Microglial dynamics during brain development

Microglia are the resident immune cells of the central nervous system （CNS）, In the normal state, microglia have a ramified shape and con- tinuously survey the conditions of the brain.

FREQUENCY-DIFFERENTIATED BRAIN NETWORK DYNAMICS IN REAL WORDS AND PSEUDOWORDS PERCEPTION

Brain mechanisms of lexical-semantic processing have been well researched using electroencephalography(EEG)technique with high temporal resolution.However,the detailed brain dynamics regarding spatial connectivity and the spectral characteristics remain to be clarified.For this reason,this study performed frequency-specific effective connectivity analysis for the EEG recordings during the processing of real and pseudowords.In addition,we introduced f MRI-based network templates into a representational similarity analysis to compare the functional differences between real and pseudowords in different frequency bands.Our results revealed that real words could rapidly activate the brain network for speech perception and complete its comprehension with efficiency,especially when the first syllable of the real word has clear categorical features.In contrast,the pseudowords were delayed in the initiation of speech perception and required a longer time span to retrieve its meaning.The frequency-specific analysis showed that the theta,alpha,and beta rhythms contribute more to semantic processing than the gamma oscillation.These results showed that semantic processing is frequency-specific and time-dependent on the word categories.

Modeling and Analysis of EEG Brain Network in High Altitude Task State

Long-term exposure to high altitude,low pressure and low oxygen will seriously threaten people’s cognitive function.To explore the changes in wholebrain network dynamics during brain activity in long-term high-altitude migrants,EEG signals from three subjects of 75 different altitudes were analyzed using the Stroop experimental paradigm and the network recombination prediction model.The sliding window method was used to explore the dynamic change process of the brain network.At the same time,the time period with significant difference between the brain networks of the altitude group was selected as the real response network to measure the model prediction accuracy.Then,according to different network prediction model rules,the weights of brain network 200 ms before stimulation were updated for each subject.Finally,the prediction model with the least difference between the prediction network and the real response network was selected for each subject.The experimental results showed that the prediction accuracy of the model reach 98.95%,and there is a significant difference in model selection between the elevation groups.It helps to understand the brain dynamics of healthy people,and reveals the abnormal changes in the brain networks of those who have stayed at high altitude for a long time,providing an important reference for the cognitive rehabilitation training of victims ex-posed at high altitude.

Dynamic Organization of Large-scale Functional Brain Networks Supports Interactions Between Emotion and Executive Control

Emotion and executive control are often conceptualized as two distinct modes of human brain functioning.Little,however,is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control,especially their interactions.The amygdala and prefrontal systems have long been thought to play crucial roles in these processes.Recent advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion,executive control,and their interactions.Here,we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based approaches.In this model,dynamic interactions among the executive control network,the salience network,the default mode network,and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes;neural oscillations across multiple frequency bands and the locus coeruleus−norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain networks.This model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions.