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.
Humans ; Scalp ; Brain Mapping/methods* ; Epilepsy/diagnosis* ; Electroencephalography/methods* ; Brain

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.
Humans ; Wakefulness ; Electroencephalography/methods* ; Brain Mapping/methods* ; Brain

Sensory conflict impacts postural control, yet its effect on cortico-muscular interaction remains underexplored. We aimed to investigate sensory conflict's influence on the cortico-muscular network and postural stability. We used a rotating platform and virtual reality to present subjects with congruent and incongruent sensory input, recorded EEG (electroencephalogram) and EMG (electromyogram) data, and constructed a directed connectivity network. The results suggest that, compared to sensory congruence, during sensory conflict: (1) connectivity among the sensorimotor, visual, and posterior parietal cortex generally decreases, (2) cortical control over the muscles is weakened, (3) feedback from muscles to the cortex is strengthened, and (4) the range of body sway increases and its complexity decreases. These results underline the intricate effects of sensory conflict on cortico-muscular networks. During the sensory conflict, the brain adaptively decreases the integration of conflicting information. Without this integrated information, cortical control over muscles may be lessened, whereas the muscle feedback may be enhanced in compensation.
Humans ; Muscle, Skeletal ; Electromyography/methods* ; Electroencephalography/methods* ; Brain ; Brain Mapping

The aim of the present study was to explore the changes in some functional connectivity in the resting-state electroencephalogram (EEG) based functional brain network of depressed college students, and to understand the brain regions involved in the onset of depression and the electrophysiological activity of subcortical nerve cells, hoping to provide additional information for the diagnosis of depression. Twenty female college students with depressive symptoms were selected according to the Beck Depression Inventory-II (BDI-II) and the Self-rating Depression Scale (SDS). The EEG information of 20 female college students under resting-state was collected by using a 32-conduction EEG acquisition system (Neuroscan). Then Pearson correlation analysis, coherence analysis, phase locking value analysis, phase lag index analysis and weighted phase lag index analysis were used to construct the resting-state brain functional network. The results showed that, compared with the normal group, the depression group exhibited significantly increased correlation in θ and β bands of EEG (P < 0.05), and extremely significantly increased in α band (P < 0.01). Among them, the coherence in α and β bands was significantly increased (P < 0.05), mainly concentrated in the left hemisphere frontal lobe and temporal lobe region. The phase locking value in θ, α and β bands was significantly increased (P < 0.05), mainly concentrated in the prefrontal region and the left hemisphere from the frontal region to the temporal region, and the connectivity in α band was the most obvious. Correlation analysis showed a significant positive correlation between indicators of differential functional connectivity (coherence and phase locking value) and BDI-II scores in the depression group, and the receiver operating characteristics (ROC) curve indicated a high specificity of 85% for the differential indicators. These results suggest that the abnormal brain function of the depressed college students is related to the change of functional connectivity in the left hemisphere, especially α frequency band in the frontal region, which is of great significance for the diagnosis of depression in the future.
Brain/physiology* ; Brain Mapping/methods* ; Depression ; Electroencephalography ; Female ; Humans ; Students

In this paper, we describe a study on visualization of SW atlases. Firstly, data structures in axial, coronal and sagittal directions are generated by SW atlases' raw data after pre-processing. Secondly, we produce 3D SW atlases through setting gray intensity and spaces between slices. Thirdly, we integrate the atlas into the neurosurgery navigation system and realize the visualization of SW atlases. Finally, we realize brain anatomy structures labeling and real-time display in neurosurgery navigation system.
Anatomy, Artistic ; Brain Mapping ; Humans ; Neuronavigation ; methods ; Neurosurgery ; methods

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.
Humans ; Epilepsy/surgery* ; Brain/surgery* ; Electrocorticography/methods* ; Drug Resistant Epilepsy/surgery* ; Brain Mapping/methods* ; Electroencephalography/methods*

Connectome/methods* ; Magnetic Resonance Imaging/methods* ; Brain/diagnostic imaging* ; Head ; Brain Mapping/methods* ; Nerve Net

Recent research has highlighted structural and functional abnormalities in the cerebral cortex of patients with premature ejaculation (PE). These anomalies could play a pivotal role in the physiological mechanisms underlying PE. This study leveraged functional magnetic resonance imaging (fMRI), a noninvasive technique, to explore these neural mechanisms. We conducted resting-state fMRI scans on 36 PE patients and 22 healthy controls (HC), and collected data on Premature Ejaculation Diagnostic Tool (PEDT) scores and intravaginal ejaculation latency time (IELT). Employing a surface-based regional homogeneity (ReHo) approach, we analyzed local neural synchronous spontaneous activity, diverging from previous studies that utilized a volume-based ReHo method. Areas with significant ReHo differences between PE and HC groups underwent surface-based functional connectivity (FC) analysis. Significant discrepancies in ReHo and FC across the cortical surface were observed in the PE cohort. Notably, PE patients exhibited decreased ReHo in the left triangular inferior frontal gyrus and enhanced ReHo in the right middle frontal gyrus. The latter showed heightened connectivity with the left lingual gyrus and the right orbital superior frontal gyrus. Furthermore, a correlation between ReHo and FC values with PEDT scores and IELT was found in the PE group. Our findings, derived from surface-based fMRI data, underscore specific brain regions linked to the neurobiological underpinnings of PE.
Male ; Humans ; Premature Ejaculation ; Brain Mapping/methods* ; Brain ; Cerebral Cortex ; Magnetic Resonance Imaging/methods*

The aim of the present study was to explore the specific pattern of brain deactivation elicited by painful stimuli, in contrast with that elicited by tactile stimuli. Functional magnetic resonance imaging (fMRI) data were collected from 62 healthy subjects under painful and tactile stimuli with varying intensities. The brain deactivations under different conditions were identified using the general linear model. Two-way analysis of variance (ANOVA) was performed to test whether there was a significant interaction between perceived stimulus intensity (factor 1: high intensity, low intensity) and stimulus modality (factor 2: pain, touch) on the brain deactivations. The results showed that there were significant interactions between stimulus intensity and stimulus modality on the deactivations of left medial superior frontal gyrus, left middle occipital gyrus, left superior frontal gyrus and right middle occipital gyrus (P < 0.05, Cluster-level FWE). The deactivations induced by painful stimuli with low perceived intensity (β = -3.38 ± 0.52) were significantly stronger than those induced by painful stimuli with high perceived intensity (β = -1.22 ± 0.54) (P < 0.001), whereas the differences between the deactivations induced by tactile stimuli with different perceived intensities were not statistically significant. In addition, there were no significant differences between the deactivations elicited by painful and tactile stimuli with the same stimulus intensities. These results suggest that there is a specific relationship between the deactivations induced by painful stimuli in multiple brain regions (such as the left medial superior frontal gyrus) and the stimulus intensity, providing evidence for a deeper understanding of the brain mechanisms underlying pain perception.
Humans ; Touch/physiology* ; Physical Stimulation/methods* ; Pain ; Brain/physiology* ; Magnetic Resonance Imaging/methods* ; Brain Mapping

The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.
Animals ; Brain/physiology* ; Brain Mapping/methods* ; Neurons/physiology* ; Optical Imaging/methods* ; Mammals