BACKGROUND Mild cognitive impairment(MCI)has a high risk of progression to Alzheimer’s disease.The disease is often accompanied by sleep disorders,and whether sleep disorders have an effect on brain function in patie...BACKGROUND Mild cognitive impairment(MCI)has a high risk of progression to Alzheimer’s disease.The disease is often accompanied by sleep disorders,and whether sleep disorders have an effect on brain function in patients with MCI is unclear.AIM To explore the near-infrared brain function characteristics of MCI with sleep disorders.METHODS A total of 120 patients with MCI(MCI group)and 50 healthy subjects(control group)were selected.All subjects underwent the functional near-infrared spec-troscopy test.Collect baseline data,Mini-Mental State Examination,Montreal Cognitive Assessment scale,fatigue severity scale(FSS)score,sleep parameter,and oxyhemoglobin(Oxy-Hb)concentration and peak time of functional near-infrared spectroscopy test during the task period.The relationship between Oxy-RESULTS Compared with the control group,the FSS score of the MCI group was higher(t=11.310),and the scores of Pittsburgh sleep quality index,sleep time,sleep efficiency,nocturnal sleep disturbance,and daytime dysfunction were higher(Z=-10.518,-10.368,-9.035,-10.661,-10.088).Subjective sleep quality and total sleep time scores were lower(Z=-11.592,-9.924).The sleep efficiency of the MCI group was lower,and the awakening frequency,rem sleep latency period,total sleep time,and oxygen desaturation index were higher(t=5.969,5.829,2.887,3.003,5.937).The Oxy-Hb concentration at T0,T1,and T2 in the MCI group was lower(t=14.940,11.280,5.721),and the peak time was higher(t=18.800,13.350,9.827).In MCI patients,the concentration of Oxy-Hb during T0 was negatively correlated with the scores of Pittsburgh sleep quality index,sleep time,total sleep time,and sleep efficiency(r=-0.611,-0.388,-0.563,-0.356).It was positively correlated with sleep efficiency and total sleep time(r=0.754,0.650),and negatively correlated with oxygen desaturation index(r=-0.561)and FSS score(r=-0.526).All comparisons were P<0.05.CONCLUSION Patients with MCI and sleep disorders have lower near-infrared brain function than normal people,which is related to sleep quality.Clinically,a comprehensive assessment of the near-infrared brain function of patients should be carried out to guide targeted treatment and improve curative effect.展开更多
Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuro...Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuronal damage,it is crucial to find a biomarker to distinguish individuals with these diseases from healthy people.In this study,we construct a brain function network based on electroencephalography data to study changes in AD and MCI patients.Using a graph-theoretical approach,we examine connectivity features and explore their contributions to dementia recognition at edge,node,and network levels.We find that connectivity is reduced in AD and MCI patients compared with healthy controls.We also find that the edge-level features give the best performance when machine learning models are used to recognize dementia.The results of feature selection identify the top 50 ranked edge-level features constituting an optimal subset,which is mainly connected with the frontal nodes.A threshold analysis reveals that the performance of edge-level features is more sensitive to the threshold for the connection strength than that of node-and network-level features.In addition,edge-level features with a threshold of 0 provide the most effective dementia recognition.The K-nearest neighbors(KNN)machine learning model achieves the highest accuracy of 0.978 with the optimal subset when the threshold is 0.Visualization of edge-level features suggests that there are more long connections linking the frontal region with the occipital and parietal regions in AD and MCI patients compared with healthy controls.Our codes are publicly available at https://github.com/Debbie-85/eeg-connectivity.展开更多
Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby c...Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.展开更多
Background: The mechanisms by which acupuncture affects poststroke cognitive impairment (PSCI) remain unclear. Objective: To investigate brain functional network (BFN) changes in patients with PSCI after acupuncture t...Background: The mechanisms by which acupuncture affects poststroke cognitive impairment (PSCI) remain unclear. Objective: To investigate brain functional network (BFN) changes in patients with PSCI after acupuncture therapy. Methods: Twenty-two PSCI patients who underwent acupuncture therapy in our hospital were enrolled as research subjects. Another 14 people matched for age, sex, and education level were included in the normal control (HC) group. All the subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans;the PSCI patients underwent one scan before acupuncture therapy and another after. The network metric difference between PSCI patients and HCs was analyzed via the independent-sample t test, whereas the paired-sample t test was employed to analyze the network metric changes in PSCI patients before vs. after treatment. Results: Small-world network attributes were observed in both groups for sparsities between 0.1 and 0.28. Compared with the HC group, the PSCI group presented significantly lower values for the global topological properties (γ, Cp, and Eloc) of the brain;significantly greater values for the nodal attributes of betweenness centrality in the CUN. L and the HES. R, degree centrality in the SFGdor. L, PCG. L, IPL. L, and HES. R, and nodal local efficiency in the ORBsup. R, ORBsupmed. R, DCG. L, SMG. R, and TPOsup. L;and decreased degree centrality in the MFG. R, IFGoperc. R, and SOG. R. After treatment, PSCI patients presented increased degree centrality in the LING.L, LING.R, and IOG. L and nodal local efficiency in PHG. L, IOG. R, FFG. L, and the HES. L, and decreased betweenness centrality in the PCG. L and CUN. L, degree centrality in the ORBsupmed. R, and nodal local efficiency in ANG. R. Conclusion: Cognitive decline in PSCI patients may be related to BFN disorders;acupuncture therapy may modulate the topological properties of the BFNs of PSCI patients.展开更多
OBJECTIVE: To investigate the effect of brain functional recovery decoction(BFRD) on expression of vascular endothelial growth factor(VEGF) and angiopoietin-1(Ang-1) protein in rats with cerebral ischemia reperfusion ...OBJECTIVE: To investigate the effect of brain functional recovery decoction(BFRD) on expression of vascular endothelial growth factor(VEGF) and angiopoietin-1(Ang-1) protein in rats with cerebral ischemia reperfusion injury, and to explore the mechanism of action of BFRD.METHODS: Using the suture-occlusion method, a Wistar rat model of focal cerebral ischemia reperfusion was established. The rats were randomly divided into treatment group, model group, and sham operation group. The treatment group was administered BFRD. In situ hybridization was used to detect VEGF m RNA expression. Immunohistochemistry was used to observe expression of Ang-1 protein.RESULTS: VEGF mRNA expression was greater in the model group compared with the sham operation group(P < 0.05); Ang-1 protein expression was more obvious in the treatment group than the model group(P < 0.05).CONCLUSION: BFRD promoted VEGF m RNA and Ang-1 protein expression in the brains of rats with cerebral ischemia, suggesting increased angiogenesis.展开更多
Currently,functional connectomes constructed from neuroimaging data have emerged as a powerful tool in identifying brain disorders.If one brain disease just manifests as some cognitive dysfunction,it means that the di...Currently,functional connectomes constructed from neuroimaging data have emerged as a powerful tool in identifying brain disorders.If one brain disease just manifests as some cognitive dysfunction,it means that the disease may affect some local connectivity in the brain functional network.That is,there are functional abnormalities in the sub-network.Therefore,it is crucial to accurately identify them in pathological diagnosis.To solve these problems,we proposed a sub-network extraction method based on graph regularization nonnegative matrix factorization(GNMF).The dynamic functional networks of normal subjects and early mild cognitive impairment(eMCI)subjects were vectorized and the functional connection vectors(FCV)were assembled to aggregation matrices.Then GNMF was applied to factorize the aggregation matrix to get the base matrix,in which the column vectors were restored to a common sub-network and a distinctive sub-network,and visualization and statistical analysis were conducted on the two sub-networks,respectively.Experimental results demonstrated that,compared with other matrix factorization methods,the proposed method can more obviously reflect the similarity between the common subnetwork of eMCI subjects and normal subjects,as well as the difference between the distinctive sub-network of eMCI subjects and normal subjects,Therefore,the high-dimensional features in brain functional networks can be best represented locally in the lowdimensional space,which provides a new idea for studying brain functional connectomes.展开更多
Since the outbreak and spread of corona virus disease 2019(COVID-19),the prevalence of mental disorders,such as depression,has continued to increase.To explore the abnormal changes of brain functional connections in p...Since the outbreak and spread of corona virus disease 2019(COVID-19),the prevalence of mental disorders,such as depression,has continued to increase.To explore the abnormal changes of brain functional connections in patients with depression,this paper proposes a depression analysis method based on brain function network(BFN).To avoid the volume conductor effect,BFN was constructed based on phase lag index(PLI).Then the indicators closely related to depression were selected from weighted BFN based on small-worldness(SW)characteristics and binarization BFN based on the minimum spanning tree(MST).Differences analysis between groups and correlation analysis between these indicators and diagnostic indicators were performed in turn.The resting state electroencephalogram(EEG)data of 24 patients with depression and 29 healthy controls(HC)was used to verify our proposed method.The results showed that compared with HC,the information processing of BFN in patients with depression decreased,and BFN showed a trend of randomization.展开更多
Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenou...Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.展开更多
Objective: To explore the characteristics of brain functional network with anxiety in patients with acute cerebral infarction. Methods: A total of 39 patients with acute cerebral infarction by cranial magnetic resonan...Objective: To explore the characteristics of brain functional network with anxiety in patients with acute cerebral infarction. Methods: A total of 39 patients with acute cerebral infarction by cranial magnetic resonance examination were included, and all the patients were scored by the Hamilton Anxiety Scale. The anxiety scale is scored by a professional psychiatrist. There are a total of 14 items, including anxiety, nervousness, fear, insomnia, cognitive function, depressed mood, somatic anxiety, sensory system, etc. The total score ≥ 29 points may be severe;≥21 points, there must be obvious;≥14 points, there must be anxiety;a score of more than 7 may indicate anxiety. If the score is less than 7, there are no anxiety symptoms. All patients within 24 to 72 hours, complete the head examination magnetic resonance, computerized calculation of the DWI sequence images, according to the results of the calculation to superimpose the image of the lesion, image reconstruction in space, and carry out Binarization, defining the value of lesions as 1, and the value of non as 0. All lesions are superimposed into one image and integrated. The relationship between the lesions in this superimposed image and anxiety after cerebral infarction was analyzed. Results: The lesions were basically concentrated around the lateral ventricle, and they were mainly concentrated around the lateral ventricle. Conclusion: Patients with acute cerebral infarction in the lateral ventricle or basal ganglia are more prone to post-stroke anxiety. This has a certain evaluation value for the prognosis of future cerebral infarction, and has a certain understanding of the exploration of complications, and has a certain understanding of the exploration of complications.展开更多
<strong>Objective</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"><strong>: </strong>To evaluate the clinical value of...<strong>Objective</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"><strong>: </strong>To evaluate the clinical value of transcranial color Doppler ultrasound (TCCD) in assessing cerebral function after cardiopulmonary resuscitation (CPR). </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: A prospective study was conducted in 52 patients with cardiac arrest treated by CPR from January 2018 to January 2020, and its clinical data were analyzed</span></span><span style="font-family:Verdana;">. </span><span style="font-family:;" "=""><span style="font-family:Verdana;">According to classification of cerebral performance category (CPC), 31 cases (CPC grade 1 - 2) were selected in the good prognosis group and 21 cases (CPC grade 3 - 5) in the poor prognosis group. The cerebral blood flow was measured by transcranial Doppler ultrasound (TCCD) 24 h after CPR, and the differences were compared between the two groups in stroke index, diastolic blood flow velocity (Vd), systolic peak blood flow velocity (Vs) and mean peak blood flow velocity (Vm). The ROC curve of cerebral blood flow after CPR was drawn to predict the prognosis of brain function. </span><b><span style="font-family:Verdana;">Results</span></b><span style="font-family:Verdana;">: The data showed that the pulsatility index of middle cerebral artery of the poor prognosis group decreased within 24 h</span></span><span style="font-family:Verdana;">;</span><span style="font-family:Verdana;">the difference between the two groups was statistically significant (p < 0.05);the Vd, Vs, Vm increased in the good prognosis group</span><span style="font-family:Verdana;">;</span><span style="font-family:;" "=""><span style="font-family:Verdana;">the difference between the two groups was statistically significant (p < 0.05). The ROC curve of cerebral blood flow after CPR was drawn to predict the prognosis of brain function, and the results showed that the area under the curve and the optimal critical value of cerebral blood flow were 0.731 and 5.69. The sensitivity and specificity were 67.3% and 79.1% respectively. </span><b><span style="font-family:Verdana;">Conclusion</span></b><span style="font-family:Verdana;">: The cerebral blood flow increase in the early stage of successful CPR is positively correlated with the prognosis of cerebral functional resuscitation. Monitoring intracranial blood flow after CPR by TCCD has clinical value to evaluate prognosis of brain function.</span></span>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 structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot rep...The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.展开更多
To better understand the spatial distribution of brain functions,we need to monitor and analyze neuronal activities.Electrophysiological technique has provided an important method for the exploration of some neural ci...To better understand the spatial distribution of brain functions,we need to monitor and analyze neuronal activities.Electrophysiological technique has provided an important method for the exploration of some neural circuits.However,this method cannot simultaneously detect the activities of nerve cell groups.Therefore,methods that can monitor the spatial distribution of neuronal population activity are demanded to explore brain functions.Voltage-sensitive dyes(VSDs)shift their absorption or emission optical signals in response to different membrane potentials,allowing assessing the global electrical state of neurons.Optical recording technique coupled with VSDs is a promising method to monitor the brain functions by detecting optical signal changes.This review focuses on the fast and slow responses of VSDs to membrane potential changes and optical recordings utilized in the central nervous system.In this review,we attempt to show how VSDs and optical recordings can be used to obtain brain functional monitoring at high spatial and temporal resolution.Understanding of brain functions will not only greatly improve the cognition of information transmission of complex neural network,but also provide new methods of treating brain diseases such as Parkinson’s and Alzheimer’s diseases.展开更多
To investigate the effects of magnetic stimulation at acupoints on brain functional network during mental fatigue, magnetic stimulation was applied to stimulate SHENMEN (HT7), HEGU (LI4) and LAOGONG (PC8) acupoint in ...To investigate the effects of magnetic stimulation at acupoints on brain functional network during mental fatigue, magnetic stimulation was applied to stimulate SHENMEN (HT7), HEGU (LI4) and LAOGONG (PC8) acupoint in this paper. The brain functional networks of normal state, mental fatigue state and stimulated state were constructed and the characteristic parameters were comparatively studied based on the complex network theory. The results showed that the connection of the network was enhanced by stimulating the HT7, LI4 and PC8 acupoint. In conclusion, magnetic stimulation at acupoints can effectively relieve mental fatigue.展开更多
Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representativ...Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.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
Objective:To analyze the effect of ventriculoperitoneal shunt on the recovery of brain function in children with hydrocephalus.Methods:The clinical data of 40 children with hydrocephalus were retrospectively analyzed....Objective:To analyze the effect of ventriculoperitoneal shunt on the recovery of brain function in children with hydrocephalus.Methods:The clinical data of 40 children with hydrocephalus were retrospectively analyzed.Ventriculoperitoneal shunt was performed with 9003 shunt tube and P.S.Shunt tube,B.C.E.shunt tube.Electroencephalogram(EEG),and brain CT/MRI were performed before and after surgery,and postoperative follow-up was carried out to observe the therapeutic effect.Results:In this study,there were seven cases of intracranial injury,seven cases of congenital hydrocephalus,11 cases of ventricular end obstruction,three cases of abdominal end obstruction,nine cases complicated with bacterial infection,and 3 cases of shunt entering the scrotum.The prognosis of all the children was good,and there were no significant changes in eight cases.Conclusion:Ventriculoperitoneal shunt is effective in the treatment of children with hydrocephalus.展开更多
Objective To evaluate the feasibility and safety of the self developed sound outside the ventilation device-esophageal nasopharynx catheter in brain functional areas surgery applications. Methods 13 patients involved ...Objective To evaluate the feasibility and safety of the self developed sound outside the ventilation device-esophageal nasopharynx catheter in brain functional areas surgery applications. Methods 13 patients involved functional areas of brain surgery were chosed. After induction of general anesthesia,the catheters were placed in the esophagus,then connected to anesthesia machines to an external展开更多
Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the...Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.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
文摘BACKGROUND Mild cognitive impairment(MCI)has a high risk of progression to Alzheimer’s disease.The disease is often accompanied by sleep disorders,and whether sleep disorders have an effect on brain function in patients with MCI is unclear.AIM To explore the near-infrared brain function characteristics of MCI with sleep disorders.METHODS A total of 120 patients with MCI(MCI group)and 50 healthy subjects(control group)were selected.All subjects underwent the functional near-infrared spec-troscopy test.Collect baseline data,Mini-Mental State Examination,Montreal Cognitive Assessment scale,fatigue severity scale(FSS)score,sleep parameter,and oxyhemoglobin(Oxy-Hb)concentration and peak time of functional near-infrared spectroscopy test during the task period.The relationship between Oxy-RESULTS Compared with the control group,the FSS score of the MCI group was higher(t=11.310),and the scores of Pittsburgh sleep quality index,sleep time,sleep efficiency,nocturnal sleep disturbance,and daytime dysfunction were higher(Z=-10.518,-10.368,-9.035,-10.661,-10.088).Subjective sleep quality and total sleep time scores were lower(Z=-11.592,-9.924).The sleep efficiency of the MCI group was lower,and the awakening frequency,rem sleep latency period,total sleep time,and oxygen desaturation index were higher(t=5.969,5.829,2.887,3.003,5.937).The Oxy-Hb concentration at T0,T1,and T2 in the MCI group was lower(t=14.940,11.280,5.721),and the peak time was higher(t=18.800,13.350,9.827).In MCI patients,the concentration of Oxy-Hb during T0 was negatively correlated with the scores of Pittsburgh sleep quality index,sleep time,total sleep time,and sleep efficiency(r=-0.611,-0.388,-0.563,-0.356).It was positively correlated with sleep efficiency and total sleep time(r=0.754,0.650),and negatively correlated with oxygen desaturation index(r=-0.561)and FSS score(r=-0.526).All comparisons were P<0.05.CONCLUSION Patients with MCI and sleep disorders have lower near-infrared brain function than normal people,which is related to sleep quality.Clinically,a comprehensive assessment of the near-infrared brain function of patients should be carried out to guide targeted treatment and improve curative effect.
基金supported by the National Natural Science Foundation of China(Grant Nos.62071451,62331025,and U21A20447)the National Key Research and Development Project(Grant No.2021YFC3002204)the CAMS Innovation Fund for Medical Sciences(Grant No.2019-I2M-5-019).
文摘Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuronal damage,it is crucial to find a biomarker to distinguish individuals with these diseases from healthy people.In this study,we construct a brain function network based on electroencephalography data to study changes in AD and MCI patients.Using a graph-theoretical approach,we examine connectivity features and explore their contributions to dementia recognition at edge,node,and network levels.We find that connectivity is reduced in AD and MCI patients compared with healthy controls.We also find that the edge-level features give the best performance when machine learning models are used to recognize dementia.The results of feature selection identify the top 50 ranked edge-level features constituting an optimal subset,which is mainly connected with the frontal nodes.A threshold analysis reveals that the performance of edge-level features is more sensitive to the threshold for the connection strength than that of node-and network-level features.In addition,edge-level features with a threshold of 0 provide the most effective dementia recognition.The K-nearest neighbors(KNN)machine learning model achieves the highest accuracy of 0.978 with the optimal subset when the threshold is 0.Visualization of edge-level features suggests that there are more long connections linking the frontal region with the occipital and parietal regions in AD and MCI patients compared with healthy controls.Our codes are publicly available at https://github.com/Debbie-85/eeg-connectivity.
基金sponsored by the National Defense Science and Technology Key Laboratory Fund(Grant No.61422062205)the Equipment Pre-Research Fund(Grant No.JCKYS2022LD9)。
文摘Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.
文摘Background: The mechanisms by which acupuncture affects poststroke cognitive impairment (PSCI) remain unclear. Objective: To investigate brain functional network (BFN) changes in patients with PSCI after acupuncture therapy. Methods: Twenty-two PSCI patients who underwent acupuncture therapy in our hospital were enrolled as research subjects. Another 14 people matched for age, sex, and education level were included in the normal control (HC) group. All the subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans;the PSCI patients underwent one scan before acupuncture therapy and another after. The network metric difference between PSCI patients and HCs was analyzed via the independent-sample t test, whereas the paired-sample t test was employed to analyze the network metric changes in PSCI patients before vs. after treatment. Results: Small-world network attributes were observed in both groups for sparsities between 0.1 and 0.28. Compared with the HC group, the PSCI group presented significantly lower values for the global topological properties (γ, Cp, and Eloc) of the brain;significantly greater values for the nodal attributes of betweenness centrality in the CUN. L and the HES. R, degree centrality in the SFGdor. L, PCG. L, IPL. L, and HES. R, and nodal local efficiency in the ORBsup. R, ORBsupmed. R, DCG. L, SMG. R, and TPOsup. L;and decreased degree centrality in the MFG. R, IFGoperc. R, and SOG. R. After treatment, PSCI patients presented increased degree centrality in the LING.L, LING.R, and IOG. L and nodal local efficiency in PHG. L, IOG. R, FFG. L, and the HES. L, and decreased betweenness centrality in the PCG. L and CUN. L, degree centrality in the ORBsupmed. R, and nodal local efficiency in ANG. R. Conclusion: Cognitive decline in PSCI patients may be related to BFN disorders;acupuncture therapy may modulate the topological properties of the BFNs of PSCI patients.
基金International Cooperation Projects of Shaanxi Province(The Protection on Ischemia-reperfusion Rats and the influence of VEGF RNA Expression of Brain Functional Recovery Decoction,No.2012-Kw-33-02)
文摘OBJECTIVE: To investigate the effect of brain functional recovery decoction(BFRD) on expression of vascular endothelial growth factor(VEGF) and angiopoietin-1(Ang-1) protein in rats with cerebral ischemia reperfusion injury, and to explore the mechanism of action of BFRD.METHODS: Using the suture-occlusion method, a Wistar rat model of focal cerebral ischemia reperfusion was established. The rats were randomly divided into treatment group, model group, and sham operation group. The treatment group was administered BFRD. In situ hybridization was used to detect VEGF m RNA expression. Immunohistochemistry was used to observe expression of Ang-1 protein.RESULTS: VEGF mRNA expression was greater in the model group compared with the sham operation group(P < 0.05); Ang-1 protein expression was more obvious in the treatment group than the model group(P < 0.05).CONCLUSION: BFRD promoted VEGF m RNA and Ang-1 protein expression in the brains of rats with cerebral ischemia, suggesting increased angiogenesis.
基金supported by the National Natural Science Foundation of China(No.51877013),(ZJ),(http://www.nsfc.gov.cn/)the Natural Science Foundation of Jiangsu Province(No.BK20181463),(ZJ),(http://kxjst.jiangsu.gov.cn/)sponsored by Qing Lan Project of Jiangsu Province(no specific grant number),(ZJ),(http://jyt.jiangsu.gov.cn/).
文摘Currently,functional connectomes constructed from neuroimaging data have emerged as a powerful tool in identifying brain disorders.If one brain disease just manifests as some cognitive dysfunction,it means that the disease may affect some local connectivity in the brain functional network.That is,there are functional abnormalities in the sub-network.Therefore,it is crucial to accurately identify them in pathological diagnosis.To solve these problems,we proposed a sub-network extraction method based on graph regularization nonnegative matrix factorization(GNMF).The dynamic functional networks of normal subjects and early mild cognitive impairment(eMCI)subjects were vectorized and the functional connection vectors(FCV)were assembled to aggregation matrices.Then GNMF was applied to factorize the aggregation matrix to get the base matrix,in which the column vectors were restored to a common sub-network and a distinctive sub-network,and visualization and statistical analysis were conducted on the two sub-networks,respectively.Experimental results demonstrated that,compared with other matrix factorization methods,the proposed method can more obviously reflect the similarity between the common subnetwork of eMCI subjects and normal subjects,as well as the difference between the distinctive sub-network of eMCI subjects and normal subjects,Therefore,the high-dimensional features in brain functional networks can be best represented locally in the lowdimensional space,which provides a new idea for studying brain functional connectomes.
基金supported by the National Natural Science Foundation of China(Nos.61962034,61862058)Longyuan Youth Innovation and Entrepreneurship Talent(Individual)Project and Tianyou Youth Talent Lift Program of Lanzhou Jiaotong Univesity。
文摘Since the outbreak and spread of corona virus disease 2019(COVID-19),the prevalence of mental disorders,such as depression,has continued to increase.To explore the abnormal changes of brain functional connections in patients with depression,this paper proposes a depression analysis method based on brain function network(BFN).To avoid the volume conductor effect,BFN was constructed based on phase lag index(PLI).Then the indicators closely related to depression were selected from weighted BFN based on small-worldness(SW)characteristics and binarization BFN based on the minimum spanning tree(MST).Differences analysis between groups and correlation analysis between these indicators and diagnostic indicators were performed in turn.The resting state electroencephalogram(EEG)data of 24 patients with depression and 29 healthy controls(HC)was used to verify our proposed method.The results showed that compared with HC,the information processing of BFN in patients with depression decreased,and BFN showed a trend of randomization.
基金supported by National Institutes of Health grants NS076815
文摘Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.
文摘Objective: To explore the characteristics of brain functional network with anxiety in patients with acute cerebral infarction. Methods: A total of 39 patients with acute cerebral infarction by cranial magnetic resonance examination were included, and all the patients were scored by the Hamilton Anxiety Scale. The anxiety scale is scored by a professional psychiatrist. There are a total of 14 items, including anxiety, nervousness, fear, insomnia, cognitive function, depressed mood, somatic anxiety, sensory system, etc. The total score ≥ 29 points may be severe;≥21 points, there must be obvious;≥14 points, there must be anxiety;a score of more than 7 may indicate anxiety. If the score is less than 7, there are no anxiety symptoms. All patients within 24 to 72 hours, complete the head examination magnetic resonance, computerized calculation of the DWI sequence images, according to the results of the calculation to superimpose the image of the lesion, image reconstruction in space, and carry out Binarization, defining the value of lesions as 1, and the value of non as 0. All lesions are superimposed into one image and integrated. The relationship between the lesions in this superimposed image and anxiety after cerebral infarction was analyzed. Results: The lesions were basically concentrated around the lateral ventricle, and they were mainly concentrated around the lateral ventricle. Conclusion: Patients with acute cerebral infarction in the lateral ventricle or basal ganglia are more prone to post-stroke anxiety. This has a certain evaluation value for the prognosis of future cerebral infarction, and has a certain understanding of the exploration of complications, and has a certain understanding of the exploration of complications.
文摘<strong>Objective</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"><strong>: </strong>To evaluate the clinical value of transcranial color Doppler ultrasound (TCCD) in assessing cerebral function after cardiopulmonary resuscitation (CPR). </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: A prospective study was conducted in 52 patients with cardiac arrest treated by CPR from January 2018 to January 2020, and its clinical data were analyzed</span></span><span style="font-family:Verdana;">. </span><span style="font-family:;" "=""><span style="font-family:Verdana;">According to classification of cerebral performance category (CPC), 31 cases (CPC grade 1 - 2) were selected in the good prognosis group and 21 cases (CPC grade 3 - 5) in the poor prognosis group. The cerebral blood flow was measured by transcranial Doppler ultrasound (TCCD) 24 h after CPR, and the differences were compared between the two groups in stroke index, diastolic blood flow velocity (Vd), systolic peak blood flow velocity (Vs) and mean peak blood flow velocity (Vm). The ROC curve of cerebral blood flow after CPR was drawn to predict the prognosis of brain function. </span><b><span style="font-family:Verdana;">Results</span></b><span style="font-family:Verdana;">: The data showed that the pulsatility index of middle cerebral artery of the poor prognosis group decreased within 24 h</span></span><span style="font-family:Verdana;">;</span><span style="font-family:Verdana;">the difference between the two groups was statistically significant (p < 0.05);the Vd, Vs, Vm increased in the good prognosis group</span><span style="font-family:Verdana;">;</span><span style="font-family:;" "=""><span style="font-family:Verdana;">the difference between the two groups was statistically significant (p < 0.05). The ROC curve of cerebral blood flow after CPR was drawn to predict the prognosis of brain function, and the results showed that the area under the curve and the optimal critical value of cerebral blood flow were 0.731 and 5.69. The sensitivity and specificity were 67.3% and 79.1% respectively. </span><b><span style="font-family:Verdana;">Conclusion</span></b><span style="font-family:Verdana;">: The cerebral blood flow increase in the early stage of successful CPR is positively correlated with the prognosis of cerebral functional resuscitation. Monitoring intracranial blood flow after CPR by TCCD has clinical value to evaluate prognosis of brain function.</span></span>
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 National Natural Science Foundation of China (No.51877013),(ZJ),(http://www.nsfc.gov.cn/)the Jiangsu Provincial Key Research and Development Program (No.BE2021636),(ZJ),(http://kxjst.jiangsu.gov.cn/)+1 种基金the Science and Technology Project of Changzhou City (No.CE20205056),(ZJ),(http://kjj.changzhou.gov.cn/)by Qing Lan Project of Jiangsu Province (no specific grant number),(ZJ),(http://jyt.jiangsu.gov.cn/).
文摘The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.
基金financially supported by the National Natural Science Foundation of China(Nos.81922034,91859113)the Science Fund for Distinguished Young Scholars of Fujian Province(No.2018J06024)。
文摘To better understand the spatial distribution of brain functions,we need to monitor and analyze neuronal activities.Electrophysiological technique has provided an important method for the exploration of some neural circuits.However,this method cannot simultaneously detect the activities of nerve cell groups.Therefore,methods that can monitor the spatial distribution of neuronal population activity are demanded to explore brain functions.Voltage-sensitive dyes(VSDs)shift their absorption or emission optical signals in response to different membrane potentials,allowing assessing the global electrical state of neurons.Optical recording technique coupled with VSDs is a promising method to monitor the brain functions by detecting optical signal changes.This review focuses on the fast and slow responses of VSDs to membrane potential changes and optical recordings utilized in the central nervous system.In this review,we attempt to show how VSDs and optical recordings can be used to obtain brain functional monitoring at high spatial and temporal resolution.Understanding of brain functions will not only greatly improve the cognition of information transmission of complex neural network,but also provide new methods of treating brain diseases such as Parkinson’s and Alzheimer’s diseases.
文摘To investigate the effects of magnetic stimulation at acupoints on brain functional network during mental fatigue, magnetic stimulation was applied to stimulate SHENMEN (HT7), HEGU (LI4) and LAOGONG (PC8) acupoint in this paper. The brain functional networks of normal state, mental fatigue state and stimulated state were constructed and the characteristic parameters were comparatively studied based on the complex network theory. The results showed that the connection of the network was enhanced by stimulating the HT7, LI4 and PC8 acupoint. In conclusion, magnetic stimulation at acupoints can effectively relieve mental fatigue.
文摘Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.
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.
文摘Objective:To analyze the effect of ventriculoperitoneal shunt on the recovery of brain function in children with hydrocephalus.Methods:The clinical data of 40 children with hydrocephalus were retrospectively analyzed.Ventriculoperitoneal shunt was performed with 9003 shunt tube and P.S.Shunt tube,B.C.E.shunt tube.Electroencephalogram(EEG),and brain CT/MRI were performed before and after surgery,and postoperative follow-up was carried out to observe the therapeutic effect.Results:In this study,there were seven cases of intracranial injury,seven cases of congenital hydrocephalus,11 cases of ventricular end obstruction,three cases of abdominal end obstruction,nine cases complicated with bacterial infection,and 3 cases of shunt entering the scrotum.The prognosis of all the children was good,and there were no significant changes in eight cases.Conclusion:Ventriculoperitoneal shunt is effective in the treatment of children with hydrocephalus.
文摘Objective To evaluate the feasibility and safety of the self developed sound outside the ventilation device-esophageal nasopharynx catheter in brain functional areas surgery applications. Methods 13 patients involved functional areas of brain surgery were chosed. After induction of general anesthesia,the catheters were placed in the esophagus,then connected to anesthesia machines to an external
基金supported by the Natural Science Foundation of Guangdong Province,No.2016A030313180(to FCJ)
文摘Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.
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.
