The dynamics of hemispheric global signal with the fluctuation of wakefulness during resting state
Poster No:
2579
Submission Type:
Abstract Submission
Authors:
xiangyu kong1, Gaolang Gong1
Institutions:
1State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Resea, Beijing, Beijing
First Author:
Xiangyu Kong
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Resea
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Resea
Beijing, Beijing
Co-Author:
Gaolang Gong
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Resea
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Resea
Beijing, Beijing
Introduction:
Wakefulness reflects responsiveness to external stimuli and internal consciousness, which is vital for understanding brain function[1], [2]. Changes in wakefulness states accompany with alteration of brain activity, including the global signal (GS)[3], [4]. Interestingly, such alteration showed distinct patterns between the left and right hemispheres during the wakefulness-to-sleep transition[5], [6]. To date, it remains largely unknown whether and how the change of wakefulness states during non-sleeping conditions is associated with hemisphere-specific brain activity changes. This study was designed to systematically assess the dynamics of the GS within each hemisphere, along with the fluctuation of non-sleeping wakefulness during resting state.
Methods:
The study used 7T dataset from the Human Connectome Project (HCP) S1200 release[7]. It includes 184 subjects with 723 resting-state fMRI scans and concurrent eye-tracking data. The eye-tracking data was processed following Gonzalez-Castillo et al, and resting-state fMRI data was preprocessed using the HCP minimal pipeline. As did previously[8], 30-second nonoverlap sliding windows were applied to calculate the percentage of eye closure (PERCLOS) as a quantitative measure of wakefulness.
For each sliding time window, the hemispheric GS timeseries were derived by averaging preprocessed BOLD signals across all cortical vertices within each hemisphere. The global signal fluctuation (GSF) and global signal topography (GST) were then calculated[3], [9].
A linear mixed model was applied to evaluate the main effects of PERCLOS and hemisphere, as well as their interaction effect, while controlling for age, sex, and handedness as covariates. Multiple comparison was corrected by permutation-based family-wise error method.
For each sliding time window, the hemispheric GS timeseries were derived by averaging preprocessed BOLD signals across all cortical vertices within each hemisphere. The global signal fluctuation (GSF) and global signal topography (GST) were then calculated[3], [9].
A linear mixed model was applied to evaluate the main effects of PERCLOS and hemisphere, as well as their interaction effect, while controlling for age, sex, and handedness as covariates. Multiple comparison was corrected by permutation-based family-wise error method.
Results:
As shown in Fig 1, there was significant main effects of both PERCLOS and hemisphere on the GSF (the PERCLOS effect: left hemisphere, r = 0.24, p < 0.001; right hemisphere, r = 0.23, p < 0.001; the hemisphere effect: right-greater-than-left, t = 6.664, p < 0.001). No significant hemisphere *PERCLOS interaction effect was observed.
Regarding the main PERCLOS effect on the GST, positive correlation with PERCLOS (warm-colored) was mainly located around the primary somatosensory cortex and temporo-occipital cortex. In contrast, the intraparietal sulcus, parieto-occipital sulcus, and primary visual cortex showed negative correlation with PERCLOS (cold-colored) (Fig. 2A).
Significant main hemisphere effects on the GST were also observed. Specifically, compared with the right hemisphere, the left hemisphere showed higher GST values (warm-colored) in the inferior parietal cortex, primary auditory cortex, and ventral posterior cingulate cortex, but lower GST values around the inferior parietal lobule, parieto-occipital sulcus, and superior parietal lobule (cold-colored) (Fig. 2B).
Finally, there were significant PERCLOS* hemisphere interaction effect (Fig 2C). For example, the supramarginal gyrus and inferior frontal junction area showed a positive correlation with PERCLOS in the left hemisphere but a negative correlation in the right hemisphere.
Regarding the main PERCLOS effect on the GST, positive correlation with PERCLOS (warm-colored) was mainly located around the primary somatosensory cortex and temporo-occipital cortex. In contrast, the intraparietal sulcus, parieto-occipital sulcus, and primary visual cortex showed negative correlation with PERCLOS (cold-colored) (Fig. 2A).
Significant main hemisphere effects on the GST were also observed. Specifically, compared with the right hemisphere, the left hemisphere showed higher GST values (warm-colored) in the inferior parietal cortex, primary auditory cortex, and ventral posterior cingulate cortex, but lower GST values around the inferior parietal lobule, parieto-occipital sulcus, and superior parietal lobule (cold-colored) (Fig. 2B).
Finally, there were significant PERCLOS* hemisphere interaction effect (Fig 2C). For example, the supramarginal gyrus and inferior frontal junction area showed a positive correlation with PERCLOS in the left hemisphere but a negative correlation in the right hemisphere.
Conclusions:
The present study demonstrated an association of dynamic change of hemispheric global signal (e.g., GSF and GST) with fluctuation of wakefulness during resting state. Particularly, the two hemispheres exhibited significant difference in the global signal, which could be modulated by the wakefulness state.
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 1
Keywords:
FUNCTIONAL MRI
Hemispheric Specialization
Other - wakefulness; global signal; resting-state; Pupillometry
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[2] Scammell, T.E. (2017), 'Neural Circuitry of Wakefulness and Sleep', Neuron, vol. 93, no. 4, pp. 747–765
[3] Wong, C.W. (2013), 'The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures', NeuroImage, vol. 83, pp. 983–990
[4] Turchi, J. (2018), 'The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations', Neuron, vol. 97, no. 4, pp. 940-952.e4
[5] Bolduc, C. (2003), 'Hemispheric lateralization of the EEG during wakefulness and REM sleep in young healthy adults', Brain and Cognition, vol. 53, no. 2, pp. 193–196
[6] Tamaki, M. (2016), 'Night Watch in One Brain Hemisphere during Sleep Associated with the First-Night Effect in Humans', Current Biology, vol. 26, no. 9, pp. 1190–1194
[7] Glasser, M.F. (2013), 'The minimal preprocessing pipelines for the Human Connectome Project', NeuroImage, vol. 80, pp. 105–124
[8] Wilson, R.S. (2015), 'Influence of epoch length on measurement of dynamic functional connectivity in wakefulness and behavioural validation in sleep', NeuroImage, vol. 112, pp. 169–179
[9] Yang, G.J. (2016), 'Altered Global Signal Topography in Schizophrenia', Cerebral Cortex, vol. 27, pp. 5156–5169