TY - JOUR
T1 - Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states – A high-density EEG study
AU - Buccellato, Andrea
AU - Zang, Di
AU - Zilio, Federico
AU - Gomez-Pilar, Javier
AU - Wang, Zhe
AU - Qi, Zengxin
AU - Zheng, Ruizhe
AU - Xu, Zeyu
AU - Wu, Xuehai
AU - Bisiacchi, Patrizia
AU - Felice, Alessandra Del
AU - Mao, Ying
AU - Northoff, Georg
N1 - Funding Information:
GN has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785,907 (Human Brain Project SGA2). GN is grateful for funding provided by UMRF, uOBMRI, CIHR (201103MOP-244,752-BSBCECA-179,644; 201103CCI- 248,496-CCI-CECA), the Canada-UK Artificial Intelligence Initiative (ES/T01279X/1), and PSI. D.Z., Z.W., Z. Q., R.Z., Z. X., X.W. and Y.M. were funded by the Shanghai Municipal Science and Technology Major Project [2018SHZDZX01], ZJLab, by the Shanghai center for Brain Science and Brain-Inspired Technology, and by the Lingang Laboratory, [grant number LG202105–02–03].
Funding Information:
ADF received funding from the MSCA H2020 European Funding, from the Italian Ministry for International Affairs and Cooperation, and the University of Padova research grants.
Publisher Copyright:
© 2022
PY - 2023/1
Y1 - 2023/1
N2 - Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.
AB - Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.
KW - Alpha peak frequency
KW - Anaesthesia
KW - Disorders of consciousness
KW - Electroencephalography
KW - Intrinsic neural timescales
KW - Temporal input processing
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U2 - 10.1016/j.neuroimage.2022.119802
DO - 10.1016/j.neuroimage.2022.119802
M3 - Article
C2 - 36503159
AN - SCOPUS:85144444216
SN - 1053-8119
VL - 265
JO - NeuroImage
JF - NeuroImage
M1 - 119802
ER -