Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep’s recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. Compared to conventional algorithms TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Closed-loop modulation of local slow oscillations in human NREM sleep


    Beteiligte:
    Ruch, Simon (Autor:in) / Schmidig, Flavio Jean (Autor:in) / Knüsel, Leona (Autor:in) / Henke, Katharina (Autor:in)

    Erscheinungsdatum :

    09.11.2021


    Anmerkungen:

    oai:zenodo.org:6243351



    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




    Closed-loop modulation of local slow oscillations in human NREM sleep

    Ruch, Simon / Schmidig, Flavio Jean / Knüsel, Leona et al. | BASE | 2021

    Freier Zugriff

    Detecting Sleep Disorders from NREM Using DeepSDBPLM

    Almutairi, Haifa / Hassan, Ghulam Mubashar / Datta, Amitava | Springer Verlag | 2024


    Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

    Shimizu, Renee E. / Connolly, Patrick M. / Cellini, Nicola et al. | BASE | 2018

    Freier Zugriff

    Closed loop controls human centrifuge

    Peirce, T.F. | Engineering Index Backfile | 1952


    PROPELLER BLADE ANGLE CLOSED LOOP CONTROL BY SOLENOID MODULATION

    MAVER TIMOTHY / LASSALLE JULIEN / MARGER THIBAUT et al. | Europäisches Patentamt | 2020

    Freier Zugriff