Headache-related circuits and high frequencies evaluated by EEG,MRI, PET as potential biomarkers to differentiate chronic and episodic migraine: Evidence from a systematic review

BackgroundThe diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number of days of migraine headache per month. Thus, we consider it timely to perform a systematic review to search for physiological evidence from functional activity (as opposed to anatomical structure) for the differentiation between CM and EM, as well as potential functional biomarkers. For this purpose, Web of Science (WoS), Scopus, and PubMed databases were screened.FindingsAmong the 24 studies included in this review, most of them (22) reported statistically significant differences between the groups of CM and EM. This finding is consistent regardless of brain activity acquisition modality, ictal stage, and recording condition for a wide variety of analyses. That speaks for a supramodal and domain-general differences between CM and EM that goes beyond a differentiation based on the days of migraine per month. Together, the reviewed studies demonstrates that electro- and magneto-physiological brain activity (M/EEG), as well as neurovascular and metabolic recordings from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), show characteristic patterns that allow to differentiate between CM and EM groups.ConclusionsAlthough a clear brain activity-based biomarker has not yet been identified to distinguish these subtypes of migraine, research is approaching headache specialists to a migraine diagnosis based not only on symptoms and signs reported by patients. Future studies based on M/EEG should pay special attention to the brain activity in medium and fast frequency bands, mainly the beta band. On the other hand, fMRI and PET studies should focus on neural circuits and regions related to pain and emotional processing.     

Cardiac sympathetic-vagal activity initiates a functional brain–body response to emotional arousal

A century-long debate on bodily states and emotions persists. While the involvement of bodily activity in emotion physiology is widely recognized, the specificity and causal role of such activity related to brain dynamics has not yet been demonstrated. We hypothesize that the peripheral neural control on cardiovascular activity prompts and sustains brain dynamics during an emotional experience, so these afferent inputs are processed by the brain by triggering a concurrent efferent information transfer to the body. To this end, we investigated the functional brain–heart interplay under emotion elicitation in publicly available data from 62 healthy subjects using a computational model based on synthetic data generation of electroencephalography and electrocardiography signals. Our findings show that sympathovagal activity plays a leading and causal role in initiating the emotional response, in which ascending modulations from vagal activity precede neural dynamics and correlate to the reported level of arousal. The subsequent dynamic interplay observed between the central and autonomic nervous systems sustains the processing of emotional arousal. These findings should be particularly revealing for the psychophysiology and neuroscience of emotions.

“What Is an Emotion?” by William James (1), published more than a century ago, started the scientific debate on the nature of emotions. However, a shared and definitive theory of emotions is not in place yet, and the very definition of emotions and their nature is still a matter of debate. While more “classical” theories point to emotions as “the functional states of the brain that provide causal explanations of certain complex behaviors—like evading a predator or attacking prey” (2), other theories suggest how they are constructions of the world, not reactions to it (3). Namely, emotions are internal states constructed on the basis of previous experiences as predictive schemes to react to external stimuli.The role of bodily activity in emotions is often questioned. Despite the vast literature showing bodily correlates with emotions, a long-lasting debate about the relationship between bodily states and emotions persists (4). For instance, a feeling is defined as the subjective metarepresentation and labeling of physiological changes (such as an increase in heart rate, the increase of blood pressure, or changes in peristalsis) (5) that are strictly related to the body state on the one hand and to emotions on the other. To this extent, emotions are complex psychological phenomena in which feelings are interpreted and labeled. In a particular psychopathological condition known as alexithymia, individuals experience difficulties in experiencing and understanding emotions to various degrees (6). Indeed, some of these patients can perceive the physical changes connected to a feeling but are unable to label it as emotion, so that emotional experience is described only as its physical counterpart [e.g., described an experience as “I have my heart beating too fast” instead of “I’m fearful” (7)]. From a biological point of view the way in which physical changes become feelings and emotions is based on the interplay between the central and the autonomic nervous systems.The central nervous system (CNS) communicates with the autonomic nervous system (ANS) through interoceptive neural circuits that contribute to physiological functions beyond homeostatic control, from the emotional experience and the genesis of feelings (8) to decision making (9, 10). The debate about the role of the ANS in emotions can be condensed into two views: specificity or causation (4). The specificity view is related to the James–Lange theory, which states that bodily responses precede emotions’ central processing, meaning that bodily states would be a response to the environment, followed by an interpretation carried out by the CNS that would result in the feeling felt. However, causation theories represent an updated view of the James–Lange theory, suggesting that peripheral changes influence the conscious emotional experience; from a biological point of view this may reflect the fact that autonomic nervous signals from the body do influence perceptual activity in the brain (11, 12). In this regard, subjective perception may be influenced or shaped by ascending communication from visceral inputs to the brain (13–15).Functional models of CNS and ANS interplay have described bidirectional dynamics in emotions (16–18). In particular, the functional brain–heart interplay (BHI) involves brain structures that comprise the central autonomic network (CAN), which has been described as being in charge of autonomic control (19, 20). Moreover, the default mode network (DMN) has been found to be involved in autonomic control (21) and tasks of self-related cognition and interoception (22, 23), suggesting that the DMN participates in both ascending and descending communications with the heart. Finally, the constructed emotion theory suggests how DMN together with other intrinsic networks is crucial in the genesis of emotion and emotional experience (3).Psychophysiological studies have uncovered several correlates of different autonomic signals in the brain during emotional experiences (24–27). To understand these correlations and the functional interactions between the heart and brain, various signal processing methods have been proposed to investigate functional BHI through noninvasive recordings (28). The study of emotions using these methods comprises the analysis of heartbeat-evoked potentials (29), nonlinear couplings (30), and information transfer modeling (31). However, the causative role of bodily inputs remains unknown (4) and, more specifically, the temporal and causal links between cortical and peripheral neural dynamics in both ascending and descending directions, i.e., from the brain to the body and from the body to the brain, are still to be clarified.In this study, we take a step forward in answering these scientific questions and investigate whether peripheral neural dynamics play a causal role in the genesis of emotions. We applied a mathematical model of functional BHI based on synthetic data generation (SDG) (32), estimating the directionality of the functional interplay using simultaneous electroencephalography (EEG) and electrocardiography (ECG) recordings gathered from healthy subjects undergoing emotion elicitations with video clips, the publicly available DEAP and MAHNOB datasets (33, 34). ECG series were analyzed to derive heart-rate variability (HRV) series, which result from the concurrent activity of the sympathetic and parasympathetic (vagal) branches of the ANS acting to regulate the heartbeat. We hypothesize that, from a neurobiological point of view, feelings and subsequent emotional experiences arise from the mutual interplay between brain and body, particularly in which the CNS integrates the afferent ANS information outflow, namely from-heart-to-brain interplay, which actually triggers a cascade of cortical neural activations that, in turn, modulate directed neural control onto the heart, namely from brain-to-heart interplay.     

航天警戒作业模拟及脑力负荷评价系统的设计与实现

研制了一套用于中国航天员心理、生理状态检测及评价的应用系统。该系统使用2台计算机,合同完成模拟航天警戒任务状态下多项心理指标的检测与评价以及不同心理刺激条件下自发脑电和诱发脑电的检测与处理功能。用于研究通过听觉、视觉等模拟刺激通道在不同应激条件和工作负荷下,人员的生理和心理状态、工作绩效的变化及评价方法,研究绩效评价方面新的综合方法与指标,还可用于心理负荷能力训练,提高心理负荷能力和工作绩效水平。     

脑-机接口技术进展与挑战

近几年来,脑-机接口的研究逐渐形成了热点,引起了世界科学家的广泛关注.非侵入式脑-机接口正向临床实用化方向发展.植入式脑-机接口目前的研究多以动物做实验,实现了对光标、游戏杆、机械臂、运动小车等的控制.它们的发展有赖于神经科学、工程学、心理学、计算机和康复学等各交叉学科专家间的密切合作.这种全新的通信技术可望为那些不能使用常规通信手段的残疾患者提供与外界进行交流的途径.     

Sleep-Specific Processing of Auditory Stimuli Is Reflected by Alpha and Sigma Oscillations

Recent research revealed a surprisingly large range of cognitive operations to be preserved during sleep in humans. The new challenge is therefore to understand functions and mechanisms of processes, which so far have been mainly investigated in awake subjects. The current study focuses on dynamic changes of brain oscillations and connectivity patterns in response to environmental stimulation during non-REM sleep. Our results indicate that aurally presented names were processed and neuronally differentiated across the wake-sleep spectrum. Simultaneously recorded EEG and MEG signals revealed two distinct clusters of oscillatory power increase in response to the stimuli: (1) vigilance state-independent θ synchronization occurring immediately after stimulus onset, followed by (2) sleep-specific α/σ synchronization peaking after stimulus offset. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep, and work toward a unified theory of brain rhythms and their functions during sleep.SIGNIFICANCE STATEMENT Previous research has revealed (residual) capacity of the sleeping human brain to interact with the environment. How sensory processing is realized by the neural assemblies in different stages of sleep is however unclear. To tackle this question, we examined simultaneously recorded MEG and EEG data. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep. In contrast to versatile θ band response that reflected early stimulus processing step, succeeding α and σ band activity was sensitive to the saliency of the incoming information, and contingent on the sleep stage. Our findings suggest that the specific reorganization of mechanisms involved in later stages of sensory processing takes place upon falling asleep.     

Beyond broadband: Towards a spectral decomposition of electroencephalography microstates

Originally applied to alpha oscillations in the 1970s, microstate (MS) analysis has since been used to decompose mainly broadband electroencephalogram (EEG) signals (e.g., 1–40 Hz). We hypothesised that MS decomposition within separate, narrow frequency bands could provide more fine‐grained information for capturing the spatio‐temporal complexity of multichannel EEG. In this study, using a large open‐access dataset (n = 203), we first filtered EEG recordings into four classical frequency bands (delta, theta, alpha and beta) and thereafter compared their individual MS segmentations using mutual information as well as traditional MS measures (e.g., mean duration and time coverage). Firstly, we confirmed that MS topographies were spatially equivalent across all frequencies, matching the canonical broadband maps (A, B, C, D and C′). Interestingly, however, we observed strong informational independence of MS temporal sequences between spectral bands, together with significant divergence in traditional MS measures. For example, relative to broadband, alpha/beta band dynamics displayed greater time coverage of maps A and B, while map D was more prevalent in delta/theta bands. Moreover, using a frequency‐specific MS taxonomy (e.g., ϴA and αC), we were able to predict the eyes‐open versus eyes‐closed behavioural state significantly better using alpha‐band MS features compared with broadband ones (80 vs. 73% accuracy). Overall, our findings demonstrate the value and validity of spectrally specific MS analyses, which may prove useful for identifying new neural mechanisms in fundamental research and/or for biomarker discovery in clinical populations.     

Frequency‐dependent modulation of neural oscillations across the gait cycle

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.     

Inter-brain synchronization is weakened by the introduction of external punishment

Punishment is a popular institution to enforce social norms in human society. However, how the punishment institution impacts the inter-brain neural signatures of two-person social interactions is still an open question. By performing electroencephalography recording of brain activity in two interacting parties as they simultaneously played both the revised repeated ultimatum game (rrUG) and the revised repeated dictator game (rrDG), this study focused on exploring how the introduction of external punishment influences inter-brain synchronization between the two parties. The data showed a significant negative effect of external punishment on inter-brain synchronization, with greater inter-brain synchronization observed in the rrDG than in the rrUG. We proposed a possible mechanism underlying this result. In the rrDG, the similar moral motivation of both proposers and responders results in inter-brain synchronization between them. However, in the rrUG, the introduction of external punishment crowds out the intrinsic moral motivation of the proposers, thereby undermining the inter-brain synchronization. Moreover, we found a significant positive correlation between the rejection rate from responders for disadvantageous inequal offer and inter-brain synchronization in the rrDG. These findings contribute to understanding the negative effect of punishment institution and shed light on the inter-brain mechanism underlying social interaction.     

缺陷型与非缺陷型精神分裂症的脑电图分析

目的 研究缺陷型、非缺陷型精神分裂症患者在脑电图(EEG)方面的差异。方法 采用国产ND-82B型八道EEG机对69例精神分裂症患者进行标准EEG描记,并对结果进行分析。结果 缺陷型精神分裂症的EEG异常率明显高于非缺陷型精神分裂症,二者有显著性差异(P<0.01)。结论 提示缺陷型与非缺陷型患者相比,有更明显的病理性生物学基础。