AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished...AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.展开更多
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 ...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.展开更多
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.
Objective Using resting-state functional magnetic resonance imaging (rs-fMRI),we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ)and...Objective Using resting-state functional magnetic resonance imaging (rs-fMRI),we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ)and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.展开更多
Brain network control theory(NCT)is a groundbreaking field in neuroscience that employs system engineering and cybernetics prin-ciples to elucidate and manipulate brain dynamics.This review examined the development an...Brain network control theory(NCT)is a groundbreaking field in neuroscience that employs system engineering and cybernetics prin-ciples to elucidate and manipulate brain dynamics.This review examined the development and applications of NCT over the past decade.We highlighted how NCT has been effectively utilized to model brain dynamics,offering new insights into cognitive control,brain development,the pathophysiology of neurological and psychiatric disorders,and neuromodulation.Additionally,we summa-rized the practical implementation of NCT using the nctpy package.We also presented the doubts and challenges associated with NCT and efforts made to provide better empirical validations and biological underpinnings.Finally,we outlined future directions for NCT,covering its development and applications.展开更多
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...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.展开更多
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-altitu...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.展开更多
基金Supported by National Natural Science Foundation of China(No.82160195No.82460203)Key R&D Program of Jiangxi Province(No.20223BBH80014).
文摘AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.
基金supported by the National Natural Science Foundation of China(31920103009,32371104,and 32130045)the Major Project of National Social Science Foundation(20&ZD153)the Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions(2023SHIBS0003).
文摘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.
文摘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.
文摘Objective Using resting-state functional magnetic resonance imaging (rs-fMRI),we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ)and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.
基金supported by Research Start-up Fund of USTC,National Natural Science Foundation of China(grant number 82271491)National Key R&D Program of China(2023YFC3341302).
文摘Brain network control theory(NCT)is a groundbreaking field in neuroscience that employs system engineering and cybernetics prin-ciples to elucidate and manipulate brain dynamics.This review examined the development and applications of NCT over the past decade.We highlighted how NCT has been effectively utilized to model brain dynamics,offering new insights into cognitive control,brain development,the pathophysiology of neurological and psychiatric disorders,and neuromodulation.Additionally,we summa-rized the practical implementation of NCT using the nctpy package.We also presented the doubts and challenges associated with NCT and efforts made to provide better empirical validations and biological underpinnings.Finally,we outlined future directions for NCT,covering its development and applications.
基金supported partially by JSPS KAKENHI Grant(20K11883)
文摘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.
基金This work was supported by the Next Generation Internet Technology Innovation Project of Celtic Network(No.NGII20181206)the National Natural Science Foundation of China(No.61976150)the Key R&D Projects of Shanxi Province(No.201803D31038).
文摘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.
