Biology subjects

Ladenbauer, J.

Publications and source records attributed to Ladenbauer, J..

8 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↗

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↗

bioRxiv2021

Towards optimization of oscillatory stimulation during sleep

BackgroundOscillatory rhythms during sleep such as slow oscillations (SO) and spindles, and most importantly their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolidation, however, effects varied quite markedly between individuals, studies, and species. Here, we aimed to determine how precisely the frequency of stimulation has to match the naturally occurring SO frequency in individuals to optimally improve SO-spindle coupling. Moreover, we systematically tested stimulation durations necessary to induce changes. MethodsWe addressed these questions by comparing so-tDCS with individualized frequency to standardized frequency of 0.75 Hz in a within-subject design with 28 older participants during napping while systematically varying stimulation train durations between 30 s, 2 min, and 5 min. ResultsStimulation trains as short as 30 s were sufficient to modulate the coupling between SOs and spindle activity. Contrary to our expectations, so-tDCS with standardized frequency indicated stronger aftereffects with regard to SO-spindle coupling compared to individualized frequency. Angle and variance of spindle maxima occurrence during the SO cycle were similarly modulated. ConclusionIn sum, short stimulation trains were sufficient to induce significant changes in sleep physiology allowing for more trains of stimulation, which provides methodological advantages and possibly even larger behavioral effects in future studies. With regard to individualized stimulation frequency, further options of optimization need to be investigated, such as closed-loop stimulation to calibrate stimulation frequency to the SO frequency at time of stimulation onset. Significance statementApplication of slow oscillatory transcranial direct current stimulation during sleep has been shown to enhance specific memory-relevant sleep parameters and memory performance after sleep, albeit with a high degree of variability. Here, we systematically explored two major stimulation parameters possibly accounting for this variability in humans: frequency and duration of stimulation. We found, contrary to our expectations, standardized frequency stimulation with 0.75 Hz being superior to individualized frequency stimulation in enhancing specific sleep parameters. Moreover short stimulation trains of 30 seconds were as effective as 5 min in modulating aftereffects. These are encouraging findings, implying methodological advantages as larger quantity of aftereffects data can be obtained within the same time window, which may also lead to enhanced behavioral stimulation effects.

neuroscience↗

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.

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bioRxiv2019

Inferring the collective dynamics of neuronal populations from single-trial spike trains using mechanistic models

Multi-neuronal spike-train data recorded in vivo often exhibit rich dynamics as well as considerable variability across cells and repetitions of identical experimental conditions (trials). Efforts to characterize and predict the population dynamics and the contributions of individual neurons require model-based tools. Abstract statistical models allow for principled parameter estimation and model selection, but possess only limited interpretive power because they typically do not incorporate prior biophysical constraints. Here we present a statistically principled approach based on a population of doubly-stochastic integrate-and-fire neurons, taking into account basic biophysics. This model class comprises an idealized description for the dynamics of the neuronal membrane voltage in response to fast independent and slower shared input fluctuations. To efficiently estimate the model parameters and compare different model variants we compute the likelihood of observed single-trail spike trains by leveraging analytical methods for spiking neuron models combined with inference techniques for hidden Markov models. This allows us to reconstruct the shared input variations, classify their dynamics, obtain precise spike rate estimates, and quantify how individual neurons couple to the low-dimensional overall population dynamics, all from a single trial. Extensive evaluations based on simulated data show that our method correctly identifies the dynamics of the shared input process and accurately estimates the model parameters. Validations on ground truth recordings of neurons in vitro demonstrate that our approach successfully reconstructs the dynamics of hidden inputs and yields improved fits compared to a typical phenomenological model. Finally, we apply the method to a neuronal population recorded in vivo, for which we assess the contributions of individual neurons to the overall spiking dynamics. Altogether, our work provides statistical inference tools for a class of reasonably constrained, mechanistic models and demonstrates the benefits of this approach to analyze measured spike train data.

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bioRxiv2018

Weak electric fields promote resonance in neuronal spiking activity: analytical results from two-compartment cell and network models

Transcranial brain stimulation and evidence of ephaptic coupling have sparked strong interests in understanding the effects of weak electric fields on the dynamics of neuronal populations. While their influence on the subthreshold membrane voltage can be biophysically well explained using spatially extended neuron models, mechanistic analyses of neuronal spiking and network activity have remained a methodological challenge. More generally, this challenge applies to phenomena for which single-compartment (point) neuron models are oversimplified. Here we employ a pyramidal neuron model that comprises two compartments, allowing to distinguish basal-somatic from apical dendritic inputs and accounting for an extracellular field in a biophysically minimalistic way. Using an analytical approach we fit its parameters to reproduce the response properties of a canonical, spatial model neuron and dissect the stochastic spiking dynamics of single cells and large networks. We show that oscillatory weak fields effectively mimic anti-correlated inputs at the soma and dendrite and strongly modulate neuronal spiking activity in a rather narrow frequency band. This effect carries over to coupled populations of pyramidal cells and inhibitory interneurons, boosting network-induced resonance in the beta and gamma frequency bands. Our work contributes a useful theoretical framework for mechanistic analyses of population dynamics going beyond point neuron models, and provides insights on modulation effects of extracellular fields due to the morphology of pyramidal cells.\n\nAuthor SummaryThe elongated spatial structure of pyramidal neurons, which possess large apical dendrites, plays an important role for the integration of synaptic inputs and mediates sensitivity to weak extracellular electric fields. Modeling studies at the population level greatly contribute to our mechanistic understanding but face a methodological challenge because morphologically detailed neuron models are too complex for use in noisy, in-vivo like conditions and large networks in particular. Here we present an analytical approach based on a two-compartment spiking neuron model that can distinguish synaptic inputs at the apical dendrite from those at the somatic region and accounts for an extracellular field in a biophysically minimalistic way. We devised efficient methods to approximate the responses of a spatially more detailed pyramidal neuron model, and to study the spiking dynamics of single neurons and sparsely coupled large networks in the presence of fluctuating inputs. Using these methods we focused on how responses are affected by oscillatory weak fields. Our results suggest that ephaptic coupling may play a mechanistic role for oscillations of population activity and indicate the potential to entrain networks by weak electric stimulation.

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bioRxiv2018

Inferring mechanistic models of neuronal microcircuits from single-trial spike trains

The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic models are useful to interpret microcircuit dynamics, but are rarely quantitatively matched to experimental data due to methodological challenges. Here we present analytical methods to efficiently fit spiking circuit models to single-trial spike trains. Using derived likelihood functions, we statistically infer the mean and variance of hidden inputs, neuronal adaptation properties and connectivity for coupled integrate-and-fire neurons. Comprehensive evaluations on synthetic data, validations using ground truth in-vitro and in-vivo recordings, and comparisons with existing techniques demonstrate that parameter estimation is very accurate and efficient, even for highly subsampled networks. Our methods bridge statistical, data-driven and theoretical, model-based neurosciences at the level of spiking circuits, for the purpose of a quantitative, mechanistic interpretation of recorded neuronal population activity.

neuroscience↗

bioRxiv2016

Transcranial stimulation enhances memory-relevant sleep oscillations and their functional coupling in mild cognitive impairment

Alzheimers disease (AD) not only involves loss of memory functions but also prominent deterioration of sleep physiology, already evident in the stage of mild cognitive impairment (MCI). Cortical slow oscillations (SO, 0.5-1 Hz) and thalamo-cortical spindle activity (12-15 Hz) during sleep, and their temporal coordination, are considered critical for memory formation. We investigated the potential of slow oscillatory transcranial direct current stimulation (so-tDCS), applied during a daytime nap in a sleep state-dependent manner, to modulate these activity patterns and sleep-related memory consolidation in 16 patients with MCI.\n\nStimulation significantly increased overall SO and spindle power, amplified spindle power during SO up-phases, and led to stronger synchronization between SO and spindle power fluctuations in electroencephalographic recordings. Moreover, visual declarative memory was improved by so-tDCS compared to sham stimulation, associated with stronger synchronization. These findings indicate a well-tolerated therapeutic approach for disordered sleep physiology and deficits in memory consolidation in MCI patients.

neuroscience↗