Subjective perception of sleep is not necessarily consistent with electroencephalography (EEG) indications of sleep. The mismatch between subjective reports and objective measures is often referred to as "sleep state misperception." Previous studies evince that this mismatch is found in both patients with insomnia and in normal sleepers, but the neurophysiological mechanism remains unclear. The aim of the study is to explore the neurophysiological basis of this mechanism, from the perspective of both EEG power and functional magnetic resonance imaging (fMRI) fluctuations. Thirty-six healthy young adults participated in the study. Simultaneous EEG and fMRI recordings were conducted while the participants were trying to fall asleep in an MRI scanner at approximately 9:00 pm. They were awakened after achieving stable N1 or N2 sleep, or after 90 min without falling into stable sleep. Next they were asked to recall their conscious experiences from the moment immediately prior to awakening. Sixty-one instances of scheduled awakenings were collected: 21 of these after having achieved stable stage N2 sleep; 12, during stage N1 sleep; and, 20 during the waking state. Relative to those awakenings without subjective-objective discrepancy (n = 27), these awakenings with discrepancy (n = 14) were associated with lower θ power, as well as higher α, β, and γ power. Moreover, we found that participants who exhibited the discrepancy, compared with those who did not, evinced a higher amplitude of low-frequency fluctuation levels in the prefrontal cortex. These results lend support to the conjecture that the subjective-objective discrepancy is associated with central nervous system hyperarousal.
Frequency-dependent modulation between neuronal assemblies may provide insightful mechanisms of functional organization in the context of neural connectivity. We present a conjoined time-frequency cross mutual information (TFCMI) method to explore the subtle brain neural connectivity by magnetoencephalography (MEG) during a self-paced finger lifting task. Surface electromyogram (sEMG) was obtained from the extensor digitorum communis. Both within-modality (MEG-MEG) and between-modality studies (sEMG-MEG) were conducted. The TFCMI method measures both the linear and nonlinear dependencies of the temporal dynamics of signal power within a pre-specified frequency band. Each single trial of MEG across channels and sEMG signals was transformed into time-frequency domain with use of the Morlet wavelet to obtain better temporal spectral (power) information. As compared to coherence approach (linear dependency only) in broadband analysis, the TFCMI method demonstrated advantages in encompassing detection for the mesial frontocentral cortex and bilateral primary sensorimotor areas, clear demarcation of event- and non-event-related regions, and robustness for sEMG - MEG between-modality study, i.e., corticomuscular communication. We conclude that this novel TFCMI method promises a possibility to better unravel the intricate functional organizations of brain in the context of oscillation-coded communication.
HIV testing, care, and treatment policies would be less than optimal without addressing barriers to testing, including stigma related to sexual orientation, among A/PI MSM.
Postmovement beta-rebounds induced by different intermovement intervals were investigated using magnetoencephalography in 14 healthy participants to test the hypothesis that postmovement motor cortical deactivation over the primary motor cortex depends on movement-related cognitive demands. Shorter latency and lower amplitude in postmovement beta-rebounds over the contralateral primary motor cortex were noted in the short-movement interval movement (repetitive finger lifting). Greater latency span of postmovement beta-rebounds jittering using single-trial analysis in the long-movement interval movement (discrete finger lifting) was observed. The study elucidates that the temporal interval between two adjacent movements reflecting different degrees of cognitive demands can affect postmovement motor cortical deactivation in terms of postmovement beta-rebounds latency and amplitude, and latency span of postmovement beta-rebounds jittering. Postmovement motor cortical deactivation can reflect cognitive demands in addition to motor and somatosensory processing.
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