Neuroimage
May 1, 2021
Pengmin Qin, Xuehai Wu, Changwei W Wu et al.
51 citations
Consciousness depends on a network of brain regions that integrate sensory and motor information. Analyzing fMRI data from people in preserved (awake, fully conscious brain-injury survivors), reduced (N1-sleep, minimally conscious), and lost (N3-sleep, anesthesia, unresponsive wakefulness) states, plus a unique rapid-eye-movement (REM) sleep group, researchers identified key hubs whose degree centrality—a measure of network importance—dropped significantly when consciousness was reduced or absent. These hubs included the supplementary motor area, bilateral supramarginal gyrus, supragenual/dorsal anterior cingulate cortex, and left middle temporal gyrus. A higher-order sensorimotor circuit connecting these regions showed functional connectivity that correlated with consciousness levels across groups and remained active in REM sleep, suggesting this circuit supports consciousness and offers new targets for treating disorders of consciousness.
Frontiers in Behavioral Neuroscience
March 21, 2023
Shiao-Fei Guu, Yi-Ping Chao, Feng-Ying Huang et al.
28 citations
Two distinct mindfulness practices—breathing and body scan—produce different patterns of brain connectivity after an 8-week mindfulness-based stress reduction (MBSR) program. Using fMRI, the study examined the salience network (SN) in 18 meditation-naïve participants who completed MBSR and 14 waitlist controls. Breathing (fixed attention) increased long-distance SN connectivity to occipital regions, while body scan (shifting attention) increased SN connectivity to frontal and central gyri and boosted local neural coherence in the parietal lobe. During mindfulness practices after MBSR, distant and local connections became positively correlated, suggesting globally enhanced SN information processing. The small sample limits generalizability.
Computer methods and programs in biomedicine
December 1, 2024
Ai-Ling Hsu, Chun-Yu Wu, Hei-Yin Hydra Ng et al.
Electroencephalography (EEG) effective connectivity can predict whether someone has experience with mindfulness-based stress reduction (MBSR). Machine learning algorithms classified participants' MBSR history using gamma-band brain connectivity. The decision tree algorithm achieved the highest prediction accuracy of 91.7% during resting state, outperforming classifications during focus-breathing and body-scan sessions. Support vector machine and naïve Bayes classifiers also showed significant accuracies above chance across all three sessions. Preserving just four EEG channels (F7, F8, T7, P7) out of 19 yielded 83.3% accuracy. Connectivity features predominantly in the frontal lobe contributed most to classifier construction, consistent with existing mindfulness literature.
Journal of Neuroscience Research
June 1, 2023
Hei-Yin Hydra Ng, Changwei W Wu, Feng-Ying Huang et al.
Low-gamma band effective connectivity increased globally after an 8-week mindfulness-based stress reduction (MBSR) program, while high-beta band effective connectivity increased only during breathing. Outgoing effective connectivity was stronger during resting, breathing, and body-scan. Changes in effective connectivity of the right lateral prefrontal area predicted mindfulness and emotional regulation abilities, partially supporting the theory that lateral prefrontal areas exert top-down modulatory control, implying that mindfulness training cultivates better emotional regulation.
bioRxiv
September 23, 2020
Pengmin Qin, Xuehai Wu, Changwei W Wu et al.
preprint
Local brain regions may support consciousness by acting as hubs within the brain's global network. Using resting-state fMRI data from people in various conscious states—NREM-sleep, REM-sleep, anesthesia, and brain injury patients—and a graph-theoretical measure for detecting local hubs, the authors identify higher-order sensory and motor regions whose degree centrality is significantly reduced during unconsciousness. These regions form a sensorimotor circuit that correlates with levels of consciousness. The findings suggest that integration of higher-order sensorimotor function may be a key mechanism of consciousness, opening novel perspectives for therapeutic modulation of unconsciousness.
Human Brain Mapping
August 1, 2019
Yi-Chia Kung, Chia-Wei Li, Shuo Chen et al.
During nonrapid eye movement (NREM) sleep, consciousness fades as the brain's dynamic functional connectivity changes. Using simultaneous EEG-fMRI recordings in 12 healthy men, the study examined two aspects of dynamic connectivity: mean (dFCmean), reflecting stable network integrity, and variance (dFCvar), indicating instability of information transfer. As sleep deepened, dFCmean decreased progressively across waking and NREM stages (N0~N1 > N2 > N3), while dFCvar peaked during N2 stage (N0~N1 < N3 < N2), suggesting unstable whole-brain synchronizations. In N3 stage, overall network integration was disrupted, with lowest dFCmean and elevated dFCvar. The findings suggest that consciousness dissipates when network specificity breaks down alongside increasing variability of information exchange.
Neuroimage
July 1, 2018
Qihong Zou, Shuqin Zhou, Jing Xu et al.
Dream recall frequency and REM sleep percentage are linked to different brain functional networks. In 43 healthy adults, resting-state fMRI and polysomnography showed that both measures negatively correlated with multiple networks. Dream recall frequency was mainly associated with connectivity in the lateral visual network and thalamus, while REM sleep percentage was mainly associated with connectivity in frontoparietal networks and cerebellum. A time-of-day effect emerged: dream recall frequency had stronger coupling with the lateral visual network at night, and REM sleep percentage had stronger coupling with the cerebellum in the morning. The findings indicate that the neural substrates for dream recall and REM sleep are distinct.