Biology subjects

Huber, R.

Publications and source records attributed to Huber, R..

At least 19 recordsLinked to original sources

bioRxiv2026

REM Sleep Iota Oscillations Across the Lifespan

Iota oscillations are a newly discovered marker of wakefulness and rapid eye movement (REM) sleep. So far, iota in REM sleep has only been reported in the surface electroencephalography (EEG) of a small sample of young adults and in intracranial recordings of epileptic patients. Here, we investigated the presence of these oscillations in a large dataset (N=937) of high-density sleep EEG recordings from individuals 7 to 70 years old. We found that iota spectral peaks during REM sleep were between 25 and 40 Hz, slightly faster than in wake (25-35 Hz). Iota power was significantly associated with REM sleep architecture, increasing with both REM duration and across progressive sleep cycles. Iota peaks were observed in individuals of all ages, although the prevalence decreased gradually with age, from 88% in children to 44% in older adults. Most iota spectral peak properties (frequency, amplitude, timing, topography) likewise shifted with age. The most striking effect, however, was in bandwidth, such that children had narrow iota peaks, older adults had broad iota peaks, and 20-30 year olds could have either. It remains unclear whether narrowband and broadband iota are functionally equivalent. On shorter time scales (< 1 year), iota properties remained stable across measurements. Analyses of a separate dataset of monozygotic and dizygotic twins revealed high heritability of all iota peak properties except bandwidth. Overall, these results establish iota as a genetically determined trait-like marker of REM sleep with unique age-related changes. Iota oscillations open new avenues to investigate the interaction between sleep, genetics, development, and aging.

neuroscience↗

bioRxiv2026

Programmable design of functional RNAs through multimodal generative learning

RNA engineering is bottlenecked by the tight coupling among sequence, structure, and function, leaving the field reliant on heuristics or screening. We introduce RNAverse, a multimodal generative model that learns a conditionable design grammar from RNA sequences, experimental structural probing profiles, and functional annotations. Beyond setting a new state of the art across 16 predictive modeling tasks, RNAverse inverts into generative design across four distinct RNA classes through three regimes, requiring experimental testing of no more than 20 candidates per-task. Zero-shot in-painting generates snoRNAs that promote premature termination codon (PTC) readthrough, and chimeric aptazymes for ligand-controlled gene regulation, exceeding rational design or large-scale screens. In both settings, RNAverse outperforms family-adapted sequence-only baselines. Fine-tuned in-painting extends to an unseen functional class, yielding IGFBP3-binding aptamers with picomolar affinity that outperform SELEX winners. Iterative optimization engineers 5' UTRs that outperform clinical benchmarks, enhancing protein production in cell-based assays for both the Zolgensma gene therapy and the BNT162b2 COVID-19 vaccine, and boosting antibody responses to BNT162b2 in mice. Together, these results establish multimodal generative learning as a route from predictive RNA modeling to programmable specification of functional RNAs.

bioinformatics↗

bioRxiv2026

Gene model for the ortholog of Ilp3 in Drosophila pseudoobscura

Gene model for the ortholog of Insulin-like peptide 3 (Ilp3) in the D. pseudoobscura Apr. 2013 (BCM-HGSC Dpse_3.0/DpseGB3) Genome Assembly (GenBank Accession: GCA_000001765.2) of Drosophila pseudoobscura. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

genomics↗

bioRxiv2026

A nutrient-derived dietary gradient links gut microbiome composition, network structure, and host physiology

Diet is an important determinant of gut microbiome composition and host physiology. However, dietary exposure is often represented using categorical groups that may not fully capture variation in nutrient intake or its associations with gut microbiome and host biomarkers. Here, we analyzed diet-microbiome-host physiology relationships in healthy adults with long-term adherence ([≥]2 years) to omnivore, vegetarian, or vegan diets. We integrated four-day weighed dietary records, blood biomarkers, and 16S rRNA gene sequencing to characterize dietary intake, host physiology, and gut microbiome composition. We derived nutrient intake gradients by dimensionality reduction of representative nutrients and identified the second nutrient intake gradient (NIG2) as a quantitative axis reflecting variation between animal- and plant-leaning nutrient profiles, broadly recapitulating categorical dietary groups. While NIG2 showed no association with microbiome within-sample diversity, it explained gut microbiome compositional variation that was not detected using categorical dietary groups. Mediation analyses identified nominal candidate microbiome-mediated diet-biomarker relationships involving thyroid-related, hematological, and vitamin-related biomarkers. Network analyses of NIG2-defined animal-leaning and plant-leaning subsets identified subset-specific microbial associations and differences in microbial community structure and potential interactions. Overall, this continuous nutrient-derived dietary gradient provides a quantitative exposure metric for characterizing diet-microbiome-host physiology relationships. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/740531v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@104a825org.highwire.dtl.DTLVardef@bb2b33org.highwire.dtl.DTLVardef@114171org.highwire.dtl.DTLVardef@df9c38_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Field-Correcting GRAPPA (FCG): a technique to correctspatiotemporal-varying phase errors in Echo Planar Imaging

PurposeTo develop a Field-Correcting GRAPPA (FCG) technique to correct the spatiotemporal-varying phase errors in EPI caused by eddy currents. MethodsThe fast-changing gradient in EPI causes strong eddy current effects and associated spatiotemporal-varying phase errors, producing significant image artifacts. The use of higher gradient amplitude, slew rate, and ramp sampling factor for faster imaging exacerbates this problem. In this work, FCG was developed to address this challenge by using a multi-layer perceptron (MLP) to provide a compact representation of a family of GRAPPA-like kernels that correct the spatiotemporal-varying phase errors in the data. A dedicated calibration pipeline was designed to acquire high-quality source and target data for MLP training in both slice-by-slice and simultaneous multi-slice (SMS) acquisitions. To validate FCGs assumptions and performance, a field camera was used to provide ground-truth measurement of phase patterns. The performance of FCG was further validated on phantom and in vivo experiments using demanding EPI trajectories across multiple 3T and 7T systems. ResultsField camera measurements revealed strong spatiotemporal phase variations along the kx direction that repeat along ky during EPI readouts. The experiments on high-performance systems across 3T and 7T demonstrate that FCG can provide superior correction for the artifacts induced by spatiotemporal-varying phase errors compared with existing approaches. ConclusionFCG is an effective and robust method for correcting spatiotemporal phase errors in EPI, enabling improved image quality on high-performance systems.

bioengineering↗

bioRxiv2026

Intracortical vessel density mapping at mesoscale reveals regionally specific angioarchitecture in the human brain

The metabolic demands of the human brain are met by a complex vascular architecture, yet our characterization of this network remains incomplete. While we have mapped the macroscopic vessels on the brains surface and the microscopic capillaries within small tissue samples, the mesoscopic scale consisting of the penetrating vessels that plunge through cortex remains an anatomical terra incognita. Mapping the interface between the macroscopic and microscopic scales is essential to understanding the critical vascular supply that sustains brain health. Here, we leveraged the BigBrain dataset and developed custom detection and tracing algorithms to reveal a whole-cortex record of the mesoscopic vascular network. We find that vascular density is not uniform across the cortex, but is a heterogeneous landscape that shows clear relationships to traditional areal boundaries. Our results constitute a reference for human mesoscopic angioarchitecture and demonstrates the power of repurposing high-resolution histological at-lases. Ultimately, this work lays the groundwork for validating recently developed in vivo MRI techniques for imaging the human cerebrovascular system at mesoscale.

neuroscience↗

bioRxiv2026

A Universal, AI-based Design Framework for Efficient Manufacturing of mRNA Therapeutics

The growth of mRNA therapeutics is limited by bespoke manufacturing processes. To overcome this barrier to access and innovation, we introduce an AI-driven framework that decouples sequence design from manufacturing, analogous to the universal design principles that revolutionized the semiconductor industry. We performed a large-scale screen, quantifying the in vitro transcription (IVT) efficiency of one million diverse sequences. We then trained an interpretable deep learning model that accurately predicts manufacturability from sequences alone and learned underlying molecular mechanisms. An algorithm using this model prospectively improved the IVT yield of a vaccine and a gene-editing therapeutic by over 7.5-fold. Co-optimization for manufacturability and translation efficiency provided improvements over state-of-the-art commercial mRNA products. Our AI-driven framework establishes a universal design paradigm with the promise to democratize and accelerate the development of mRNA medicines, potentially unlocking a new era in biotechnology.

bioengineering↗

bioRxiv2026

Gene model for the ortholog of Ilp4 in Drosophila simulans

Gene Model for Insulin-like peptide 4 (Ilp4) in the D. simulans DsimGB2 assembly (GCA_000754195.3). The characterization of this ortholog was carried out as part of a larger, ongoing dataset designed to explore the evolution of the insulin/insulin-like growth factor signaling (IIS) pathway across the genus Drosophila, utilizing the Genomics Education Partnership gene annotation protocol within Course-based Undergraduate Research Experiences.

genomics↗

bioRxiv2025

Feedforward representation of face information in the fusiform face area revealed by VASO 7T layer fMRI

Recognizing faces is a critical cognitive process in social interaction. Face recognition has been extensively studied with functional magnetic resonance imaging (fMRI), ranging from large coverage studies comprehensively examining the entire face pathway to high-resolution laminar-specific (layer) fMRI studies probing feedforward and feedback signals in early visual and face-selective areas during particular face processing. However, it is still unclear which brain region structures face information in the face pathway. To further elucidate this mechanism, we investigated fusiform face area (FFA) during passive face image presentation using a whole-brain vascular space occupancy (VASO) 7T layer fMRI open dataset combined with multi-voxel pattern analysis (MVPA). We analysed lateral occipital cortex (LOC) as a control region and BOLD data in the dataset as a control contrast. We trained multiple binary classification decoders with various image categories (e.g., face vs. others, house vs. others) and three cortical layer groups independently to assess information representation across cortical depths. Our results revealed that decoding accuracies in VASO data peaked in the middle layer of FFA, suggesting a feedforward signature specifically during face processing. This effect was not observed in LOC or in decoders for other image categories. These findings indicate that face information is structured prior to processing in the FFA, consistent with previous reports suggesting that face-related features are partially extracted before reaching higher-level face areas. Overall, this study highlights the potential of combining high-specificity VASO layer-fMRI with high-sensitivity MVPA to dissect cortical information flow.

neuroscience↗

bioRxiv2025

Smartphone behavior is suppressed during bursts of wake slow wave

Real-world behavior unfolds as a continuous flow of actions over time. One possibility is that this continuous flow is enabled by a seamless stream of cortical activity. However, emerging evidence suggests that even during ongoing behaviors, cortical neural populations undergo brief periods of silence. This off-state can be detected as wake slow waves in EEG, similar to the slow waves characterizing deep sleep. Here, we leveraged the spontaneously occurring fluctuations in smartphone touchscreen interactions in combination with EEG to investigate the dynamics of slow waves during behavior. We find that slow waves occur in bursts - characterized by short consecutive intervals - interleaved with longer periods of absent slow waves. During smartphone use, the probability of bursts increased compared to rest, and the duration of burst-absent periods was lower. During the bursts, however, the likelihood of generating smartphone interactions was substantially diminished. Conversely, the periods of absent slow waves were more permissive to the behavioral output. We propose that slow wave burst dynamics are state-dependent, configured to create temporal windows permissive to action generation. This configuration, in turn, allows behavioral outputs to leverage the windows of opportunity that emerge between slow wave bursts. Our study, combining smartphone behavior with EEG, reveals how brief cortical silencing events structure the computations underlying everyday actions.

neuroscience↗

bioRxiv2025

RNA structure directs RNA partitioning and is actively disrupted inside stress granules to enable cellular recovery

RNA structures play important roles in liquid-liquid phase separation. However, how it is regulated during stress response and stress granule formation is still under studied. Here, we performed in vivo RNA structure probing before and after sodium arsenite treatment, and in stress granules. While RNAs generally become more double-stranded upon stress, they maintain their single-strandedness inside stress granules. We showed that RNA single-strandedness enables increased inclusion inside stress granules and that stress granule-enriched RNAs form fewer intra- and intermolecular RNA-RNA interactions. Additionally, several RNA binding proteins including SRSF1 are enriched in differential structure regions. eCLIP analysis revealed that SRSF1 binds to single-stranded regions along RNAs, and increased SRSF1 binding enabled better inclusion of RNAs in stress granules, whereas depletion of SRSF1 decreased stress granule formation under mild oxidative stress. We also observed the active unwinding of RNAs inside stress granules regulated by helicases, including DDX3X, and showed that inhibition of DDX3X results in slower dissolution of stress granules during recovery. Our study reveals the existence of multiple mechanisms to maintain RNA single-strandedness inside stress granules and to allow reversibility of stress granule formation, highlighting the importance of regulating RNA structure to enable cellular plasticity and stress response.

molecular biology↗

bioRxiv2025

The Infraslow Fluctuation of Sigma Power During Sleep in Young Individuals with Schizophrenia

A reduction in sleep spindles, a major electrophysiological characteristic of Non-Rapid Eye Movement sleep, has been suggested as a potential biomarker of schizophrenia. While research has primarily focused on the spindle quantity, recent studies have begun to explore their temporal dynamics throughout the night. In healthy individuals, sleep spindles fluctuate on an infraslow [~]50-second timescale, alternating between phases of high and low spindle activity. This fluctuation is referred to as the infraslow fluctuation of sigma power (ISFS), which is modulated by noradrenergic activity from the locus coeruleus and linked to the organization of arousal and memory reactivation processes during sleep. Given the known deficit in sleep spindles, dysregulation of noradrenergic activity, and impairments in sleep maintenance and memory in schizophrenia, this study investigates the ISFS in sleep electroencephalography data from individuals with either Childhood-Onset Schizophrenia (COS; N = 17) or Early-Onset Schizophrenia (EOS; N = 11), aged 9 to 21 years, alongside age- and sex-matched healthy controls (N = 56). The presence and strength of the ISFS were reduced in both COS and EOS groups compared to controls, particularly in central-parietal electrodes. No significant differences in these features of the ISFS were found between the two clinical groups, despite group differences in sleep spindle density and clinical characteristics. These findings suggest that the ISFS is observable but reduced in young patients with schizophrenia and support the notion that the timing of sleep spindles may inform pathomechanistic models of the disorder, as well as future diagnostic approaches and interventions.

neuroscience↗

bioRxiv2025

Application of Down-Phase Targeted Auditory Stimulation During Sleep in a Home Setting: A Feasibility Study Across Seven Consecutive Nights

IntroductionSleep deprivation, also known as "wake therapy", has long been recognized as a powerful antidepressant. Phase-targeted auditory stimulation (PTAS) has been suggested as an auspicious non-invasive nocturnal substitute for sleep deprivation. Down-PTAS with stimuli presentation during the down-phase of slow waves, in particular, may have therapeutic potential to improve mood by selectively reducing slow-wave activity (SWA). With down-PTAS being more nuanced than sleep deprivation, its effects presumably develop over multiple nights, thus necessitating transfer from sleep laboratory to home settings. Therefore, in this study, we investigated the technical feasibility, tolerability, and potential risks associated with a wearable device employed for down-PTAS in an unsupervised home setting. MethodsWe recorded frontal EEG using the MHSL Sleepband Version 3 (MHSL-SB) in five healthy participants (23.8 {+/-} 0.8 years, three women) over seven consecutive nights with (STIM) and without (SHAM) tone application at their homes. Tones were delivered shortly before the negative peak of slow waves during N2/N3 sleep, using alternating 10-s ON-OFF windows. Sleep staging followed American Academy of Sleep Medicine (AASM) guidelines. Of the 67 available sleep recordings, we excluded three due to parameter adjustments and another six for technical issues, leaving 58 sleep recordings (29 SHAM, 29 STIM) for further analyses. Low SWA (0.5-2 Hz, lSWA) was computed across the entire night, ON-OFF windows, and sleep cycles. Time-frequency analyses were performed time-locked to stimulus onset. We computed linear mixed effect models with condition (STIM vs. SHAM) as a fixed effect and random participant intercepts. ResultsData quality was sufficient for analyses in 87% of the available sleep recordings, with an average of over 1500 correctly delivered stimuli per recording. Down-PTAS did not affect sleep architecture, but it reduced lSWA primarily during the first sleep cycle when sleep pressure and lSWA were highest, and particularly in OFF windows. Additionally, stimulation elicited a K-complex-like auditory evoked response, aligning with previous laboratory findings. ConclusionOur results demonstrate the successful implementation of down-PTAS in a home setting, confirming its feasibility for long-term, unsupervised use. The K-complex-like auditory evoked response may mask potential reductions in lSWA during ON windows, posing a scientific analytical challenge. Taken together, future clinical research should now assess the effects of down-PTAS in depressed patients, in whom reducing lSWA may partly mimic sleep deprivation.

neuroscience↗

bioRxiv2025

In vivo reconstruction of Duvernoy's postmortem vasculature images

Non-invasive measurement of the human brains angioarchitecture is critical for understanding the basis of functional neuroimaging signals, diagnosing cerebrovascular diseases, and tracking neurodegeneration. Ultra-high-field magnetic resonance imaging (MRI) has achieved mesoscopic (< 0.5 mm) imaging of angioarchitecture, revealing fine vascular details that were previously inaccessible in vivo. However, current mesoscopic MRI methods for imaging angioarchitecture face two major limitations. First, acquisition times are prohibitively long, often exceeding 40 minutes, making integration into everyday clinical practice and research projects impractical. Second, even with data successfully acquired, conventional data visualization methods, such as 2D slice browsing and 3D vessel segmentation renders, are rudimentary and have limited effectiveness for navigating and interpreting the complex vascular network. In this paper, we present a fast whole-brain MRI protocol that provides robust images of the brains venous network at 0.35 mm resolution in under seven minutes. Additionally, we introduce novel data processing and visualization techniques that enable identification of specific vessel types and more informative navigation of the complex vascular network. We demonstrate that, with these advancements, we can reproduce, in vivo and without intravenous contrast application, the seminal postmortem vasculature images of Duvernoy and Vannson (1999). Furthermore, leveraging the ability for MRI to cover the entire brain, we achieve, for the first time, whole-brain intracortical mesoscopic vein maps in humans. Our acquisition and post-processing methods lay the groundwork for detailed examination of vascular organization across individuals, brain regions, and cortical layers. More generally, these methods make mesoscopic imaging of angioarchitecture viable for broad neuroscientific and clinical applications.

neuroscience↗

bioRxiv2025

Local modulation of sleep slow waves depends on timing between auditory stimuli

Conflicting evidence exists regarding the role of the targeted slow-wave phase in determining the direction and spatial specificity of slow-wave activity (SWA) modulation via phase-targeted auditory stimulation (PTAS) during sleep. To reconcile these discrepancies, we re-analyzed high-density electroencephalography (hd-EEG) data from previous studies, focusing on SWA responses to auditory stimuli presented with varying inter-stimulus intervals (ISIs). Our analysis reveals that ISI is a primary determinant of PTAS-induced SWA modulation, exceeding the influence of targeted phase alone. Specifically, auditory stimulation with longer ISIs evoked a global increase in SWA, consistent with a stereotypical auditory-evoked K-complex (KC), independent of targeted phase. Conversely, longer stimulus trains with rapid successive stimulus presentation resulted in spatially localized, phase-dependent SWA modulation, with up-PTAS enhancing and down-PTAS reducing SWA locally around the targeted area. This distinction resolves inconsistencies in prior PTAS studies by demonstrating that phase alone in insufficient in predicting slow-wave responses. Rather, it was the ISI which determined whether PTAS resulted in a global, KC-mediated response or a local, phase-specific modulation of SWA. Consequently, our findings refine the mechanistic understanding of PTAS, suggesting that ISI regulates the engagement of distinct neural circuits and thereby potentially enables the targeted manipulation of specific slow-wave subtypes and their associated functions.

neuroscience↗

bioRxiv2024

Longer Interstimulus Intervals Enhance Efficacy of Automated Phase-Targeted Auditory Stimulation on Procedural Memory Consolidation

Up-phase-targeted auditory stimulation (up-PTAS) during slow-wave sleep has become a valuable tool for modulating slow oscillations and slow-oscillation-spindle-coupling in favor of overnight memory retention. Developing effective, automated protocols for translation into more naturalistic or clinical settings is an ongoing challenge, especially given that current PTAS protocols and their behavioral effects vary greatly between different studies. Here, we assessed the electrophysiological and behavioral effects of systematically varying interstimulus intervals (ISIs) in automated up-PTAS in the home setting, using a mobile PTAS device and app-based behavioral tasks. Building on studies suggesting a non-linear relationship between stimulus number and PTAS effects, we show that applying fewer stimuli with longer ISIs enhanced overnight memory consolidation of a finger-tapping sequence more effectively than applying more stimuli with shorter ISIs. The behavioral response was predicted by the number of stimuli with auditory evoked K-complexes relative to the number of stimuli without K-complexes. PTAS stimuli applied at longer ISIs (> 1.25) were associated with a higher likelihood of K-complex responses and fast spindles nesting in the K-complex up-phase. Our results suggest that up-PTAS can be optimized for overnight memory consolidation by introducing ISIs of at least 1.25s. Our study highlights the feasibility of longitudinal at-home PTAS combined with app-based behavioral tasks in healthy participants while leveraging the mechanistic insights such data can offer. Statement of SignificancePhase-targeted auditory stimulation (PTAS) holds great promise for non-invasively enhancing essential functions of slow-wave sleep. However, current protocols have produced variable results and are often confined to laboratory settings. Our study demonstrates the feasibility of a mobile application of automated PTAS and provides experimental evidence that prolonging interstimulus intervals positively affects overnight procedural memory consolidation via K-complexes and coupled sleep spindles. As K-complexes may also be involved in cardiovascular function and brain waste clearance, the proposed protocol optimization may have effects beyond memory enhancement. Together, our findings lay a foundation for a broader application of PTAS in clinical longitudinal studies to improve patient care and recovery outcomes.

neuroscience↗

bioRxiv2024

The Infraslow Fluctuation of Sigma Power During Sleep: Links to Markers of Arousal and Memory Reactivation Across Development

Sleep is both a state of disconnection from the environment and a critical period for restoration. But how does sleep balance responsiveness with the protection of key functions? The infraslow fluctuation of sigma power (ISFS)--the clustering of sleep spindles over 10-100 seconds--is thought to regulate this trade-off in rodents. However, the organization of arousal and memory reactivation markers within the human ISFS and its conservation in younger ages remain unclear. This study characterizes the ISFS from childhood to young adulthood (N = 154; ages 8-26), examining its relationship with functional markers. Results indicate that the ISFS is present across all ages, with frequency, variability, and strength increasing from early to late adolescence. Notably, markers of arousal and memory reactivation are organized within the spindle-rich ISFS peak. The consistent presence and organization of the ISFS suggest it is intrinsic to sleep, with adolescence marking a dynamic window. These insights may guide interventions to promote healthier sleep across development.

neuroscience↗

bioRxiv2024

Cardiovascular responses to natural and auditory evoked slow waves predict post-sleep cardiac function

The interplay between slow-wave sleep and cardiovascular health is increasingly recognized. Our prior research showed that auditory-enhanced slow waves can boost cardiac function, yet the mechanisms behind this remain unclear. Advancing these findings, our current analysis dissected the effects of two slow wave types on cardiovascular function, using data from 18 middle-aged men across three nights. We found that the strength of heart rate and blood pressure responses concurrent with slow waves predicts cardiac function post-sleep. Notably, we identified that highly synchronized type I slow waves, as opposed to lower-amplitude type II slow waves, primarily co-occur with these cardiovascular pulsations. While auditory stimulation enhances both types of slow waves, they exhibit distinct temporal dynamics, pointing to different underlying biological mechanisms. This study crucially addresses how distinct slow wave types can affect cardiovascular function, implying that targeted slow wave stimulation could be a strategic approach to improve heart health.

neuroscience↗