Biology subjects

Klinzing, J. G.

Publications and source records attributed to Klinzing, J. G..

3 recordsLinked to original sources

bioRxiv2024

Automatic sleep scoring for real-time monitoring and stimulation in individuals with and without sleep apnea

Digital therapeutics, enabled by advanced machine learning algorithms and medical wearable devices, offer a promising approach to streamline diagnostics and improve access to healthcare. Within this framework, automatic sleep scoring can provide accurate and efficient sleep analysis from electrophysiological signals recorded with wearable sensors, such as electroencephalography (EEG). However, the optimal configuration and temporal dynamics of automatic sleep scoring systems remain unclear, especially concerning their performance across different population samples. This study systematically investigates the impact of electrode setup, temporal scope, and population characteristics on the performance of automatic sleep scoring algorithms. Utilizing a convolutional neural network (CNN) model, we analyzed various electrode configurations and temporal dynamics using datasets comprising both healthy participants and individuals with sleep apnea. Our findings reveal that sleep scoring based on a single frontal EEG channel demonstrates reliable congruency with human expert scorers, with minimal improvement observed with additional sensors. Moreover, we demonstrate that real-time sleep scoring can be achieved with comparable accuracy to offline methods, which rely on past and future information to classify a window of interest. Remarkably, a notable reduction in decoding accuracy is observed for individuals with sleep disorders compared to healthy participants, highlighting the challenges inherent in accurately assessing sleep stages in clinical populations. Digital solutions for automatic sleep scoring hold promise for facilitating timely diagnoses and personalized treatment plans, with applications extending beyond sleep analysis to include closed-loop neurostimulation interventions. Our findings provide valuable insights into the complexities of automatic sleep scoring and offer considerations for the development of effective and efficient sleep assessment tools in both clinical and research settings.

neuroscience↗

bioRxiv2023

Neural signatures of declarative memory cueing using odors during sleep

Long-term memories are formed by repeated reactivation of newly encoded information during sleep. This process can be enhanced by using memory-associated reminder cues like sounds and odors. While auditory cueing has been researched extensively, few electrophysiological studies have exploited the various benefits of olfactory cueing. We used high-density electroencephalography in an odor-cueing paradigm that was designed to isolate the neural responses specific to the cueing of declarative memories. We show widespread cueing-induced increases in the duration and rate of sleep spindles. Higher spindle rates were most prominent over centro-parietal areas and largely overlapping with a concurrent increase in the amplitude of slow oscillations (SOs). Interestingly, greater SO amplitudes were linked to a higher likelihood of coupling a spindle and coupled spindles expressed during cueing were more numerous in particular around SO up states. We thus identify temporally and spatially coordinated enhancements to sleep spindles and slow oscillations as a candidate mechanism behind the benefits of odor cueing. Our results further demonstrate the feasibility of studying neural activity patterns related to memory processing using olfactory cueing during sleep. Statement of SignificanceMemory cueing during sleep allows insights into memory consolidation. This study is the first to investigate olfactory cueing-induced declarative memory processing using high-density EEG, while robustly controlling for critical confounding factors. The use of odors as cues, instead of more common auditory stimuli, further minimizes possible distortions due to sensory-evoked potentials. We demonstrate intricate changes in brain activity in response to cueing, such as the patterns of sleep spindles, slow oscillations, and their spatiotemporal coupling. We provide evidence that the enhancement of slow oscillation amplitudes, together with associated increases in sleep spindle rates, could be the key mechanism behind cueing-related memory benefits. We moreover show that prior findings obtained using auditory cueing are not the mere result of tone-evoked responses but might be genuine signatures of memory processing.

neuroscience↗

bioRxiv2020

Binocular disparity-based learning does not generalize to the other visual hemifield

Visual perceptual learning refers to long-lasting performance improvements on a visual skill, an ability presumably supported by plastic changes in early visual brain areas. Visual perceptual learning has been shown to be induced by training and to benefit from consolidation during sleep, presumably via the reactivation of learning-associated neuronal firing patterns. However, previous studies have almost exclusively relied on a single paradigm, the texture discrimination task, on which performance improvements may not rely on strictly perceptual skills. Here, we tested whether sleep has beneficial effects on a visual disparity discrimination task. We confirm previous findings in showing that the ability to discriminate different disparities is unaffected by sleep during a 12-hour retention period after training. Importantly, we extend these results by providing evidence against an effect of sleep on the generalization of improved disparity discrimination across the vertical meridian. We further rule out carry-over effects as a possible confound in our earlier within-subject study by relying on a between-subject design. The combined data from both studies argue against sleep as an important factor in the consolidation of a strictly perceptual skill. This sets important constraints on models of the role of sleep and sleep-associated neural reactivation in the consolidation of non-declarative memories.

neuroscience↗