Biology subjects

Floeel, A.

Publications and source records attributed to Floeel, A..

13 recordsLinked to original sources

bioRxiv2026

Enhancing slow-wave sleep via non-invasive brain stimulation modulates brain-to-blood clearance of Alzheimer's disease biomarkers

Sleep disturbances and neurodegeneration form a bidirectional vicious cycle. During slow-wave sleep, glymphatic processes are thought to facilitate the clearance of metabolic waste, including proteins implicated in Alzheimers disease (AD). Aging, and more prominently neurodegeneration, is associated with reductions in slow-wave activity (SWA), which may impair these processes. Within SWA, slow oscillations (SO, <1 Hz) and their coupling to sleep spindles capture key aspects of sleep microstructure. Non-invasive brain stimulation during sleep has emerged as a potential approach to modulate these dynamics; however, human evidence linking such modulation to AD biomarkers remains scarce. In this exploratory mechanistic study, ten healthy older adults underwent one night of slow-oscillatory transcranial current stimulation (so-tDCS) and one sham night in a randomized crossover design, followed by five consecutive stimulation nights. Stimulation was applied during NREM sleep (N2/N3) in the first half of the night. Plasma phosphorylated tau (p-tau)181, {beta}-amyloid (A{beta})42, A{beta}40, and total tau were assessed overnight and longitudinally. EEG analyses quantified SO power and SO-spindle coupling. Due to the exploratory character of the study, analyses emphasized effect size estimation and explained variance. So-tDCS induced small-to-moderate increases in SO power and SO-spindle coupling. Overnight increases in plasma p-tau181 were observed following stimulation relative to sham. Increases in SO power were strongly and positively associated with p-tau181 changes, explaining a substantial proportion of inter-individual variance. In contrast, shifts in SO-spindle coupling phase toward the SO up-state were associated with overnight increases in A{beta}42 and A{beta}40 and with longitudinal decreases in A{beta}42 and the A{beta}42/40 ratio. Enhancing slow oscillatory dynamics during sleep is associated with changes in peripheral AD biomarkers. Differential associations for SO power and SO-spindle coupling timing suggest partially distinct links to tau and A{beta} dynamics. These findings support sleep microstructure as a potential intervention target, and should be confirmed in larger cohorts.

neuroscience↗

bioRxiv2026

Normative Deviations Reveal Task-Evoked and Clinical Network Reorganization

Understanding how cognitive demands and pathology reshape large-scale functional connectivity (FC) requires methods that are both multivariate and region-specific. Here we introduce One-class SVM-based Connectome Anomaly Recognition (OSCAR), a normative modelling framework that detects condition-related deviations in the multivariate connectivity profile of a brain region. OSCAR learns the distribution of region-to-whole-brain connectivity patterns given a reference state sample (e.g. resting-state data; RS) using a one-class support vector machine (OCSVM). The trained models are then applied to FC profiles from a target condition (e.g., task or patient group). The outlier proportions are used to quantify the difference between the reference and target condition. We validated OSCAR on three diverse tasks and a patient cohort with early psychosis. OSCAR consistently identified condition-sensitive regions in networks known to support conflict processing, object-location memory, lexical learning, and early psychosis, respectively, including thalamic and basal ganglia regions. Moreover, it detected additional well-established task- or disease-relevant parcels not captured by the comparison method permutation-based multivariate analysis of variance (perMANOVA). Regions flagged by OSCAR were at least as close, and often closer, to independent task-activation findings than those identified by perMANOVA. These results demonstrate that OSCAR provides an interpretable, region-centred normative modelling approach that is sensitive to subtle multivariate FC deviations, and offers a practical tool for mapping condition-specific reconfigurations of functional brain networks with high external validity, in both experimental and clinical settings.

neuroscience↗

bioRxiv2026

Harmonizing the stimulation dose of focal tDCS across target sites

Non-invasive brain stimulation is an established tool for modulating neural activity that holds promise for advancing both cognitive neuroscience and clinical interventions. Focal transcranial direct current stimulation (tDCS), using center-surround electrode montages, enables more region-specific targeting. Although computational models can simulate individual electric fields, no existing approach enables the prospective individualization of electrode placement while standardizing the dose across targeted brain regions. In the current preparatory methodological study, we present a modeling-based framework that harmonizes the electric field strength between different target regions at the group level, but preserves inter-individual variability. This enables systematic examination of dose-response relationships and their regional differences. Positioning of the center-surround electrode montages is individualized to ensure focusing of the electric field on the target regions. We started by defining brain targets for eight cognitive and motor functions using MRI data from 43 participants. Using field simulations, we then estimated a group-average field strength in the target regions that had led to behavioral and physiological effects in prior tDCS studies (resulting in 0.2 V/m). The radii of the center-surround montages were optimized for each target region to achieve the intended field strength while maximizing focality. Validation in an independent sample (n=53) confirmed that the intended target field strength is achieved on average for new participants. The described computational tools are made available as open-source software, allowing other researchers to apply our individualization framework with parameters (target regions and target field strengths) tailored to their specific research questions; and are currently being implemented in a multi-center study involving approximately 1,000 datasets.

neuroscience↗

bioRxiv2026

Multimodal Imaging-Based Targeting Approach for Network-Level Brain Stimulation

BackgroundNeural network effects of transcranial direct current stimulation (tDCS) are poorly understood. Here, we introduce an empirically informed, multimodal functional magnetic resonance imaging (fMRI) based framework suited for guiding stimulation target selection and hypothesis-based data analysis in focal tDCS-fMRI studies. MethodsWe illustrate our approach using data of 37 healthy individuals (19 females; mean {+/-} SD age = 25.8 {+/-} 5.9) recruited from a multicenter tDCS-fMRI study. Participants completed resting-state (RS- and task-fMRI (object-location memory, OLM, or associative picture-pseudoword learning, APPL, experiments) with placebo tDCS. Seed-based RS data analysis identified the functional networks originating from project-specific target regions for focal tDCS (right occipito-temporal cortex, rOTC; left ventral IFG, lvIFG) and also established their test-retest reliability using intraclass correlation coefficients (ICC). Dice coefficients analyzed the overlap between the seeded RS- and task-evoked networks. This aimed to identify task-active regions potentially affected by downstream neural network effects from the target regions. ResultsSeed-based analyses identified two highly reliable ventral visual-limbic (rOTC) and language-related networks (lvIFG), with >72-77% of voxels showing good-to-excellent TRR (ICC [≥] 0.75). Only a subset of voxels identified by the RS analyses overlapped with activity elicited by the experimental paradigms (ranging from 7.5-55%), with larger correspondence for the OLM task (Dice OLM: 0.249-0.349; APPL 0.065-0.106). Therefore, the degree of potential tDCS network effects varied substantially depending on the target region, the extent of its functional network and task-specific activity patterns. Degree of correspondence was further mediated by the selected contrasts-of-interest in the task-based analyses, with more conservative control conditions resulting in reduced overlap. ConclusionWe established a principled, multimodal fMRI framework bridging a critical gap in neuromodulation research. By integrating reliable intrinsic connectivity maps with task-evoked activity patterns, we provide a method to prospectively identify network-level targets for focal brain stimulation and to generate hypotheses for data analyses in tDCS-fMRI studies. This approach paves the way for investigating modulation of specific functional networks, shifting the rationale from stimulating an isolated brain region to strategically targeting key nodes within a predefined functional pathway.

neuroscience↗

bioRxiv2025

Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies

Combining transcranial direct current stimulation (tDCS) with fMRI enables investigation of stimulation effects, while structural MRI verifies electrode positioning, critical for focal montages where minor misplacements reduce target current dose. Currently, no fully automated methods exist for precise electrode extraction from MRI. We developed an Attention U-Net-based deep learning approach to automate electrode detection in focal tDCS-fMRI studies, using structural pointwise-encoding time reduction with radial acquisition (PETRA) MRI scans from a multicenter trial (N = 392 images; 1,568 electrodes, https://www.memoslap.de/en/home/). Performance was compared to manual and semi-automated methods for a 3x1 montage (three cathodes around a central anode). The network achieved robust segmentation (Dice Score = 0.76, Hausdorff distance = 36.76 mm), identifying all electrodes in 95% of cases (323/340). These metrics compared network-segmented electrodes to highly accurate, manually segmented electrodes, which are also called "ground truth". Linear mixed-effects models on 52 "ground truth" images showed deep learning outperformed manual and semi-automated methods, aligning best with ground truth. Fully/semi-automated methods comparison of 290 images showed highest agreement (ICC = 0.990, bias = 1.3 mm), while manual extraction exhibited larger biases (-5.77 to -7.06 mm) and systematic errors. The automated approach overcomes manual limitations by improving precision, eliminating human variability and bias, and enabling scalability for large studies. It sets a new standard for electrode verification in focal tDCS, particularly for studies requiring precise localization. The model is open-source, with future refinements discussed

neuroscience↗

bioRxiv2025

Occipital tACS does not modulate manual performance but fixation variability under visuo-proprioceptive conflict

The modulation of oscillations at alpha and beta frequency ranges recorded over sensory cortices has been linked to the top-down weighting of sensory information relative to (competing) information from other modalities. Here, using a virtual reality-based hand-target matching task under visuo-proprioceptive conflict, we tested whether alpha-/beta-tACS over the occipital cortex would improve action performance when conflicting visual movement feedback needed to be ignored in favor of proprioception. Participants had to match a target rhythm with either their unseen real hand (RH) grasping movements, or with the movements of a virtual hand (VH) that displayed their actual movements after a constant time delay. Visual movement feedback was, consequently, either task-relevant (VH task) or a distractor (RH task). In a cross-over, double-blind, within-subject design, we applied either low-intensity (2 mA peak-to-peak) transcranial alternating current stimulation (tACS) at 10 Hz ("alpha") or 20 Hz ("beta"), or sham, over the occipital cortex during this task. Neither alpha- nor beta-tACS significantly affected hand-target matching performance, but fixation variability in the RH condition significantly decreased during beta-tACS relative to sham stimulation. Thus, despite not directly modulating manual performance, occipital beta-tACS could have facilitated ignoring the mismatching (distracting) visual movement feedback when needed.

animal behavior and cognition↗

bioRxiv2025

Functionally Relevant and Reliable Brain Stimulation Targets for Enhancement of Novel Word-Learning

Linking word-forms and their meanings is central to language learning. Transcranial direct current stimulation (tDCS), has shown potential to enhance this process, but with variable effects. This study aimed to (1) identify reliable and functionally relevant tDCS target brain regions to enhance novel-word learning and (2) assess test-retest reliability (TRR) of behavioral and imaging outcomes. Twenty healthy individuals completed two functional magnetic resonance imaging (fMRI) sessions using parallel task versions. Participants learned picture-pseudoword associations across six learning blocks. Behavioral learning was analyzed using linear-mixed-models. Whole-brain and region-of-interest (ROI) analyses examined learning-related activity changes and their behavioral relevance. TRR was assessed using intraclass correlation coefficients (ICCs). Participants successfully acquired the novel-word forms, indexed by increased accuracy and faster latency across stages. Behavioral outcomes showed good-to-excellent TRR. The task elicited robust language-learning related activity and activity changes across stages were correlated with learning success. Task-related activity was variable, but voxels within significant clusters ([~]81%) and most ROIs showed moderate-to-excellent consistency. Power analyses confirmed a sufficient sample size for detecting the reported ICCs. Current modeling suggested that focal-tDCS can induce neurophysiologically relevant electrical field strength in the identified target regions. Hence, we identified accessible, reliable and functionally relevant cortical targets for enhancing novel-word learning. TRR results support the usefulness of the paradigm for future concurrent tDCS-fMRI research. Our study also outlines a general path towards optimization of brain stimulation studies by implementing an empirically informed approach for selecting reliable and relevant target regions and implementation of reliable experimental and imaging paradigms.

neuroscience↗

bioRxiv2025

Polarity-dependent modulation of sleep oscillations and cortical excitability in aging

During non-rapid eye movement (NREM) sleep, cortical slow oscillation (SO; <1 Hz) and thalamic sleep spindle activity (12-15 Hz) interact through precise phase coupling to support memory consolidation. Slow oscillatory transcranial direct current stimulation (so-tDCS) can modulate these oscillations. Traditionally, anodal so-tDCS is used to depolarize the cortex during SO up-states, thereby promoting SO activity and SO-spindle coupling. However, intracranial findings suggest that SO down-states, characterized by cortical hyperpolarization, can trigger thalamic spindle bursts. This raises the hypothesis that cathodal so-tDCS, by promoting hyperpolarization, could selectively enhance down-states and more effectively improve SO-spindle coupling. We tested this hypothesis in twenty-two healthy older adults, a population known to exhibit diminished NREM oscillatory activity. Each participant received cathodal, anodal, and sham so-tDCS in separate nap sleep sessions. We quantified SO and spindle characteristics, their temporal coupling, and cortical excitation/inhibition (E/I) balance using EEG spectral slope. We also assessed individual circadian preference (chronotype) as a potential moderator. We found that anodal so-tDCS improved SO-spindle synchrony, and increased spindle power over sham in participants with intermediate or evening chronotypes, while cathodal so-tDCS did not enhance these oscillatory measures compared to sham, despite prolonging SO down-states. Anodal stimulation also elevated E/I balance, indicating increased cortical excitability, whereas cathodal stimulation did not produce the anticipated opposite shift. In summary, anodal, but not cathodal so-tDCS, effectively enhanced thalamocortical interactions underlying memory consolidation. Furthermore, these findings highlight the importance of individual factors such as chronotype in brain stimulation responsiveness.

neuroscience↗

bioRxiv2024

A candidate reference method for the quantification of α-synuclein in cerebrospinal fluid using an SI traceable primary calibrator and multiple reaction monitoring

Objectives-synuclein aggregation is an indicator of neurodegenerative diseases such as Parkinsons disease (PD) and recent advances have suggested that this protein could serve as a potential biomarker. It has been indicated that soluble and oligomeric -synuclein in biological fluids could have diagnostic applications for PD. Clinical laboratories currently rely on antibody-based assays to detect -synuclein. These assays have limited specificity, low sensitivity and poor inter-lab reproducibility, which prevents the validation of -synuclein as a biomarkers. This study aims to fill the unmet need for the standardisation of clinical measurements for -synuclein. MethodsWe report the first candidate reference method for -synuclein, using an SI traceable primary calibrator for -synuclein and isotope dilution mass spectrometry. The primary calibrator was traceably quantified utilising a combination of amino acid analysis and nuclear magnetic resonance. A targeted sample clean-up procedure involving a non-denaturing Lys-C digestion and solid-phase extraction allowed for the sensitive detection of multiple proteotypic -synuclein peptides in cerebrospinal fluid (CSF) samples. ResultsThe candidate reference method procedure showed linearity across three orders of magnitude, covering the physiological levels of -synuclein in CSF (LOQ = 0.1 ng/g). The method was used to quantify a cohort of CSF samples and the measurements were correlated with immunoassay-based quantifications. ConclusionsThe SI traceable quantification of -synuclein in complex biological matrices means that the role of this protein can be further elucidated in synucleinopathies. This candidate reference method would lead to the harmonisation of -synuclein measurements, which may allow for development of high throughput clinical tests.

biochemistry↗

bioRxiv2023

Brain oscillatory processes related to sequence memory in healthy older adults

Sequence memory is subject to age-related decline, but the underlying processes are not yet fully understood. We analyzed electroencephalography (EEG) in 21 healthy older (60-80 years) and 26 young participants (20-30 years) and compared time-frequency spectra and theta-gamma phase-amplitude-coupling (PAC) during encoding of the order of visually presented items. In older adults, desynchronization in theta (4-8 Hz) and synchronization in gamma (30-45 Hz) power did not distinguish between subsequently correctly and incorrectly remembered trials, while there was a subsequent memory effect for young adults. Theta-gamma PAC was modulated by item position within a sequence for older but not young adults. Specifically, position within a sequence was coded by higher gamma amplitude for successive theta phases for later correctly remembered trials. Thus, deficient differentiation in theta desynchronization and gamma oscillations during sequence encoding in older adults may reflect neurophysiological correlates of age-related memory decline. Furthermore, our results indicate that sequences are coded by theta-gamma PAC in older adults, but that this mechanism might lose precision in aging.

neuroscience↗

bioRxiv2022

Gender imbalances in citation rates are mediated by field specific author gender distributions

Gender biases are well documented in science and typically favor male scientists. In this context, a particularly pervasive gender bias is undercitation of publications authored by women, resulting in profound negative effects on academic visibility and career advancement. This bias has been well documented in fields where author gender distributions are strongly skewed towards men (e.g., astronomy, physics, neuroscience). By investigating citation practices in a field that has traditionally been more accessible to female scientists (Speech and Language Pathology, SLP), we demonstrate that gendered citation practices are mediated by author gender distribution, rather than being a universal pattern. Specifically, our results revealed a citation pattern in SLP that (a) overall tends to favor female authors, (b) persists after controlling for potential confounding factors and, (c) is particularly strong when female authors are citing publications involving female first and senior author teams. This research also implies that the implementation of effective measures to increase the number and influence of underrepresented individuals in specific fields of science may be suitable to mitigate downstream disadvantages for career advancement of either sex.

scientific communication and education↗

bioRxiv2021

Interrelations between delta waves, spindles and slow oscillations in human NREM sleep and their functional role in memory

Certain neurophysiological characteristics of sleep, in particular slow oscillations (SO), sleep spindles, and their temporal coupling, have been well characterized and associated with human memory formation. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SO, have only recently been found to play a critical role in memory processing of rodents, through a competitive interplay between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta waves, their interactions with spindles and SOs as well as their functional role for memory are still lacking. Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories. Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found that increased delta activity was accompanied by stronger SO-spindle coupling. Moreover, we identified the ratio between SO- and delta-nested spindles as the sleep parameter that predicted ability to form novel memories best. Our study suggests that SOs, delta waves and sleep spindles should be jointly considered when aiming to link sleep physiology and memory formation in aging. Significance statementInterrelations between delta waves, slow oscillations and sleep spindles have recently been causally linked to the balance between consolidation and forgetting in rats using optogenetics. In humans, SO-spindle coupling has been intensively investigated, but delta waves and their interaction with spindles were only studied jointly as SWA. Here we delineate the coupling of delta waves to spindles, investigate interactions of delta- and SO-related activity and investigate their role for the ability to form novel memories in healthy older individuals. Our results show differences as well as dependencies between SO- and delta-related activities including spindle coupling. Further, our results indicate that the ratio of SO- to delta-nested spindles might be the most informative sleep parameter for memory formation of older adults.

neuroscience↗

bioRxiv2020

Beneficial effects of cerebellar tDCS on motor learning are associated with altered putamen-cerebellar connectivity: a simultaneous tDCS-fMRI study

Non-invasive transcranial stimulation of cerebellum and primary motor cortex (M1) has been shown to enhance motor learning. However, the mechanisms by which stimulation improves learning remain largely unknown. Here, we sought to shed light on the neural correlates of transcranial direct current stimulation (tDCS) during motor learning by simultaneously recording functional magnetic resonance imaging (fMRI). We found that right cerebellar tDCS, but not left M1 tDCS, led to enhanced sequence learning in the serial reaction time task. Performance was also improved following cerebellar tDCS compared to sham in a sequence production task, reflecting superior training effects persisting into the post-training period. These behavioral effects were accompanied by increased learning-specific activity in right M1, left cerebellum lobule VI, left inferior frontal gyrus and right inferior parietal lobule during cerebellar tDCS compared to sham. Despite the lack of group-level changes comparing left M1 tDCS to sham, activity increase in right M1, supplementary motor area, and bilateral superior frontal cortex, under M1 tDCS, was associated with better sequence performance. This suggests that lack of group effects in M1 tDCS relate to inter-individual variability in learning-related activation patterns. We further investigated how tDCS modulates effective connectivity in the cortico-striato-cerebellar learning network. Using dynamic causal modelling, we found altered connectivity patterns during both M1 and cerebellar tDCS when compared to sham. Specifically, during cerebellar tDCS, negative modulation of a connection from putamen to cerebellum was decreased for sequence learning only, effectively leading to decreased inhibition of the cerebellum. These results show specific effects of cerebellar tDCS on functional activity and connectivity in the motor learning network and may facilitate the optimization of motor rehabilitation involving cerebellar non-invasive stimulation.

neuroscience↗