NIfTI-MRS format specification

Zenodo (CERN European Organization for Nuclear Research) · 2026-04-09

Data format specification for the NIfTI-MRS file format. NIfTI-MRS is a NIfTI derived format for storing magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) data. Generated from the specification at the NIfTI-MRS GitHub repository. Documentation for the format is available online.

Oxygenation and Organ Function: The Timeless Quest to Preserve Function and Avoid Toxicity

American Journal of Respiratory and Critical Care Medicine · 2026-01-30

GABA and Glx Distinctively Predict Motor Learning and Retention in Young and Older Adults

Journal of Neuroscience · 2026-03-09

Gamma-aminobutyric acid (GABA) and glutamate are fundamental in neural plasticity. Motor learning is predicted by baseline levels of these metabolites and their modulation in the sensorimotor cortex (SM1), but less is known about the metabolic activity in other areas that support learning, such as the dorsolateral prefrontal cortex (DLPFC), as well as the practice-induced metabolic modulation and age-associated differences. We investigated whether: (1) motor learning induces a differential degree of metabolic modulation in the SM1 and DLPFC, (2) learning tasks with higher difficulty levels enhance metabolic modulation as compared with those with lower difficulty levels, (3) metabolic modulation during motor learning is age dependent, and (4) training-induced metabolic modulation may have a differential effect on motor learning and retention. Young ( n = 25, 12 females) and older ( n = 21, 10 females) human adults completed a 6 d motor learning protocol with magnetic resonance spectroscopy scans being administered before, during, and after a low and high task complexity training condition. We observed a training-induced reduction of SM1 GABA+, regardless of age and task difficulty level, but no significant changes in DLPFC. Neither region showed a significant Glx (combined glutamate and glutamine) modulation. In addition, baseline GABA+ levels predicted learning, but this effect was region and task difficulty dependent. Age-related differences emerged in the prediction of retention, with older adults showing a beneficiary role of task-induced increase in the SM1 inhibitory tone. These results highlight the complexity of metabolic dynamics in learning and retention, showing their dependency on age, brain region, and task difficulty.

Intensive Care Unit Quality Metrics

Critical Care Clinics · 2026-01-23

Eye-Tracking-BIDS: the Brain Imaging Data Structure extended to gaze position and pupil data

bioRxiv (Cold Spring Harbor Laboratory) · 2026-02-05

The Brain Imaging Data Structure (BIDS) is a widely adopted, community-driven standard to organize neuroimaging data and metadata. Although numerous extensions have been developed to incrementally extend coverage to new modalities and data types, an unambiguous, granular specification for eye-tracking recordings is lacking. Here, we present how BIDS will structure data and metadata produced by eye-tracking devices, including gaze position and pupil data. In addition to prescribing the organization of the unprocessed (raw) recordings and associated metadata as produced by the device, BEP20 also resolves gaps in current BIDS specifications beyond the scope of eye tracking. In particular, it adds a mechanism for including asynchronous model parameters and messages, such as contextual information, statuses, and events, such as triggers, generated by the device. BEP20 includes examples that illustrate its applicability in various experimental settings. This BIDS extension provides a robust standard that supports the development of self-adaptive, open, and automated eye-tracking data structures, thereby bolstering transparency and reliability of results in this field.

NIfTI-MRS format specification

Zenodo (CERN European Organization for Nuclear Research) · 2026-04-09

Data format specification for the NIfTI-MRS file format. NIfTI-MRS is a NIfTI derived format for storing magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) data. Generated from the specification at the NIfTI-MRS GitHub repository. Documentation for the format is available online.

The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification

Magnetic Resonance in Medicine · 2026-04-10

PURPOSE: Quantification of metabolite concentrations using MRS requires tissue-dependent signal corrections. Accurate estimation of voxel tissue composition is therefore essential. Commonly used brain tissue segmentation tools differ in their algorithms and implementation, potentially introducing variability in MRS-derived concentration estimates. This study investigates the impact and reliability of tissue segmentation on metabolite quantification. METHODS: Three segmentation tools (ANTs, FSL, SPM) were evaluated using an in vivo test-retest MRI/MRS dataset. Voxelwise GM/WM/CSF fractions were applied to compute tissue-corrected total creatine (tCr) concentrations. Linear mixed-effects modeling, variance-component partitioning, and intraclass correlation coefficients (ICCs) quantified tool-, session-, and participant-related variance under permutation scenarios that isolated segmentation- and MRS-related effects. As a benchmark for segmentation performance, comparisons with manually segmented data were conducted across three brain regions. RESULTS: Segmentation tools produced systematically different tissue fractions that propagated into differences in tCr concentration estimates. Variance partitioning attributed 56.8%, 50.0%, and 51.3% of total tCr concentration variability to segmentation tool across the three permutations, with participant-specific factors accounting for 34.7%, 36.2%, and 28.5%, respectively. When segmentation variability was held constant, test-retest reliability was high (ICC > 0.8) but dropped to ∼0.5 when both segmentation and MRS variability varied. Agreement with manual segmentation was region- and tool-dependent, with the lowest agreement in the thalamus. CONCLUSION: Tissue segmentation contributes substantially to the variability in MRS-derived metabolite concentration estimates. These results underscore the need for transparent segmentation reporting and data sharing to ensure reproducibility and cross-study comparability in MRS research.

The role of glutathione in cognition, cognitive effort, and cognitive endurance in young and older adults

Frontiers in Aging Neuroscience · 2026-02-27 · 1 citations

Glutathione (GSH) is an abundant antioxidant that protects against endogenous and exogenous toxic agents. The evidence over the relationship between GSH and cognitive integrity during aging is still scarce. In this study we investigated the relationship between GSH and cognitive integrity, cognitive effort and sustained cognitive effort. Second, we explored whether GSH modulation is related to other physiological properties such as blood oxygenation (BOLD response) and to brain excitability (measured by GABA+ and Glx levels). We measured GSH levels through magnetic resonance spectroscopy (HERMES) at baseline and during cognitive task performance in 40 young (18-35 years; 26 female) and 40 older (60-85 years; 21 female) adults in two higher-order processing areas in the brain: the inferior frontal and the inferior parietal cortices (IFC and IPL). GSH in IPL related in opposite directions to distinct memory tasks in young and older adults. GSH levels in both regions showed a modulation as a result of sustained cognitive performance; the direction of this modulation was age- and region-dependent. Furthermore, GSH modulation positively related to cognitive performance in young adults. Finally, GSH showed a relationship with GABA that was region, age and state dependent. These results highlight the heterogeneity of GSH physiology, while its relation with cognition is dependent on age and brain region.

Melatonin Use in the ICU: Mind the (Evidence) Gaps

Critical Care Medicine · 2025-07-18

BIASS: Benchmarking the Impact of Anatomical Segmentation in Spectroscopy

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

Motivation: Water-scaled metabolite estimates in brain magnetic resonance spectroscopy (MRS) usually require corrections accounting for differences in water content and water and metabolite relaxation behavior gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Goal(s): This study aims to determine how strongly commonly used segmentation tools differ in determining partial volumes from a typical MRS single-voxel volume. Approach: By analyzing GM, WM, and CSF fractions obtained from segmentation tools (e.g., FSL, ANTs, and SPM) and comparing them to manual segmentation as "ground truth". Results: Significant variability in tissue fraction estimates across segmentation methods for different brain regions, with CSF showing the highest inconsistencies. Impact: This study demonstrates that segmentation tools obtain different tissue volume fraction estimates in a typical MRS voxel. These findings help researchers and clinicians understand the variability that the choice of segmentation algorithm contributes to the uncertainty of water-scaled concentration estimates.