Biology subjects

Bjornerud, A.

Publications and source records attributed to Bjornerud, A..

10 recordsLinked to original sources

bioRxiv2026

Functional neural signatures of navigation impairment in early Alzheimer's Disease

Spatial navigation is impaired early in Alzheimers disease (AD), but the neural computations affected by AD pathology remain unclear. We combined virtual-reality navigation with fMRI in aged controls, preclinical AD, and early AD participants, relating navigation activity to cerebrospinal fluid biomarkers and genetic risk. Early AD was associated with dissociable alterations: amyloid-{beta}-linked hippocampal hyperactivity during memory-demanding navigation, tau-linked reductions in hexadirectional modulation near the entorhinal cortex, and altered object-centered representations in posterior cingulate and entorhinal-adjacent regions. Object-centered changes related to how participants encoded and retrieved target locations. Hippocampal hyperactivity was the earliest, most robust effect and the only functional measure distinguishing preclinical individuals from controls. These findings connect AD biomarkers to distinct spatial computations in humans and reveal navigation-based functional signatures of neural dysfunction before overt dementia.

neuroscience↗

bioRxiv2025

Cortical thickness changes precede high levels of amyloid by at least seven years

Alzheimers disease (AD) is now defined based on its underlying brain pathology1, with the presence of amyloid (A{beta}) plaques at high enough levels sufficient to warrant a diagnosis in the absence of cognitive symptoms. High levels of PET-detectable A{beta} are widely thought to be the first imaging marker, with structural brain changes detectable on MRI scans thought to occur later. We combined 4570 longitudinal MRIs and 1684 A{beta} PET scans from three cognitively healthy cohorts to test the difference in cortical thickness and its change between those that subsequently converted to be A{beta}-positive or stayed A{beta}-negative, using MRIs acquired exclusively in the years before conversion. We found those that subsequently developed elevated A{beta} levels show both thicker cortex and less cortical thinning, even when the last MRI used to estimate their thickness trajectories was acquired at least seven years before conversion. Many effects remained when accounting for quantitative A{beta} levels, suggesting some cortical thickness effects may be partly independent of A{beta}. Differences in cortical thickness and its change between converters and A{beta}-negative individuals showed moderate alignment with patterns of A{beta} deposition, and the timing of thickness changes tracked the temporal progression of A{beta} accumulation. Thus, if amyloid is AD1, we show that high levels of PET-detectable amyloid are not the first imaging marker of AD, as cortical thickness changes can be traced years before pathological amyloid. This has implications for understanding the sequence of events leading up to the earliest stages of AD.

neuroscience↗

bioRxiv2025

Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes

Individual differences in the volumes of brain structures are often linked to various conditions, including Alzheimers disease, schizophrenia, and overall brain health. However, it remains unclear to what extent these differences reflect individual levels present from young adulthood or diverging aging trajectories from later ages. In this study, we analyze the aging dynamics of the volumes of six brain structures based on magnetic resonance imaging (MRI) scans from a large cross-cohort longitudinal sample of cognitively healthy adults (n = 8,311 with 18,520 MRIs, ages from 18 to 97 years). From general assumptions about structural brain dynamics and measurement noise, a stochastic dynamical model was fitted to the data to estimate both the variability and persistence of structural changes across adulthood. Using this model, we calculated how much of the variance of volumetric differences between individuals can be attributed to stable levels from young adulthood versus systematic changes at older ages, as well as the theoretical sensitivity of longitudinal studies to detect individual differences in change. The findings were as follows: 1) Before age 60 years, inter-individual differences in neuroanatomical volumes almost exclusively reflect stable differences between individuals, while the influence from systematic differences in rate-of-change increases thereafter; up to 50 % of the variation being due to differences in change at 80 years. In contrast, ventricular volume reflects differences in change from early adulthood. 2) Current brain-age models are unlikely to be sensitive to detect differences in aging trajectories. 3) Imaging studies have low reliability in detecting inter-individual brain changes before age 60. After 60 years, the study reliability increases sharply with longer intervals between scans and more modestly with additional intermediate observations. In conclusion, our results reinforce the view that it is critical to distinguish stable early-adulthood levels from systematic differences in change when studying adult brain aging.

neuroscience↗

bioRxiv2022

Normalization of MRI T1w between-scan effects for improved longitudinal volumetric estimates

Variations in image intensities and contrasts between magnetic resonance imaging (MRI) acquisitions affect the subsequent image processing and its derived outcomes. Therefore, comparability between acquisitions is improved if we reduce these variations. This is especially relevant for longitudinal studies where a change of scanner or acquisition protocol often happens between subsequent examinations. In this study, we use a robust intensity distribution alignment (RIDA) method to reduce between-scan effects and improve longitudinal volume change estimates between two MRI scanners - Siemens 1.5T Avanto and 3T Skyra. The method is based on MRI T1w images acquired in close succession and robustly aligns two cumulative distribution functions of voxel intensities to harmonize image intensities and improve image-derived outcomes of a range of subcortical brain. We compare RIDA with volume-based correction - a simple linear regression model. In both cases, we derive intensity and volume transformations from a training dataset of 20 participants scanned on both scanners on the same day and apply to an independent longitudinal test dataset of 243 participants. All participants in the test set were scanned at the Avanto scanner at the baseline and then at the Avanto and Skyra scanners on the same day at the follow-up, on average 4.4 years (sd = 0.5 years) later. This allowed us to directly assess the effect of scanner and protocol change on the longitudinal change estimates. Eight subcortical brain regions were segmented using SAMSEG, and annualized symmetrized percent change in volume between time points was calculated. We find that RIDA significantly reduces between-scan effects and improves longitudinal volume estimates for the amygdala and lateral ventricles. It also reduces between-scan effects for caudate, putamen, and thalamus, but not as much as linear regression models. Whether the method will be useful for a particular study will depend on the image intensity profiles of the scans. Therefore, a pilot study of double-scanned participants is recommended to assess the advantages of the method for the analysis in question.

neuroscience↗

bioRxiv2022

A robust intensity distribution alignment for harmonization of T1w intensity values

Variations in image intensities between magnetic resonance imaging (MRI) acquisitions affect the subsequent image processing and its derived outcomes. Therefore, it is necessary to normalize images of different scanners/acquisitions, especially for longitudinal studies where a change of scanner or pulse sequence often happens. Here, we propose a robust intensity distribution alignment (RIDA) method to remove between-scan effects. The method is based on MRI T1w images acquired in close succession and robustly aligns two cumulative distribution functions (CDF) of voxel intensities to improve image-derived outcomes of a range of subcortical brain structures with different acquisition parameters. We compare RIDA with the other image harmonization methods: mica and RAVEL. We study three intra-scanner and three inter-scanner protocol variations among the same 20 participants scanned with Siemens 1.5T Avanto, 3T Skyra, and 3T Prisma scanners on the same day and use image-derived volumetric outputs from the Sequence Adaptive Multimodal Segmentation (SAMSEG) method. We find that CDF-based intensity harmonization (mica and RIDA) significantly reduces intensity differences, improves consistency in volume quantification, and increases spatial overlap between two images acquired in close succession. The improvements are most considerable if the intensity normalization is based on subcortical structures only (RIDA), excluding cortical regions, instead of the whole brain. However, the effect of the corrections varies considerably as a function of the compared scanners and sequences. In conclusion, the RIDA scaneffect normalization improves the consistency of image-derived measures, but its performance depends on several factors.

neuroscience↗

bioRxiv2021

Evidence for widespread alterations in cortical microstructure after 32 hours of sleep deprivation

Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T1-weighted and T2-weighted magnetic resonance images (T1w/T2w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T1w/T2w ratio in 41 healthy young adults (26 women) before and after 32 hours of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T1w/T2w ratio change after 32 hours in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T1w/T2w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 hours of sleep deprivation yields intracortical T1w/T2w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

neuroscience↗

bioRxiv2020

Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer - ASEG and SAMSEG

An accurate and reliable whole-brain segmentation is a key aspect of longitudinal neuroimaging studies. The ability to measure structural changes reliably is fundamental to detect confidently biological effects, especially when these affects are small. In this work, we undertake a thorough comparative analysis of reliability, bias, sensitivity to detect longitudinal change and diagnostic sensitivity to Alzheimers disease of two subcortical segmentation methods, Automatic Segmentation (ASEG) and Sequence Adaptive Multimodal Segmentation (SAMSEG). These are provided by the recently released version 7.1 of the open-source neuroimaging package FreeSurfer, with ASEG being the default segmentation method. First, we use a large sample of participants (n = 1629) distributed across the lifespan (age range = 4-93 years) to assess the within-session test-retest reliability in eight bilateral subcortical structures: amygdala, caudate, hippocampus, lateral ventricles, nucleus accumbens, pallidum, putamen and thalamus. We performed the analyses separately for a sub-sample scanned on a 1.5T Siemens Avanto (n = 774) and a sub-sample scanned on a 3T Siemens Skyra (n = 855). The absolute symmetrized percent differences across the lifespan indicated relatively constant reliability trajectories across age except for the younger children in the Avanto dataset for ASEG. Although both methods showed high reliability (ICC > 0.95), SAMSEG yielded significantly lower volumetric differences between repeated measures for all subcortical segmentations (p < 0.05) and higher spatial overlap in all structures except putamen, which had significantly higher spatial overlap for ASEG. Second, we tested how well each method was able to detect neuroanatomic volumetric change using longitudinal follow up scans (n = 491 for Avanto and n = 245 for Skyra; interscan interval = 1-10 years). Both methods showed excellent ability to detect longitudinal change, but yielded age-trajectories with notable differences for most structures, including the hippocampus and the amygdala. For instance, ASEG hippocampal volumes showed a steady age-decline from subjects in their twenties, while SAMSEG hippocampal volumes were stable until their sixties. Finally, we tested sensitivity of each method to clinically relevant change. We compared annual rate of hippocampal atrophy in a group of cognitively normal older adults (n = 20), patients with mild cognitive impairment (n = 20) and patients with Alzheimers disease (n = 20). SAMSEG was more sensitive to detect differences in atrophy between the groups, demonstrating ability to detect clinically relevant longitudinal changes. Both ASEG and SAMSEG were reliable and led to detection of within-person longitudinal change. However, SAMSEG yielded more consistent measurements between repeated scans without a lack of sensitivity to changes.

neuroscience↗

bioRxiv2020

Sleep and sleep deprivation differentially alter white matter microstructure: a mixed model design utilising advanced diffusion modelling

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across 4 time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group x time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

neuroscience↗

bioRxiv2019

ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

neuroscience↗

bioRxiv2018

Waves of maturation and senescence in micro-structural MRI markers of human cortical myelination over the lifespan

Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker linked to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8-85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of 7 cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30s but there was a second wave reaching stability in the 50s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60s, but in other left hemisphere regions, there was no significant decline from the stable plateau. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination.

neuroscience↗