Cortical excitability signatures for the degree of sleepiness in human
Chin-Hsuan Chia, Xinwei Tang, Yue Cao, Huateng Cao, Wei Zhang, Junfa Wu, Yulian Zhu, Ying Chen, Yi Lin, Yi Wu, Zhe Zhang, Ti‐Fei Yuan, Ruiping Hu
Abstract
Sleep is essential in maintaining physiological homeostasis in the brain. While the underlying mechanism is not fully understood, a 'synaptic homeostasis' theory has been proposed that synapses continue to strengthen during awake and undergo downscaling during sleep. This theory predicts that brain excitability increases with sleepiness. Here, we collected transcranial magnetic stimulation measurements in 38 subjects in a 34 hr program and decoded the relationship between cortical excitability and self-report sleepiness using advanced statistical methods. By utilizing a combination of partial least squares regression and mixed-effect models, we identified a robust pattern of excitability changes, which can quantitatively predict the degree of sleepiness. Moreover, we found that synaptic strengthen occurred in both excitatory and inhibitory connections after sleep deprivation. In sum, our study provides supportive evidence for the synaptic homeostasis theory in human sleep and clarifies the process of synaptic strength modulation during sleepiness.