Abstract
The study of consciousness is crucial to understand how the human mind functions. Within the last twenty years new approaches to this question have been formulated and “establishing neural consciousness correlations” is one of the most promising. The sleep-wake paradigm is one of the most promising methodologies in this field, allowing the study of healthy subjects without medical interventions. We developed a monotonous psychomotor test that induces several episodes of losing consciousness because of falling asleep and its full or partial recovery while awakening within the 60 min. The following behavioral measures of consciousness level were noted: counting accuracy, time between presses, pressing force, so one could observe not only lapses, but also light sleep when subject starts to make mistakes. In our recent study, this method allowed us to assess 441 short episodes of falling asleep (“microsleep”), followed by spontaneous awakenings in 23 experimental sessions. Two different electroencephalographic patterns of awakening were observed. After deeper sleep stages the performance restoration was preceded by K-complexes. According to recent studies, it confirms that K-complex not only helps to maintain sleep, but also eases necessary awakenings. Our recent data suggest that not only external stimuli, but also the internal test instruction recall could start such awakening process. We believe that our experimental design could be used for wide range of consciousness studies because it gives researchers several continuous and objective indices of the subject’s mind state.
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This study was partially supported by the Russian Foundation for Basic Research grant #ofi-m 17-29-02518.
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Dorokhov, V.B., Tkachenko, O.N., Ushakov, V.L., Chernorizov, A.M. (2021). Neuronal Correlates of Spontaneous Awakening and Recovery of Psychomotor Performance. In: Velichkovsky, B.M., Balaban, P.M., Ushakov, V.L. (eds) Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Intercognsci 2020. Advances in Intelligent Systems and Computing, vol 1358. Springer, Cham. https://doi.org/10.1007/978-3-030-71637-0_49
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