Journals
2025 EN
Nielsen Brian Skriver · Larsen Brian Roland · Ghazal Afnan Bilal
+4 more
ABSTRACT Neuronal activity in the central nervous system is associated with a [K + ] o transient that is swiftly cleared from the extracellular space, predominantly by the Na + /K + ‐ATPase. The temporal contribution of the glial (α2β2) and the neuronal (α3β1) isoform complexes remains unresolved due to the lack of an isoform‐specific inhibitor. The role of the two main brain isoform complexes in spreading depression (SD) also remains unresolved, but an SD‐mediated increase in [K + ] o may suppress Na + /K + ‐ATPase activity and thereby promote SD propagation. As demonstrated here, inhibitor assays of purified recombinant human and heterologously expressed rat Na + /K + ‐ATPase isoforms demonstrated significant selectivity for inhibition of α2β2 compared to α3β1 isoform complexes by a cyclobutyl perhydro‐1,4‐oxazepine derivative of digoxin (DcB). This phenomenon was utilized to demonstrate the temporal role of α2β2 and α3β1 in [K + ] o clearance in electrically stimulated rat hippocampal slices, as monitored with ion‐sensitive microelectrodes. The observations demonstrate a role of α2β2 in regulating the [K + ] o during electrical stimulus of hippocampal slices, whereas α3β1 serves to restore [K + ] o to baseline post‐stimulus. SD can be triggered by elevated [K + ] o but elevated [K + ] o did not reduce the activity of the Na + /K + ‐ATPase or the glutamate transporters in hippocampal brain slices or upon heterologous expression of individual isoforms in Xenopus oocytes. Our results demonstrate the temporal contribution of the glial and neuronal Na + /K + ‐ATPase isoform complexes to clearance of [K + ] o but do not support the concept that direct effects of elevated [K + ] o on Na + /K + ‐ATPase activity or glutamate transport underlie SD propagation.
Journals
2025 EN
Baljer Levente · Zhang Yiqi · Bourke Niall J.
+8 more
ABSTRACT Owing to the high cost of modern magnetic resonance imaging (MRI) systems, their use in clinical care and neurodevelopmental research is limited to hospitals and universities in high income countries. Ultra‐low‐field systems with significantly lower scanning costs present a promising avenue towards global MRI accessibility; however, their reduced SNR compared to 1.5 or 3 T systems limits their applicability for research and clinical use. In this paper, we describe a deep learning‐based super‐resolution approach to generate high‐resolution isotropic T 2 ‐weighted scans from low‐resolution paediatric input scans. We train a ‘multi‐orientation U‐Net’, which uses multiple low‐resolution anisotropic images acquired in orthogonal orientations to construct a super‐resolved output. Our approach exhibits improved quality of outputs compared to current state‐of‐the‐art methods for super‐resolution of ultra‐low‐field scans in paediatric populations. Crucially for paediatric development, our approach improves reconstruction of deep brain structures with the greatest improvement in volume estimates of the caudate, where our model improves upon the state‐of‐the‐art in: linear correlation ( r = 0.94 vs. 0.84 using existing methods), exact agreement (Lin's concordance correlation = 0.94 vs. 0.80) and mean error (0.05 cm 3 vs. 0.36 cm 3 ). Our research serves as proof‐of‐principle of the viability of training deep‐learning based super‐resolution models for use in neurodevelopmental research and presents the first model trained exclusively on paired ultra‐low‐field and high‐field data from infants.
Journals
2025 EN
Tomas Carissa W. · Fitzgerald Jacklynn M. · Baird C. Lexi
+72 more
ABSTRACT Using functional magnetic resonance imaging (fMRI), symptoms of posttraumatic stress disorder (PTSD) have been associated with aberrations in brain networks in the absence of a given cognitive demand or task, called resting‐state networks. Prior work has focused on disruption in the static functional connectivity (FC) among specific regions constrained by a priori hypotheses. However, dynamic FC, an approach that examines brain network characteristics over time, may provide a more sensitive measure to understand the network properties underlying dysfunction in PTSD. Further, using a data‐driven analytic approach may reveal the contribution of other larger network disturbances beyond those revealed by hypothesis‐driven examinations of ROIs or canonical networks. Therefore, the current study used group independent components analysis (ICA) and graph theory principles to identify, characterize, and subsequently compare brain network dynamics and recurrent connectivity states in a large sample of trauma exposed individuals ( N = 1035) with and without PTSD from the ENIGMA‐PGC PTSD workgroup. Neither static FC nor dynamic FC results showed robust differences between groups. There were also no group differences in dwell time or number of transitions of recurrent connectivity states. This multi‐cohort sample with heterogenous trauma types and demographic features offers a significantly larger scale approach than prior literature with smaller homogenous trauma cohorts. Heterogeneity of PTSD, especially within diffuse brain networks, may not be captured by evaluating only diagnostic groups, further work should be done to evaluate brain network dynamics with respect to specific symptom profiles and trauma types.
Journals
2025 EN
AdesAron Benjamin · Coelho Santiago · Lemberskiy Gregory
+5 more
ABSTRACT The clinical translation of diffusion magnetic resonance imaging (dMRI)‐derived quantitative contrasts hinges on robust reproducibility, minimizing both same‐scanner and cross‐scanner variability. As multi‐site data sets, including multi‐shell dMRI, expand in scope, enhancing reproducibility across variable MRI systems and MRI protocols becomes crucial. This study evaluates the reproducibility of diffusion kurtosis imaging (DKI) metrics (beyond conventional diffusion tensor imaging (DTI)), at the voxel and region‐of‐interest (ROI) levels on magnitude and complex‐valued dMRI data, using denoising with and without harmonization. We compared same‐scanner, cross‐scanner, and cross‐protocol variability for a multi‐shell dMRI protocol (2‐mm isotropic resolution, b = 0, 1000, 2000 s/mm 2 ) in 20 subjects. We first evaluated the effectiveness of Marchenko‐Pastur Principal Component Analysis (MPPCA) based denoising strategies for both magnitude and complex data to mitigate noise‐induced bias and variance, to improve dMRI parametric maps and reproducibility. Next, we examined the impact of denoising under different population analysis approaches, specifically comparing voxel‐wise versus region of interest (ROI)‐based methods. We also evaluated the role of denoising when harmonizing dMRI across scanners and protocols. The results indicate that DTI and DKI maps visually improve after MPPCA denoising, with noticeably fewer outliers in kurtosis maps. Denoising, either using magnitude or complex dMRI, enhances voxel‐wise reproducibility, with test–retest variability of kurtosis indices reduced from 15%–20% without denoising to 5%–10% after denoising. Complex dMRI denoising reduces the noise floor by up to 60%. Denoising not only reduced variability across scans and protocols, but also increased statistical power for low SNR voxel‐wise comparisons when comparing cross sectional groups. In conclusion, MPPCA denoising, either over magnitude or complex dMRI data, enhances the reproducibility and precision of higher‐order diffusion metrics across same‐scanner, cross‐scanner, and cross‐protocol assessments. The enhancement in data quality and precision facilitates the broader application and acceptance of these advanced imaging techniques in both clinical practice and large‐scale neuroimaging studies.
Journals
2025 EN
Ljungberg Emil · Padormo Francesco · Poorman Megan
+31 more
ABSTRACT The lower infrastructure requirements of portable ultra‐low field MRI (ULF‐MRI) systems have enabled their use in diverse settings such as intensive care units and remote medical facilities. The UNITY Project is an international neuroimaging network harnessing this technology, deploying portable ULF‐MRI systems globally to expand access to MRI for studies into brain development. Given the wide range of environments where ULF‐MRI systems may operate, there are external factors that might influence image quality. This work aims to introduce the quality control (QC) framework used by the UNITY Project to investigate how robust the systems are and how QC metrics compare between sites and over time. We present a QC framework using a commercially available phantom, scanned with 64 mT portable MRI systems at 17 sites across 12 countries on four continents. Using automated, open‐source analysis tools, we quantify signal‐to‐noise, image contrast, and geometric distortions. Our results demonstrated that the image quality is robust to the varying operational environment, for example, electromagnetic noise interference and temperature. The Larmor frequency was significantly correlated to room temperature, as was image noise and contrast. Image distortions were less than 2.5 mm, with high robustness over time. Similar to studies at higher field, we found that changes in pulse sequence parameters from software updates had an impact on QC metrics. This study demonstrates that portable ULF‐MRI systems can be deployed in a variety of environments for multi‐center neuroimaging studies and produce robust results.
Journals
2025 EN
Kemp Sarah A. · Bazin PierreLouis · Miletić Steven
+4 more
ABSTRACT Response inhibition, the cancellation of planned movement, is essential for everyday motor control. Extensive fMRI and brain stimulation research provides evidence for the crucial role of a number of cortical and subcortical regions in response inhibition, including the subthalamic nucleus (STN), presupplementary motor area (preSMA) and the inferior frontal gyrus (IFG). Current models assume that these regions operate as a network, with action cancellation originating in the cortical areas and then executed rapidly via the subcortex. Response inhibition slows in older age, a change that has been attributed to deterioration or changes in the connectivity and integrity of this network. However, previous research has mainly used whole‐brain approaches when investigating changes in structural connectivity across the lifespan or has used simpler measures to investigate structural ageing. Here, we used high‐resolution quantitative and diffusion MRI to extensively examine the anatomical changes that occur in this network across the lifespan. We found age‐related changes in iron concentration in these tracts, increases in the apparent diffusion coefficient and some evidence for a decrease in myelin content. Conversely, we found very little evidence for age‐related anatomical changes in the regions themselves. We propose that some of the functional changes observed in these regions in older adult populations (e.g., increased BOLD recruitment) are a reflection of alterations to the connectivity between the regions rather than localised regional change.
Journals
2025 EN
Zhou Xiaojue · Lauharatanahirun Nina · Thurman Steven M.
+9 more
ABSTRACT Previous research has shown that laboratory‐controlled sleep deprivation leads to cognitive impairments, including low vigilance and deficits in working memory. However, the robustness of sleep effects on behavior and brain dynamics in naturalistic settings remains underexplored. In this study, we investigated the impact of naturalistic, unfettered variations in sleep on behavioral performance and brain network dynamics in 39 healthy adults. Using a dynamic networks approach combined with ordinal regression, we show a significant increase in flexibility, a measure of rapid reconfigurations within the brain modules, with decreasing sleep time, particularly in the fronto‐parietal control network, during a psychomotor vigilance (PVT) and visual working memory (VWM) task. This change in network flexibility was not observed during the resting state. Critically, performance itself did not change as a function of sleep, providing preliminary evidence that brain networks may compensate for having a poor night's sleep by recruiting the necessary resources to complete the task. Additional analysis assessing the regularity of sleep indicates a wider change in flexibility during PVT for irregular sleepers in networks including the limbic system, ventral attention network, and somatomotor system. These results provide new insights into the neural and behavioral correlates of naturalistic sleep modulations.
Journals
2025 EN
Rauland Amelie · Meisler Steven L. · AlexanderBloch Aaron F.
+16 more
ABSTRACT Deriving white matter (WM) bundles in vivo has thus far mainly been applied in research settings, leveraging high angular resolution, multi‐shell diffusion MRI (dMRI) acquisitions that enable modern reconstruction methods. However, these advanced acquisitions are both time‐consuming and costly to acquire. The ability to reconstruct WM bundles in the massive amounts of existing single‐shelled, lower angular resolution data from legacy research studies and healthcare systems would offer much broader clinical applications and population‐level generalizability. While legacy scans may offer a valuable, large‐scale complement to contemporary research datasets, the reliability of white matter bundles derived from these scans remains unclear. Here, we leverage a large research dataset where each 64‐direction dMRI scan was acquired as two independent 32‐direction runs per subject. To investigate how a state‐of‐the‐art bundle‐specific reconstruction method generalizes to this data, we evaluated the test–retest reliability of WM bundles reconstructed from the two 32‐direction scans across three orientation distribution function (ODF) reconstruction methods: generalized q‐sampling imaging (GQI), constrained spherical deconvolution (CSD), and single‐shell three‐tissue CSD (SS3T). We found that the majority of WM bundles could be reliably extracted from dMRI scans that were acquired using the 32‐direction, single‐shell acquisition scheme. The mean Dice coefficient of reconstructed WM bundles was consistently higher within subject than between subject for all WM bundles and ODF reconstruction methods, illustrating preservation of person‐specific anatomy. Further, when using features of the bundles to predict complex reasoning assessed using a computerized cognitive battery, we observed stable prediction accuracies ( r : 0.15–0.36) across the test–retest data. Among the three ODF reconstruction methods, SS3T had a good balance between sensitivity and specificity when comparing the reconstructed bundles to atlas bundles, a high intra‐class correlation of extracted features, more plausible bundles, and strong predictive performance. More broadly, these results demonstrate that bundle‐specific reconstruction can achieve robust performance even on lower angular resolution, single‐shell dMRI, with particular advantages for ODF methods optimized for single‐shell data. This highlights the considerable potential for dMRI collected in healthcare settings and legacy research datasets to accelerate and expand the scope of WM research.
Journals
2025 EN
Frenkel Catherine H. · Donahue Erin E. · Cochran Allyson
+6 more
Abstract Objective The Commission on Cancer (CoC) recently introduced a quality metric to optimize time between major head and neck surgery and adjuvant treatment (TAT) ≤6 weeks, as TAT delay adversely impacts patient survival. This study evaluates whether enhanced recovery after surgery (ERAS) for this population reduces the rate of postoperative complications, length of stay (LOS), and TAT. Methods Patients undergoing larynx or oral cavity resection with free flap reconstruction, ERAS, and adjuvant treatment after 2018 were compared to a historical pre‐ERAS cohort. Patients underwent surgery at a single‐institution tertiary referral center for complex head and neck oncology. Differences between groups were compared by chi‐square, Fisher's exact, or Wilcoxon rank‐sum test. TAT >6 weeks was evaluated with univariate and multivariable logistic regression. Results Thirty‐nine pre‐ERAS patients were compared to 39 ERAS patients. No demographic differences existed between groups. LOS was improved with ERAS ( p = 0.005). ERAS patients were discharged to home and returned to their activities of daily living (ADL) earlier ( p = 0.004, 0.001). ADL recovery was associated with on‐time TAT ≤42 days on univariate analysis (OR 1.36, 95% CI 1.13–1.63, p = 0.001). TAT delay was less frequent with ERAS (51.3% vs. 69.2%), but this was not significant after multivariable logistic regression ( p = 0.11). Conclusion ERAS decreases LOS and returns advanced head and neck cancer patients to their ADL sooner. Postoperative ADL recovery independently predicts on‐time adjuvant treatment. Still, compliance beyond 50% with the TAT ≤6 weeks CoC quality metric remains a major treatment barrier.
Journals
2025 EN
Cui Zhibin · Kang Hyunseok · Li Hua
+6 more
ABSTRACT Background Human papilloma virus (HPV)‐associated head and neck squamous cell carcinoma (HNSCC) is an emerging epidemic and a subset of HPV‐positive patients experience aggressive disease with metastases. The CYLD gene is frequently altered in HPV‐positive HNSCC, but the role of these alterations in disease progression is poorly understood. Methods We identified 11 HPV‐positive HNSCC patients with CYLD alterations and assessed their clinical course. We also characterized a unique, HPV‐positive, metastatic, HNSCC patient‐derived xenograft (PDX). Results All 11 patients developed metastasis with reduced overall survival when compared with metastatic HPV‐positive patients with wild‐type CYLD . The metastatic PDX harbored a CYLD mutation (S371*) and exhibited reduced expression of connexin 43, a potentially antimetastatic protein. We also investigated the functional impact of the S371* mutation, as well as 2 CYLD mutations from our 11‐patient cohort. Conclusion Our findings indicate that alterations in CYLD in HPV‐positive HNSCC are associated with metastasis and poor prognosis.