Abstract
Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep’s effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with ‘sleep and stimulation’ and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.
Highlights
Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms
Among 20 studies, we found common keywords for categorization relating to stimulation modality, feedback target, and the main hypothesis of the study
We found great advancement in slow oscillation (SO) and spindle-targeted feedback experiments since the early 2010s, and there is great potential to expand sleep research with closed-loop feedback systems under the consideration of various stimulation modalities
Summary
Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. Stimuli are presented according to predefined stimulation parameters independent of brain activity This is referred to as an open-loop stimulation paradigm, which is a conventional way to investigate cause-and-effect phenomena. Implementation of a loop between neural circuits (e.g., human brain and data acquisition device) and external environments (such as computer, robot, or device to be controlled) is referred to as a closed-loop stimulation paradigm [1], which is among the ways to control the external environment based on neurophysiological information and to provide feedback to subjects, influencing their brain activities. Researchers have introduced some feedback systems to improve the ability to use neuroprosthetic devices [6,7,8,9], as well as closed-loop deep brain stimulation (DBS) systems, to reduce dyskinesia and paralysis caused by Parkinson’s disease [10,11,12]. In the field of the brain-computer interface (BCI), closed-loop techniques are used more naturally in the form of neurofeedback to increase BCI systems’ operability [13,14,15]
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