The pig as a preclinical traumatic brain injury model:current models,functional outcome measures,and translational detection strategies

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.

Identification of predictive MRI and functional biomarkers in a pediatric piglet traumatic brain injury model

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.

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

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.

Effects of exercise on brain functions in diabetic animal models

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.

How does the motor relearning program improve neurological function of brain ischemia monkeys?

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.

Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models

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.

Functional magnetic resonance imaging and the brain: A brief review

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.

Microglia and astrocytes mediate synapse engulfment in a MER tyrosine kinase-dependent manner after traumatic brain injury

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.

基于fNIRS和神经反馈的记忆认知训练研究

该研究使用功能性近红外光谱技术和神经反馈机制开发了记忆任务训练系统,并对被试的脑电信号进行采集和分析。结果显示,参与神经反馈任务的被试在前额叶部右半脑区具有更高的相关性脑网络节点度和平均集群系数,中介中心度的分散程度相对降低。此外,被试的前额叶部左半脑区在神经反馈任务中的核心地位上升。通过通道网络模型和支持向量机模型对脑数据进行分类,结果表明两个模型在任务态和静息态的分类准确率高于反馈任务和对照任务,且通道网络模型的分类准确率更高。该研究结果表明神经反馈任务的被试具有明显的脑数据特征,并且这些特征能够被有效识别。

强迫症的功能脑网络机制研究进展

强迫症(obsessive-compulsive disorder,OCD)是一种以强迫思维、强迫行为为主要临床表现的常见精神疾病。近年来,许多基于功能磁共振成像的影像学研究关注到强迫症状与大尺度脑网络之间的关联,现就OCD病理生理过程中涉及的默认网络、突显网络及额顶网络的功能异常,结合三网络模型假说,对强迫症状所对应的脑网络机制研究现状进行综述,以期为OCD的早期识别及干预提供新线索。

Potential rat model of anxiety-like gastric hypersensitivity induced by sequential stress

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.

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

正常人眼睫状肌不同调节负荷下的大脑皮层激活状态

目的 探讨正常人眼不同调节负荷下的大脑皮层激活状态、功能脑网络及脑区间有效连接关系。方法 选择正常受试者33例,进行任务态功能核磁共振扫描,基于MATLAB平台的SPM12、GroupICATv4.0a软件包进行影像数据预处理和后续分析。使用单样本t检验分析正常人群调节相关脑激活模式;运用Informax算法将数据分解为独立的空间成分,提取任务对应的成分,分析相关的功能脑网络;基于动态因果模型分析任务激活区之间的有效连接,明确相应脑区的有效连接关系。应用体素水平阈值P <0.001,FWE团块水平P≤0.05为多重比较校正方法。结果 正常人眼-3D和-6D调节刺激下的大脑激活信号表明,支配睫状肌的神经信号所涉及的大脑皮层区域广泛,有枕叶、颞叶、小脑、边缘叶、丘脑、顶叶和额叶,且正常人眼不同调节负荷下大脑激活的区域和强度均有变化;参与调节任务态相关的功能脑网络,主要为视觉网络、小脑网络和注意网络;各脑区间有效连接分析初步表明,参与调节的回路有2个,分别是枕叶、小脑与顶叶组成一个神经环路,枕叶、小脑和额叶组成一个神经环路,丘脑为信息传导中介。结论 参与大脑加工调节信号的区域较广,涉及多个脑区,多个脑网络,2个神经回路;不同调节负荷下脑激活的区域和强度均有差异。

Functional Connectivity-Based Modelling Simulates SubjectSpecific Network Spreading Effects of Focal Brain Stimulation

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.

脑肿瘤患者及照顾者家庭功能与经济毒性的纵向主客体模型研究

目的 探讨脑肿瘤患者和主要照顾者的家庭功能对双方经济毒性的预测效应,为临床干预提供参考。方法 便利抽取脑肿瘤患者及主要照顾者233对为研究对象,于诊断后3 d及诊断后6个月采用一般情况调查表、家庭亲密度和适应性量表、患者报告结局的经济毒性综合评分量表、照顾者报告结局的经济毒性综合评分量表进行调查;基于纵向的主-客体互倚模型分析脑肿瘤患者和主要照顾者的家庭功能对双方经济毒性的预测效应。结果 脑肿瘤患者家庭功能总分为65(55,71)分,主要照顾者总分为68(61,72)分;脑肿瘤患者经济毒性总分为23(18,27)分,主要照顾者总分为21(16,27)分。从主体效应来看,脑肿瘤患者及主要照顾者的家庭功能对其自身的经济毒性均具有显著预测作用(β=0.346、0.510,均P<0.05);从客体效应看,仅主要照顾者的家庭功能对患者的经济毒性有显著预测作用(β=0.372,P<0.05)。结论 脑肿瘤患者的经济毒性受到自身和主要照顾者所感知家庭功能的影响,医护人员应重视脑肿瘤患者家庭功能的评估,积极探索以家庭功能为焦点的干预方案。

Research on Modeling Approach of Brain Function Network Based on Anatomical Distance

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.

电针不同穴位对功能性腹泻大鼠血清和组织中P物质、血管活性肠肽的影响

【目的】观察不同穴位处方的电针疗法对功能性腹泻(FD)大鼠血清和组织中P物质(SP)、血管活性肠肽(VIP)含量的影响。【方法】将SD大鼠50只随机分为5组,即正常组、模型组、电针Ⅰ组(取双侧天枢、大肠俞)、电针Ⅱ组(取双侧曲池、上巨虚)、电针Ⅲ组(取单侧天枢、大肠俞、曲池、上巨虚),采用番泻叶灌胃法建立FD大鼠模型,电针各组分别按设定穴位给予电针治疗,连续治疗10 d后检测各组血清和组织中SP、VIP含量的变化。【结果】除电针Ⅱ组对大鼠血清VIP含量无显著影响外,各电针组均可使血清和组织中SP含量显著降低,VIP含量显著升高,与模型组比较差异有统计学意义(P<0.05或P<0.01)。【结论】电针可能通过降低大鼠血清和组织中SP含量、提高VIP含量而改善功能性腹泻,电针Ⅰ组作用优于其他2组。

对语言神经机制的新认识

本文针对语言神经机制的研究现状 ,分析了失语症和裂脑人研究的成果 ,并且较为详细地介绍了最近十年脑功能成像得到的有关语言神经活动的新成就 ,在此基础上 ,提出了一种动态分布式竞争的解释理论 ,用来解释语言神经活动现象和规律 。

甲状腺激素在脑学习和记忆功能中的作用

甲状腺激素是生长发育所必需的一类激素,在脑高级认知功能中也起到了重要作用。作者引用了自己和他人的研究结果,从动物模型的建立、神经行为学和神经电生理学等方面总结了甲状腺激素在脑学习和记忆功能中的作用。