis. Decreases in FA and increases in MD were found across multiple white matter pathways in chronic TBI, with more pronounced effects in moderate-to-severe TBI compared with mild injury. The overall largest and most consistent effects were observed in the corpus callosum. Changes in FA were influenced by age, sex, and magnetic field strength. Conclusion This meta-analysis provides quantitative evidence of widespread white matter alterations in the chronic stage of TBI. dMRI measures (FA and MD) are sensitive biomarkers of white matter disruptions and exhibit changes associated with injury severity. Future research should carefully control for confounding factors to enhance data comparability across studies.
Background Prenatal brain development represents a vulnerability window for schizophrenia (SZ). To explore early alterations related to the disorder, we examined sulcal pits —lifespan stable landmarks of fetal cortical folding— as markers of neurodevelopmental differences between SZ patients and healthy controls (HC). Methods T1-weighted MRIs (1.5 T) were obtained from 426 individuals (237 SZ patients: 173 males, 64 females; 189 HC: 93 males, 96 females). Sulcal pits were identified from white matter cortical surfaces reconstructed using FreeSurfer. Graphs were constructed for each lobe and hemisphere and compared based on sulcal pits (SP) features: SP-Position, SP-Depth, SP-SurfaceAreaBasin, SP-Topology, and all combined features (SP-Combined). We tested: i) group differences in the sulcal pits heterogeneity between patients and HC; ii) sulcal pits divergence in patients relative to HC; iii) the association between sulcal pits divergence and Positive and Negative Syndrome Scale (PANSS) scores; iv) regional covariation between the sulcal pits heterogeneity differences and transcriptional profiles across lobes using Partial Least Squared regressions (PLS-R). Analyses were performed in the sex-pooled sample and stratified by sex. Results Patients showed increased heterogeneity compared to HC across hemispheres, frontal, temporal, and parietal lobes. Divergence analyses revealed reduced similarity relative to HC, in the left frontal SP-Combined in males (with a trend-level negative correlation with PANSS scores) and right parietal SP-Topology in females. PLS-R showed sex-specific molecular underpinnings related to the identified differences in the heterogeneity of sulcal pits. Conclusion This study provides novel evidence supporting sulcal pits as early neurodevelopmental markers of sex-specific structural brain variability in SZ.
Despite advances in neuromelanin-sensitive brain imaging and a plethora of software solutions, the reliable non-invasive delineation of the locus coeruleus (LC) in the human brainstem remains challenging. We sought to evaluate the spatial accuracy and consistency of atlas- and probabilistic spatial prior-based LC delineation. We acquired neuromelanin-sensitive 3 T MRI data in healthy volunteers (n = 24; mean age 40.0 ± 16.8 years; 42% female). Manual labelling by 9 raters performed twice provided the basis for individual- and group-level comparisons, showing moderate inter-rater agreement (mean Dice = 0.7). For the atlas-based labelling, we tested seven open-access LC atlases, a consensus reference representing the atlases' overlap and the averaged manual labelling. Open-access atlases demonstrated low spatial concordance (Dice = 0.2-0.4), while the averaged manual labelling atlas had higher spatial overlap (Dice = 0.6). Probabilistic delineation using spatial priors showed the strongest voxel-wise similarity with manual labelling (r = 0.3) when the averaged manual labelling atlas was used as prior. Principal component analysis confirmed the greater spatial compactness for atlas-based labelling. Atlas-based labelling using the averaged manual labelling atlas in an extended 3 T cohort (n = 2393, mean age 58.44 ± 13.75 years) identified that tissue myelin and iron declined continuously from early adulthood, while free tissue water increased - a neurobiological trend robust to atlas choice. LC volume showed an inverted-U trajectory. Our results highlight the potential of atlas-based labelling for LC identification and demonstrate its sensitivity to physiologically grounded aging processes, suggesting that harmonised validation strategies and context-sensitive approaches can improve reliability.
