Brain Systems Underlying Fundamental Motivations of Human Social Conformity / 神经科学通报·英文版

From birth to adulthood, we often align our behaviors, attitudes, and opinions with a majority, a phenomenon known as social conformity. A seminal framework has proposed that conformity behaviors are mainly driven by three fundamental motives: a desire to gain more information to be accurate, to obtain social approval from others, and to maintain a favorable self-concept. Despite extensive interest in neuroimaging investigation of social conformity, the relationship between brain systems and these fundamental motivations has yet to be established. Here, we reviewed brain imaging findings of social conformity with a componential framework, aiming to reveal the neuropsychological substrates underlying different conformity motivations. First, information-seeking engages the evaluation of social information, information integration, and modification of task-related activity, corresponding to brain networks implicated in reward, cognitive control, and tasks at hand. Second, social acceptance involves the anticipation of social acceptance or rejection and mental state attribution, mediated by networks of reward, punishment, and mentalizing. Third, self-enhancement entails the excessive representation of positive self-related information and suppression of negative self-related information, ingroup favoritism and/or outgroup derogation, and elaborated mentalizing processes to the ingroup, supported by brain systems of reward, punishment, and mentalizing. Therefore, recent brain imaging studies have provided important insights into the fundamental motivations of social conformity in terms of component processes and brain mechanisms.

The neural basis underlying primary dysmenorrhea: evidence from neuroimaging and animal model studies / 生理学报

Primary dysmenorrhea (PDM), cyclic menstrual pain in the absence of pelvic anomalies, is characterized by acute and chronic gynecological pain disorders in childbearing age women. PDM strongly affects the quality of life of patients and leads to economic losses. PDM generally do not receive radical treatment and often develop into other chronic pain disorders later in life. The clinical treatment status of PDM, the epidemiology of PDM and chronic pain comorbidities, and the abnormal physiological and psychological characteristics of patients with PDM suggest that PDM not only is related to the inflammation around the uterus, but also may be related to the abnormal pain processing and regulation function of patients' central system. Therefore, exploring the brain neural mechanism of PDM is indispensable and important to understand the pathological mechanism of PDM, and is also a hotspot of brain science research in recent years, which will bring new inspiration to explore the target of PDM intervention. Based on the progress of the neural mechanism of PDM, this paper systematically summarizes the evidence from neuroimaging and animal model studies.

Network controllability analysis of awake and asleep conditions in the brain / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

The difference between sleep and wakefulness is critical for human health. Sleep takes up one third of our lives and remains one of the most mysterious conditions; it plays an important role in memory consolidation and health restoration. Distinct neural behaviors take place under awake and asleep conditions, according to neuroimaging studies. While disordered transitions between wakefulness and sleep accompany brain disease, further investigation of their specific characteristics is required. In this study, the difference is objectively quantified by means of network controllability. We propose a new pipeline using a public intracranial stereo-electroencephalography (stereo-EEG) dataset to unravel differences in the two conditions in terms of system neuroscience. Because intracranial stereo-EEG records neural oscillations covering large-scale cerebral areas, it offers the highest temporal resolution for recording neural behaviors. After EEG preprocessing, the EEG signals are band-passed into sub-slow (0.1‍-‍1 Hz), delta (1‍-‍4 Hz), theta (4‍-‍8 Hz), alpha (8‍-‍13 Hz), beta (13‍-‍30 Hz), and gamma (30‍-‍45 Hz) band oscillations. Then, dynamic functional connectivity is extracted from time-windowed EEG neural oscillations through phase-locking value (PLV) and non-overlapping sliding time windows. Next, average and modal network controllability are implemented on these time-varying brain networks. Based on this preliminary study, it appears that significant differences exist in the dorsolateral frontal-parietal network (FPN), salience network (SN), and default-mode network (DMN). The combination of network controllability and dynamic functional networks offers new insight for characterizing distinctions between awake and asleep stages in the brain. In other words, network controllability captures the underlying brain dynamics under both awake and asleep conditions.

A research on epilepsy source localization from scalp electroencephalograph based on patient-specific head model and multi-dipole model / 生物医学工程学杂志

Accurate source localization of the epileptogenic zone (EZ) is the primary condition of surgical removal of EZ. The traditional localization results based on three-dimensional ball model or standard head model may cause errors. This study intended to localize the EZ by using the patient-specific head model and multi-dipole algorithms using spikes during sleep. Then the current density distribution on the cortex was computed and used to construct the phase transfer entropy functional connectivity network between different brain areas to obtain the localization of EZ. The experiment result showed that our improved methods could reach the accuracy of 89.27% and the number of implanted electrodes could be reduced by (19.34 ± 7.15)%. This work can not only improve the accuracy of EZ localization, but also reduce the additional injury and potential risk caused by preoperative examination and surgical operation, and provide a more intuitive and effective reference for neurosurgeons to make surgical plans.

The measurements of the similarity of dynamic brain functional network / 生物医学工程学杂志

Brain functional network changes over time along with the process of brain development, disease, and aging. However, most of the available measurements for evaluation of the difference (or similarity) between the individual brain functional networks are for charactering static networks, which do not work with the dynamic characteristics of the brain networks that typically involve a long-span and large-scale evolution over the time. The current study proposes an index for measuring the similarity of dynamic brain networks, named as dynamic network similarity (DNS). It measures the similarity by combining the "evolutional" and "structural" properties of the dynamic network. Four sets of simulated dynamic networks with different evolutional and structural properties (varying amplitude of changes, trend of changes, distribution of connectivity strength, range of connectivity strength) were generated to validate the performance of DNS. In addition, real world imaging datasets, acquired from 13 stroke patients who were treated by transcranial direct current stimulation (tDCS), were used to further validate the proposed method and compared with the traditional similarity measurements that were developed for static network similarity. The results showed that DNS was significantly correlated with the varying amplitude of changes, trend of changes, distribution of connectivity strength and range of connectivity strength of the dynamic networks. DNS was able to appropriately measure the significant similarity of the dynamics of network changes over the time for the patients before and after the tDCS treatments. However, the traditional methods failed, which showed significantly differences between the data before and after the tDCS treatments. The experiment results demonstrate that DNS may robustly measure the similarity of evolutional and structural properties of dynamic networks. The new method appears to be superior to the traditional methods in that the new one is capable of assessing the temporal similarity of dynamic functional imaging data.

Research on depression recognition based on brain function network / 生物医学工程学杂志

Traditional depression research based on electroencephalogram (EEG) regards electrodes as isolated nodes and ignores the correlation between them. So it is difficult to discover abnormal brain topology alters in patients with depression. To resolve this problem, this paper proposes a framework for depression recognition based on brain function network (BFN). To avoid the volume conductor effect, the phase lag index is used to construct BFN. BFN indexes closely related to the characteristics of "small world" and specific brain regions of minimum spanning tree were selected based on the information complementarity of weighted and binary BFN and then potential biomarkers of depression recognition are found based on the progressive index analysis strategy. The resting state EEG data of 48 subjects was used to verify this scheme. The results showed that the synchronization between groups was significantly changed in the left temporal, right parietal occipital and right frontal, the shortest path length and clustering coefficient of weighted BFN, the leaf scores of left temporal and right frontal and the diameter of right parietal occipital of binary BFN were correlated with patient health questionnaire 9-items (PHQ-9), and the highest recognition rate was 94.11%. In addition, the study found that compared with healthy controls, the information processing ability of patients with depression reduced significantly. The results of this study provide a new idea for the construction and analysis of BFN and a new method for exploring the potential markers of depression recognition.

Representations of object animacy and real-world size in the ventral visual pathway / 生理学报

How the brain perceives objects and classifies perceived objects is one of the important goals of visual cognitive neuroscience. Previous research has shown that when we see objects, the brain's ventral visual pathway recognizes and classifies them, leading to different ways of interacting with them. In this paper, we summarize the latest research progress of the ventral visual pathway related to the visual classification of objects. From the perspective of the neural representation of objects and its underlying mechanisms in the visual cortex, we summarize the current research status of the two important organizational dimensions of object animacy and real-world size, provide new insights, and point out the direction of further research.

Localization of epileptogenic zone based on reconstruction of dynamical epileptic network and virtual resection / 生物医学工程学杂志

Drug-refractory epilepsy (DRE) may be treated by surgical intervention. Intracranial EEG has been widely used to localize the epileptogenic zone (EZ). Most studies of epileptic network focus on the features of EZ nodes, such as centrality and degrees. It is difficult to apply those features to the treatment of individual patients. In this study, we proposed a spatial neighbor expansion approach for EZ localization based on a neural computational model and epileptic network reconstruction. The virtual resection method was also used to validate the effectiveness of our approach. The electrocorticography (ECoG) data from 11 patients with DRE were analyzed in this study. Both interictal data and surgical resection regions were used. The results showed that the rate of consistency between the localized regions and the surgical resections in patients with good outcomes was higher than that in patients with poor outcomes. The average deviation distance of the localized region for patients with good outcomes and poor outcomes were 15 mm and 36 mm, respectively. Outcome prediction showed that the patients with poor outcomes could be improved when the brain regions localized by the proposed approach were treated. This study provides a quantitative analysis tool for patient-specific measures for potential surgical treatment of epilepsy.

Assessment of changes in the electrical activity of the brain during general anesthesia using portable electroencephalography / Evaluación de los cambios de la actividad eléctrica cerebral durante anestesia general usando electroencefalografía portable

Abstract Introduction The analysis of the electrical activity of the brain using scalp electrodes with electroencephalography (EEG) could reveal the depth of anesthesia of a patient during surgery. However, conventional EEG equipment, due to its price and size, are not a practical option for the operating room and the commercial units used in surgery do not provide access to the electrical activity. The availability of low-cost portable technologies could provide for further research on the brain activity under general anesthesia and facilitate our quest for new markers of depth of anesthesia. Objective To assess the capabilities of a portable EEG technology to capture brain rhythms associated with the state of consciousness and the general anesthesia status of surgical patients anesthetized with propofol. Methods Observational, cross-sectional study that reviewed 10 EEG recordings captured using OpenBCI portable low-cost technology, in female patients undergoing general anesthesia with propofol. The signal from the frontal electrodes was analyzed with spectral analysis and the results were compared against the reports in the literature. Results The signal captured with frontal electrodes, particularly α rhythm, enabled the distinction between resting with eyes closed and with eyes opened in a conscious state, and sustained anesthesia during surgery. Conclusions It is possible to differentiate a resting state from sustained anesthesia, replicating previous findings with conventional technologies. These results pave the way to the use of portable technologies such as the OpenBCI tool, to explore the brain dynamics during anesthesia.

Resumen Introducción El análisis de la actividad eléctrica cerebral mediante electrodos ubicados sobre el cuero cabelludo con electroencefalografía (EEG) podría permitir conocer la profundidad anestésica de un paciente durante cirugía. Sin embargo, los equipos de EEG convencionales, por su precio y tamaño, no son una alternativa práctica en quirófanos y los equipos comerciales usados en cirugía no permiten acceder a la actividad eléctrica. Disponer de tecnologías portables y de bajo costo aumentaría el número de investigaciones sobre la actividad cerebral bajo anestesia general y facilitaría la búsqueda de nuevos marcadores para la profundidad anestésica. Objetivo Evaluar la capacidad de una tecnología EEG portable de adquirir ritmos cerebrales relacionados con el estado consciente y el estado de anestesia general de pacientes en cirugía anestesiados con propofol. Métodos Estudio observacional de corte transversal en el que se analizaron datos de 10 registros EEG obtenidos mediante tecnología portable y de bajo costo OpenBCI, de pacientes de sexo femenino que fueron sometidas a anestesia general con propofol. La señal obtenida de los electrodos frontales se analizó mediante análisis espectral y se contrastaron los resultados con lo descrito en la literatura. Resultados La señal obtenida con electrodos frontales, especialmente el ritmo α, permitió diferenciar el reposo con ojos cerrados y ojos abiertos en estado consciente, del estado de mantenimiento de la anestesia durante cirugía. Conclusiones Se logra la diferenciación de estado de reposo y de mantenimiento de la anestesia replicando hallazgos previos de tecnologías convencionales. Estos resultados abren la posibilidad de utilizar las tecnologías portables como el OpenBCI para investigar la dinámica cerebral durante la anestesia.

Evaluación de la actividad cerebro-cerebelar cruzada para determinar la lateralidad del lenguaje en pacientes con tumores cerebrales / Evaluation of the crossed cerebro-cerebellar activation to determine language lateralization in patients with brain tumors

Background: The crossed cerebro-cerebellar (CCC) activation facilitates the diagnosis of cortical language lateralization, but needs to be explored with language tasks suitable for patients with different age ranges, educational attainment and eventual presence of language deficits. Aim: To determine the effect of demographic variables in the performance of three language tasks in healthy volunteers and to determine the CCC activation of these tasks as a functional magnetic resonance imaging (fMRI) paradigm in brain tumor patients. Material and Methods: The behavioral performance (correct responses and reaction time) of three language tasks (verbal fluency, semantic and phonological decision tasks) was first examined in 76 healthy volunteers balanced by age and educational level. Later, these tasks were implemented as fMRI paradigms to explore CCC language activation of 20 patients with potential diagnosis of brain tumors. Results: The performance of the verbal fluency task was affected by age. The CCC language activation was reproducible with the semantic and phonological tasks. The combination of the tasks determined typical and atypical language lateralization in 60% and 40% of our patients, respectively. Conclusions: The verbal fluency task must be implemented with care as a clinical fMRI paradigm. Our results suggest that semantic and phonological tasks can be a good alternative for brain tumor patients with language deficits.

Clinical applications of neurolinguistics in neurosurgery / 医学前沿

The protection of language function is one of the major challenges of brain surgery. Over the past century, neurosurgeons have attempted to seek the optimal strategy for the preoperative and intraoperative identification of language-related brain regions. Neurosurgeons have investigated the neural mechanism of language, developed neurolinguistics theory, and provided unique evidence to further understand the neural basis of language functions by using intraoperative cortical and subcortical electrical stimulation. With the emergence of modern neuroscience techniques and dramatic advances in language models over the last 25 years, novel language mapping methods have been applied in the neurosurgical practice to help neurosurgeons protect the brain and reduce morbidity. The rapid advancements in brain-computer interface have provided the perfect platform for the combination of neurosurgery and neurolinguistics. In this review, the history of neurolinguistics models, advancements in modern technology, role of neurosurgery in language mapping, and modern language mapping methods (including noninvasive neuroimaging techniques and invasive cortical electroencephalogram) are presented.

The relationship between brain networks and symptoms of schizophrenia / 生理学报

The pathogenesis of schizophrenia (SCZ) is not yet clear, and the pathological changes of the brain activity remains debatable. There are still numerous unresolved issues and debates regarding the relationship between functional connection of the brain network and the symptoms of SCZ. In this paper, we provide a comprehensive review of recent research progresses on resting-state and task-based brain networks, which covers the symptoms of SCZ. Furthermore, we discuss the relationship between large-scale brain networks and SCZ symptoms, and propose possible future research directions in the field of SCZ diagnosis and treatment.

Dynamic characteristics of brain networks in patients with irritable bowel syndrome based on functional magnetic resonance imaging / 生理学报

The disorder of brain-gut interaction is an important cause of irritable bowel syndrome (IBS), but the dynamic characteristics of the brain remain unclear. Since there are many shortcomings for evaluating brain dynamic nature in the previous studies, we proposed a new method based on slope calculation by point-by-point analysis of the data from functional magnetic resonance imaging, and detected the abnormalities of brain dynamic changes in IBS patients. The results showed that compared with healthy subjects, there were dynamic changes in the brain for the IBS patients. After correction by false discovery rate (FDR), significant abnormalities were only found in two functional connections of the right posterior cingulate gyrus linked to left middle frontal gyrus, and the right posterior cingulate gyrus linked to left pallidus. The above results of the brain dynamic analysis were totally different from those of the brain static analysis of IBS patients. Our findings provide novel complementary information for illustrating the central nervous mechanism of IBS and may offer a new direction to explore central target for patients with IBS.

Topography of Visual Features in the Human Ventral Visual Pathway / 神经科学通报·英文版

Visual object recognition in humans and nonhuman primates is achieved by the ventral visual pathway (ventral occipital-temporal cortex, VOTC), which shows a well-documented object domain structure. An on-going question is what type of information is processed in the higher-order VOTC that underlies such observations, with recent evidence suggesting effects of certain visual features. Combining computational vision models, fMRI experiment using a parametric-modulation approach, and natural image statistics of common objects, we depicted the neural distribution of a comprehensive set of visual features in the VOTC, identifying voxel sensitivities with specific feature sets across geometry/shape, Fourier power, and color. The visual feature combination pattern in the VOTC is significantly explained by their relationships to different types of response-action computation (fight-or-flight, navigation, and manipulation), as derived from behavioral ratings and natural image statistics. These results offer a comprehensive visual feature map in the VOTC and a plausible theoretical explanation as a mapping onto different types of downstream response-action systems.

Optimized multi-scale entropy to localize epileptogenic hemisphere of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging / 生物医学工程学杂志

Entropy model is widely used in epileptic electroencephalogram (EEG) analysis, but there are few reports on how to objectively select the parameters to compute the entropy model in the analysis of resting-state functional magnetic resonance imaging (rfMRI). Therefore, an optimization algorithm to confirm the parameters in multi-scale entropy (MSE) model was proposed, and the location of epileptogenic hemisphere was taken as an example to test the optimization effect by supervised machine learning. The rfMRI data of 20 temporal lobe epilepsy (TLE) patients with hippocampal sclerosis, positive on structural magnetic resonance imaging, were divided into left and right groups. Then, the parameters in MSE model were optimized by the receiver operating characteristic curves (ROC) and area under ROC curve (AUC) values in sensitivity analysis, and the entropy value of the brain regions with statistically significant difference between the groups were taken as sensitive features to epileptogenic hemisphere lateral. The optimized entropy values of these bio-marker brain areas were considered as feature vectors input into the support vector machine (SVM). Finally, combining optimized MSE model with SVM could accurately distinguish epileptogenic hemisphere in TLE at an average accuracy rate of 95%, which was higher than the current level. The results show that the MSE model parameter optimization algorithm can accurately extract the functional imaging markers sensitive to the epileptogenic hemisphere, and achieve the purpose of objectively selecting the parameters for MSE in rfMRI, which provides the basis for the application of entropy in advanced technology detection.

Intra-operative mapping and language protection in glioma / 中华医学杂志(英文版)

The demand for acquiring different languages has increased with increasing globalization. However, knowledge of the modification of the new language in the neural language network remains insufficient. Although many details of language function have been detected based on the awake intra-operative mapping results, the language neural network of the bilingual or multilingual remains unclear, which raises difficulties in clinical practice to preserve patients' full language ability in neurosurgery. In this review, we present a summary of the current findings regarding the structure of the language network and its evolution as the number of acquired languages increased in glioma patients. We then discuss a new insight into the awake intra-operative mapping protocol to reduce surgical risks during the preservation of language function in multilingual patients with glioma.

Effect of acupuncture on default mode network in patients with migraine based on functional Magnetic Resonance Imaging: a preliminary study / 中国针灸

OBJECTIVE@#To investigate the effect of acupuncture on default mode network (DMN) in migraine patients without aura based on functional Magnetic Resonance Imaging (fMRI).@*METHODS@#Fifteen patients with migraine were included and treated with acupuncture based on "root-knot" theory (Zuqiaoyin [GB 44] for @*RESULTS@#Compared before acupuncture, the functional connections of left parahippocampal cortex (PHC) and anterior medial prefrontal cortex (aMPFC), dorsal medial prefrontal cortex (dMPFC) and lateral temporal cortex (LTC) in DMN after acupuncture were weakened (@*CONCLUSION@#Acupuncture shows good clinical efficacy for migraine without aura, and could adjust the functional connection of DMN.

Cortical Brain Functions ­ The Brodmann Legacy in the 21st Century

In 1909, Korbinian Brodmann described 52 functional brain areas, 43 of them found in the human brain. More than a century later, his devoted functional map was incremented by Glasser et al in 2016, using functional nuclear magnetic resonance imaging techniques to propose the existence of 180 functional areas in each hemisphere, based on their cortical thickness, degree of myelination (cortical myelin content), neuronal interconnection, topographic organization, multitask answers, and assessment in their resting state. This opens a huge possibility, through functional neuroanatomy, to understand a little more about normal brain function and its functional impairment in the presence of a disease.

Parte I: Anatomía microquirúrgica tridimensional de la ínsula / Part I: Three-dimensional microsurgical anatomy of the insula

Introducción: El lóbulo de la ínsula, o ínsula, se encuentra oculto en la superficie lateral del cerebro. La ínsula está localizada profundamente en el surco lateral o cisura silviana, recubierta por los opérculos frontal, parietal y temporal. Objetivo: Estudiar la compleja anatomía del lóbulo de la ínsula, una de las regiones de mayor complejidad quirúrgica del cerebro humano, y su correlación anatómica con casos quirúrgicos. Material y Métodos: En la primera parte de este estudio presentamos los resultados de nuestras disecciones microquirúrgicas en fotografías 2 D y 3D; en la segunda parte de nuestro trabajo, la correlación anatómica con una serie de 44 cirugías en pacientes con tumores de la ínsula, principalmente gliomas, operados entre 2007 y 2014. Resultados: Extenso conjunto de fibras subcorticales, incluyendo el fascículo uncinado, fronto-occipital inferior y el fascículo arcuato, conectan la ínsula a las regiones vecinas. Varias estructuras anatómicas responsables por déficits neurológicos severos están íntimamente relacionadas con la cirugía de la ínsula, tales como lesiones de la arteria cerebral media, cápsula interna, áreas del lenguaje en el hemisferio dominante y arterias lenticuloestriadas. Conclusión: El entrenamiento en laboratorio de neuroanatomía, estudio de material impreso en 3D, el conocimiento sobre neurofisiología intra-operatoria y el uso de armamento neuroquirúrgico moderno son factores que influencian en los resultados quirúrgicos

Introduction: The insular lobe, or insula, is the cerebral lobe sitting deep in the sylvian fissure and hidden by the lateral surface of the brain. It is covered by the frontal, parietal and temporal operculum. Objectives: To study the anatomy of the insular lobe, one of the most complex parts of the human brain, and to correlate this anatomy with intraoperative findings. Materials and Methods: In the first part of this article we show the results of our dissections, documented in 2D and 3D, and focus on microsurgical anatomy. In the second part we correlate the anatomical structures with intraoperative findings from 44 insular tumor surgeries, mainly gliomas, of patients operated on from 2007 to 2014. Results: Huge bundles of subcortical fibers, like uncinate, inferior fronto-occipital and arcuate fascicles, connect the insula to the neighboring structures. Several anatomical structures related to neurological disabilities are closely related to insular surgery, like the middle cerebral artery, internal capsule, lenticulostriate arteries and cortical and subcortical language circuits. Conclusions: Microsurgical laboratory training, 3D documentation, knowledge of brain mapping and modern neurosurgical armamentarium are important factors in achieving good results with insular glioma tumors.