TY - JOUR
T1 - Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep
AU - Tagliazucchi, Enzo
AU - Laufs, Helmut
N1 - Funding Information:
This work was funded by the Bundesministerium für Bildung und Forschung (grant 01 EV 0703) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). We thank Helmuth Steinmetz, Astrid Morzelewski, Kolja Jahnke, Sandra Anti, Ralf Deichmann, and Steffen Volz for extensive support and our volunteers for participation in the study. We are grateful to the International Neuroimaging Data-Sharing Initiative (INDI), especially Michael Milham, for making the 1000 Functional Connectomes Project data set publicly available. We thank Thomas Sattler for excellent IT infrastructure maintenance, without which the analysis of this data would not have been possible. Finally, we thank the anonymous reviewers for their constructive suggestions, which at times found literal entrance to this manuscript version.
PY - 2014/5/7
Y1 - 2014/5/7
N2 - The mining of huge databases of resting-state brain activity recordings represents state of the art in the assessment of endogenous neuronal activity-and may be a promising tool in the search for functional biomarkers. However, the resting state is an uncontrolled condition and its heterogeneity is neither sufficiently understood nor accounted for. We test the hypothesis that subjects exhibit unstable wakefulness, i.e., drift into sleep during typical resting-state experiments. Analyzing 1,147 resting-state functional magnetic resonance data sets, we revealed a reliable loss of wakefulness in a third of subjects within 3min and demonstrated the dynamic nature of the resting state, with fundamental changes in the associated functional neuroanatomy. Implications include the necessity of wakefulness monitoring and modeling, taking measures to maintain a state of wakefulness, acknowledging the possibility of sleep and exploring its consequences, and especially the critical assessment of possible false-positive or false-negative results.
AB - The mining of huge databases of resting-state brain activity recordings represents state of the art in the assessment of endogenous neuronal activity-and may be a promising tool in the search for functional biomarkers. However, the resting state is an uncontrolled condition and its heterogeneity is neither sufficiently understood nor accounted for. We test the hypothesis that subjects exhibit unstable wakefulness, i.e., drift into sleep during typical resting-state experiments. Analyzing 1,147 resting-state functional magnetic resonance data sets, we revealed a reliable loss of wakefulness in a third of subjects within 3min and demonstrated the dynamic nature of the resting state, with fundamental changes in the associated functional neuroanatomy. Implications include the necessity of wakefulness monitoring and modeling, taking measures to maintain a state of wakefulness, acknowledging the possibility of sleep and exploring its consequences, and especially the critical assessment of possible false-positive or false-negative results.
UR - http://www.scopus.com/inward/record.url?scp=84899812494&partnerID=8YFLogxK
U2 - 10.1016/j.neuron.2014.03.020
DO - 10.1016/j.neuron.2014.03.020
M3 - Article
C2 - 24811386
AN - SCOPUS:84899812494
SN - 0896-6273
VL - 82
SP - 695
EP - 708
JO - Neuron
JF - Neuron
IS - 3
ER -