bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/646273

BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain

Kumral, D.·Sansal, F.·Cesnaite, E.·Mahjoory, K.·Al, E.·Gaebler, M.·Nikulin, V. V.·Villringer, A.
View original source ↗Export metadata ↓

Abstract

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25{+/-}3 years, N=135) and older (67{+/-}4 years, N=54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kumral, D., Sansal, F., Cesnaite, E., Mahjoory, K., Al, E., Gaebler, M., Nikulin, V. V., Villringer, A.. 2019-05-23. BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain. https://doi.org/10.1101/646273

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Epidermal Langerhans Cells Act as Neuroimmune Regulators of Pain and Itch

Neuroimmune interactions in the skin coordinate immune defense and somatosensory perception, yet how immune cells shape sensory signaling remains poorly defined. Here, we show that Langerhans cells (LCs), epidermal antigen-presenting cells, function as local immune-derived amplifiers of cutaneous sensory signaling. Anatomical and transcriptomic analyses reveal preferential LC association with non-peptidergic sensory neurons. LC activation increases neuronal and behavioral responses to thermal, mechanical, and pruritic stimuli without directly exciting sensory neurons, whereas LC inhibition or ablation selectively reduces pruritogen-evoked itch. We identified semaphorin 7A as a candidate LC-expressed mediator. Semaphorin 7A sensitized cultured sensory neurons to chloroquine and histamine, and neutralizing semaphorin 7A abolished the increase in chloroquine-evoked scratching produced by LC activation. Its receptor PlexinC1 was expressed by most MrgprA3 pruriceptors and blocking PlexinC1 reduced semaphorin 7A-evoked neuronal responses. Together, these findings identify epidermal LCs as local immune-derived amplifiers that regulate the responsiveness of cutaneous sensory circuits and identify semaphorin 7A as a mediator of LC-induced itch potentiation.

neuroscience↗
bioRxiv2026

Feasible closed-loop stimulation for neural latent dynamics control

Modern neuroscience benefits from powerful computational and experimental methods for studying neural populations, including latent dynamics models that predict behavior with few dimensions. But despite their explanatory utility, latent factors are seldom targeted explicitly with experimental perturbations, leaving causal relationships to behavior and inferred dynamical landscapes untested. A promising solution is closed-loop, multi-channel optogenetic control, which, when paired with model predictions, could steer neural trajectories in real time--a feat impossible for traditional, hand-designed stimulation. However, because closed-loop latent control has not been demonstrated in vivo, the hardware and software requirements remain unclear--particularly the necessary stimulation dimensionality and how limited resources such as implant volume and bandwidth should be allocated between stimulation and recording capabilities. Preliminary experiments would thus help guide ongoing technological development. As large-scale exploration of these design spaces in vivo is prohibitively expensive, we conducted a high-throughput simulation survey using biophysically grounded spiking neural networks. We found that low-dimensional actuation is sufficient: in the reference configuration, ~20% of the stimulation channels achieved ~85% of peak control performance, far fewer than the number of neurons. Furthermore, allocating channels roughly equally between stimulation and recording optimized behavioral control, whereas pairing many electrodes with a single light source--the prevailing practice in experimental labs--performed poorly. Even without heavily optimizing modeling or control, we obtained >60% tracking error reduction and >90% evoked behavior accuracy on average for optimal channel counts. These results held across extensive parameter variations, suggesting that closed-loop latent control is feasible with accessible channel counts and establishing design principles for future tool development and in vivo experiments.

neuroscience↗
bioRxiv2026

Identification of Kinome Biomarkers and Therapeutic Rescue in cGMP-Linked Retinal Degeneration

Inherited retinal degenerations, such as Retinitis Pigmentosa (RP) and Leber's congenital amaurosis (LCA), are major causes of progressive and irreversible vision loss. The large number of genes associated with these disorders makes their clinical and molecular characterization difficult, while systemic biomarkers for disease progression or treatment response remain limited. These challenges were addressed by targeting cGMP-associated mechanisms shared by RP and LCA and integrating systemic biomarker profiling with retinal outcomes. Kinase activity analysis (kinome analysis) in peripheral blood mononuclear cells distinguished healthy and diseased states and captured therapy-associated signatures in rd10 mice treated with LP-CN03, a liposomal formulation of the cGMP analog CN03. This first systemic analysis in a therapeutically responsive animal model highlights kinome analysis as a potential translational readout. Given shared cGMP signaling in RP and AIPL1-associated LCA, LP-CN03's therapeutic potential was further evaluated in a new CRISPR-Cas9-generated Aipl1-/- mouse model. Treatment with LP-CN03 preserved retinal structure and function, as shown by electroretinography, longitudinal optical coherence tomography, fundus imaging, optomotor testing, and photoreceptor-specific gene expression. Together, these findings provide independent in vivo evidence for the neuroprotective effect of LP-CN03 in both cGMP-related RP and LCA, also highlighting the translational value of kinome profiling.

neuroscience↗