Background Multi-compartment diffusion models and multi-shell acquisitions are increasingly used to overcome limitations of conventional diffusion tensor imaging, but require longer scans and more complex processing. Meanwhile, diffusion MRI classification studies often rely on a narrow set of tensor-derived metrics, especially fractional anisotropy. We investigated whether broader use of tensor-derived features, including shape descriptors, could improve classification without increasing acquisition complexity. Methods Multi-shell diffusion MRI (b = 0, 1000 and 2000 s/mm2) was acquired in 220 participants, including 84 healthy controls and 136 patients with relapsing-remitting multiple sclerosis. Thirteen tensor-derived metrics and three neurite orientation dispersion and density imaging (NODDI) metrics were extracted from 98 automatically parcellated brain regions. Classification was performed using L2-regularized logistic regression within a repeated stratified cross-validation framework. Results A four-metric set comprising fractional anisotropy, mean diffusivity, spherical and linear anisotropy reached an AUC of 0.967, above fractional anisotropy alone (0.922) and comparable to the full 13-metric representation. The point-estimate gain was concentrated in linear anisotropy; spherical anisotropy did not increase performance. NODDI showed no advantage at matched dimensionality; single-shell yielded similar point estimates, with no significant difference detected. Removing lesion voxels reduced performance only in white matter, where classification remained well above chance. Free-water correction and adjustment for age, sex and intracranial volume did not improve classification. Conclusions In this ROI-based diffusion MRI classification, broader use of conventional tensor-derived information showed similar within-cohort discrimination to more complex representations. Linear anisotropy, computed from eigenvalues already available, adds complementary information without requiring additional diffusion contrasts. These findings support exploiting conventional tensor-derived features more comprehensively before adopting more complex diffusion MRI frameworks.
Background Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy alleviates tremor in tremor-dominant Parkinson's disease (TD-PD). However, its effects on the functional network topology remain unclear. Methods Twenty-one TD-PD patients underwent unilateral MRgFUS thalamotomy and clinical and MRI assessments. For the overall cohort, graph theory analysis was employed to examine differences in small-world properties and modular structure between baseline and 6 months after MRgFUS. Changes in topological properties were assessed using paired t-tests or Wilcoxon tests, and their associations with clinical improvement. Additionally, subgroup analyses were performed on responder (n = 10) and relapser (n = 9) data. Results Tremor scores decreased significantly after MRgFUS contralateral to the lesioned thalamus. Significant increases were observed in small-worldness and normalized clustering coefficient after MRgFUS. Inter-modular connectivity showed trend-level enhancement between cortical-basal ganglia and thalamic modules, and between cerebellar and temporal-hippocampal modules. In responder, significant increases were observed in small-worldness, normalized clustering coefficient, and global efficiency, whereas characteristic path length showed a significant decrease. Changes in global efficiency and characteristic path length were significantly correlated with clinical improvement. Conclusion MRgFUS thalamotomy for TD-PD induced partial reorganization of small-world properties, indicating a shift toward a more integrated network topology, especially in responder. Changes correlated with tremor reduction and improved functional disability, highlighting that effective treatment impacts on global network integration.
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.
This study investigated age-related differences in auditory detection and attentional processing in school-aged children with attention-deficit/hyperactivity disorder (ADHD) compared to typically developing (TD) peers, focusing on mismatch negativity (MMN), P3a, and P3b components. Participants were children aged 7-12 years with ADHD (N = 80; 12.0% female) and age-matched TD children (N = 80; 26.3% female). All children completed a three-stimulus auditory oddball task with unilateral presentation of standard, nontarget deviant, and target deviant tones while electroencephalography (EEG) was recorded. Compared with the steady increase in MMN amplitudes observed in TD children, children with ADHD showed reduced MMN amplitudes at ages 9-12 years and a U-shaped MMN age-related pattern. In TD children, more negative MMN amplitudes were associated with faster responses on hit trials. In contrast, children with ADHD showed reduced P3a amplitude at ages 7-8 years, and their P3b latency was significantly associated with behavioral performance. Our findings suggest that children with ADHD may rely more on late-stage cognitive processing to complete auditory attention tasks, whereas TD children benefit from more efficient early perceptual and involuntary attention mechanisms. Altered age-related differences across MMN, P3a, and P3b highlight disruptions in the development of auditory attention systems and may represent candidate neural indices that warrant further evaluation in longitudinal and intervention studies.
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.
Background The clinical efficacy of repetitive transcranial magnetic stimulation (rTMS) in schizophrenia is limited by significant inter-individual heterogeneity, largely due to the lack of personalized targeting. Hypothesis To develop and validate an epicenter-guided computational framework that identifies personalized rTMS targets by integrating individual neuroanatomical and connectome profiles. Study design We established an epicenter-guided framework in a discovery cohort including 532 schizophrenia and 526 healthy controls. The pipeline involved: (1) identifying subject-specific pathological epicenters by correlating regional gray-matter volume reductions with normative functional connectivity profiles; (2) mapping the voxels within the left dorsolateral prefrontal cortex that exhibited maximal functional connectivity to these epicenters; and (3) computing the harmonic centroid of these voxels to define the optimal personalized target. The framework was retrospectively validated in a cohort of schizophrenia receiving a 4-week rTMS treatment. Study results The epicenter-guided framework defined a personalized candidate target for each participant with an identifiable individual epicenter. Individual epicenters converged within higher-order association cortices and subcortical structures, consistent with previous findings in schizophrenia. In the retrospective treatment cohort, nodal integration capability within individual epicenter regions increased significantly after rTMS. Smaller target distance was associated with greater concordance between activity-flow-predicted and observed FC changes and with greater improvement in PANSS negative symptoms. Conclusions We developed an epicenter-guided framework to derive personalized DLPFC targets and, in retrospective validation, found that target proximity relates to both FC normalization and symptom improvement. These findings support further prospective testing of connectivity-informed personalized targeting for rTMS in schizophrenia.
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.
BACKGROUND:The apolipoprotein E ε4 (APOE ε4) allele is the strongest genetic risk factor for Alzheimer's disease (AD); however, its neurobiological impact assessed by neuroimaging outcomes during midlife, before the onset of cognitive impairment, has not been summarised. This systematic review synthesises evidence on neuroimaging differences associated with APOE ε4-carrier status in cognitively healthy midlife adults and evaluates whether AD-related risk can be detected across imaging modalities. METHODS:A literature search was conducted up until November 2025 to identify studies reporting neuroimaging outcomes in healthy adults aged 30-60 years with known APOE genotype. Eligible studies employed positron emission tomography (PET) and/or magnetic resonance imaging (MRI) and reported outcomes stratified by APOE ε4-carrier status. Risk of bias was assessed using the ROBINS-E tool, and a narrative synthesis was performed. RESULTS:Searches yielded 7786 articles, and 46 studies met the inclusion criteria. Nine studies used PET, forty used MRI, and three of these studies employed both modalities. Substantial heterogeneity in methods and outcome reporting meant that a meta-analysis was not feasible. PET evidence consistently identified greater amyloid deposition and lower glucose metabolism in midlife APOE ε4-carriers compared with non-carriers, while MRI findings most reliably indicate higher cerebral blood flow. In contrast, other MRI-derived structural, microstructural, functional, and metabolic findings were mixed and largely inconclusive. CONCLUSION:Cognitively healthy APOE ε4-carriers demonstrate measurable neurobiological differences as early as midlife, consistent with a preclinical vulnerability associated with genetic risk for AD. These findings highlight the importance of characterising APOE-related mechanisms during midlife to inform early detection strategies and the development of preventative interventions for AD.
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 Progressive supranuclear palsy (PSP) is a 4-repeat tauopathy characterized by clinicopathological heterogeneity. The complex interplay between tau deposition, structural changes, and disease spread are unclear. Objectives To investigate the temporospatial patterns of tau propagation and neurodegeneration using multimodal imaging with MRI and flortaucipir (FTP) PET, and determine relationship with clinical heterogeneity. Methods 150 PSP patients (n = 66 Richardson's syndrome [PSP-RS], n = 26 parkinsonism [PSP-P], n = 25 speech-language [PSP-SL], n = 13 progressive gait freezing (PSP-PGF), n = 10 corticobasal syndrome [PSP-CBS], n = 3 frontal, n = 1 oculomotor and n = 6 postural instability) underwent 3 T-MRI and FTP-PET. Forty-three patients died and underwent autopsy. Subtype and Stage Inference (SuStaIn), an unsupervised machine learning algorithm that separates data-driven disease phenotypes distinguished by diverse temporal progression patterns, was applied to both MRI and FTP-PET W-scores (adjusted for age, sex and scanner, using 102 controls). Longitudinal MRI (n = 76) and FTP (n = 56) data, analysed with linear mixed models, were used to assess regional progression patterns and compared with the machine learning predictions. Results Two subtypes emerged across modalities. Subtype 1 exhibited initial subcortical involvement, mainly included PSP-RS and PSP-P patients and mostly featured PSP pathology, while subtype 2 exhibited early cortical involvement, PSP-SL patients and CBD pathology. FTP-PET stages preceded MRI stages, suggesting tau deposition anticipates atrophy. MRI stages were better in capturing clinical progression and predicting longitudinal disease evolution. Conclusions These findings suggest the existence of subcortical and cortical subtypes of PSP, with distinct clinicopathological features. Tau PET and MRI provide complementary insights into disease progression, with MRI more closely reflecting clinical evolution.
Aphasia is increasingly understood as a disorder of disrupted language networks rather than damage to isolated language regions. However, most resting-state functional connectivity studies treat people with aphasia as a single group or classify individuals by overall severity, potentially obscuring qualitative differences in network organization across aphasia types. The present study examined how resting-state functional connectivity varies across aphasia types and how aphasia severity relates to network organization following left-hemisphere stroke. Resting-state fMRI data were analyzed from 89 individuals in the chronic stage of recovery drawn from the open-source Aphasia Recovery Cohort dataset. Network-level and ROI-to-ROI functional connectivity analyses were conducted across 32 predefined dorsal and ventral stream language regions. Lesion-overlap analyses were additionally performed to characterize group-level lesion distributions. Network-level analyses revealed relatively limited effects, whereas ROI-to-ROI analyses demonstrated substantial heterogeneity across aphasia subgroups. Broca's aphasia and severe aphasia demonstrated clearer and more spatially convergent connectivity patterns, whereas anomic, mild, and moderate aphasia groups showed greater heterogeneity and limited group-level effects. Groups showing clearer functional connectivity patterns were also characterized by greater convergence in lesion distributions. Within Broca's aphasia, milder impairment was associated with stronger left-hemisphere and interhemispheric connectivity. Overall, aphasia type-based analyses revealed more differentiated connectivity patterns than severity-based groupings alone. These findings suggest that post-stroke language network organization varies across aphasia types characterized by partially shared clinical and lesion features and may not be fully captured by severity measures alone.
