Biology subjects

Mikkelsen, M.

Publications and source records attributed to Mikkelsen, M..

10 recordsLinked to original sources

bioRxiv2026

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

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.

neuroscience↗

bioRxiv2025

Benchmarking the Impact of Anatomical Segmentation on In Vivo Magnetic Resonance Spectroscopy

PurposeEstimation of metabolite concentrations in brain magnetic resonance spectroscopy (MRS) requires correction for differences in tissue water content, relaxation properties, and the proportions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Accurate knowledge of the relative proportions of these tissue classes within the volume of interest is therefore essential for reliable quantification. Commonly used brain segmentation tools differ in their algorithms, priors, and implementation, potentially introducing variability in MRS-derived concentration estimates. This study investigates the impact of segmentation software on estimated absolute concentrations. MethodsThree segmentation software tools, ANTs, FSL, and SPM, were evaluated. Segmentations were applied to an in vivo test-retest MR dataset to assess (1) differences in estimated tissue fractions, and (2) how these differences propagate into tissue-corrected metabolite concentrations. As an additional validity check and biological benchmark of segmentation performance, age-related associations with GM and total creatine (tCr) were examined. ResultsSignificant differences (p < 0.0001) were observed in tissue fraction estimates between segmentation tools, leading to differences in metabolite concentration estimates of up to 9% under identical acquisition and modeling conditions. Although the strength of the correlation varied between segmentation methods, no statistically significant differences were found. ConclusionThe choice of segmentation methodology contributed substantially to variability in MRS "absolute" metabolite concentration estimates. These results underscore the need for transparent segmentation reporting to ensure reproducibility and cross-study comparability in MRS research. Quantifying the segmentation-driven variability allows researchers to contextualize cross-study differences, helping determine whether observed effects are methodological or biologically meaningful.

neuroscience↗

bioRxiv2025

Test-retest reliability of multi-metabolite edited MRS at 3T using PRESS and sLASER

PurposeSpectral editing is the most common MRS approach for noninvasive in vivo measurement of low-concentration, strongly overlapped metabolites in the brain, such as {gamma}-aminobutyric acid (GABA) and glutathione (GSH). Multi-metabolite editing methods, including HERMES and HERCULES, have recently been introduced, where multiple J-coupled metabolites can be edited in a single acquisition without increasing total scan time. Yet little is known regarding the reliability of these methods. This study assessed the test-retest reliability of HERMES and HERCULES, where volume localization was achieved using either PRESS or sLASER. MethodsSixteen healthy adult volunteers were scanned twice in two separate sessions. Single-voxel edited MRS data were acquired in the medial parietal lobe using the following sequences: (1) HERMES-PRESS; (2) HERMES-sLASER; (3) HERCULES-PRESS; (4) HERCULES-sLASER. Spectra were processed and metabolites were quantified using the Osprey software. Data quality metrics and reliability statistics were estimated for all four acquisitions. ResultsHERMES-sLASER demonstrated lower within-subjects coefficients of variation (CVws) for GSH, glutamine (Gln), and glutamate (Glu) + Gln (Glx), suggesting improved reliability compared to HERMES-PRESS. However, GABA + co-edited macromolecules (GABA+) and Glu showed higher CVws for HERMES-sLASER. HERCULES-sLASER produced better reliability than HERCULES-PRESS for GABA+, GSH, Glu, Gln, Glx, aspartate (Asp), and lactate (Lac). N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) showed higher CVws for HERCULES-sLASER. These findings suggest that sLASER may be more advantageous than PRESS for volume localization in simultaneous multi-metabolite editing. ConclusionUsing sLASER yielded better test-retest reliability for most metabolites than using PRESS for volume localization for HERMES and HERCULES.

neuroscience↗

bioRxiv2025

Noise decorrelation optimizes SNR of GABA-edited MRS data: A comparison of RF coil combination methods

Introduction: Determining the best radiofrequency (RF) coil combination method is crucial for maximizing the signal-to-noise ratio (SNR) to detect low concentration metabolites (e.g., {gamma}-aminobutyric acid (GABA)) in magnetic resonance spectroscopy (MRS). We hypothesized that algorithms accounting for noise correlations between coil elements would optimize SNR, given that phased-array coils provide better SNR than surface coils and allow accelerated acquisitions, and methods accounting for noise correlations outperform those assuming no correlations. Methods: We examined six coil combination methods, the latter half accounting for noise correlations: 1) equal weighting; 2) signal weighting; 3) S/N2 weighting; 4) noise-decorrelated combination (nd-comb); 5) whitened singular value decomposition (WSVD); 6) generalized least squares (GLS). We utilized MEGA-PRESS data from 119 participants (mean age: 26.4 {+/-} 1 SD 4.2 years; males/females: 54/65) acquired on 3T GE and Siemens MRI scanners at 11 research sites, obtained from the Big GABA study. We measured the SNR of GABA and N-acetylaspartate (NAA). We also calculated the intersubject coefficients of variation of GABA. Results: There were significant differences in SNR between coil combination methods for both GABA+ and NAA. More specifically, the noise decorrelation methods produced higher GABA+ and NAA SNR than the other approaches, where nd-comb, WSVD, and GLS produced, on average, ~37% and ~34% more SNR than equal weighting, respectively. GLS produced the highest SNR for GABA+ and NAA. The coefficients of variation for GABA+ were generally slightly smaller for the noise decorrelation methods. Conclusion: Noise-decorrelation methods produced higher SNR than other methods, especially GLS, which should be investigated in advanced editing protocols.

neuroscience↗

bioRxiv2022

Transcranial electrical stimulation modulates emotional experience and metabolites in the prefrontal cortex in a donation task

In this study we investigated whether transcranial Direct Current Stimulation (tDCS) applied to two prefrontal cortex regions, the ventromedial prefrontal cortex (vmPFC, anode) and right dorsolateral prefrontal cortex (DLPFC, cathode) can be used to induce changes in self-reported emotions and modulate metabolite concentrations under both electrodes. We employed in vivo quantitative MR Spectroscopy (MRS) in healthy adult participants and quantified the changes in GABA and Glx complex (Glutamate and Glutamine) before and after five sessions of tDCS stimulation. tDCS was delivered at 2mA intensity for 20 minutes for the active group and 1 minute for the sham group. tDCS was applied over five days while participants were engaged in a charitable donation task, known to engage the reward network. We observed increased levels of GABA in vmPFC, but not in DLPFC. Glx levels were decreased in both vmPFC and DLPFC. We found that self-reported happiness increased significantly over time only in the active group. There was a decrease in self-reported guiltiness in both active and sham groups. Altogether, the results indicate that self-reported emotions can be modulated by prefrontal stimulation. This may be because the changes in GABA and Glx concentrations following repeated stimulation induce remote changes in the reward network through interactions with other metabolites, previously thought to be unreachable with noninvasive stimulation techniques.

neuroscience↗

bioRxiv2021

Comparison of seven modelling algorithms for GABA-edited 1H-MRS

Edited MRS sequences are widely used for studying GABA in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multi-site study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An inter-class correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies. HighlightsO_LIGABA-edited MRS data from 222 healthy adults across 20 research sites were analyzed C_LIO_LIData were modelled using seven different algorithms, yielding GABA+ and Glx estimates C_LIO_LIModerate agreement was seen across all the tested algorithms C_LIO_LIAdding a component to represent co-edited macromolecule signals improved concordance C_LIO_LIBaseline modelling emerged as major factor differentiating outcomes C_LI

neuroscience↗

bioRxiv2021

NIfTI-MRS: A standard format for magnetic resonance spectroscopic data

PurposeThe use of multiple data formats in the MRS community currently hinders data sharing and integration. NIfTI-MRS is proposed as a standard MR spectroscopy data format, which is implemented as an extension to the neuroimaging informatics technology initiative (NIfTI) format. Using this standardised format will facilitate data sharing, ease algorithm development, and encourage the integration of MRS analysis with other imaging modalities. MethodsA file format based on the NIfTI header extension framework was designed to incorporate essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to enable conversion of single-voxel and spectroscopic imaging data to NIfTI-MRS. To provide visualisation of data in NIfTI-MRS, a dedicated plugin is implemented for FSLeyes, the FSL image viewer. ResultsAlongside online documentation, ten example datasets are provided in the proposed format. In addition, minimal examples of NIfTI-MRS readers have been implemented. The conversion software, spec2nii, currently converts fourteen formats to NIfTI-MRS, including DICOM and vendor proprietary formats. ConclusionThe proposed format aims to solve the issue of multiple data formats being used in the MRS community. By providing a single conversion point, it aims to simplify the processing and analysis of MRS data, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. It also opens possibility of greater standardisation and harmonisation. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, as a viewer.

neuroscience↗

bioRxiv2021

The Macromolecular MR Spectrum in Healthy Aging

PurposeMobile macromolecules (MMs) from amino acids, cytosolic proteins and mobile lipids contribute a significant spectral background underlying the metabolite signals in the MR spectrum. A recent consensus recommends that MM contributions should be removed or included in modeling basis sets for determination of metabolite concentrations and/or metabolite ratios. The purpose of this study was to acquire the MM spectrum from healthy participants at a range of ages, and to investigate changes in the signals with age and sex groups. MethodsInversion time (TI) series were acquired to determine an optimal inversion time to null the metabolite signals. Experiments were carried out using a single adiabatic hyperbolic-secant inversion pulse. After the preliminary experiment, 102 volunteers (49M/53F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). The protocol consisted of a T1-weighted MPRAGE for structural images, followed by PRESS localization using a voxel size of 30 x 26 x 26 mm3 with pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled using a reduced basis set (NAA, Cr, Cho, Glu) and a flexible spline baseline (0.1 ppm knot spacing) followed by subtraction of the modeled metabolite signals to yield a clean MM spectrum, using the Osprey software. Pearsons correlation coefficient was calculated between integrals and age for the 14 MM signals between 0.9-4.2 ppm. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes. Relationships between brain tissues with age and sex groups were also measured. ResultsMM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM integrals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > 0.004). No differences were observed between sex groups. The voxels were segmented as 80 {+/-} 4% white matter, 18 {+/-} 4% gray matter, and 2 {+/-} 1% CSF for CSO and 28 {+/-} 4% white matter, 61 {+/-} 4% gray matter and 11 {+/-} 1% CSF for PCC. WM and GM showed a significant (p < 0.05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions. ConclusionOur findings indicate that the MM spectrum is stable across a large age range and between sexes, suggesting a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups. HighlightsO_LIA large publicly available MM-aging dataset is presented. C_LIO_LIMacromolecule signals do not change with age between 20 and 70. C_LIO_LIThere is no sex difference for macromolecule integrals. C_LI

bioengineering↗

bioRxiv2020

In Vivo Brain Glutathione is Higher in Older Age and Correlates with Mobility

Brain markers of oxidative damage increase with advancing age. In response, brain antioxidant levels may also increase with age, although this has not been well investigated. Here we used edited magnetic resonance spectroscopy to quantify endogenous levels of glutathione (GSH, one of the most abundant brain antioxidants) in 37 young (mean: 21.8 (2.5) years; 19 F) and 23 older adults (mean: 72.8 (8.9) years; 19 F). Accounting for age-related atrophy, we identified higher frontal and sensorimotor GSH levels for the older compared to the younger adults. For the older adults only, higher sensorimotor (but not frontal) GSH was correlated with poorer balance, gait, and manual dexterity. This suggests a regionally-specific relationship between higher brain oxidative stress levels and motor performance declines with age. We suggest these findings reflect a compensatory upregulation of GSH in response to increasing brain oxidative stress with normal aging. Together, these results provide insight into age differences in brain antioxidant levels and implications for motor function.

neuroscience↗

bioRxiv2020

Osprey: Open-Source Processing, Reconstruction & Estimation of Magnetic Resonance Spectroscopy Data

BackgroundProcessing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization. New MethodOsprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects. ResultsOsprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques. Comparison with Existing Method(s)Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Ospreys open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis. ConclusionsOsprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.

biochemistry↗