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Background: Hypobaric hypoxic conditions encountered at high altitudes can significantly impact the physiological functions of human body. Therefore, accurate and real-time monitoring of physiological characteristics is crucial for the prevention of brain injuries in individuals with acute and chronic high-altitude exposure. Methods: In this study, a wireless wearable cerebral oximeter (WORTH band) was used for the continuous, real-time monitoring of physiological parameters, including regional cerebral oxygen saturation (rSO2) and heart rate (HR), among subjects with high-altitude exposure. Results: During the high-altitude (from 46 m to 4300 m) expedition task, there was a significant decrease in rSO2 accompanied by a corresponding increase in heart rate as the altitude increased. Additionally, during the long-term (52 days) high-altitude (from 356 m to 4658 m) cycling task, the altitudes were significantly correlated with the rSO2 and SpO2 in the elderly subjects. Conclusion: The current findings indicate that the WORTH band oximeter can serve as a promising instrument for measuring rSO2 at high altitudes. We hope that the insights derived from this study could contribute to the management of cerebral oxygenation for individuals with high-altitude exposure and further expand the existing understanding of brain functional detection at high altitudes. [ABSTRACT FROM AUTHOR]

Maintenance of adequate blood perfusion and oxygen delivery is essential for cerebral metabolism. Cerebral oximeters based on near-infrared spectroscopy (NIRS) have been used for noninvasive, continuous, real-time monitoring of cerebral oxygen saturation and management of cerebral oxygen adequacy perioperatively and intraoperatively in various clinical situations, such as cardiac surgery, anesthesia, and cerebral auto-regulation. In this study, a portable and modular cerebral tissue oximeter (BRS-1) was designed for real-time detection of regional oxygen saturation over the brain, finger, or other targeted body tissues, as well as for wireless cerebral oxygenation monitoring. The compact and lightweight design of the system makes it easy to use during ambulance transport, in an emergency cart, or in an intensive care unit. The system performance of the BRS-1 oximeter was evaluated and compared with two US FDA-cleared cerebral oximeters during a controlled hypoxia experiment. The results showed that the BRS-1 oximeter can be used for real-time detection of cerebral desaturation with an accuracy similar to the two commercial oximeters. More importantly, the BRS-1 oximeter is capable of capturing cerebral oxygen saturation wirelessly. The BRS-1 cerebral oximeter can provide valuable insights for clinicians for real-time monitoring of cerebral/tissue perfusion and management of patients in prehospital and perioperative periods. [ABSTRACT FROM AUTHOR]

It remains challenging to identify depression accurately due to its biological heterogeneity. As people suffering from depression are associated with functional brain network alterations, we investigated subtypes of patients with first‐episode drug‐naive (FEDN) depression based on brain network characteristics. This study included data from 91 FEDN patients and 91 matched healthy individuals obtained from the International Big‐Data Center for Depression Research. Twenty large‐scale functional connectivity networks were computed using group information guided independent component analysis. A multivariate unsupervised normative modeling method was used to identify subtypes of FEDN and their associated networks, focusing on individual‐level variability among the patients for quantifying deviations of their brain networks from the normative range. Two patient subtypes were identified with distinctive abnormal functional network patterns, consisting of 10 informative connectivity networks, including the default mode network and frontoparietal network. 16% of patients belonged to subtype I with larger extreme deviations from the normal range and shorter illness duration, while 84% belonged to subtype II with weaker extreme deviations and longer illness duration. Moreover, the structural changes in subtype II patients were more complex than the subtype I patients. Compared with healthy controls, both increased and decreased gray matter (GM) abnormalities were identified in widely distributed brain regions in subtype II patients. In contrast, most abnormalities were decreased GM in subtype I. The informative functional network connectivity patterns gleaned from the imaging data can facilitate the accurate identification of FEDN‐MDD subtypes and their associated neurobiological heterogeneity. [ABSTRACT FROM AUTHOR]

Canonical correlation analysis (CCA) has been used for the steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) for a long time. However, the reference signal of CCA is relatively simple and lacks subject-specific information. Moreover, over-fitting may occur when a short time window (TW) length was used in CCA. In this article, an optimized L1-regularized multiway canonical correlation analysis (L1-MCCA) is combined with a support vector machine (SVM) to overcome the aforementioned shortcomings in CCA. The correlation coefficients obtained by L1-MCCA were transferred into a particle-swarm-optimization (PSO)-optimized support vector machine (SVM) classifier to improve the classification accuracy. The performance of the proposed method was evaluated and compared with the traditional CCA and power spectral density (PSD) methods. The results showed that the accuracy of the L1-MCCA-PSO-SVM was 96.36% and 98.18% respectively when the TW lengths were 2 s and 6 s. This accuracy is higher than that of the traditional CCA and PSD methods. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a common neurodegeneration disease associated with substantial disruptions in the brain network. However, most studies investigated static resting-state functional connections, while the alteration of dynamic functional connectivity in AD remains largely unknown. This study used group independent component analysis and the sliding-window method to estimate the subject-specific dynamic connectivity states in 1704 individuals from three data sets. Informative inherent states were identified by the multivariate pattern classification method, and classifiers were built to distinguish ADs from normal controls (NCs) and to classify mild cognitive impairment (MCI) patients with informative inherent states similar to ADs or not. In addition, MCI subgroups with heterogeneous functional states were examined in the context of different cognition decline trajectories. Five informative states were identified by feature selection, mainly involving functional connectivity belonging to the default mode network and working memory network. The classifiers discriminating AD and NC achieved the mean area under the receiver operating characteristic curve of 0.87 with leave-one-site-out cross-validation. Alterations in connectivity strength, fluctuation, and inter-synchronization were found in AD and MCIs. Moreover, individuals with MCI were clustered into two subgroups, which had different degrees of atrophy and different trajectories of cognition decline progression. The present study uncovered the alteration of dynamic functional connectivity in AD and highlighted that the dynamic states could be powerful features to discriminate patients from NCs. Furthermore, it demonstrated that these states help to identify MCIs with faster cognition decline and might contribute to the early prevention of AD., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Spinal cord stimulation (SCS) is a promising treatment for disorders of consciousness (DOC), but the underlying mechanism and most effective procedures remain uncertain. To optimize the protocol, previous studies evaluated the frequency-specific effects of SCS on neurophysiological activities. However, whether and how the inter-stimulus interval (ISI) parameter affects the SCS neuromodulation in DOC remains unknown. We enrolled nine DOC patients who had implanted SCS devices and conducted three different durations of ISIs. Using functional near-infrared spectroscopy (fNIRS), we monitored the blood volume fluctuations in the prefrontal and occipital cortices during the SCS. The results showed that short stimuli (30 s) induced significant cerebral blood volume changes, especially in the prefrontal cortex, an important area in the consciousness system. By comparing the mean value of the responses from the first and the last block in each session, a shorter ISI was found to improve the blood volume in the prefrontal cortex. This phenomenon was more significant for the subgroup of patients with a favorable prognosis. These preliminary results imply that the ISI may be an important factor for SCS. The research paradigm proposed here also provides insights for further quantitative evaluations of the therapeutic effects of neuromodulation.