Hemodynamic Activity Research Articles

Topographic gradients of intrinsic dynamics across neocortex.

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns of neural activity throughout the human brain. Applying massive temporal feature extraction to regional haemodynamic activity, we systematically estimate over 6000 statistical properties of individual brain regions' time-series across the neocortex. We identify two robust spatial gradients of intrinsic dynamics, one spanning a ventromedial-dorsolateral axis and dominated by measures of signal autocorrelation, and the other spanning a unimodal-transmodal axis and dominated by measures of dynamic range. These gradients reflect spatial patterns of gene expression, intracortical myelin and cortical thickness, as well as structural and functional network embedding. Importantly, these gradients are correlated with patterns of meta-analytic functional activation, differentiating cognitive versus affective processing and sensory versus higher-order cognitive processing. Altogether, these findings demonstrate a link between microscale and macroscale architecture, intrinsic dynamics, and cognition.

Differentiating between bipolar and unipolar depression using prefrontal activation patterns: Promising results from functional near infrared spectroscopy (fNIRS) findings

BackgroundBipolar depression (BD) is a unique, severe and prevalent mental illness that shares many similarities in symptoms with unipolar depression (UD). Improving precision of their diagnoses would enhance treatment outcome and prognosis for both conditions. This study aims to provide evidence from functional Near-Infrared Spectroscopy (fNIRS) as a potential tool to differentiate UD and BD based on their differences in hemodynamic change in the prefrontal cortex during verbal fluency tasks (VFT). MethodsWe enrolled 179 participants with clinically confirmed diagnoses, including 69 UD patients, 68 BD patients and 42 healthy controls(HC). Every participant was assessed using a 45-channel fNIRS and various clinical scales. FindingsCompared with HC, region-specific fNIR leads show UD patients had significant lower hemodynamic activation in 4 particular pre-frontal regions: 1) the left dorsolateral prefrontal cortex (DLPFC), 2) orbitofrontal cortex (OFC), 3) bilateral ventrolateral prefrontal cortex (VLPFC) and 4) left inferior frontal gyrus (IFG). In contrast, BD vs. HC comparisons showed only significant lower hemodynamic activation in the LIFG area. Furthermore, compared to BD patients, UD patients showed decreased hemodynamic activation changes in the VLPFC region. ConclusionOur results show significant frontal lobe activation pattern differences between UD and BD groups. fNIRS can be a potential tool to increase diagnostic precision for these conditions. In particular, the VLPFC area holds promise to be a useful site for such differentiation for further investigations.

Reduced functional connectivity in the prefrontal cortex of elderly catatonia patients: A longitudinal study using functional near-infrared spectroscopy

Catatonia is a syndrome that manifests in patients with mental disorders and general medical conditions. However, functional changes to the brain that cause catatonia remain unknown. In the present study, we used functional near-infrared spectroscopy (fNIRS) to assess spontaneous hemodynamic activities in the brain at the times of onset and resolution of catatonic symptoms in patients with catatonia. We used 22-channel and 49-channel fNIRS to examine hemodynamic activities in the prefrontal cortex (PFC), and both frontal and parietal cortices, respectively. A total of ten patients who were diagnosed with catatonia were included in the study. Resting state measurements were taken for five minutes at the time of the onset and resolution of catatonic symptoms. Analyses were performed for the prefrontal region and the motor cortex within the parietal-frontal region of the brain. Functional connectivity between the cerebral hemispheres was evaluated systematically based on spontaneous oscillation of Δ[HbO2]. In the PFC, the resting state functional connectivity (RSFC) was significantly lower in the catatonic state than in the eyes-closed non-catatonic state (p = 0.047). The study demonstrated that the RSFC in the PFC, measured using fNIRS, may be an objective indicator of the change in catatonic symptoms.

Neural Correlates of Age-Related Changes in Precise Grip Force Regulation: A Combined EEG-fNIRS Study.

Motor control is associated with suppression of oscillatory activity in alpha (8–12 Hz) and beta (12–30 Hz) ranges and elevation of oxygenated hemoglobin levels in motor-cortical areas. Aging leads to changes in oscillatory and hemodynamic brain activity and impairments in motor control. However, the relationship between age-related changes in motor control and brain activity is not yet fully understood. Therefore, this study aimed to investigate age-related and task-complexity-related changes in grip force control and the underlying oscillatory and hemodynamic activity. Sixteen younger [age (mean ± SD) = 25.4 ± 1.9, 20–30 years] and 16 older (age = 56.7 ± 4.7, 50–70 years) healthy men were asked to use a power grip to perform six trials each of easy and complex force tracking tasks (FTTs) with their right dominant hand in a randomized within-subject design. Grip force control was assessed using a sensor-based device. Brain activity in premotor and primary motor areas of both hemispheres was assessed by electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Older adults showed significantly higher inaccuracies and higher hemodynamic activity in both FTTs than did young adults. Correlations between grip force control owing to task complexity and beta activity were different in the contralateral premotor cortex (PMC) between younger and older adults. Collectively, these findings suggest that aging leads to impairment of grip force control and an increase in hemodynamic activity independent of task complexity. EEG beta oscillations may represent a task-specific neurophysiological marker for age-related decline in complex grip force control and its underlying compensation strategies. Further EEG-fNIRS studies are necessary to determine neurophysiological markers of dysfunctions underlying age-related motor disabilities for the improvement of individual diagnosis and therapeutic approaches.

Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS.

Alzheimer’s disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey–Osterrieth complex figure and Raven’s progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study.

Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.

Multispectral diffuse reflectance can discriminate blood vessels and bleeding during neurosurgery based on low-frequency hemodynamics.

.Significance: The practicality of optical methods detecting tissue optical contrast (absorption, elastic and inelastic scattering, fluorescence) for surgical guidance is limited by interferences from blood pooling and the resulting partial or complete inability to interrogate cortex and blood vessels.Aim: A multispectral diffuse reflectance technique was developed for intraoperative brain imaging of hemodynamic activity to automatically discriminate blood vessels, cortex, and bleeding at the brain surface.Approach: A manual segmentation of blood pooling, cortex, and vessels allowed the identification of a frequency range in hemoglobin concentration variations associated with high optical signal in blood vessels and cortex but not in bleeding. Reflectance spectra were then used to automatically segment areas with and without hemodynamic activity as well as to discriminate blood from cortical areas.Results: The frequency range associated with low-frequency hemodynamics and respiratory rate (0.03 to 0.3 Hz) exhibits the largest differences in signal amplitudes for bleeding, blood vessels, and cortex. A segmentation technique based on simulated reflectance spectra initially allowed discrimination of blood (bleeding and vessels) from cortical tissue. Then, a threshold applied to the low-frequency components from deoxyhemoglobin allowed the segmentation of bleeding from vessels. A study on the minimum acquisition time needed to discriminate all three components determined that was necessary to detect changes in the low-frequency range. Other frequency ranges such as heartbeat (1 to 1.7 Hz) can be used to reduce the acquisition time to few seconds but would necessitate optimizing instrumentation to ensure larger signal-to-noise ratios are achieved.Conclusions: A method based on multispectral reflectance signals and low-frequency hemoglobin concentration changes can be used to distinguish bleeding, blood vessels, and cortex. This could be integrated into fiber optic probes to enhance signal specificity by providing users an indication of whether measurements are corrupted by blood pooling, an important confounding factor in biomedical optics applied to surgery.

Prefrontal haemodynamics based classification of inter‐individual working memory difference

This Letter illustrates prefrontal haemodynamics as a neurovascular basis of inter-personal working memory differences. A functional near-infrared spectroscopy with sampling frequency ∼2 Hz is used to record the blood oxyhaemoglobin and deoxyhaemoglobin signals from 19 subjects engaged in working memory task of encoding and retrieval of ten symbol-meaning association learning. The individual difference in working memory performance is classified by supervised learning-based linear discriminant analysis and ensemble classifiers. Prior to the classification approach, individual performance is labelled as high, moderate and low on the basis of the performance index. The spontaneous haemodynamic activity and task-evoked responses are marked as background and foreground signals, respectively, which are scaled by means of stream-independent and stream-dependent models. The classifiers' performance shows that the stream-dependent model-based feature construction-classification improves classification accuracy to a major extent compared to the stream-independent model and no gain model. To understand the neurovascular basis of the inter-individual performance difference, diffused voxel plots are constructed. The voxel plots showed that concurrent activation of orbitofrontal and dorsolateral prefrontal cortex could have a possible association with persons' higher working memory performance.

An adaptive fractal model for sublingual microcirculation

The hemodynamic conditions and partial pressure of oxygen in microcirculation generally indicate the status of tissue perfusion, which provides essential information for the assessment and treatment of critical diseases such as sepsis. The human tongue is known to have abundant microcirculation and is an ideal window to observe the microcirculation. At present, the monitoring of sublingual microcirculation is mostly achieved using handheld vital microscopy (HVM). Microcirculation is organized and works as a network. However, HVM can obtain only limited view of few vessels and is not able to acquire information regarding the entire network. In this work, we proposed a method to construct a mathematical network model of sublingual microcirculation to solve the problems. The proposed method is based on fractal analysis to model and simulate the hemodynamic and functional activities of sublingual microcirculation. Specifically, the HVM technology is used to obtain the partial morphological and hemodynamic data of sublingual microcirculation, and fractal analysis is applied thereafter to establish the hemodynamic model of the network based on the data from few vessels. Further, the adaptive regulation mechanism of microcirculation is introduced to enhance the performance of the model. The model was validated by the experimental data and the results are consistent with the characteristics of microcirculation. The work demonstrates the potential of the proposed method in sublingual microcirculation research and for the further assessment of tissue perfusion.

Shedding Light on the Effects of Moderate Acute Exercise on Working Memory Performance in Healthy Older Adults: An fNIRS Study.

Numerous studies have reported the beneficial effects of acute exercise on executive functions. Less is known, however, about the effects of exercise on working memory as one subcomponent of executive functions and about its effects on older adults. We investigated the effects of acute moderate-intensity exercise on working memory performance, the respective cortical hemodynamic activation patterns, and the development and persistence of such effects in healthy older adults. Forty-four participants (M: 69.18 years ± 3.92; 21 females) performed a letter 2-back task before and at three time points after (post 15 min, post 30 min, and post 45 min) either listening to an audiobook or exercising (15 min; 50% VO2-peak). Functional near-infrared spectroscopy (fNIRS) was used to assess cortical hemodynamic activation and brain-behavior correlations in the fronto-parietal working memory network. Overall, we found no group differences for working memory performance. However, only within the experimental group, 2-back performance was enhanced 15 min and 45 min post-exercise. Furthermore, 15 min post-exercise frontal activation predicted working memory performance, regardless of group. In sum, our results indicate slight beneficial effects of acute moderate-intensity exercise on working memory performance in healthy older adults. Findings are discussed in light of the cognitive aging process and moderators affecting the exercise-cognition relationship.

Cap-Based Transcranial Optical Tomography in an Awake Infant.

Although Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI) is widely used to examine brain function in adults, the need for general anesthesia limits its practical utility in infants and small children. Functional Near-Infrared Spectroscopy - Diffuse Optical Tomography (fNIRS-DOT) imaging promises to be an alternative brain network imaging technique. Yet current versions of continuous-wave fNIRS-DOT systems are restricted to the cortical surface measurements and do not probe deep structures that are frequently injured especially in premature infants. Herein we report a transcranial near infrared optical imaging system, called Cap-based Transcranial Optical Tomography (CTOT) able to image whole brain hemodynamic activity with 3 seconds of data acquisition time. We show the system is capable of whole brain oxygenation mapping in an awake child, and that tomographically reconstructed static CTOT-derived oxy- and deoxygenated blood volumes are spatially correlated with the time-averaged BOLD fMRI volumes. By removing time bottlenecks in the current system, dynamic CTOT mapping should be possible, which would then enable evaluation of functional connectivity in awake infants.

A near-infrared genetically encoded calcium indicator for in vivo imaging.

While calcium imaging has become a mainstay of modern neuroscience, the spectral properties of current fluorescent calcium indicators limit deep tissue imaging as well as simultaneous use with other probes. Using two monomeric near-infrared fluorescent proteins, we engineered a near-infrared FRET-based genetically encoded calcium indicator (iGECI). iGECI exhibits high brightness, high photostability, and up to 600% increase in fluorescence response to calcium. In dissociated neurons, iGECI detects spontaneous neuronal activity, and electrically and optogenetically induced firing. We validated iGECI performance up to a depth of almost 400 μm in acute brain slices using one-photon light-sheet imaging. Applying hybrid photoacoustic and fluorescence microscopy, we simultaneously monitored neuronal and hemodynamic activities in the mouse brain through an intact skull, with ~3 μm lateral and ~25–50 μm axial resolution. Using two-photon imaging, we detected evoked and spontaneous neuronal activity in the mouse visual cortex, with fluorescence changes of up to 25%. iGECI allows biosensors and optogenetic actuators to be multiplexed without spectral crosstalk.

A Platform for Brain-wide Volumetric Functional Ultrasound Imaging and Analysis of Circuit Dynamics in Awake Mice

Imaging large-scale circuit dynamics is crucial to understanding brain function, but most techniques have a limited depth of field. Here, we describe volumetric functional ultrasound imaging (vfUSI), a platform for brain-wide vfUSI of hemodynamic activity in awake head-fixed mice. We combined a high-frequency 1,024-channel 2D-array transducer with advanced multiplexing and high-performance computing for real-time 3D power Doppler imaging at a high spatiotemporal resolution (220× 280× 175μm3, up to 6Hz). We developed a standardized software pipeline for registration, segmentation, and temporal analysis in 268 individual brain regions based on the Allen Mouse Common Coordinate Framework. We demonstrated the high sensitivity of vfUSI under multiple experimental conditions, and we successfully imaged stimulus-evoked activity when only a few trials were averaged. We also mapped neural circuits invivo across the whole brain during optogenetic activation of specific cell types. Moreover, we identified the sequential activation of sensory-motor networks during a grasping water-droplet task.

Task-related brain activity and functional connectivity in upper limb dystonia: a functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) study.

.Significance: Dystonia is a dynamic and complex disorder. Real-time analysis of brain activity during motor tasks may increase our knowledge on its pathophysiology. Functional near-infrared spectroscopy (fNIRS) is a noninvasive method that enables the measurement of cortical hemodynamic activity in unconstrained environments.Aim: We aimed to explore the feasibility of using fNIRS for the study of task-related brain activity in dystonia. Task-related functional magnetic resonance imaging (fMRI) and resting-state functional connectivity were also analyzed.Approach: Patients with idiopathic right-upper limb dystonia and controls were assessed through nonsimultaneous fMRI and fNIRS during a finger-tapping task. Seed-based connectivity analysis of resting-state fMRI was performed in both groups.Results: The fMRI results suggest nonspecific activation of the cerebellum and occipital lobe in dystonia patients during the finger-tapping task with the affected hand. Moreover, fNIRS data show lower activation in terms of oxyhemoglobin and total hemoglobin in the frontal, ipsilateral cortex, and somatosensory areas during this task. In dystonia, both fMRI and fNIRS data resulted in hypoactivation of the frontal cortex during finger tapping with both hands simultaneously. Resting-state functional connectivity analysis suggests that the cerebellar somatomotor network in dystonia has an increased correlation with the medial prefrontal cortex and the paracingulate gyrus.Conclusions: These data suggest that unbalanced activation of the cerebellum, somatosensory, and frontal cortical areas are associated with dystonia. To our knowledge, this is the first study using fNIRS to explore the pathophysiology of dystonia. We show that fNIRS and fMRI are complementary methods and highlight the potential of fNIRS for the study of dystonia and other movement disorders as it can overcome movement restrictions, enabling experiments in more naturalistic conditions.

Characterisation of Haemodynamic Activity in Resting State Networks by Fractal Analysis.

Intrinsic brain activity is organized into large-scale networks displaying specific structural-functional architecture, known as resting-state networks (RSNs). RSNs reflect complex neurophysiological processes and interactions, and have a central role in distinct sensory and cognitive functions, making it crucial to understand and quantify their anatomical and functional properties. Fractal dimension (FD) provides a parsimonious way of summarizing self-similarity over different spatial and temporal scales but despite its suitability for functional magnetic resonance imaging (fMRI) signal analysis its ability to characterize and investigate RSNs is poorly understood. We used FD in a large sample of healthy participants to differentiate fMRI RSNs and examine how the FD property of RSNs is linked with their functional roles. We identified two clusters of RSNs, one mainly consisting of sensory networks (C1, including auditory, sensorimotor and visual networks) and the other more related to higher cognitive (HCN) functions (C2, including dorsal default mode network and fronto-parietal networks). These clusters were defined in a completely data-driven manner using hierarchical clustering, suggesting that quantification of Blood Oxygen Level Dependent (BOLD) signal complexity with FD is able to characterize meaningful physiological and functional variability. Understanding the mechanisms underlying functional RSNs, and developing tools to study their signal properties, is essential for assessing specific brain alterations and FD could potentially be used for the early detection and treatment of neurological disorders.

A Neurocognitive Comparison of Listening to Academic Lectures and Natural Sounds: Implications for Test Validity

ABSTRACT With the advent of new technologies, assessment research has adopted technology-based methods to investigate test validity. This study investigated the neurocognitive processes involved in an academic listening comprehension test, using a biometric technique called functional near-infrared spectroscopy (fNIRS). Sixteen right-handed university students completed two tasks: (1) a linguistic task that involved listening to a mini-lecture (i.e., Listening condition) and answering of questions (i.e., Questions condition) and (2) a non-linguistic task that involved listening to a variety of natural sounds and animal vocalizations (i.e., Sounds condition). The hemodynamic activity in three left brain regions was measured: the inferior frontal gyrus (IFG), dorsomedial prefrontal cortex (dmPFC), and posterior middle temporal gyrus (pMTG). The Listening condition induced higher activity in the IFG and pMTG than the Sounds condition. Although not statistically significant, the activity in the dmPFC was higher during the Listening condition than in the Sounds conditions. The IFG was also significantly more active during the Listening condition than in the Questions condition. Although a significant gender difference was observed in listening comprehension test scores, there was no difference in brain activity (across the IFG, dmPFC, and pMTG) between male and female participants. The implications for test validity are discussed.

Watching video of discrete maneuvers yields better action memory and greater activation in the middle temporal gyrus in half-pipe snowboarding athletes

Although motor performance training often involves action observation, it has been controversial whether individual aesthetic sport athletes benefit more from watching videos of discrete maneuvers (DMs) or continuous runs (CRs). In the present study, half-pipe snowboarding athletes completed a visual 2-back task with DM and CR conditions. To explore the neural mechanisms of action memory processing, brain hemodynamic activity during the task was monitored with functional near-infrared spectroscopy (fNIRS). Compared to watching CR videos, watching DM videos tended to yield better action memory performance and greater activation in the middle temporal gyrus to these athletes, suggesting that watching DM videos may have a tendency to improve action memory more effectively. Evidence of two pathways underlying half-pipe snowboarding action processing was obtained. Watching of CR videos and watching of DM videos might be associated with activation of more sensorimotor regions and more semantic regions, respectively, during memory consolidation.

Gender Differences and Unfairness Processing during Economic and Moral Decision-Making: A fNIRS Study.

Decisional conflicts have been investigated with social decision-making tasks, which represent good models to elicit social and emotional dynamics, including fairness perception. To explore these issues, we created two modified versions of the UG framed within an economic vs. a moral context that included two kinds of unfair offers: advantageous (upside, U) or disadvantageous (downside, D) from the responder’s perspective, and vice-versa for the proponent. The hemodynamic activity of 36 participants, 20 females and 16 males, was continuously recorded with fNIRS to investigate the presence of general or specific circuits between the different experimental conditions. Results showed that disadvantageous offers (D) are associated with an increased widespread cortical activation. Furthermore, we found that advantageous moral choices at the expense of others (U) were related to the activation of the right prefrontal cortex. Finally, we found gender-related differences in brain activations in the different frameworks. In particular, the DLPFC was recruited by females during the economic task, and by males during the moral frame. In conclusion, the present study confirmed and expanded previous data about the role of the prefrontal cortices in decision-making, suggesting the need for further studies to understand better the different prefrontal networks serving moral and economic decisions also considering gender-related differences.

Computational methods of brain-to-brain coupling during human interaction

Hyperscanning—the simultaneous recording of hemodynamic or neuroelectric activity of the brain——is the new technology to directly observe the brain communication between individuals. Since the publication of the first hyperscanning study in 2002, it has developed rapidly in the past decade. Brain-to-brain coupling (BBC) technology of human interaction was widely used in the research of action coordination, cooperative game, classroom teaching and other interactive tasks, which involved the use of functional magnetic resonance imaging (fMRI), Electroencephalogram (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS) and other neuroimaging technologies. In addition, hyperscanning research experienced a leap from pseudo-interaction to real interaction, a leap from a strictly controlled laboratory paradigm to the “field research” paradigm in nature situations. Based on the differentiation and analysis of the core concepts such as coupling and synchronization, taking the development of time and technology as the main line, this paper reviewed the common BBC indicators and their application conditions, introduced the related theories and forecasted the future research direction of BBC. In hyperscanning study, BBC refers to the interaction and influence of two or more brains, or between two or more brain regions within a single brain, while the inter-brain synchronization (IBS) refers to the consistency (relative stability) in frequency, phase, and other characteristics of signals from different brain or different regions of the brain. Thus, the similarities and differences between hyperscanning, BBC and IBS can be summarized as follows: Hyperscanning is the technique of recording the neural activity of two or more brains simultaneously. BBC refers to the interaction or interaction between two or more brains. BBC sometimes manifests as IBS, the degree of IBS can represent the strength of BBC in this case, but BBC is not the same as IBS: (1) In addition to IBS, BBC can also be manifested as functional connections and interactions between the brains; (2) due to the possibility of pseudo-synchronization, the occurrence of IBS does not mean that there must be BBC. In the field of physics and electronic engineering, the characteristics of a signal can be described by multiple indicators such as amplitude, period, frequency and phase. Accordingly, neurologic studies have found that brain activity induced by external events may take the form of phase response, frequency response, amplitude response, and production of new components. Therefore, it is not surprising that many different indicators are used to characterize the strength of BBC in existing hyperscanning studies. These indicators including the circular correlation coefficient (CCorr), wavelet transform coherence (WTC), directed coherence, phase-locking value (PLV), the coupling indexes based on the event-related potentials (ERP) such as the latency difference and the amplitude difference, the coupling indexes based on the Graph Theory such as the shortest path length, global efficiency, local efficiency, divisibility, modularity, small-word network. Through the review, we found the following three issues deserve the attention of the future hyperscanning research. Firstly, as different coupling indicators have different characteristics and applicable conditions, we suggest that the selection of indicators should be based on specific research methods, technical equipment and research problems. There are no best indicators, only the most suitable ones. Secondly, the existing theory of BBC is not complete, integrating existing theories and proposing theories with stronger explanatory power should be the focus of future hyperscanning theory research. Thirdly, there are many forms of coupling in neural processing, and the meaning of coupling is different in different forms. Therefore, it is necessary to take into account the comprehensive consideration of the specific research task type, interactive mode and other factors when discussing the significance of coupling.

Machine learning techniques for computer-based decision systems in the operating theatre: application to analgesia delivery

Abstract This work focuses on the application of machine learning techniques to assist the clinicians in the administration of analgesic drug during general anaesthesia. Specifically, the main objective is to propose the basis of an intelligent system capable of making decisions to guide the opioid dose changes based on a new nociception monitor, the analgesia nociception index (ANI). Clinical data were obtained from 15 patients undergoing cholecystectomy surgery. By means of an off-line study, machine learning techniques were applied to analyse the possible relationship between the analgesic dose changes performed by the physician due to the hemodynamic activity of the patients and the evolution of the ANI. After training different classifiers and testing the results under cross validation, a preliminary relationship between the evolution of ANI and the dosage of remifentanil was found. These results evidence the potential of the ANI as a promising index to guide the infusion of analgesia.