NeuroImage: Clinical

Magnetic Resonance Spectroscopy Imaging (MRSI) offers spatially-resolved, neurometabolic information, acquired non-invasively at whole-brain scales from human subjects. Analysis of MRSI however, is extremely challenging. The metabolic information is highly convolved, and sparsely distributed across millions of spatial-spectral datapoints, allowing for little direct human interpretation. Conversely, the overall low signal-to-noise with high-intensity artifacts can confound unsupervised machine le...

Premature birth occurs during a phase of intense brain maturation, making white matter (WM) particularly vulnerable to injury. Beyond major lesions, subtle and widespread microstructural alterations also contribute to later neurodevelopmental impairments. We aimed to characterize the impact of key clinical risk factors on global and tract-specific WM microstructure at term-equivalent age (TEA), using 3T-diffusion-MRI data of 111 infants born before 33 weeks of gestation. We developed a lesion-ro...

BackgroundSpeech cortical mapping (SCM) conducted with widely available functional MRI (fMRI) can yield divergent results compared to the more commonly used navigated TMS (nTMS). The impact of specific fMRI task paradigms and preprocessing choices on reaching similarity with nTMS has not been explored before. ObjectiveTo test how the fMRI experimental task and spatial smoothing of the data compare with nTMS-based results, to subsequently increase the reliability of object naming fMRI for SCM. ...

BackgroundRecovery from chronic post-stroke aphasia is highly heterogeneous and shaped by lesion characteristics, brain integrity, and systemic health. Traditional group-level models struggle to capture this multidimensional, dynamic variability. Digital twin approaches - patient-specific, continually updating models - may enable individualized prediction and counterfactual evaluation of modifiable risk factors. Therefore, the aim was to develop and validate a proof-of-concept digital twin that ...

Sleep problems and sensory over-responsivity (SOR) are common, co-occurring, and early-emerging features of Autism Spectrum Disorder (ASD). Yet, the early neural mechanisms underlying this relationship remain unclear. Here, we used resting-state fMRI data from the Infant Brain Imaging Study (IBIS) to examine how brain connectivity at 6 months may relate to parent-reported measures of sleep-onset problems and SOR in infants at varying familial likelihood for ASD. The right anterior insula was use...

BACKGROUND AND PURPOSEStructural changes following pediatric intracerebral hemorrhage (ICH) caused by ruptured brain vascular malformations remain poorly understood. We conducted a longitudinal study to examine morphometric changes in brain volume and cortical thickness across ipsilesional and contralesional hemispheres following unilateral ICH. METHODSBrain magnetic resonance imaging (MRI) was acquired in 20 patients aged 6-18 years (Median: 13, IQR: 9.3-16) at presentation of ICH prior to tre...

PurposeMELD Graph is a state-of-the-art artificial intelligence (AI) model for automated detection of focal cortical dysplasia (FCD), but its performance remains limited, highlighting the need to investigate which aspects of the pipeline affect its accuracy. MethodsA retrospective failure-mode analysis of the MELD Graph pipeline was performed in 242 subjects, with model predictions and FreeSurfer segmentations reviewed to classify errors as segmentation-associated or algorithm-related. FCD imag...

Task-based functional magnetic resonance imaging (fMRI) examines how the brain dynamically responds to cognitive and perceptual demands, offering complementary insight beyond traditional activation-based analyses in schizophrenia. Prior task-based fMRI studies have identified reduced functional connectivity within auditory and associated cortical areas. In this study, we investigated task-evoked functional connectivity and brain state dynamics in 25 healthy controls, 23 patients with schizophren...

Reading proficiency is essential for everyday life, with the Visual Word Form Area (VWFA) of the brains reading network playing a key role in fluent reading. Reduced VWFA activation has been linked to impaired reading. Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback allows individuals to learn to regulate brain activity in targeted brain areas. While our previous study demonstrated the feasibility of VWFA regulation in adults with typical reading skills, this study invest...

BackgroundMRI plays an essential role in diagnosing and monitoring neurological diseases. Conventional protocols rely on multiple sequences to obtain complementary contrasts, increasing scan time, cost, and tolerability. Generating multiple contrasts from a single acquisition may streamline workflow while maintaining clinical utility. PurposeTrain attention-based convolutional neural networks (ACNNs) to generate clinical-quality FLAIR, MPRAGE, R2*, and derived contrasts from a single Gradient E...

Dystonia is one of the most prevalent movement disorders, but its neural substrates have remained enigmatic despite decades of research. Brain lesions leading to dystonia offer unique causal inference that could lend insight into the neural networks driving the disorder. Here, we studied the published cases of lesions causing dystonia to a variety of different body parts (n=179) and used lesion network mapping to test whether lesion locations mapped to a common brain network. Specificity was inv...

BackgroundAberrant myelination represents a critical but understudied mechanism in cognitive difficulties associated with neurodevelopmental conditions. Neurofibromatosis 1 (NF1), provides a unique monogenic model to investigate this relationship, as white matter abnormalities are consistently observed, yet their microstructural basis remains uncharacterized. We present the first dual-modality quantitative myelin mapping study in NF1, employing Magnetization Transfer and T1W/T2W ratio imaging to...

BackgroundMild cognitive impairment (MCI) precedes Alzheimers disease (AD) in [~]40% of cases, with early language deficits distinguishing converters. This study develops a DTI radiomics model from language network gray matter to predict MCI to AD conversion and identify preclinical biomarkers. MethodsThis retrospective case-control study analyzed diffusion tensor imaging (DTI) data from 97 individuals with MCI (29 converters, 68 non-converters) from the Alzheimers Disease Neuroimaging Initiati...

BackgroundDeep grey matter structures such as the thalamus and basal nuclei are implicated in numerous neurological disorders, yet accurate segmentation of these structures from standard T1-weighted MRI remains challenging due to poor intra-subcortical contrast, long preprocessing pipelines, and fragmented toolsets. MethodsWe introduce THOMASINA a deep learning pipeline for comprehensive subcortical segmentation from standard T1-weighted (T1w) as well as white-matter-nulled (WMn) MRI. The metho...

Deep-learning based super-resolution has shown promise for enhancing the spatial resolution of brain magnetic resonance images, which may help visualize small anatomical structures more clearly. However, when only limited training data are available, it remains uncertain which model assessment method provides the most reliable estimate of out-of-sample performance. In this study, three widely used assessment strategies (three-way holdout, k-fold cross-validation, and nested cross-validation) wer...

IntroductionIdiopathic normal pressure hydrocephalus (iNPH) is a partially reversible neurological disorder in which imaging biomarkers support diagnosis and surgical decision-making. The callosal angle (CA) is one of the most robust radiological markers of iNPH and has also been associated with postoperative shunt outcome. However, several manual measurement variants exist and artificial intelligence (AI)-based tools now enable automatic CA measurement. Materials and MethodsIn total 71 patient...

Traumatic brain injury (TBI), particularly sports- and recreational activity related mild TBI (mTBI), is common in young adults and can be followed by persistent attentional and executive complaints. This study investigated chronic ([≥]6 months post-injury) structural brain alterations in gray matter (GM) and white matter (WM) and their associations with self-reported inattentive and hyperactive/impulsive symptoms, with a focus on sex-differentiated patterns. Structural brain properties in gr...

Focused ultrasound can be delivered through the temporal window to modulate heterogeneously located brain areas. Acoustic simulations allow for safety assessments when dynamically targeting brain structures, but the mismatch between simulation and measured focal pressure can vary across the steerable range due to mechanically inaccurate assumptions made about the skull and transducer. Here, we describe efficient methods for simulation-measurement calibration using axisymmetric projections and sp...

Neuroimaging faces a reproducibility crisis, where studies on small, heterogeneous datasets produce unreliable brain-wide associations and AI models that fail to generalize. To address this, we introduce GenBrain, a generative foundation model pretrained on approximately 1.2 million 3D scans from over 44,000 individuals across 34 imaging modalities to learn a population prior of brain structure and function. Crucially, GenBrain enables rapid, data-efficient adaptation, allowing any targeted stud...

Vortioxetine has been reported to alleviate cognitive deficits in patients with depression, accompanied by changes in functional connectivity (FC). An open-label study suggested potential benefits of vortioxetine in patients with mild cognitive impairment (MCI), a condition also characterized by both cognitive and FC alterations. However, controlled studies are required to rule out nonspecific treatment effects and to determine whether FC changes are generalizable to this population. To address...