Mapping of neural activity produced by thermal pain in the healthy human spinal cord and brain stem: a functional magnetic resonance imaging study

Functional magnetic resonance imaging (fMRI) has greatly advanced our current understanding of pain, although most studies to date have focused on imaging of cortical structures. In the present study, we have used fMRI at 3 T to investigate the neural activity evoked by thermal sensation and pain (42°C and 46°C) throughout the entire lower neuroaxis from the first synapse in the spinal cord rostral to the thalamus in healthy subjects. The results demonstrate that noxious thermal stimulation (46°C) produces consistent activity within various structures known to be involved in the pain matrix including the dorsal spinal cord, reticular formation, periaqueductal gray and rostral ventral medulla. However, additional areas of activity were evident that are not considered to be part of the pain matrix, including the olivary nucleus. Thermal stimulation (42°C) reported as either not painful or mildly painful produced quantitative, but not qualitative, differences in neuronal activity depending on the order of experiments. Activity was greater in the spinal cord and brain stem in earlier experiments, compared with repeated experiments after the more noxious (46°C) stimulus had been applied. This study provides significant insight into how the lower neuroaxis integrates and responds to pain in humans.     

Fine-scale functional connectivity in somatosensory cortex revealed by high-resolution fMRI

High-resolution functional magnetic resonance imaging (fMRI) at high field (9.4 T) has been used to measure functional connectivity between subregions within the primary somatosensory (SI) cortex of the squirrel monkey brain. The hand-face region within the SI cortex of the squirrel monkey has been previously well mapped with functional imaging and electrophysiological and anatomical methods, and the orderly topographic map of the hand region is characterized by a lateral to medial representation of individual digits in four subregions of areas 3a, 3b, 1 and 2. With submillimeter resolution, we are able to detect not only the separate islands of activation corresponding to vibrotactile stimulations of single digits but also, in subsequent acquisitions, the degree of correlation between voxels within the SI cortex in the resting state. The results suggest that connectivity patterns are very similar to stimulus-driven distributions of activity and that connectivity varies on the scale of millimeters within the same primary region. Connectivity strength is not a reflection of global larger-scale changes in blood flow and is not directly dependent on distance between regions. Preliminary electrophysiological recordings agree well with the fMRI data. In human studies at 7 T, high-resolution fMRI may also be used to identify the same subregions and assess responses to sensory as well as painful stimuli, and to measure connectivity dynamically before and after such stimulations.     

Mirror Observation of Finger Action Enhances Activity in Anterior Intraparietal Sulcus: A Functional Magnetic Resonance Imaging Study

Mirror therapy can be used to promote recovery from paralysis in patients with post-stroke hemiplegia, There are a lot of reports that mirror-image observation of the unilateral moving hand enhanced the excitability of the primary motor area (M1) ipsilateral to the moving hand in healthy subjects. but the neural mechanisms underlying its therapeutic effects are currently unclear. To investigate this issue, we used functional magnetic resonance imaging to measure activity in brain regions related to visual information processing during mirror image movement observation. Thirteen healthy subjects performed a finger-thumb opposition task with the left and right hands separately, with or without access to mirror observation. In the mirror condition, one hand was reflected in a mirror placed above the abdomen in the MRI scanner. In the masked mirror condition, subjects performed the same task but with the mirror obscured. In both conditions, the other hand was held at rest behind the mirror. A between-task comparison (mirror versus masked mirror) revealed significant activation in the ipsilateral hemisphere in the anterior intraparietal sulcus (aIP) while performing all tasks, regardless of which hand was used. The right aIP was significantly activated while moving the right hand. In contrast, in the left aIP, a small number of voxels showed a tendency toward activation during both left and right hand movement. The enhancement of ipsilateral aIP activity by the mirror image observation of finger action suggests that bimodal aIP neurons can be activated by visual information. We propose that activation in the M1 ipsilateral to the moving hand can be induced by information passing through the ventral premotor area from the aIP.     

Modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case studying

Manual acupuncture is widely used for pain treatment and stress control. Previous studies on acupuncture have shown its modulatory effects on functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of threshold, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas characteristic path length is shorter. We provide further support for the presence of "small-world" network characteristics in functional networks by acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of acupuncture effects on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.     

静息状态下脑功能连接的磁共振成像研究

静息状态下脑功能连接的磁共振成像研究近年来取得了迅猛发展. 通过对fMRI信号低频涨落成分的同步性分析,可以得到大脑静息态任意脑区的功能连接和多套网络系统,其中“默认网络”的发现可能为人脑固有网络的研究提供新的思路. 而静息态网络与解剖连接之间可能存在的对应,以及在神经精神疾病患者脑中性质和连接的异常改变,使其具有重要的研究和临床应用价值. 该文总结了静息状态功能磁共振成像的主要研究成果,对静息状态脑功能网络的发现和发展、研究方法、各网络及其特点以及在临床方面的应用进行简单的介绍和分析.     

The modulation of brain functional connectivity with manual acupuncture in healthy subjects:An electroencephalograph case study

Manual acupuncture is widely used for pain relief and stress control.Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions.To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level,we acupuncture at ST36 of a right leg to obtain electroencephalograph(EEG) signals.By coherence estimation,we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states.The resulting synchronization matrices are converted into functional networks by applying a threshold,and the clustering coefficients and path lengths are computed as a function of threshold.The results show that acupuncture can increase functional connections and synchronizations between different brain areas.For a wide range of thresholds,the clustering coefficient during acupuncture and postacupuncture period is higher than that during the pre-acupuncture control period,whereas the characteristic path length is shorter.We provide further support for the presence of "small-world" network characteristics in functional networks by using acupuncture.These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture,which could contribute to the understanding of the effects of acupuncture on the entire brain,as well as the neurophysiological mechanisms underlying acupuncture.Moreover,the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.     

The anxiolytic effects of midazolam during anticipation to pain revealed using fMRI

BACKGROUND AND PURPOSE: Functional neuroimaging can distinguish components of the pain experience associated with anticipation to pain from those associated with the experience of pain itself. Anticipation to pain is thought to increase the suffering of chronic pain patients. Inappropriate anxiety, of which anticipation is a component, is also a cause of disability. We present a pharmacological functional magnetic resonance imaging (fMRI) study in which we investigate the selective modulation by midazolam of brain activity associated with anticipation to pain compared to pain itself. METHODS: Eight right-handed male volunteers underwent fMRI combined with a thermal pain conditioning paradigm and midazolam (30 mug/kg) or saline administration on different occasions, with order randomized across volunteers. Volunteers learned to associate a colored light with either painful, hot stimulation or nonpainful, warm stimulation to the back of the left hand. RESULTS: Comparison of the period during thermal stimulation (pain-warm) revealed a network of brain activity commonly associated with noxious stimulation, including activities in the anterior cingulate cortex (ACC), the bilateral insular cortices (anterior and posterior), the thalamus, S1, the motor cortex, the brainstem, the prefrontal cortex and the cerebellum. Comparison of the periods preceding thermal stimulation (anticipation to pain-anticipation to warm) revealed activity principally in the ACC, the contralateral anterior insular cortex and the ipsilateral S2/posterior insula. Detected by a region-of-interest analysis, midazolam reduced the activity associated specifically with anticipation to pain while controlling for anticipation to warm. This was most significant in the contralateral anterior insula (P<.05). There were no significant drug effects on the activity associated with pain itself. CONCLUSION: In identifying a pharmacological effect on activity preceding but not during pain, we have successfully demonstrated an fMRI assay that can be used to study the action of anxiolytic agents in a relatively small cohort of humans.     

fMRI assessment of thalamocortical connectivity during attentional performance

Functional magnetic resonance imaging (fMRI) studies have shown dysfunction in key areas associated with the thalamocortical circuit in patients with schizophrenia. This study examined the functional connectivity involving the frontal-thalamic circuitry during a spatial focusing-of-attention task in 18 unmedicated patients with schizophrenia and 38 healthy controls. Functional connectivity was analyzed by assigning seed regions (in the thalamic nuclei (mediodorsal nucleus (MDN), pulvinar, anterior nucleus (AN)), the dorsolateral prefrontal cortex (Brodmann areas 9 and 46), and the caudate), and correlating their respective activity with that in the non-seed regions voxel-wise. Functional connectivity analysis demonstrated that functional connectivity was significantly impaired in patients, e.g., between the right pulvinar and regions such as the prefrontal and temporal cortices and the cerebellum. On the other hand, enhanced functional connectivity was found in patients e.g., between the AN and regions such as the prefrontal and temporal cortices. In addition, the patients had significantly lower task performance and less (but non-significant) brain activation than those of controls. These results revealed disturbed functional integration in schizophrenia, and suggested that the functional connectivity abnormalities in the thalamocortical circuitry, especially the frontal-thalamic circuitry, may underlie the attention deficits in schizophrenia patients. Further, this study suggested that functional connectivity analysis might be more sensitive than brain activation analysis in detecting the functional abnormalities in schizophrenia.     

Percept-related activity in the human somatosensory system: functional magnetic resonance imaging studies

In this paper, we review blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies addressing the neural correlates of touch, thermosensation, pain and the mechanisms of their cognitive modulation in healthy human subjects. There is evidence that fMRI signal changes can be elicited in the parietal cortex by stimulation of single mechanoceptive afferent fibers at suprathreshold intensities for conscious perception. Positive linear relationships between the amplitude or the spatial extents of BOLD fMRI signal changes, stimulus intensity and the perceived touch or pain intensity have been described in different brain areas. Some recent fMRI studies addressed the role of cortical areas in somatosensory perception by comparing the time course of cortical activity evoked by different kinds of stimuli with the temporal features of touch, heat or pain perception. Moreover, parametric single-trial functional MRI designs have been adopted in order to disentangle subprocesses within the nociceptive system.

Available evidence suggest that studies that combine fMRI with psychophysical methods may provide a valuable approach for understanding complex perceptual mechanisms and top-down modulation of the somatosensory system by cognitive factors specifically related to selective attention and to anticipation. The brain networks underlying somatosensory perception are complex and highly distributed. A deeper understanding of perceptual-related brain mechanisms therefore requires new approaches suited to investigate the spatial and temporal dynamics of activation in different brain regions and their functional interaction.     

Occipital-parietal interactions during shifts of exogenous visuospatial attention: trial-dependent changes of effective connectivity

We studied neural interactions between brain areas involved in exogenous (stimulus-driven) control of visuospatial attention. With event-related functional magnetic resonance imaging (fMRI), we investigated changes of connectivity during shifts of spatial attention from an attended location to a previously unattended target location. Using a 3-T scanner, fMRI data were acquired from three healthy volunteers. According to a central visual cue, participants directed endogenous spatial attention to the left or the right visual hemifield for blocks of 56 s. Peripheral visual targets were presented unpredictably in either the attended hemifield (valid trials, 80%) or in the unattended hemifield (invalid trials, 20%) and participants performed a two-alternative forced-choice discrimination task with the target, irrespective of cue validity. In accordance with previous results, we found that the temporal–parietal junction (TPJ) mediates the shift of spatial attention toward stimuli presented at the unattended side (i.e., invalid trials). We critically studied the interaction between occipital areas responding to the visual stimuli and other brain regions in order to find regions functionally coupled with the occipital cortex during invalid trials. We found that the coupling between occipital areas processing visual stimuli and the TPJ selectively increased during invalid trials. Our results highlight how changes of connectivity between brain areas can describe attentional processes such as stimulus-driven shifts of spatial attention.     

Disrupted functional connectivity in social anxiety disorder: a resting-state fMRI study

Dysfunction of the corticolimbic circuitry has been highlighted in social anxiety disorder (SAD) during social stimuli. However, few studies have investigated functional connectivity in SAD during the resting state, which may improve our understanding of SAD pathophysiology. The aim of this study was to investigate whether whole-brain functional connectivity might be aberrant in SAD patients, and if so, whether these changes are related to the measured clinical severity. Seventeen SAD patients and 19 healthy controls participated in resting-state functional magnetic resonance imaging. The brain was first divided into 90 paired brain regions and functional connectivity was then estimated by temporal correlation between each of these regions. Furthermore, connections that were significantly disrupted in SAD patients were correlated with clinical severity measured using the Liebowitz Social Anxiety Scale. Compared with healthy controls, SAD patients showed decreased positive connections within the frontal lobe and decreased negative connections between the frontal and occipital lobes. In particular, the weaker negative connections between the frontal lobe, which mainly involved the right median prefrontal cortex, and the occipital lobe had a significant positive correlation with the severity of SAD symptoms. The results support the hypothesis that some abnormalities of functional connectivity exist in SAD patients, which relate to the frontal cortex and occipital cortex. In addition, decreased functional connectivity between the frontal and occipital lobes and within the frontal lobe might be related to abnormal information processing and reflect disturbed neural organization resulting in defective social cognition, which could represent an early imaging biomarker for SAD.     

Common brain activations for painful and non-painful aversive stimuli

Background

Identification of potentially harmful stimuli is necessary for the well-being and self-preservation of all organisms. However, the neural substrates involved in the processing of aversive stimuli are not well understood. For instance, painful and non-painful aversive stimuli are largely thought to activate different neural networks. However, it is presently unclear whether there is a common aversion-related network of brain regions responsible for the basic processing of aversive stimuli. To help clarify this issue, this report used a cross-species translational approach in humans (i.e. meta-analysis) and rodents (i.e. systematic review of functional neuroanatomy).

Results

Animal and human data combined to show a core aversion-related network, consisting of similar cortical (i.e. MCC, PCC, AI, DMPFC, RTG, SMA, VLOFC; see results section or abbreviation section for full names) and subcortical (i.e. Amyg, BNST, DS, Hab, Hipp/Parahipp, Hyp, NAc, NTS, PAG, PBN, raphe, septal nuclei, Thal, LC, midbrain) regions. In addition, a number of regions appeared to be more involved in pain-related (e.g. sensory cortex) or non-pain-related (e.g. amygdala) aversive processing.

Conclusions

This investigation suggests that aversive processing, at the most basic level, relies on similar neural substrates, and that differential responses may be due, in part, to the recruitment of additional structures as well as the spatio-temporal dynamic activity of the network. This network perspective may provide a clearer understanding of why components of this circuit appear dysfunctional in some psychiatric and pain-related disorders.     

Assessing functional connectivity in the human brain by fMRI

Functional magnetic resonance imaging (fMRI) is widely used to detect and delineate regions of the brain that change their level of activation in response to specific stimuli and tasks. Simple activation maps depict only the average level of engagement of different regions within distributed systems. FMRI potentially can reveal additional information about the degree to which components of large-scale neural systems are functionally coupled together to achieve specific tasks. In order to better understand how brain regions contribute to functionally connected circuits, it is necessary to record activation maps either as a function of different conditions, at different times or in different subjects. Data obtained under different conditions may then be analyzed by a variety of techniques to infer correlations and couplings between nodes in networks. Several multivariate statistical methods have been adapted and applied to analyze variations within such data. An approach of particular interest that is suited to studies of connectivity within single subjects makes use of acquisitions of runs of MRI images obtained while the brain is in a so-called steady state, either at rest (i.e., without any specific stimulus or task) or in a condition of continuous activation. Interregional correlations between fluctuations of MRI signal potentially reveal functional connectivity. Recent studies have established that interregional correlations between different components of circuits in each of the visual, language, motor and working memory systems can be detected in the resting state. Correlations at baseline are changed during the performance of a continuous task. In this review, various methods available for assessing connectivity are described and evaluated.     

Investigating directed influences between activated brain areas in a motor-response task using fMRI

Localization of cognitive processes is a strength of functional neuroimaging. However, information about functional interactions between brain areas is crucial for a deeper understanding of brain function. We applied vector autoregressive modeling in the context of Granger causality as a method to analyze directed connectivity in a standard event-related fMRI study using a simple auditory-motor paradigm. The basic idea is to use temporal information in stochastic time series of a brain region in order to predict signal time courses in other brain regions. Thus, we predicted that the method should demonstrate causal influence of the auditory cortex and the supplementary motor area (SMA) on primary motor cortex. Eleven right-handed healthy female subjects were instructed to press a ball with either their left or their right hand when hearing the command "left" or "right" in the scanner. Influence to the left motor cortex was found from bilateral auditory cortex as well as from the SMA in 9 of 11 subjects. Granger causality to the right motor cortex existed from bilateral auditory cortex in 5 and from SMA in 6 subjects. Granger causality to the SMA existed from right auditory cortex in 7 subjects and from left auditory cortex in 8 subjects. Our findings in a simple task show that even under suboptimal circumstances (a relatively long TR of 2440 ms), Granger causality can be a useful tool to explore effective connectivity. Temporally optimized scanning should increase that potential.     

Investigation of the large-scale functional brain networks modulated by acupuncture

Previous neuroimaging studies have primarily focused on the neural activities involving the acute effects of acupuncture. Considering that acupuncture can induce long-lasting effects, several researchers have begun to pay attention to the sustained effects of acupuncture on the resting brain. Most of these researchers adopted functional connectivity analysis based on one or a few preselected brain regions and demonstrated various function-guided brain networks underlying the specific effect of acupuncture. Few have investigated how these brain networks interacted at the whole-brain level. In this study, we sought to investigate the functional correlations throughout the entire brain following acupuncture at acupoint ST36 (ACUP) in comparison with acupuncture at nearby nonacupoint (SHAM). We divided the whole brain into 90 regions and constructed functional brain network for each condition. Then we examined the network hubs and identified statistically significant differences in functional correlations between the two conditions. Following ACUP, but not SHAM, the limbic/paralimbic regions such as the amygdala, hippocampus and anterior cingulate gyrus emerged as network hubs. For direct comparisons, increased correlations for ACUP compared to SHAM were primarily related with the limbic/paralimbic and subcortical regions such as the insula, amygdala, anterior cingulate gyrus, and thalamus, whereas decreased correlations were mainly related with the sensory and frontal cortex. The heterogeneous modulation patterns between the two conditions may relate to the functional specific modulatory effects of acupuncture. The preliminary findings may help us to better understand the long-lasting effects of acupuncture on the entire resting brain, as well as the neurophysiological mechanisms underlying acupuncture.     

Fastest learning in small-world neural networks

We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition.     

Biophysical and neural basis of resting state functional connectivity: Evidence from non-human primates

Functional MRI (fMRI) has evolved from simple observations of regional changes in MRI signals caused by cortical activity induced by a task or stimulus, to task-free acquisitions of images in a resting state. Such resting state signals contain low frequency fluctuations which may be correlated between voxels, and strongly correlated regions are deemed to reflect functional connectivity within synchronized circuits. Resting state functional connectivity (rsFC) measures have been widely adopted by the neuroscience community, and are being used and interpreted as indicators of intrinsic neural circuits and their functional states in a broad range of applications, both basic and clinical. However, there has been relatively little work reported that validates whether inter-regional correlations in resting state fluctuations of fMRI (rsfMRI) signals actually measure functional connectivity between brain regions, or to establish how MRI data correlate with other metrics of functional connectivity. In this mini-review, we summarize recent studies of rsFC within mesoscopic scale cortical networks (100 μm–10 mm) within a well defined functional region of primary somatosensory cortex (S1), as well as spinal cord and brain white matter in non-human primates, in which we have measured spatial patterns of resting state correlations and validated their interpretation with electrophysiological signals and anatomic connections. Moreover, we emphasize that low frequency correlations are a general feature of neural systems, as evidenced by their presence in the spinal cord as well as white matter. These studies demonstrate the valuable role of high field MRI and invasive measurements in an animal model to inform the interpretation of human imaging studies.     

时变动态贝叶斯网络模型及其在皮层脑电网络连接中的应用

大脑执行语言的发音需要顶叶、颞叶、额叶等多个脑区协同完成.皮层脑电具有高时间分辨率、较高空间分辨率和高信噪比等优势,为研究大脑的电生理特性提供了重要的技术手段.为了探索大脑对语言的动态处理过程,利用多尺度皮层脑电(标准电极与微电极)分析了被试在执行音节朗读任务时的皮层脑电信号的高频gamma段特征,提出采用时变动态贝叶斯网络构建单次实验任务的有向网络.结果显示该方法能够快速有效地构建语言任务过程中标准电极、微电极以及二者之间的有向网络连接,且反映了大规模网络(标准电极之间的连接)、局部网络(微电极之间的连接)以及大规模网络与局部网络之间的连接(标准电极与微电极之间的连接)随语言任务发生的动态改变.研究还发现,发音时刻之前与之后的网络连接存在显著性差异,且发音方式不同的音节网络间也存在明显差异.该研究将有助于癫痫等神经疾病的术前临床评估以及理解大脑对语言加工的实时处理过程.     

Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG

Different brain imaging devices are presently available to provide images of the human functional cortical activity, based on hemodynamic, metabolic or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions are interconnected. The concept of brain connectivity plays a central role in the neuroscience, and different definitions of connectivity, functional and effective, have been adopted in literature. While the functional connectivity is defined as the temporal coherence among the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally among cortical sites. The structural equation modeling (SEM) is the most used method to estimate effective connectivity in neuroscience, and its typical application is on data related to brain hemodynamic behavior tested by functional magnetic resonance imaging (fMRI), whereas the directed transfer function (DTF) method is a frequency-domain approach based on both a multivariate autoregressive (MVAR) modeling of time series and on the concept of Granger causality.

This study presents advanced methods for the estimation of cortical connectivity by applying SEM and DTF on the cortical signals estimated from high-resolution electroencephalography (EEG) recordings, since these signals exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. To estimate correctly the cortical signals, we used a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual MRI, a distributed source model and a regularized linear inverse source estimates of cortical current density. Before the application of SEM and DTF methodology to the cortical waveforms estimated from high-resolution EEG data, we performed a simulation study, in which different main factors (signal-to-noise ratio, SNR, and simulated cortical activity duration, LENGTH) were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). The statistical analysis returned that during simulations, both SEM and DTF estimators were able to correctly estimate the imposed connectivity patterns under reasonable operative conditions, that is, when data exhibit an SNR of at least 3 and a LENGTH of at least 75 s of nonconsecutive EEG recordings at 64 Hz of sampling rate.

Hence, effective and functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high-resolution EEG techniques and linear inverse estimation with SEM or DTF methods. We conclude that the estimation of cortical connectivity can be performed not only with hemodynamic measurements, but also with EEG signals treated with advanced computational techniques.     

Synchronization structure of evolving epileptic networks using cross-entropy

In this paper we present connectivity patterns of evolving large scale epileptic networks. We employed a cross-entropy measure in the frequency domain on EEG signals to infer the networks, before and during episodes of epileptic seizures. This measure allowed us to make a richer portrait about the node interactions on the graph and to identify emergent structures associated with the synchronization of brain activity. Our results points to a more complex scenario of network organization than the synchronized/unsynchronized dichotomy, with two main results: first, showing regions with unsynchronized (or independent) behavior, even during absence seizures, contradicting the concept of hypersynchrony. Furthermore, we explore the cross-entropy fluctuations along the seizure: a group of nodes became more similar over time while another group became more different, showing a complementary behaviour and different local brain activities. These results bring new questions about the spreading and the sustenance of the epileptic seizures and others synchronization phenomena in living systems.