Although spontaneous activity is ubiquitous across multiple spatiotemporal scales, its functional organization and cognitive relevance remain poorly understood. Following the classic neuronal avalanche framework, a spontaneous avalanche is defined as consecutively active frames separated by inactive time bins. Hence, multiple distinct avalanches may be considered as one avalanche, thereby ignoring their spatial and temporal distinguishability. Furthermore, group-level power-law fitting of such neural avalanches is often performed to evaluate brain criticality (referring to a system perched between order and disorder) due to the limited recording length of macroscale neuroimaging (such as functional magnetic resonance imaging), and the functional representation of brain-wide neural avalanches is largely unexplored. To address these issues, we proposed large-scale neural avalanches as a single, spatially consecutive cascade pattern and further investigated their functional dynamics, network propagation, and association with task-evoked activity. Compared with the conventional inactive-bin definition, our current approach is more favorable to power-law fitting of avalanche size and duration distributions at the individual level. We also demonstrated that participants whose brain activities were close to the critical point tend to have higher cognitive abilities. Notably, the ratio of neural avalanches that evolved from primary sensory to association networks negatively correlated with cognitive abilities. Moreover, the geometric distance between low-dimensional representations of task-evoked activity and spontaneous avalanches was associated with behavioral performance. This study not only provides a promising avenue for measuring avalanche criticality based on human whole-brain neuroimaging, but also suggests that spontaneous neural avalanches and their low-dimensional representations contribute to human cognitive abilities.

The dorsomedial posterior parietal cortex (dmPPC) plays an important role in episodic processing by integrating sensory, cognitive, and motor information across distributed brain systems. However, how individual dmPPC neurons participate in large-scale functional organization during naturalistic experience remains poorly understood. To address this question, we combined single-unit electrophysiology and awake fMRI in five rhesus macaques of both sexes viewing identical naturalistic video stimuli. Using single-unit fMRI mapping, we generated whole-brain neuron-BOLD functional maps by correlating individual neuronal activity with voxel-wise fMRI signals across the brain. We found that neuron-BOLD functional maps exhibited strong context-dependent organization, with neurons recorded during the same video context showing substantially greater similarity than neurons recorded during different video conditions. Compared with neuronal spiking activity or critical fMRI frames alone, neuron-BOLD functional maps more robustly captured contextual structure. Despite this shared large-scale organization, a substantial subset of neighboring neurons recorded simultaneously from the same electrode displayed markedly distinct whole-brain association patterns, revealing substantial local functional heterogeneity within the dmPPC. This local heterogeneity was not readily explained by waveform-based putative cell class or by opposing neuronal firing dynamics. In addition, distributed cortical and medial temporal regions exhibited highly context-dependent neuron-BOLD association patterns during naturalistic viewing. Together, these findings demonstrate that dmPPC neurons participate in dynamic and heterogeneous large-scale functional organization during naturalistic episodic processing. More broadly, this study establishes single-unit fMRI mapping as a framework for linking single-neuron activity to distributed whole-brain dynamics across contextual conditions.Significance Statement Using single-unit fMRI mapping, this study examined how individual dorsomedial posterior parietal cortex (dmPPC) neurons relate to large-scale brain activity during naturalistic video viewing in macaque monkeys. We found that neuron-BOLD functional maps exhibit strong context-dependent organization and capture contextual structure more robustly than neuronal spiking activity or fMRI frames alone. Despite this shared organization, a substantial subset of neighboring dmPPC neurons displayed markedly distinct whole-brain association patterns, revealing local functional heterogeneity that was not readily explained by waveform-based putative cell class or opposing firing dynamics. These findings provide insight into how local neuronal populations participate in distributed brain-wide functional organization during naturalistic episodic processing.

Although patients with type 1 or type 2 diabetes mellitus are at risk for developing the same neuropsychological disorders, their underlying pathogeneses might be heterogeneous. Here, leveraging the unique characteristics of diabetic epidemiology in China, a total of 92 participants were recruited, including 30 with type 1 and 33 with type 2 diabetes matched for age, sex, education, diabetes duration, and HbA1c, along with 29 healthy controls. Compared with controls, both type 1 and type 2 diabetes patients exhibited higher depressive symptom scores; however, no significant differences were observed between the two diabetes types. Based on functional magnetic resonance imaging and graph theory analyses, enhanced global efficiency of functional brain networks was exclusively observed in type 1 diabetes, which was negatively correlated with depression scores. Furthermore, it is only in type 1 diabetes that the increased glycemic variability negatively correlated to the functional connectivity of amygdala. These findings suggest a shared affective burden but divergent patterns of functional network organization underpinning each diabetes types and also reflect a functional reorganization potentially related to depression in type 1 diabetes.

Flexibility is a hallmark of cognitive control and can be driven externally and internally, corresponding to reactive and spontaneous flexibility. However, the convergence and divergence between these two types of flexibility and their underlying neural basis during development remain largely unknown. In this study, we aimed to determine the common and unique networks for reactive and spontaneous flexibility as a function of age and sex, leveraging both cross-sectional and longitudinal resting-state functional magnetic resonance imaging datasets with different temporal resolutions (N = 249, 6-35 years old). Functional connectivity strength and nodal flexibility, derived from static and dynamic frameworks respectively, were utilized. We found similar quadratic effects of age on reactive and spontaneous flexibility, which were mediated by the functional connectivity strength and nodal flexibility of the frontoparietal network. Divergence was observed, with the nodal flexibility of the ventral attention network at the baseline visit uniquely predicting the increase in reactive flexibility 24-30 months later, while the nodal flexibility or functional connectivity strength of the dorsal attention network could specifically predict the increase in spontaneous flexibility. Sex differences were found in tasks measuring reactive and spontaneous flexibility simultaneously, which were moderated by the nodal flexibility of the dorsal attention network. This study advances our understanding of distinct types of flexibility in cognition and their underlying mechanisms throughout developmental stages. Our findings also suggest the importance of studying specific types of cognitive flexibility abnormalities in developmental neuropsychiatric disorders.

Understanding the large-scale information processing that underlies complex human cognition is the central goal of cognitive neuroscience. While emerging activity flow models demonstrate that cognitive task information is transferred by interregional functional or structural connectivity, graph-theory-based models typically assume that neural communication occurs via the shortest path of brain networks. However, whether the shortest path is the optimal route for empirical cognitive information transmission remains unclear. Based on a large-scale activity flow mapping framework, we found that the performance of activity flow prediction with the shortest path was significantly lower than that with the direct path. The shortest path routing was superior to other network communication strategies, including search information, path ensembles, and navigation. Intriguingly, the shortest path outperformed the direct path in activity flow prediction when the physical distance constraint and asymmetric routing contribution were simultaneously considered. This study not only challenges the shortest path assumption through empirical network models but also suggests that cognitive task information routing is constrained by the spatial and functional embedding of the brain network.

Emerging studies suggest that time-dependent consolidation enables memory stabilization by promoting memory integration and hippocampal-cortical transfer. Compared to massed learning, how time-dependent consolidation contributes to forming durable memory and what neural signatures predict durable memory in spaced learning remain unclear. We recruited 48 participants who underwent either 3-day spaced learning or 1-day massed learning, and both resting-state and task-based fMRI data were collected in multiple delayed tests (i.e., immediate, 1-week, and 1-month). We use representational similarity analysis to assess neural integration and replay in the hippocampus and default mode network (DMN) subsystems. In contrast with massed learning, spaced learning induces higher neural pattern similarity during immediate retrieval only in DMN subsystems. Particularly, the neural pattern similarity in the dorsal-medial DMN (DMNdm) and medial-temporal DMN subsystems predicts the durable memory defined by 1-month delay. Moreover, we find increased neural replay of durable memory in the DMNdm for spaced learning and in the hippocampus for both spaced and massed learning. Our findings suggest that time-dependent consolidation promotes neural integration and replay in the cortex rather than in the hippocampus, which may underlie the formation of durable memory after spaced learning.

Flexible cognitive functions, such as working memory (WM), usually require a balance between localized and distributed information processing. However, it is challenging to uncover how local and distributed processing specifically contributes to task-induced activity in a region. Although the recently proposed activity flow mapping approach revealed the relative contribution of distributed processing, few studies have explored the adaptive and plastic changes that underlie cognitive manipulation. In this study, we recruited 51 healthy volunteers (31 females) and investigated how the activity flow and brain activation of the frontoparietal systems was modulated by WM load and training. While the activation of both executive control network (ECN) and dorsal attention network (DAN) increased linearly with memory load at baseline, the relative contribution of distributed processing showed a linear response only in the DAN, which was prominently attributed to within-network activity flow. Importantly, adaptive training selectively induced an increase in the relative contribution of distributed processing in the ECN and also a linear response to memory load, which were predominantly due to between-network activity flow. Furthermore, we demonstrated a causal effect of activity flow prediction through training manipulation on connectivity and activity. In contrast with classic brain activation estimation, our findings suggest that the relative contribution of distributed processing revealed by activity flow prediction provides unique insights into neural processing of frontoparietal systems under the manipulation of cognitive load and training. This study offers a new methodological framework for exploring information integration versus segregation underlying cognitive processing.

While the storage capacity is limited, accumulating studies have indicated that working memory (WM) can be improved by cognitive training. However, understanding how exactly the brain copes with limited WM capacity and how cognitive training optimizes the brain remains inconclusive. Given the hierarchical functional organization of WM, we hypothesized that the activation profiles along the posterior-anterior gradient of the frontal and parietal cortices characterize WM load and training effects. To test this hypothesis, we recruited 51 healthy volunteers and adopted a parametric WM paradigm and training method. In contrast to exclusively strengthening the activation of posterior areas, a broader range of activation concurrently occurred in the anterior areas to cope with increased memory load for all subjects at baseline. Moreover, there was an imbalance in the responses of the posterior and anterior areas to the same increment of 1 item at different load levels. Although a general decrease in activation after adaptive training, the changes in the posterior and anterior areas were distinct at different memory loads. Particularly, we found that the activation gradient between the posterior and anterior areas was significantly increased at load 4-back after adaptive training, and the changes were correlated with improvement in WM performance. Together, our results demonstrate a shift in the predominant role of posterior and anterior areas in the frontal and parietal cortices when approaching WM capacity limits. Additionally, the training-induced performance improvement likely benefits from the elevated neural efficiency reflected in the increased activation gradient between the posterior and anterior areas.

Accumulating evidence suggests that regular engagement in physical activity, especially structured physical exercise with complex movement patterns like Tai Chi, is linked to change in brain function as measured by spontaneous and task-evoked neural activities. However, studies on brain function at the early stage of Tai Chi training have yet been conducted despite the fact that understanding changes in neurological activities of motor skill learning at the early stage would facilitate more effective teaching and coaching. To this end, we conducted a longitudinal study in which functional magnetic resonance imaging（fMRI） was used to collect data on brain function and behavioral measures during the early stage of Tai Chi training at multiple time points.Nineteen college students who had no Tai Chi experience were recruited in this study and they were arranged to attend 14-week Tai Chi training program. Of note, Tai Chi training session was recorded in order to evaluate the quality of Tai Chi form and its skill level（conducted by professor specializing in Tai Chi）. Outcome measures were conducted at Week 2, Week 8, and Week 14. Meanwhile, 10 age-and gender-matched college students were considered as control group and they were asked to maintain their unaltered lifestyle with the same outcome measures being arranged at baseline and Week 14. Siemens 3.0 T MRI scanner was used to synchronously collect data on brain function when participants performed a motor imagery task. Group differences on Tai Chi skill level,temporal congruence, and functional activations were investigated using ANOVA while pearson product-moment correlation was performed to examine relationships between them.Behavioral results showed a learning curve on Tai Chi skill level from slow（Week 2 to Week 8） to fast（after Week 8） as the quality of motor imagery gradually improved. fMRI results showed a similiar pattern of change on brain activities, which changed slowly（Week 2 to Week 8） and increased fastly（after Week 8）. Such behavioral changes on skill level were significantly linked to functional activations in the left superior temporal gyrus and the left precuneus.Motor skill learning has followed a pattern of “slow first, fast later”, which is supported by changes on brain activities in the left superior temporal gyrus and the left precuneus. In addition, Tai Chi is a type of a motor-cognitive exercise with relatively complex movement and its unique routine provides learners with an opportunity to optimize brain function.

目的 探究阿尔茨海默病(Alzheimer's disease,AD)和轻度认知障碍(mild cognitive impairment,MCI)患者的大脑半球间结构连接异常及其与认知功能和日常生活活动能力的关系.材料与方法 前瞻性纳入23例AD患者(AD组)、47例MCI患者(MCI组)及37例健康对照(healthy controls,HC)者(HC组)的磁共振弥散张量成像数据.利用高分辨经胼胝体纤维束模板计算并比较通往半球间同位脑区(包括前额叶、感觉运动区、顶叶、枕叶和颞叶)的32条经胼胝体神经纤维束的2个弥散指标——分数各向异性(fractional anisotropy,FA)和平均弥散率(mean diffusivity,MD),进一步将AD组和MCI组中差异脑区的弥散指标值与蒙特利尔认知评估基本量表评分(Montreal Cognitive basic Assessment,MoCA_B)和日常生活活动能力评分(activities of daily living scale,ADL)进行相关性分析.结果 与HC组相比,AD组所有经胼胝体神经纤维束的MD值显著升高(P＜0.05,FDR校正),除了眶额叶、额下回眶部和腹侧运动前区的其他纤维束的FA值显著降低(P＜0.05,FDR校正);MCI组半球间同位脑区经胼胝体神经纤维束的FA值及MD值与HC组的差异均无统计学意义;与MCI组相较,AD组的部分经胼胝体神经纤维束(不包括前额叶和感觉运动区的部分纤维束)的FA值和MD值差异均有统计学意义(P＜0.05,FDR校正).AD组和MCI组所有经胼胝体神经纤维束的FA值及MD值与MoCA_B评分均无显著相关,但AD组多条纤维束(包括背外侧前额叶、感觉运动区、顶叶、枕叶和颞叶的部分纤维束)的FA值及MD值与ADL评分显著相关(P＜0.05,FDR校正).结论 本研究结果表明,AD患者比MCI患者的大脑半球间结构连接损伤更严重且区域更为广泛;胼胝体纤维束的半球间结构连接退变与日常生活活动能力的减退更为相关.经胼胝体神经纤维束的损伤程度可作为评估AD患者生活活动能力的重要参考指标.

Emerging evidence indicates that activity flow over resting-state network topology allows the prediction of task activations. However, previous studies have mainly adopted static, linear functional connectivity (FC) estimates as activity flow routes. It is unclear whether an intrinsic network topology that captures the dynamic nature of FC can be a better representation of activity flow routes. Moreover, the effects of between- versus within-network connections and tight versus loose (using rest baseline) task contrasts on the prediction of task-evoked activity across brain systems remain largely unknown. In this study, we first propose a probabilistic FC estimation derived from a dynamic framework as a new activity flow route. Subsequently, activity flow mapping was tested using between- and within-network connections separately for each region as well as using a set of tight task contrasts. Our results showed that probabilistic FC routes substantially improved individual-level activity flow prediction. Although it provided better group-level prediction, the multiple regression approach was more dependent on the length of data points at the individual-level prediction. Regardless of FC type, we consistently observed that between-network connections showed a relatively higher prediction performance in higher-order cognitive control than in primary sensorimotor systems. Furthermore, cognitive control systems exhibit a remarkable increase in prediction accuracy with tight task contrasts and a decrease in sensorimotor systems. This work demonstrates that probabilistic FC estimates are promising routes for activity flow mapping and also uncovers divergent influences of connectional topology and task contrasts on activity flow prediction across brain systems with different functional hierarchies.

目的 探究单侧皮质下脑卒中半球间同位脑区经胼胝体结构连接变化与临床运动功能障碍的关系.材料与方法 招募34例单侧皮质下脑卒中患者和43例健康人并采集磁共振弥散张量成像数据.利用高分辨经胼胝体纤维束模板(trancallosal tract template,TCATT)计算并比较卒中组与健康对照组通往半球间同位脑区(包括感觉运动区、前额叶、顶叶、颞叶和枕叶)的32条经胼胝体神经纤维束的各向异性分数(fractional anisotropy,FA)的差异,进一步与皮质脊髓束(corticospinal tract,CST)的FA比率(FA ratio,rFA)和上肢运动功能评分(fugl-meyer assessment of upper extremity,FM-UE)进行相关性分析.结果 与健康对照组相比,卒中组半球间同位脑区的32条经胼胝体神经纤维束在中矢状面区域的FA值均降低,其中差异有统计学意义的有29条(不包括直回、中央旁小叶和内侧眶回的同位脑区经胼胝体纤维束).这29条经胼胝体神经纤维束在中矢状面区域的FA值与rFA(CST)、FM-UE均存在显著正相关(P<0.05).卒中组rFA(CST)与FM-UE评分亦呈显著正相关(r=0.596,P=0.0004).结论 本研究证实皮质下脑卒中的胼胝体微结构受损与病灶同侧CST损伤密切相关.继发性跨半球结构连接损伤对皮质下脑卒中运动功能障碍具有同样重要的影响.

Correctly identifying interaction patterns from multivariate time series presents an important step in functional network construction. In this context, the widespread use of bivariate statistical association measures often results in a false identification of links because strong similarity between two time series can also emerge without the presence of a direct interaction due to intermediate mediators or common drivers. In order to properly distinguish such direct and indirect links for the special case of event-like data, we present here a new generalization of event coincidence analysis to a partial version thereof, which is aimed at excluding possible transitive effects of indirect couplings. Using coupled chaotic systems and stochastic processes on two generic coupling topologies (star and chain configuration), we demonstrate that the proposed methodology allows for the correct identification of indirect interactions. Subsequently, we apply our partial event coincidence analysis to multi-channel EEG recordings to investigate possible differences in coordinated alpha band activity among macroscopic brain regions in resting states with eyes open (EO) and closed (EC) conditions. Specifically, we find that direct connections typically correspond to close spatial neighbors while indirect ones often reflect longer-distance connections mediated via other brain regions. In the EC state, connections in the frontal parts of the brain are enhanced as compared to the EO state, while the opposite applies to the posterior regions. In general, our approach leads to a significant reduction in the number of indirect connections and thereby contributes to a better understanding of the alpha band desynchronization phenomenon in the EO state.

Background and ObjectiveTo investigate the pathway-specific correspondence between structural and functional changes resulting from focal subcortical stroke and their causal influence on clinical symptom.MethodsIn this retrospective, cross-sectional study, we mainly focused on patients with unilateral subcortical chronic stroke with moderate-severe motor impairment assessed by Fugl-Meyer Assessment (upper extremity) and healthy controls. All participants underwent both resting-state fMRI and diffusion tensor imaging. To parse the pathway-specific structure-function covariation, we performed association analyses between the fine-grained corticospinal tracts (CSTs) originating from 6 subareas of the sensorimotor cortex and functional connectivity (FC) of the corresponding subarea, along with the refined corpus callosum (CC) sections and interhemispheric FC. A mediation analysis with FC as the mediator was used to further assess the pathway-specific effects of structural damage on motor impairment.ResultsThirty-five patients (mean age 52.7 ± 10.2 years, 27 men) and 43 healthy controls (mean age 56.2 ± 9.3 years, 21 men) were enrolled. Among the 6 CSTs, we identified 9 structurally and functionally covaried pathways, originating from the ipsilesional primary motor area (M1), dorsal premotor area (PMd), and primary somatosensory cortex (p < 0.05, corrected). FC for the bilateral M1, PMd, and ventral premotor cortex covaried with secondary degeneration of the corresponding CC sections (p < 0.05, corrected). Moreover, these covarying structures and functions were significantly correlated with the Fugl-Meyer Assessment (upper extremity) scores (p < 0.05, uncorrected). In particular, FC between the ipsilesional PMd and contralesional cerebellum (β = −0.141, p < 0.05, CI = [−0.319 to −0.015]) and interhemispheric FC of the PMd (β = 0.169, p < 0.05, CI = [0.015–0.391]) showed significant mediation effects in the prediction of motor impairment with structural damage of the CST and CC.DiscussionsThis study reveals causal influence of structural and functional pathways on motor impairment after subcortical stroke and provides a promising way to investigate pathway-specific structure-function coupling. Clinically, our findings may offer a circuit-based evidence for the PMd as a critical neuromodulation target in more impaired patients with stroke and also suggest the cerebellum as a potential target.

Background Cognitive dysfunction is an important comorbidity of diabetes characterized by brain functional hypo-connectivity. However, our recent study demonstrated an adaptive hyper-connectivity in young type 2 diabetes with cognitive decrements. This longitudinal study aimed to further explore the changes in functional connectivity and cognitive outcomes after regular glycemic control. Methods At 18 months after recruitment, participants underwent a second cognitive assessment and magnetic resonance imaging. Three enhanced functional connectivities previously identified at baseline were followed up. Linear mixed-effects models were performed to compare the longitudinal changes of cognition and functional connectivity in patients with type 2 diabetes and non-diabetic controls. A linear regression model was used to investigate the association between changes in functional connectivity and changes in cognitive performance. Results Improvements in multiple cognitive domains were observed in diabetes; however, the enhanced functional connectivity at baseline decreased significantly. Moreover, the decrease in hippocampal connectivity was correlated with an increase in the accuracy of Stroop task and the decrease in posterior cingulate cortex connectivity was correlated with an increase in Montreal Cognitive Assessment in diabetes. Conclusion This study suggests diabetes-related cognitive dysfunction is not a one-way process and the early-stage enhancement of brain connectivity was a potential “window period” for cognitive reversal.

Specialization and flexibility are two basic attributes of functional brain organization, enabling efficient cognition and behavior. However, it is largely unknown what plastic changes in specialization and flexibility in visual-motor areas occur in support of extraordinary motor skills in expert athletes and how the selective adaptability of the visual-motor system affects general perceptual or cognitive domains. Here, we used a dynamic network framework to investigate intrinsic functional specialization and flexibility of visual-motor system in expert table tennis players (TTP). Our results showed that sensorimotor areas increased intrinsic functional flexibility, whereas visual areas increased intrinsic functional specialization in expert TTP compared to nonathletes. Moreover, the flexibility of the left putamen was positively correlated with skill level, and that of the left lingual gyrus was positively correlated with behavioral accuracy of a sport-unrelated attention task. This study has uncovered dissociable plasticity of the visual-motor system and their predictions of individual differences in skill level and general attention processing. Furthermore, our time-resolved analytic approach is applicable across other professional athletes for understanding their brain plasticity and superior behavior.

Flexibility is a hallmark of human intelligence. Emerging studies have proposed several flexibility measurements at the level of individual regions, to produce a brain map of neural flexibility. However, flexibility is usually inferred from separate components of brain activity (i.e., intrinsic/task-evoked), and different definitions are used. Moreover, recent studies have argued that neural processing may be more than a task-driven and intrinsic dichotomy. Therefore, the understanding to neural flexibility is still incomplete. To address this issue, we propose a multifaceted definition of neural flexibility according to three key features: broad cognitive engagement, distributed connectivity, and adaptive connectome dynamics. For these three features, we first review the advances in computational approaches, their functional relevance, and their potential pitfalls. We then suggest a set of metrics that can help us assign a flexibility rating to each region. Subsequently, we present an emergent probabilistic view for further understanding the functional operation of individual regions in the unified framework of intrinsic and task-driven states. Finally, we highlight several areas related to the multifaceted definition of neural flexibility for future research. This review not only strengthens our understanding of flexible human brain, but also suggests that the measure of neural flexibility could bridge the gap between understanding intrinsic and task-driven brain function dynamics.

目的 运用静息态功能磁共振成像(resting-state function magnetic resonance imaging,rs-fMRI)探究太极拳零基础者在太极拳不同学习阶段的脑功能活动的局部一致性(regional homogeneity,ReHo)变化.材料与方法 采用被试内设计,对18名太极拳零基础被试在太极拳学习初期(2周)和学习14周进行同样内容的静息态功能磁共振成像检查.然后分别计算前后两个不同时间点被试的全脑ReHo值并进行相关统计学分析.结果 与太极拳学习2周比较,太极拳学习14周被试右侧梭状回的ReHo值显著增高,而右侧小脑和左侧顶上小叶的ReHo值显著降低(AlphaSim校正P<0.05);其中右侧小脑的ReHo的变化值与太极拳技能评分的变化值呈显著负相关(r=-0.507,P=0.032).多元回归分析发现,太极拳学习2周被试的右侧颞中回、右侧前扣带回的ReHo值与太极拳技能评分的变化量呈显著正相关(r=0.908、0.818,P<0.01),而左侧枕下回及右侧颞上回的ReHo值与太极拳技能评分的变化量呈显著负相关(r=-0.474,P<0.05;r=-0.824,P<0.01).结论 研究结果 表明,随着太极拳学习技能水平的提高,被试的静息态功能活动局部一致性变化,反映了相关脑区可塑性.另外,太极拳学习初期某些脑区的ReHo值对太极拳技能学习效果有一定的潜在预测作用.

目的运用磁共振扩散张量成像(diffusion tensor imaging,DTI)探究脑卒中皮质脊髓束(corticospinal tract,CST)扩散定量指标与运动功能的关系.材料与方法采集37例单侧皮质下脑卒中患者和30例健康被试的DTI数据,运用概率性纤维束成像追踪出健康被试的CST,获得健康对照组CST模板.基于健康对照组的CST模板测量两组被试双侧CST的各向异性分数(fractional anisotropy,FA)和平均扩散率(mean diffusivity,MD),进一步计算两组被试FA比率(FA ratio,rFA)、FA不对称性(FA asymmetry,FAasy)、MD比率(MD ratio,rMD)和MD不对称性(MD asymmetry,MDasy),用这六个扩散参数相关指标来评估脑卒中患者CST完整性损伤,并与患者"手+腕"及上肢运动功能评分(Fugl-Meyer Assessment,FMA)作相关性分析.结果与健康对照组相比,卒中组病灶同侧CST的FA、rFA显著降低(分别为t=-15.775,t=-11.111,P<0.001),FAasy显著增高(t=9.473,P<0.001);而MD、rMD显著增高(分别为t=9.553,t=7.733,P<0.001),MDasy显著降低(t=-8.941,P<0.001);病灶对侧CST的FA和MD均无显著变化(P>0.05).患者病程及病灶大小与各扩散指标间均无显著相关关系(P>0.05).卒中组病灶同侧CST的FA和rFA与"手+腕"及上肢FMA呈显著正相关(分别为r=0.342,P=0.038;r=0.479,P=0.003;r=0.343,P=0.038;r=0.482,P=0.003),FAasy与"手+腕"及上肢FMA呈显著负相关(分别为r=-0.353,P=0.032;r=-0.490,P=0.002).分步回归分析进一步发现,相较于病灶同侧CST的FA和rFA,FAasy与"手+腕"和上肢运动功能评分更加相关(分别为Beta=-0.353,P=0.032;Beta=-0.490,P=0.002).结论基于健康对照组CST模板测得的FA相关指标能反映CST结构完整性.FAasy与"手+腕"及上肢运动功能评分密切相关,或许可作为评估脑卒中患者手腕部和上肢运动功能障碍的重要参考指标.

目的 探讨皮质下脑卒中后手运动相关脑区正负网络连接的变化及与运动功能障碍的关系.材料与方法 对18例单侧皮层下脑卒中患者和18名性别、年龄完全匹配的健康志愿者分别进行静息态功能磁共振成像(resting-state functional magnetic resonance imaging,rs-fMRI)检查.以左侧初级运动皮质(primary motor cortex,M1,对应病灶侧)内与手运动功能相关的区域为感兴趣区,基于体素水平的全脑功能连接方法 分析手运动相关的正网络和负网络;进一步基于感兴趣区水平的功能连接方法 分析正负网络内和网络间功能连接的变化;最后,将卒中患者异常的功能连接指标与上肢运动功能评分进行相关性分析.结果 卒中组与病灶侧M1功能连接显著大于对照组的脑区均在负网络内;而显著小于对照组的脑区均在正网络内;卒中组正负网络内和网络间的功能连接强度均显著降低;且病灶侧M1与负网络内同侧额中回的功能连接系数与上肢运动功能评分呈负相关(r=-0.735,P<0.01).结论 脑卒中后与手运动相关脑区的正负网络连接强度均下降.尤其是卒中组大于对照组的功能连接可能并非意味相关脑区的"功能代偿",而是反映了手运动相关脑区之间的负性功能连接降低,这将更有利于深入理解脑卒中神经作用机制并为康复干预提供参考价值.