Biology subjects

Hoedlmoser, K.

Publications and source records attributed to Hoedlmoser, K..

6 recordsLinked to original sources

bioRxiv2026

Children exhibit greater persistence of motor learning-related patterns of hippocampal activity into post-task wake epochs

Previous research has demonstrated that children exhibit superior - as compared to adults - consolidation of newly acquired motor sequences across post-learning periods of wakefulness. Given that consolidation is thought to be supported by the reactivation of learning-related patterns of brain activity during the rest periods following active task practice, we hypothesized that the childhood advantage in offline consolidation may be linked to greater reactivation during post-learning wakefulness. Twenty-two children (7-11 years) and 23 adults (18-30 years) completed two sessions of a motor sequence learning task, separated by a 5-hour wake interval. Multivoxel analyses of task-related and resting-state functional magnetic resonance imaging data were employed to assess the persistence of learning-related patterns of neural activity into post-task rest epochs, reflective of reactivation processes. Behavioral results demonstrated the previously reported childhood advantage in offline consolidation over a post-learning wake interval. Imaging results revealed that children exhibited greater persistence of task-related hippocampal - but not putaminal - activity into post-learning rest as compared to adults. These findings suggest that the childhood advantage in awake motor memory consolidation may be supported, at least partially, by enhanced reactivation of task-dependent hippocampal activity patterns during offline epochs.

neuroscience↗

bioRxiv2024

The Temporal Dynamics of Aperiodic Neural Activity Track Changes in Sleep Architecture

The aperiodic (1/f-like) component of electrophysiological data - whereby power systematically decreases with increasing frequency, as quantified by the aperiodic exponent - has been shown to differentiate sleep stages. Earlier work, however, has typically focused on measuring the aperiodic exponent across a narrow frequency range. In this work, we sought to further investigate aperiodic activity during sleep by extending these analyses across broader frequency ranges and considering alternate model definitions. This included measuring knees in the aperiodic component, which reflect bends in the power spectrum, indicating a change in the exponent. We also sought to evaluate the temporal dynamics of aperiodic activity during sleep. To do so, we analyzed data from two sources: intracranial EEG (iEEG) from 106 epilepsy patients and high-density EEG from 17 healthy individuals, and measured aperiodic activity, explicitly comparing different frequency ranges and model forms. In doing so, we find that fitting broadband aperiodic models and incorporating a knee feature effectively captures sleep-stage-dependent differences in aperiodic activity as well as temporal dynamics that relate to sleep stage transitions and responses to external stimuli. In particular, the knee parameter shows stage-specific variation, suggesting an interpretation of varying timescales across sleep stages. These results demonstrate that examining broader frequency ranges with the more complex aperiodic models reveals novel insights and interpretations for understanding aperiodic neural activity during sleep.

neuroscience↗

bioRxiv2023

Motor adaptation is facilitated by sleep-associated modulation of beta oscillations

Motor adaptation reflects the ability of the brains sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatized motor skill, i.e., typing. We hypothesized that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography (EEG). Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power (a) during mirrored typing as compared to regular typing, and (b) in the post-sleep vs. the pre-sleep mirrored typing sessions. Furthermore, the slope of the EEG signal, a measure of aperiodic brain activity, decreased during mirrored as compared to regular typing. Changes in the EEG spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity mechanisms supporting adaptive motor functions.

neuroscience↗

bioRxiv2022

Spectral slope and neural complexity as robust markers of task demand and brain state during sleep and wakefulness

Spectral slope and Lempel-Ziv complexity are affected in many neurophysiological disorders and are modulated by sleep, anesthesia, and aging. Yet, few studies have explored the relationship between these two parameters. We evaluated the impact of sleep stage and task-engagement (resting, attention and memory) on spectral slope and Lempel-Ziv complexity in a narrow- (30 - 45Hz) and broadband (1 - 45Hz) frequency range in 28 healthy males (21.54 {+/-} 1.90 years) over three recordings. Only in the broadband range, the slope steepens and complexity decreases continuously from wakefulness to N3. However, REM sleep is best discriminated by the narrowband slope. Importantly, slope and complexity also differentiate between tasks during wakefulness. While the narrowband complexity decreases across tasks, the slope is flattening with task engagement in both frequency ranges. In general, broadband slope and complexity are strongly positively correlated, but we observe a dissociation between them in the narrowband range. Critically, only the narrowband slope is associated with better Go/Nogo task performance. Our results demonstrate that slope and complexity are both powerful indices of sleep depth, task engagement and cognitive performance. While the broadband range is better suited to discriminate between brain states, especially the narrowband slope is a unique marker of task performance.

neuroscience↗

bioRxiv2022

Sleep spindle maturation enhances slow oscillation-spindle coupling

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz) precisely during the slow oscillation up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children aged 5 to 6, 8 to 11, and 14 to 18 years. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the canonical (adult-like) fast spindle range in all three age groups - but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and precision. Taken together, our results suggest that the increasing ability to generate canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns across child and adolescent development.

neuroscience↗

bioRxiv2021

Slow oscillation-spindle coupling strength predicts real-life gross-motor learning in adolescents and adults

Previously, we demonstrated that precise temporal coordination between slow oscillations (SO) and sleep spindles indexes declarative memory network development (Hahn et al., 2020). However, it is unclear whether these findings in the declarative memory domain also apply in the motor memory domain. Here, we compared adolescents and adults learning juggling, a real-life gross-motor task. We found that improved task proficiency after sleep lead to an attenuation of the learning curve, suggesting a dynamic juggling learning process. We employed individualized cross-frequency coupling analyses to reduce inter and intra-group variability of oscillatory features. Advancing our previous findings, we identified a more precise SO-spindle coupling in adults compared to adolescents. Importantly, coupling precision over motor areas predicted overnight changes in task proficiency and learning curve, indicating that SO-spindle coupling is sensitive to the dynamic motor learning process. Our results provide first evidence that regionally specific precisely coupled sleep oscillations support gross-motor learning.

neuroscience↗