Cerebral tissue oximeter suitable for real-time regional oxygen saturation monitoring in multiple clinical settings.

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.

A functional near-infrared spectroscopy study on hemodynamic changes of patients with prolonged disorders of consciousness responding to different auditory stimuli.

Treating prolonged disorders of consciousness (pDoC) is challenging. Thus, accurate assessment of residual consciousness in patients with pDoC is important for the management and recovery of patients. Functional near-infrared spectroscopy (fNIRS) can be used to detect brain activity through changes of oxygenated hemoglobin/deoxygenated hemoglobin (HbO/HbR) concentrations changes and has recently gained increasing attention for its potential applications in assessing residual consciousness. However, the number of fNIRS studies assessing residual awareness in patients with pDoC is still limited. In this study, fNIRS was used to evaluate the brain function in 18 patients with pDoC, including 14 vegetative states (VS) and 4 minimally conscious states (MCS), and 15 healthy controls (HC). All participants accepted two types of external stimuli, i.e., active stimulation (motor imagery, MI) and passive stimulation (subject's own name, SON). The results showed that the mean concentrations of HbO/HbR in the prefrontal cortex of the HC during the passive stimulation were significantly lower than those of the active stimulation, and the fitting slope was high. However, the hemodynamic responses of the patients with pDoC were opposite to those of the HC. Additionally, the mean concentrations of HbO/HbR increased as the level of consciousness decreased during passive stimulation. Our findings suggest that the residual level of consciousness in pDoC patients can be assessed by measuring brain responses to different stimulations using fNIRS. The present study further demonstrates the feasibility and reliability of fNIRS in assessing residual consciousness in patients with pDoC, providing a basis for its expanded clinical application.

Evaluation of residual cognition in patients with disorders of consciousness based on functional near-infrared spectroscopy.

Significance: Accurate evaluation of consciousness in patients with prolonged disorders of consciousness (DOC) is critical for designing therapeutic plans, determining rehabilitative services, and predicting prognosis. Effective ways for detecting consciousness in patients with DOC are still needed. Aim: Evaluation of the residual awareness in patients with DOC and investigation of the spatiotemporal differences in the hemodynamic responses between the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS) groups using active command-driven motor imagery (MI) tasks. Approach: In this study, functional near-infrared spectroscopy (fNIRS) was used to measure the changes of hemodynamic responses in 19 patients with DOC (9 MCS and 10 UWS) using active command-driven MI tasks. The characteristics of the hemodynamic responses were extracted to compare the differences between the MCS and UWS groups. Moreover, the correlations between the hemodynamic responses and the clinical behavioral evaluations were also studied. Results: The results showed significant differences in the spatiotemporal distribution of the hemodynamic responses between the MCS and UWS groups. For the patients with MCS, significant increases in task-evoked hemodynamic responses occurred during the "YES" questions of the command-driven MI tasks. Importantly, these changes were significantly correlated with their coma-recovery scale-revised (CRS-R) scores. However, for the patients with UWS, no significant changes of the hemodynamic responses were found. Additionally, the results did not show any statistical correlation between the hemodynamic responses and their CRS-R scores. Conclusions: The fNIRS-based command-driven MI tasks can be used as a promising tool for detecting residual awareness in patients with DOC. We hope that the findings and the active paradigm used in this study will provide useful insights into the diagnosis, therapy, and prognosis of this challenging patient population.

Altered large-scale dynamic connectivity patterns in Alzheimer's disease and mild cognitive impairment patients: A machine learning study.

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.

Heterogeneous brain dynamic functional connectivity patterns in first-episode drug-naive patients with major depressive disorder.

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.

Altered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression.

Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method was developed to identify discriminative spatio-temporal states associated with FEDN MDD. Finally, statistical analysis was applied to intrinsic and clinical brain characteristics. Compared with HC, FEDN MDD patients exhibited altered spatio-temporal functional states of the default mode network (DMN), the salience network, a hub network (centered on the dorsolateral prefrontal cortex), and a relatively complex coupling network (visual, DMN, motor-somatosensory and subcortical networks). Multi-kernel classification models to distinguish patients from HC obtained areas under the receiver operating characteristic curves up to 0.80. Classification scores correlated with Hamilton Depression Rating Scale scores and age at MDD onset. FEDN MDD patients had multiple abnormal spatio-temporal functional states. Classification scores derived from these states were related to symptom severity. The assessment of spatio-temporal states may represent a powerful clinical and research tool to distinguish between neuropsychiatric patients and controls.

Assessment of the mental workload of trainee pilots of remotely operated aircraft using functional near-infrared spectroscopy.

BACKGROUND: Operating an aircraft is associated with a large mental workload; however, knowledge of the mental workload of ROV operators is limited. The purpose of this study was to establish a digital system for assessing the mental workload of remotely operated vehicle (ROV) operators using hemodynamic parameters, and compare results of different groups with different experience levels. METHOD: Forty-one trainee pilots performed flight tasks once daily for 5 consecutive days in a flight simulation. Forty-five pilots experienced pilots and 68 experienced drivers were also included. Hemodynamic responses were measured by functional near-infrared spectroscopy (fNIRS). RESULTS: The median duration of peak oxyhemoglobin was 147.13 s (interquartile range [IQR] 21.97, 401.70 s) in the left brain and 180.74 s (IQR 34.37, 432.01 s) in the right brain in the experienced pilot group, and 184.42 s (IQR 3.41, 451.81 s) on day 5 in the left brain and 160.30 s (IQR 2.62, 528.20 s) in the right brain in the trainee group. CONCLUSION: Navigation training reduces peak oxyhemoglobin duration, and may potentially be used as a surrogate marker for mental workload of ROV operators. Peak oxyhemoglobin concentration during s task may allow development of a simplified scheme for optimizing flight performance based on the mental workload of a pilot.

Detecting Residual Awareness in Patients With Prolonged Disorders of Consciousness: An fNIRS Study.

Recent advances in neuroimaging technologies have provided insights into detecting residual consciousness and assessing cognitive abilities in patients with disorders of consciousness (DOC). Functional near-infrared spectroscopy (fNIRS) is non-invasive and portable and can be used for longitudinal bedside monitoring, making it uniquely suited for evaluating brain function in patients with DOC at appropriate spatiotemporal resolutions. In this pilot study, an active command-driven motor imagery (MI) paradigm based on fNIRS was used to detect residual consciousness in patients with prolonged DOC. A support vector machine (SVM) classifier was used to classify yes-or-no responses. The results showed that relatively reliable responses were detected from three out of five patients in a minimally consciousness state (MCS). One of the patients answered all the questions accurately when assessed according to this method. This study confirmed the feasibility of using portable fNIRS technology to detect residual cognitive ability in patients with prolonged DOC by active command-driven motor imagery. We hope to detect the exact level of consciousness in DOC patients who may have a higher level of consciousness.

White matter microstructural differences across major depressive disorder, bipolar disorder and schizophrenia: A tract-based spatial statistics study.

BACKGROUND: White matter abnormalities have been implicated in mental disorders including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ); however, the shared and distinct white matter integrity across mental disorders is still unclear. METHODS: A total of 290 participants (MDD = 85, BD = 42, SZ = 68, and healthy controls = 95) were included in the present study. Tract-based spatial statistics were performed to measure fractional anisotropy (FA) and characterize shared and distinguishing white matter changes across mental disorders. RESULTS: We found that decreased FA converged across MDD, BD and SZ in the body and genu of the corpus callosum, bilateral anterior and posterior corona radiata, and right superior corona radiata. By contrast, diagnosis-specific effect was only found in MDD in the anterior portion of anterior corona radiata. LIMITATIONS: The small and imbalanced sample size, and possible confounding effects of medication. CONCLUSIONS: Our findings suggest that abnormally reduced white matter integrity in the interhemispheric and thalamocortical circuit could be consistently involved in the pathogenesis of MDD, BD and SZ.

Spinal Cord Stimulation Frequency Influences the Hemodynamic Response in Patients with Disorders of Consciousness.

Spinal cord stimulation (SCS) is a promising technique for treating disorders of consciousness (DOCs). However, differences in the spatio-temporal responsiveness of the brain under varied SCS parameters remain unclear. In this pilot study, functional near-infrared spectroscopy was used to measure the hemodynamic responses of 10 DOC patients to different SCS frequencies (5 Hz, 10 Hz, 50 Hz, 70 Hz, and 100 Hz). In the prefrontal cortex, a key area in consciousness circuits, we found significantly increased hemodynamic responses at 70 Hz and 100 Hz, and significantly different hemodynamic responses between 50 Hz and 70 Hz/100 Hz. In addition, the functional connectivity between prefrontal and occipital areas was significantly improved with SCS at 70 Hz. These results demonstrated that SCS modulates the hemodynamic responses and long-range connectivity in a frequency-specific manner (with 70 Hz apparently better), perhaps by improving the cerebral blood volume and information transmission through the reticular formation-thalamus-cortex pathway.

Influence of inter-stimulus interval of spinal cord stimulation in patients with disorders of consciousness: A preliminary functional near-infrared spectroscopy study.

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.

Hemispheric differences in electrical and hemodynamic responses during hemifield visual stimulation with graded contrasts.

A multimodal neuroimaging technique based on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) was used with horizontal hemifield visual stimuli with graded contrasts to investigate the retinotopic mapping more fully as well as to explore hemispheric differences in neuronal activity, the hemodynamic response, and the neurovascular coupling relationship in the visual cortex. The fNIRS results showed the expected activation over the contralateral hemisphere for both the left and right hemifield visual stimulations. However, the EEG results presented a paradoxical lateralization, with the maximal response located over the ipsilateral hemisphere but with the polarity inversed components located over the contralateral hemisphere. Our results suggest that the polarity inversion as well as the latency advantage over the contralateral hemisphere cause the amplitude of the VEP over the contralateral hemisphere to be smaller than that over the ipsilateral hemisphere. Both the neuronal and hemodynamic responses changed logarithmically with the level of contrast in the hemifield visual stimulations. Moreover, the amplitudes and latencies of the visual evoked potentials (VEPs) were linearly correlated with the hemodynamic responses despite differences in the slopes.

Correlation between electrical and hemodynamic responses during visual stimulation with graded contrasts.

Brain functional activity involves complex cellular, metabolic, and vascular chain reactions, making it difficult to comprehend. Electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) have been combined into a multimodal neuroimaging method that captures both electrophysiological and hemodynamic information to explore the spatiotemporal characteristics of brain activity. Because of the significance of visually evoked functional activity in clinical applications, numerous studies have explored the amplitude of the visual evoked potential (VEP) to clarify its relationship with the hemodynamic response. However, relatively few studies have investigated the influence of latency, which has been frequently used to diagnose visual diseases, on the hemodynamic response. Moreover, because the latency and the amplitude of VEPs have different roles in coding visual information, investigating the relationship between latency and the hemodynamic response should be helpful. In this study, checkerboard reversal tasks with graded contrasts were used to evoke visual functional activity. Both EEG and fNIRS were employed to investigate the relationship between neuronal electrophysiological activities and the hemodynamic responses. The VEP amplitudes were linearly correlated with the hemodynamic response, but the VEP latency showed a negative linear correlation with the hemodynamic response.