Electrophysiological network predicts clinical response to vigabatrin in epileptic spasms.

Purpose: This study aimed to discover electrophysiologic markers correlated with clinical responses to vigabatrin-based treatment in infants with epileptic spasms (ES). Method: The study involved a descriptive analysis of ES patients from a single institution, as well as electroencephalogram (EEG) analyses of 40 samples and 20 age-matched healthy infants. EEG data were acquired during the interictal sleep state prior to the standard treatment. The weighted phase-lag index (wPLI) functional connectivity was explored across frequency and spatial domains, correlating these results with clinical features. Results: Infants with ES exhibited diffuse increases in delta and theta power, differing from healthy controls. For the wPLI analysis, ES subjects exhibited higher global connectivity compared to control subjects. Subjects who responded favorably to treatment were characterized by higher beta connectivity in the parieto-occipital regions, while those with poorer outcomes exhibited lower alpha connectivity in the frontal regions. Individuals with structural neuroimaging abnormalities exhibited correspondingly low functional connectivity, implying that ES patients who maintain adequate structural and functional integrity are more likely to respond favorably to vigabatrin-based treatments. Conclusion: This study highlights the potential utility of EEG functional connectivity analysis in predicting early response to treatments in infants with ES.

Brain Network Research of Skilled Shooters in the Shooting Preparation Stage under the Condition of Limited Sensory Function.

Shooting is a sport dominated by psychological factors. Hence, disturbing the shooter's sensory function during aiming will seriously affect his psychological state and shooting performance. Electroencephalograph (EEG) measurements of 30 skilled marksmen in the shooting preparation stage under noisy disturbance, weak light, and normal conditions were recorded. Therefore, the differences in neural mechanisms in the shooter's brain during shooting aiming in different disturbance conditions were explored using an analytical approach that employs functional connectivity and brain network analysis based on graph theory. The relationship between these brain network characteristics and shooting performance was also compared. The results showed that (1) the average connection strength in the beta frequency band and connection intensity in the left and right temporal lobes of the shooters under noise disturbance were significantly higher than those under the other two conditions, and their brain networks also showed a higher global and local efficiency. In addition, (2) the functional connection intensity in the occipital region of the beta band was higher than that in the normal condition in the weak-light condition. The information interaction in the left parietal region also increased continually during the shooting process. (3) Furthermore, the shooters' eigenvector centrality in the temporal and occipital regions with limited sensory function in the two conditions was lower than those in the normal condition. These findings suggest that noise disturbance activates the arousal level of the shooter's brain and enhances the information processing efficiency of the brain network; however, it increases the mental workload. In weak-light conditions, shooters focus more on visual information processing during aiming and strengthen the inhibition of functions in the brain regions unrelated to shooting behavior. Audiovisual disturbance renders the cortical regions equivalent to the audiovisual perception function in the shooter's brain less important in the entire brain network than in the normal condition. Therefore, these findings reveal the effect of audiovisual disturbance on the functional network of the cortex in the shooting preparation stage and provide a theoretical basis for further understanding the neural mechanism of the shooting process under sensory disturbances.

From Expert to Elite? - Research on Top Archer's EEG Network Topology.

It is not only difficult to be a sports expert but also difficult to grow from a sports expert to a sports elite. Professional athletes are often concerned about the differences between an expert and an elite and how to eventually become an elite athlete. To explore the differences in brain neural mechanism between experts and elites in the process of motor behavior and reveal the internal connection between motor performance and brain activity, we collected and analyzed the electroencephalography (EEG) findings of 14 national archers and 14 provincial archers during aiming and resting states and constructed the EEG brain network of the two archer groups based on weighted phase lag index; the graph theory was used to analyze and compare the network characteristics via local network and global network topologies. The results showed that compared with the expert archers, the elite archers had stronger functional coupling in beta1 and beta2 bands, and the difference was evident in the frontal and central regions; in terms of global characteristics of brain network topology, the average clustering coefficient and global efficiency of elite archers were significantly higher than that of expert archers, and the eigenvector centrality of expert archers was higher; for local characteristics, elite archers had higher local efficient; and the brain network characteristics of expert archers showed a strong correlation with archery performance. This suggests that compared with expert archers, elite archers showed stronger functional coupling, higher integration efficiency of global and local information, and more independent performance in the archery process. These findings reveal the differences in brain electrical network topologies between elite and expert archers in the archery preparation stage, which is expected to provide theoretical reference for further training and promotion of professional athletes.

Differential pattern of brain functional connectome in obsessive-compulsive disorder versus healthy controls.

Researchers believe that recognition of functional impairment in some of brain networks such as frontal-parietal, default mode network (DMN), anterior medial prefrontal cortex (MPFC) and striatal structures could be a beneficial biomarker for diagnosis of obsessive-compulsive disorder (OCD). Although it is well recognized brain functional connectome in OCD patients shows changes, debate still remains on characteristics of the changes. In this regard, little has been done so far to statistically assess the altered pattern using whole brain electroencephalography. In this study, resting state EEG data of 39 outpatients with OCD and 19 healthy controls (HC) were recorded. After, brain functional network was estimated from the cleaned EEG data using the weighted phase lag index algorithm. Output matrices of OCD group and HCs were then statistically compared to represent meaningful differences. Significant differences in functional connectivity pattern were demonstrated in several regions. As expected the most significant changes were observed in frontal cortex, more significant in frontal-temporal connections (between F3 and F7, and T5 regions). These results in OCD patients are consistent with previous studies and confirm the role of frontal and temporal brain regions in OCD.

Age-related changes across the primary and secondary somatosensory areas: an analysis of neuromagnetic oscillatory activities.

OBJECTIVE: Age-related changes are well documented in the primary somatosensory cortex (SI). Based on previous somatosensory evoked potential studies, the amplitude of N20 typically increases with age probably due to cortical disinhibition. However, less is known about age-related change in the secondary somatosensory cortex (SII). The current study quantified age-related changes across SI and SII mainly based on oscillatory activity indices measured with magnetoencephalography. METHODS: We recorded somatosensory evoked magnetic fields (SEFs) to right median nerve stimulation in healthy young and old subjects and assessed major SEF components. Then, we evaluated the phase-locking factor (PLF) for local field synchrony on neural oscillations and the weighted phase-lag index (wPLI) for cortico-cortical synchrony between SI and SII. RESULTS: PLF was significantly increased in SI along with the increased amplitude of N20m in the old subjects. PLF was also increased in SII associated with a shortened peak latency of SEFs. wPLI analysis revealed the increased coherent activity between SI and SII. CONCLUSIONS: Our results suggest that the functional coupling between SI and SII is influenced by the cortical disinhibition due to normal aging. SIGNIFICANCE: We provide the first electrophysiological evidence for age-related changes in oscillatory neural activities across the somatosensory areas.

Resting-state EEG power predicts conflict-related brain activity in internally guided but not in externally guided decision-making.

Most experimental studies of decision-making have specifically examined situations in which a single correct answer exists (externally guided decision-making). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making, e.g. preference judgment). We compared these two different types of decision-making in terms of conflict-monitoring and their relation with resting-state brain activity. Current electroencephalography (EEG) data demonstrated that conflict-related N2 amplitudes (i.e., difference between large-conflict and small-conflict conditions) in externally guided decision-making were modulated by the type of external stimulus (i.e., large-conflict stimulus pair or small-conflict stimulus pair) but were not found to be correlated with resting-state brain activity (i.e. resting-state EEG power). In contrast, conflict-related N2 amplitudes in internally guided decision-making were found to be correlated with resting-state brain activity, but were not found to be modulated by the type of stimulus itself: the degree to which the type of external stimulus modulates the conflict during stimulus encoding varies according to individual differences in intrinsic brain activity. Considering those results comprehensively, we demonstrate for the first time resting-state and stimulus-related differences between externally and internally guided decision-making.