European Journal of NeuroscienceNeurosciencePeer-reviewed journal article
The neurophysiology of closed-loop auditory stimulation in sleep: a magnetoencephalography study
Hugo R. JourdeiD, Raphaëlle MerloiD, Mary Brooks, Meredith Rowe, Emily B. J. CoffeyiD
Abstract
Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endoge-nous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleeps functions, as it increases slow oscillations, evokes sleep spindles, and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing, and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the EEG-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles, and associated cognitive benefits, and offer insight into how the effectiveness of brain stimulation techniques can be improved.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 21
- FWCI
- 3.14
- Field percentile
- top 8%
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