Traumatic brain injury(TBI) is a major contributor of long-term disability and a leading cause of death worldwide. A series of secondary injury cascades can contribute to cell death, tissue loss, and ultimately to the...Traumatic brain injury(TBI) is a major contributor of long-term disability and a leading cause of death worldwide. A series of secondary injury cascades can contribute to cell death, tissue loss, and ultimately to the development of functional impairments. However, there are currently no effective therapeutic interventions that improve brain outcomes following TBI. As a result, a number of experimental TBI models have been developed to recapitulate TBI injury mechanisms and to test the efficacy of potential therapeutics. The pig model has recently come to the forefront as the pig brain is closer in size, structure, and composition to the human brain compared to traditional rodent models, making it an ideal large animal model to study TBI pathophysiology and functional outcomes. This review will focus on the shared characteristics between humans and pigs that make them ideal for modeling TBI and will review the three most common pig TBI models–the diffuse axonal injury, the controlled cortical impact, and the fluid percussion models. It will also review current advances in functional outcome assessment measures and other non-invasive, translational TBI detection and measurement tools like biomarker analysis and magnetic resonance imaging. The use of pigs as TBI models and the continued development and improvement of translational assessment modalities have made significant contributions to unraveling the complex cascade of TBI sequela and provide an important means to study potential clinically relevant therapeutic interventions.展开更多
Neurostimulation remarkably alleviates the symptoms in a variety of brain disorders by modulating the brain-wide network. However, how brain-wide effects on the direct and indirect pathways evoked by focal neurostimul...Neurostimulation remarkably alleviates the symptoms in a variety of brain disorders by modulating the brain-wide network. However, how brain-wide effects on the direct and indirect pathways evoked by focal neurostimulation elicit therapeutic effects in an individual patient is unknown. Understanding this remains crucial for advancing neural circuit-based guidance to optimize candidate patient screening, pre-surgical target selection, and post-surgical parameter tuning. To address this issue, we propose a functional brain connectome-based modeling approach that simulates the spreading effects of stimulating different brain regions and quantifies the rectification of abnormal network topology in silico. We validated these analyses by pinpointing nuclei in the basal ganglia circuits as top-ranked targets for 43 local patients with Parkinson’s disease and 90 patients from a public database. Individual connectome-based analysis demonstrated that the globus pallidus was the best choice for 21.1% and the subthalamic nucleus for 19.5% of patients. Down-regulation of functional connectivity(up to 12%) at these prioritized targets optimally maximized the therapeutic effects. Notably, the priority rank of the subthalamic nucleus significantly correlated with motor symptom severity(Unified Parkinson’s Disease Rating Scale III) in the local cohort. These findings underscore the potential of neural network modeling for advancing personalized brain stimulation therapy,and warrant future experimental investigation to validate its clinical utility.展开更多
Traumatic brain injury(TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments;ho...Traumatic brain injury(TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments;however, identification of specific magnetic resonance imaging(MRI) biomarkers that are most reflective of injury severity and functional prognosis remain elusive. Therefore, the objective of this study was to utilize advanced statistical approaches to identify clinically relevant MRI biomarkers and predict functional outcomes using MRI metrics in a translational large animal piglet TBI model. TBI was induced via controlled cortical impact and multiparametric MRI was performed at 24 hours and 12 weeks post-TBI using T1-weighted, T2-weighted, T2-weighted fluid attenuated inversion recovery, diffusion-weighted imaging, and diffusion tensor imaging. Changes in spatiotemporal gait parameters were also assessed using an automated gait mat at 24 hours and 12 weeks post-TBI. Principal component analysis was performed to determine the MRI metrics and spatiotemporal gait parameters that explain the largest sources of variation within the datasets. We found that linear combinations of lesion size and midline shift acquired using T2-weighted imaging explained most of the variability of the data at both 24 hours and 12 weeks post-TBI. In addition, linear combinations of velocity, cadence, and stride length were found to explain most of the gait data variability at 24 hours and 12 weeks post-TBI. Linear regression analysis was performed to determine if MRI metrics are predictive of changes in gait. We found that both lesion size and midline shift are significantly correlated with decreases in stride and step length. These results from this study provide an important first step at identifying relevant MRI and functional biomarkers that are predictive of functional outcomes in a clinically relevant piglet TBI model. This study was approved by the University of Georgia Institutional Animal Care and Use Committee(AUP: A2015 11-001) on December 22, 2015.展开更多
Human life span has dramatically increased over several decades,and the quality of life has been considered to be equally important.However,diabetes mellitus(DM) characterized by problems related to insulin secretion ...Human life span has dramatically increased over several decades,and the quality of life has been considered to be equally important.However,diabetes mellitus(DM) characterized by problems related to insulin secretion and recognition has become a serious health problem in recent years that threatens human health by causing decline in brain functions and finally leading to neurodegenerative diseases.Exercise is recognized as an effective therapy for DM without medication administration.Exercise studiesusing experimental animals are a suitable option to overcome this drawback,and animal studies have improved continuously according to the needs of the experimenters.Since brain health is the most significant factor in human life,it is very important to assess brain functions according to the different exercise conditions using experimental animal models.Generally,there are two types of DM; insulin-dependent type 1 DM and an insulin-independent type 2 DM(T2DM); however,the author will mostly discuss brain functions in T2 DM animal models in this review.Additionally,many physiopathologic alterations are caused in the brain by DM such as increased adiposity,inflammation,hormonal dysregulation,uncontrolled hyperphagia,insulin and leptin resistance,and dysregulation of neurotransmitters and declined neurogenesis in the hippocampus and we describe how exercise corrects these alterations in animal models.The results of changes in the brain environment differ according to voluntary,involuntary running exercises and resistance exercise,and gender in the animal studies.These factors have been mentioned in this review,and this review will be a good reference for studying how exercise can be used with therapy for treating DM.展开更多
The number of common neighbor between nodes is applied to the modeling of resting-state brain function network in order to analyze the effect of anatomical distance on the modeling of resting-state brain function netw...The number of common neighbor between nodes is applied to the modeling of resting-state brain function network in order to analyze the effect of anatomical distance on the modeling of resting-state brain function network. Three models based on anatomical distance, the number of common neighbor, or anatomical distance and the number of common neighbor are designed. Basing on residuals creates the evaluation criteria for selecting the optimal brain function model network in each class model. The model is selected to simulate the human real brain function network by comparison with real data functional magnetic resonance imaging(f MRI)network. Finally, the result shows that the best model only is based on anatomical distance.展开更多
The motor relearning program can significantly improve various functional disturbance induced by ischemic cerebrovascular diseases. However, its mechanism of action remains poorly understood. In injured brain tissues,...The motor relearning program can significantly improve various functional disturbance induced by ischemic cerebrovascular diseases. However, its mechanism of action remains poorly understood. In injured brain tissues, glial fibrillary acidic protein and neurofilament protein changes can reflect the condition of injured neurons and astrocytes, while vascular endothelial growth factor and basic fibroblast growth factor changes can indicate angiogenesis. In the present study, we induced ischemic brain injury in the rhesus macaque by electrocoagulation of the M1 segment of the right middle cerebral artery. The motor relearning program was conducted for 60 days from the third day after model establishment. Immunohistochemistry and single-photon emission CT showed that the numbers of glial fibrillary acidic protein-, neurofilament protein-, vascular endothelial growth factor- and basic fibroblast growth factor-positive cells were significantly increased in the infarcted side compared with the contralateral hemisphere following the motor relearning program. Moreover, cerebral blood flow in the infarcted side was significantly improved. The clinical rating scale for stroke was used to assess neurological function changes in the rhesus macaque following the motor relearning program. Results showed that motor function was improved, and problems with consciousness, self-care ability and balance function were significantly ameliorated. These findings indicate that the motor relearning program significantly promoted neuronal regeneration, repair and angiogenesis in the surroundings of the infarcted hemisphere, and improve neurological function in the rhesus macaque following brain ischemia.展开更多
Brain encoding and decoding via functional magnetic resonance imaging(fMRI)are two important aspects of visual perception neuroscience.Although previous researchers have made significant advances in brain encoding and...Brain encoding and decoding via functional magnetic resonance imaging(fMRI)are two important aspects of visual perception neuroscience.Although previous researchers have made significant advances in brain encoding and decoding models,existing methods still require improvement using advanced machine learning techniques.For example,traditional methods usually build the encoding and decoding models separately,and are prone to overfitting on a small dataset.In fact,effectively unifying the encoding and decoding procedures may allow for more accurate predictions.In this paper,we first review the existing encoding and decoding methods and discuss the potential advantages of a“bidirectional”modeling strategy.Next,we show that there are correspondences between deep neural networks and human visual streams in terms of the architecture and computational rules.Furthermore,deep generative models(e.g.,variational autoencoders(VAEs)and generative adversarial networks(GANs))have produced promising results in studies on brain encoding and decoding.Finally,we propose that the dual learning method,which was originally designed for machine translation tasks,could help to improve the performance of encoding and decoding models by leveraging large-scale unpaired data.展开更多
Functional magnetic resonance imaging(fMRI) is em-ployed in many behavior analysis studies, with blood oxygen level dependent-(BOLD-) contrast imaging being the main method used to generate images. The use of BOLD-con...Functional magnetic resonance imaging(fMRI) is em-ployed in many behavior analysis studies, with blood oxygen level dependent-(BOLD-) contrast imaging being the main method used to generate images. The use of BOLD-contrast imaging in f MRI has been refined over the years, for example, the inclusion of a spin echo pulse and increased magnetic strength were shown to produce better recorded images. Taking careful precautions to control variables during measurement, comparisons between different specimen groups can be illustrated by f MRI imaging using both quantitative and qualitative methods. Differences have been observed in comparisons of active and resting, developing and aging, and defective and damaged brains in various studies. However, cognitive studies using f MRI still face a number of challenges in interpretation that can only be overcome by imaging large numbers of samples. Furthermore, f MRI studies of brain cancer, lesions and other brain pathologies of both humans and animals are still to be explored.展开更多
The purpose of the paper is to provide a way to model the brain functional network based on the complex networks with brain anatomical architecture. We introduce the brain structural and functional researches, and del...The purpose of the paper is to provide a way to model the brain functional network based on the complex networks with brain anatomical architecture. We introduce the brain structural and functional researches, and delineate the brain anatomical and functional networks based on complex networks, then we discuss the brain functional complex network models; at last we put forward the brain functional networks modeling process and the data processing with fMRI （functional magnetic resonance imaging） in detailed.展开更多
Transcranial direct current stimulation(tDCS)is a promising method for altering cortical excitability with clinical implications.It has been increasingly used in neurodevelopmental disorders,especially attention-defic...Transcranial direct current stimulation(tDCS)is a promising method for altering cortical excitability with clinical implications.It has been increasingly used in neurodevelopmental disorders,especially attention-deficit hyperactivity disorder(ADHD),but its efficacy(based on effect size calculations),safety,and stimulation parameters have not been systematically examined.In this systematic review,we aimed to(1)explore the effectiveness of tDCS on the clinical symptoms and neuropsychological deficits of ADHD patients,(2)evaluate the safety of tDCS application,especially in children with ADHD,(3)model the electrical field intensity in the target regions based on the commonly-applied and effective versus less-effective protocols,and(4)discuss and propose advanced tDCS parameters.Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach,a literature search identified 14 empirical experiments investigating tDCS effects in ADHD.Partial improving effects of tDCS on cognitive deficits(response inhibition,working memory,attention,and cognitive flexibility)or clinical symptoms(e.g.,impulsivity and inattention)are reported in10 studies.No serious adverse effects are reported in 747 sessions of tDCS.The left and right dorsolateral prefrontal cortex are the regions most often targeted,and anodal tDCS the protocol most often applied.An intensity of 2 mA induced stronger electrical fields than 1 mA in adults with ADHD and was associated with significant behavioral changes.In ADHD children,however,the electrical field induced by 1 mA,which is likely larger than the electrical field induced by 1 mA in adults due to the smaller head size of children,was sufficient to result in significant behavioral change.Overall,tDCS seems to be a promising method for improving ADHD deficits.However,the clinical utility of tDCS in ADHD cannot yet be concluded and requires further systematic investigation in larger sample sizes.Cortical regions involved in ADHD pathophysiology,stimulation parameters(e.g.intensity,duration,polarity,and electrode size),and types of symptom/deficit are potential determinants of tDCS efficacy in ADHD.Developmental aspects of tDCS in childhood ADHD should be considered as well.展开更多
Recent studies have shown that microglia/macrophages and astrocytes can mediate synaptic phagocytosis through the MER proto-oncokinase in developmental or stroke models,but it is unclear whether the same mechanism is ...Recent studies have shown that microglia/macrophages and astrocytes can mediate synaptic phagocytosis through the MER proto-oncokinase in developmental or stroke models,but it is unclear whether the same mechanism is also active in traumatic brain injury.In this study,we established a mouse model of traumatic brain injury and found that both microglia/macrophages and astrocytes phagocytosed synapses and expression of the MER proto-oncokinase increased 14 days after injury.Specific knockout of MER in microglia/macrophages or astrocytes markedly reduced injury volume and greatly improved neurobehavioral function.In addition,in both microglia/macrophages-specific and astrocytes-specific MER knock-out mice,the number of microglia/macrophage and astrocyte phagocytosing synapses was markedly decreased,and the total number of dendritic spines was increased.Our study suggested that MER proto-oncokinase expression in microglia/macrophages and astrocytes may play an important role in synaptic phagocytosis,and inhibiting this process could be a new strategy for treating traumatic brain injury.展开更多
Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal d...Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.展开更多
AIM To establish a rat model of anxiety-like gastric hyper-sensitivity(GHS) of functional dyspepsia(FD) induced by novel sequential stress.METHODS Animal pups were divided into two groups from postnatal day 2: control...AIM To establish a rat model of anxiety-like gastric hyper-sensitivity(GHS) of functional dyspepsia(FD) induced by novel sequential stress.METHODS Animal pups were divided into two groups from postnatal day 2: controls and the sequential-stress-treated. The sequential-stress-treated group received maternal separation and acute gastric irritation early in life and restraint stress in adulthood; controls were reared undisturbed with their mothers. Rats in both groups were followed to adulthood(8 wk) at which point the anxietylike behaviors and visceromotor responses to gastric distention(20-100 mm Hg) and gastric emptying were tested. Meanwhile, alterations in several anxiety-related brain-stomach modulators including 5-hydroxytryptamine(5-HT), γ-aminobutyric acid(GABA), brain-derived neurotrophic factor(BDNF) and nesfatin-1 in the rat hippocampus, plasma and gastric fundus and the 5-HT1 A receptor(5-HT1 AR) in the hippocampal CA1 subfield and the mucosa of the gastric fundus were examined.RESULTS Sequential-stress-treated rats simultaneously demonstrated anxiety-like behaviors and GHS in dose-dependent manner compared with the control group. Although rats in both groups consumed similar amount of solid food, the rate of gastric emptying was lower in the sequentialstress-treated rats than in the control group. Sequential stress significantly decreased the levels of 5-HT(51.91 ± 1.88 vs 104.21 ± 2.88, P < 0.01), GABA(2.38 ± 0.16 vs 5.01 ± 0.13, P < 0.01) and BDNF(304.40 ± 10.16 vs 698.17 ± 27.91, P < 0.01) in the hippocampus but increased the content of nesfatin-1(1961.38 ± 56.89 vs 1007.50 ± 33.05, P < 0.01) in the same site; significantly decreased the levels of 5-HT(47.82 ± 2.29 vs 89.45 ± 2.61, P < 0.01) and BDNF(257.05 ± 12.89 vs 536.71 ± 20.73, P < 0.01) in the plasma but increased the content of nesfatin-1 in it(1391.75 ± 42.77 vs 737.88 ± 33.15, P < 0.01); significantly decreased the levels of 5-HT(41.15 ± 1.81 vs 89.17 ± 2.31, P < 0.01) and BDNF(226.49 ± 12.10 vs 551.36 ± 16.47, P < 0.01) in the gastric fundus but increased the content of nesfatin-1 in the same site(1534.75 ± 38.52 vs 819.63 ± 38.04, P < 0.01). The expressions of 5-HT1 AR in the hippocampal CA1 subfield and the mucosa of the gastric fundus were down-regulated measured by IHC(Optical Density value: Hippocampus 15253.50 ± 760.35 vs 21149.75 ± 834.13; gastric fundus 15865.25 ± 521.24 vs 23865.75 ± 1868.60; P < 0.05, respectively) and WB(0.38 ± 0.01 vs 0.57 ± 0.03, P < 0.01)(n = 8 in each group). CONCLUSION Sequential stress could induce a potential rat model of anxiety-like GHS of FD, which could be used to research the mechanisms of this intractable disease.展开更多
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
文摘Traumatic brain injury(TBI) is a major contributor of long-term disability and a leading cause of death worldwide. A series of secondary injury cascades can contribute to cell death, tissue loss, and ultimately to the development of functional impairments. However, there are currently no effective therapeutic interventions that improve brain outcomes following TBI. As a result, a number of experimental TBI models have been developed to recapitulate TBI injury mechanisms and to test the efficacy of potential therapeutics. The pig model has recently come to the forefront as the pig brain is closer in size, structure, and composition to the human brain compared to traditional rodent models, making it an ideal large animal model to study TBI pathophysiology and functional outcomes. This review will focus on the shared characteristics between humans and pigs that make them ideal for modeling TBI and will review the three most common pig TBI models–the diffuse axonal injury, the controlled cortical impact, and the fluid percussion models. It will also review current advances in functional outcome assessment measures and other non-invasive, translational TBI detection and measurement tools like biomarker analysis and magnetic resonance imaging. The use of pigs as TBI models and the continued development and improvement of translational assessment modalities have made significant contributions to unraveling the complex cascade of TBI sequela and provide an important means to study potential clinically relevant therapeutic interventions.
基金supported by the Strategic Priority Research Program (B) of the Chinese Academy of Sciences (XDB02050006)the National Natural Science Foundation of China (81571300, 81527901, 31771174, 81271518 and 81471387)+4 种基金the National Key R&D Program of China (2017YFC1310400)the Natural Science Foundation and Major Basic Research Program of Shanghai (16JC1420100)the support from Shanghai JiaoTong University School of Medicine Institute of Neuroscience Research Center for Brain Disordersthe Shanghai JiaoTong University K.C. Wong Medical Fellowship Fundfunded by the Michael J. Fox Foundation for Parkinson’s Research
文摘Neurostimulation remarkably alleviates the symptoms in a variety of brain disorders by modulating the brain-wide network. However, how brain-wide effects on the direct and indirect pathways evoked by focal neurostimulation elicit therapeutic effects in an individual patient is unknown. Understanding this remains crucial for advancing neural circuit-based guidance to optimize candidate patient screening, pre-surgical target selection, and post-surgical parameter tuning. To address this issue, we propose a functional brain connectome-based modeling approach that simulates the spreading effects of stimulating different brain regions and quantifies the rectification of abnormal network topology in silico. We validated these analyses by pinpointing nuclei in the basal ganglia circuits as top-ranked targets for 43 local patients with Parkinson’s disease and 90 patients from a public database. Individual connectome-based analysis demonstrated that the globus pallidus was the best choice for 21.1% and the subthalamic nucleus for 19.5% of patients. Down-regulation of functional connectivity(up to 12%) at these prioritized targets optimally maximized the therapeutic effects. Notably, the priority rank of the subthalamic nucleus significantly correlated with motor symptom severity(Unified Parkinson’s Disease Rating Scale III) in the local cohort. These findings underscore the potential of neural network modeling for advancing personalized brain stimulation therapy,and warrant future experimental investigation to validate its clinical utility.
基金Financial support was provided by the University of Georgia Office of the Vice President for Research to FDW。
文摘Traumatic brain injury(TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments;however, identification of specific magnetic resonance imaging(MRI) biomarkers that are most reflective of injury severity and functional prognosis remain elusive. Therefore, the objective of this study was to utilize advanced statistical approaches to identify clinically relevant MRI biomarkers and predict functional outcomes using MRI metrics in a translational large animal piglet TBI model. TBI was induced via controlled cortical impact and multiparametric MRI was performed at 24 hours and 12 weeks post-TBI using T1-weighted, T2-weighted, T2-weighted fluid attenuated inversion recovery, diffusion-weighted imaging, and diffusion tensor imaging. Changes in spatiotemporal gait parameters were also assessed using an automated gait mat at 24 hours and 12 weeks post-TBI. Principal component analysis was performed to determine the MRI metrics and spatiotemporal gait parameters that explain the largest sources of variation within the datasets. We found that linear combinations of lesion size and midline shift acquired using T2-weighted imaging explained most of the variability of the data at both 24 hours and 12 weeks post-TBI. In addition, linear combinations of velocity, cadence, and stride length were found to explain most of the gait data variability at 24 hours and 12 weeks post-TBI. Linear regression analysis was performed to determine if MRI metrics are predictive of changes in gait. We found that both lesion size and midline shift are significantly correlated with decreases in stride and step length. These results from this study provide an important first step at identifying relevant MRI and functional biomarkers that are predictive of functional outcomes in a clinically relevant piglet TBI model. This study was approved by the University of Georgia Institutional Animal Care and Use Committee(AUP: A2015 11-001) on December 22, 2015.
基金Supported by Fund of Soonchunhyang University,South Korea
文摘Human life span has dramatically increased over several decades,and the quality of life has been considered to be equally important.However,diabetes mellitus(DM) characterized by problems related to insulin secretion and recognition has become a serious health problem in recent years that threatens human health by causing decline in brain functions and finally leading to neurodegenerative diseases.Exercise is recognized as an effective therapy for DM without medication administration.Exercise studiesusing experimental animals are a suitable option to overcome this drawback,and animal studies have improved continuously according to the needs of the experimenters.Since brain health is the most significant factor in human life,it is very important to assess brain functions according to the different exercise conditions using experimental animal models.Generally,there are two types of DM; insulin-dependent type 1 DM and an insulin-independent type 2 DM(T2DM); however,the author will mostly discuss brain functions in T2 DM animal models in this review.Additionally,many physiopathologic alterations are caused in the brain by DM such as increased adiposity,inflammation,hormonal dysregulation,uncontrolled hyperphagia,insulin and leptin resistance,and dysregulation of neurotransmitters and declined neurogenesis in the hippocampus and we describe how exercise corrects these alterations in animal models.The results of changes in the brain environment differ according to voluntary,involuntary running exercises and resistance exercise,and gender in the animal studies.These factors have been mentioned in this review,and this review will be a good reference for studying how exercise can be used with therapy for treating DM.
基金the National Natural Science Foundation of China(Nos.6117013661373101+3 种基金61472270 and61402318)the Natural Science Foundation of Shanxi(No.2014021022-5)the Special/Youth Foundation of Taiyuan University of Technology(No.2012L014)the Youth Team Fund of Taiyuan University of Technology(Nos.2013T047 and 2013T048)
文摘The number of common neighbor between nodes is applied to the modeling of resting-state brain function network in order to analyze the effect of anatomical distance on the modeling of resting-state brain function network. Three models based on anatomical distance, the number of common neighbor, or anatomical distance and the number of common neighbor are designed. Basing on residuals creates the evaluation criteria for selecting the optimal brain function model network in each class model. The model is selected to simulate the human real brain function network by comparison with real data functional magnetic resonance imaging(f MRI)network. Finally, the result shows that the best model only is based on anatomical distance.
基金supported by the Combined pecific Foundation of Department of Science and Technology of Yunnan Province and Kunming Medical University,No.2008CD037
文摘The motor relearning program can significantly improve various functional disturbance induced by ischemic cerebrovascular diseases. However, its mechanism of action remains poorly understood. In injured brain tissues, glial fibrillary acidic protein and neurofilament protein changes can reflect the condition of injured neurons and astrocytes, while vascular endothelial growth factor and basic fibroblast growth factor changes can indicate angiogenesis. In the present study, we induced ischemic brain injury in the rhesus macaque by electrocoagulation of the M1 segment of the right middle cerebral artery. The motor relearning program was conducted for 60 days from the third day after model establishment. Immunohistochemistry and single-photon emission CT showed that the numbers of glial fibrillary acidic protein-, neurofilament protein-, vascular endothelial growth factor- and basic fibroblast growth factor-positive cells were significantly increased in the infarcted side compared with the contralateral hemisphere following the motor relearning program. Moreover, cerebral blood flow in the infarcted side was significantly improved. The clinical rating scale for stroke was used to assess neurological function changes in the rhesus macaque following the motor relearning program. Results showed that motor function was improved, and problems with consciousness, self-care ability and balance function were significantly ameliorated. These findings indicate that the motor relearning program significantly promoted neuronal regeneration, repair and angiogenesis in the surroundings of the infarcted hemisphere, and improve neurological function in the rhesus macaque following brain ischemia.
基金This work was supported by the National Key Research and Development Program of China(2018YFC2001302)National Natural Science Foundation of China(91520202)+2 种基金Chinese Academy of Sciences Scientific Equipment Development Project(YJKYYQ20170050)Beijing Municipal Science and Technology Commission(Z181100008918010)Youth Innovation Promotion Association of Chinese Academy of Sciences,and Strategic Priority Research Program of Chinese Academy of Sciences(XDB32040200).
文摘Brain encoding and decoding via functional magnetic resonance imaging(fMRI)are two important aspects of visual perception neuroscience.Although previous researchers have made significant advances in brain encoding and decoding models,existing methods still require improvement using advanced machine learning techniques.For example,traditional methods usually build the encoding and decoding models separately,and are prone to overfitting on a small dataset.In fact,effectively unifying the encoding and decoding procedures may allow for more accurate predictions.In this paper,we first review the existing encoding and decoding methods and discuss the potential advantages of a“bidirectional”modeling strategy.Next,we show that there are correspondences between deep neural networks and human visual streams in terms of the architecture and computational rules.Furthermore,deep generative models(e.g.,variational autoencoders(VAEs)and generative adversarial networks(GANs))have produced promising results in studies on brain encoding and decoding.Finally,we propose that the dual learning method,which was originally designed for machine translation tasks,could help to improve the performance of encoding and decoding models by leveraging large-scale unpaired data.
文摘Functional magnetic resonance imaging(fMRI) is em-ployed in many behavior analysis studies, with blood oxygen level dependent-(BOLD-) contrast imaging being the main method used to generate images. The use of BOLD-contrast imaging in f MRI has been refined over the years, for example, the inclusion of a spin echo pulse and increased magnetic strength were shown to produce better recorded images. Taking careful precautions to control variables during measurement, comparisons between different specimen groups can be illustrated by f MRI imaging using both quantitative and qualitative methods. Differences have been observed in comparisons of active and resting, developing and aging, and defective and damaged brains in various studies. However, cognitive studies using f MRI still face a number of challenges in interpretation that can only be overcome by imaging large numbers of samples. Furthermore, f MRI studies of brain cancer, lesions and other brain pathologies of both humans and animals are still to be explored.
基金The authors thank the College of Information and Engineering Taishan Medical University colleagues for assistance with data collection and the manuscript comments. Special thanks to Polly and Xiaochen Xu for suggestions on writing in the English language. The authors are grateful to the anonymous referees for their valuable comments and suggestions. This research was supported by the Natural Science Foundation of Shandong （No. ZR2013FL031）, State Accident Prevention Key Technology of Work Safety Program （No. 2013-084）, Work Safety Science Technology Development Program of Shandong （No. LAJK2013-137）, High-level Training Project of Taishan Medical University （No. 2013GCC09）.
文摘The purpose of the paper is to provide a way to model the brain functional network based on the complex networks with brain anatomical architecture. We introduce the brain structural and functional researches, and delineate the brain anatomical and functional networks based on complex networks, then we discuss the brain functional complex network models; at last we put forward the brain functional networks modeling process and the data processing with fMRI （functional magnetic resonance imaging） in detailed.
基金This review was supported by the Department of Psychology and Neurosciences,Leibniz-Institut fiir Arbeitsforschung Ministry of Science,Research and Technology,Deputy of Scholarship and Students Affairs,Iran(95000171)the German Ministry of Research and Education(German Center for Brain Stimulation grant number 01EE1403C).
文摘Transcranial direct current stimulation(tDCS)is a promising method for altering cortical excitability with clinical implications.It has been increasingly used in neurodevelopmental disorders,especially attention-deficit hyperactivity disorder(ADHD),but its efficacy(based on effect size calculations),safety,and stimulation parameters have not been systematically examined.In this systematic review,we aimed to(1)explore the effectiveness of tDCS on the clinical symptoms and neuropsychological deficits of ADHD patients,(2)evaluate the safety of tDCS application,especially in children with ADHD,(3)model the electrical field intensity in the target regions based on the commonly-applied and effective versus less-effective protocols,and(4)discuss and propose advanced tDCS parameters.Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach,a literature search identified 14 empirical experiments investigating tDCS effects in ADHD.Partial improving effects of tDCS on cognitive deficits(response inhibition,working memory,attention,and cognitive flexibility)or clinical symptoms(e.g.,impulsivity and inattention)are reported in10 studies.No serious adverse effects are reported in 747 sessions of tDCS.The left and right dorsolateral prefrontal cortex are the regions most often targeted,and anodal tDCS the protocol most often applied.An intensity of 2 mA induced stronger electrical fields than 1 mA in adults with ADHD and was associated with significant behavioral changes.In ADHD children,however,the electrical field induced by 1 mA,which is likely larger than the electrical field induced by 1 mA in adults due to the smaller head size of children,was sufficient to result in significant behavioral change.Overall,tDCS seems to be a promising method for improving ADHD deficits.However,the clinical utility of tDCS in ADHD cannot yet be concluded and requires further systematic investigation in larger sample sizes.Cortical regions involved in ADHD pathophysiology,stimulation parameters(e.g.intensity,duration,polarity,and electrode size),and types of symptom/deficit are potential determinants of tDCS efficacy in ADHD.Developmental aspects of tDCS in childhood ADHD should be considered as well.
基金supported by the National Key R&D Program of China,No.2019YFA0112000(to YHT)the National Natural Science Foundation of China,Nos.82071284(to YHT),81974179(to ZJZ)+4 种基金Shanghai Rising-Star Program,No.21QA1405200(to YHT)the Scientific Research and Innovation Program of Shanghai Education Commission,No.2019-01-07-00-02-E00064(to GYY)Scientific and Technological Innovation Act Program of Shanghai Science and Technology Commission,No.20JC1411900(to GYY)the Notional Research Foundation of Korea,Nos.2020M3E5D9079912(to WSC),2021R1A2C3005704(to WSC),2022M3E5E8081188(to WSC)the Korea Health Technology R&D Project,No.HU20C0290(to WSC)。
文摘Recent studies have shown that microglia/macrophages and astrocytes can mediate synaptic phagocytosis through the MER proto-oncokinase in developmental or stroke models,but it is unclear whether the same mechanism is also active in traumatic brain injury.In this study,we established a mouse model of traumatic brain injury and found that both microglia/macrophages and astrocytes phagocytosed synapses and expression of the MER proto-oncokinase increased 14 days after injury.Specific knockout of MER in microglia/macrophages or astrocytes markedly reduced injury volume and greatly improved neurobehavioral function.In addition,in both microglia/macrophages-specific and astrocytes-specific MER knock-out mice,the number of microglia/macrophage and astrocyte phagocytosing synapses was markedly decreased,and the total number of dendritic spines was increased.Our study suggested that MER proto-oncokinase expression in microglia/macrophages and astrocytes may play an important role in synaptic phagocytosis,and inhibiting this process could be a new strategy for treating traumatic brain injury.
基金supported by the Natural Science Foundation of Sichuan Province of China,Nos.2022NSFSC1545 (to YG),2022NSFSC1387 (to ZF)the Natural Science Foundation of Chongqing of China,Nos.CSTB2022NSCQ-LZX0038,cstc2021ycjh-bgzxm0035 (both to XT)+3 种基金the National Natural Science Foundation of China,No.82001378 (to XT)the Joint Project of Chongqing Health Commission and Science and Technology Bureau,No.2023QNXM009 (to XT)the Science and Technology Research Program of Chongqing Education Commission of China,No.KJQN202200435 (to XT)the Chongqing Talents:Exceptional Young Talents Project,No.CQYC202005014 (to XT)。
文摘Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.
文摘AIM To establish a rat model of anxiety-like gastric hyper-sensitivity(GHS) of functional dyspepsia(FD) induced by novel sequential stress.METHODS Animal pups were divided into two groups from postnatal day 2: controls and the sequential-stress-treated. The sequential-stress-treated group received maternal separation and acute gastric irritation early in life and restraint stress in adulthood; controls were reared undisturbed with their mothers. Rats in both groups were followed to adulthood(8 wk) at which point the anxietylike behaviors and visceromotor responses to gastric distention(20-100 mm Hg) and gastric emptying were tested. Meanwhile, alterations in several anxiety-related brain-stomach modulators including 5-hydroxytryptamine(5-HT), γ-aminobutyric acid(GABA), brain-derived neurotrophic factor(BDNF) and nesfatin-1 in the rat hippocampus, plasma and gastric fundus and the 5-HT1 A receptor(5-HT1 AR) in the hippocampal CA1 subfield and the mucosa of the gastric fundus were examined.RESULTS Sequential-stress-treated rats simultaneously demonstrated anxiety-like behaviors and GHS in dose-dependent manner compared with the control group. Although rats in both groups consumed similar amount of solid food, the rate of gastric emptying was lower in the sequentialstress-treated rats than in the control group. Sequential stress significantly decreased the levels of 5-HT(51.91 ± 1.88 vs 104.21 ± 2.88, P < 0.01), GABA(2.38 ± 0.16 vs 5.01 ± 0.13, P < 0.01) and BDNF(304.40 ± 10.16 vs 698.17 ± 27.91, P < 0.01) in the hippocampus but increased the content of nesfatin-1(1961.38 ± 56.89 vs 1007.50 ± 33.05, P < 0.01) in the same site; significantly decreased the levels of 5-HT(47.82 ± 2.29 vs 89.45 ± 2.61, P < 0.01) and BDNF(257.05 ± 12.89 vs 536.71 ± 20.73, P < 0.01) in the plasma but increased the content of nesfatin-1 in it(1391.75 ± 42.77 vs 737.88 ± 33.15, P < 0.01); significantly decreased the levels of 5-HT(41.15 ± 1.81 vs 89.17 ± 2.31, P < 0.01) and BDNF(226.49 ± 12.10 vs 551.36 ± 16.47, P < 0.01) in the gastric fundus but increased the content of nesfatin-1 in the same site(1534.75 ± 38.52 vs 819.63 ± 38.04, P < 0.01). The expressions of 5-HT1 AR in the hippocampal CA1 subfield and the mucosa of the gastric fundus were down-regulated measured by IHC(Optical Density value: Hippocampus 15253.50 ± 760.35 vs 21149.75 ± 834.13; gastric fundus 15865.25 ± 521.24 vs 23865.75 ± 1868.60; P < 0.05, respectively) and WB(0.38 ± 0.01 vs 0.57 ± 0.03, P < 0.01)(n = 8 in each group). CONCLUSION Sequential stress could induce a potential rat model of anxiety-like GHS of FD, which could be used to research the mechanisms of this intractable disease.
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.
