NeuroImage最新文献_第8页

Lateralization study of the basal ganglia, thalamus and supplying arteries in healthy individuals based on structure and connectivity analysis using 7.0T MRI 基于7.0T MRI结构和连通性分析的健康人基底神经节、丘脑和供血动脉侧化研究

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-02-01 DOI: 10.1016/j.neuroimage.2025.121007

Hongqin Liang , Yawei Gu , Xiaoqi Yi , Li Kong , Jian Wang , Fajin Lv

The human cerebral cortex is known for its hemispheric specialization, which underpins a variety of functions and activities. However, it is not well understood if similar lateralization exists within the deep gray matter nuclei, such as the basal ganglia (BG) and thalamus, and their associated arteries, including the lenticulostriate arteries (LSAs). To explore this, we analyzed images from 7T MRI scans of 40 healthy young individuals. We isolated the LSAs and analyzed their morphological characteristics. Additionally, we segmented the bilateral BG and thalami into 28 subregions based on the Brainnetome atlas and calculated their volumes using single-subject voxel-based morphometry (VBM) analysis. We also obtained four parameters from Diffusion Tensor Imaging (DTI) within these 28 subregions. Bilateral comparisons were conducted using paired t-tests for all measurements. Connectivity-network matrices, based on the number of connecting fibers and fractional anisotropy between subregions, were constructed. The results showed that in the right-handed dominant population, we observed that the total number and length of LSAs in the left hemisphere exceeded those in the right. Among the 28 subregions, several showed leftward volume dominance, including the ventral caudate, globus pallidus, ventromedial putamen, medial pre-frontal thalamus, occipital thalamus, and caudal temporal thalamus. In contrast, the nucleus accumbens, dorsal caudate, dorsolateral putamen, pre-motor thalamus, sensory thalamus, posterior parietal thalamus, and lateral pre-frontal thalamus showed rightward volume dominance. Except for the ventral medial putamen (vmPu), all other subnuclei displayed at least three DTI measures with left-right differences. The connectivity between subregions revealed distinct patterns in the bilateral hemispheres, with a leftward dominance. Collectively, these findings enhance our understanding of lateralization within subcortical structures.

人类大脑皮层以其半球特化而闻名，它支撑着各种功能和活动。然而，是否类似的侧化存在于深部灰质核，如基底神经节（BG）和丘脑，以及它们的相关动脉，包括皮质纹状体动脉（LSAs），目前还不清楚。为了探讨这一点，我们分析了40名健康年轻人的7T MRI扫描图像。我们分离了LSAs并分析了它们的形态特征。此外，我们基于脑组图谱将双侧BG和丘脑划分为28个亚区，并使用基于单受试者体素的形态测量（VBM）分析计算了它们的体积。我们还从这28个子区域的扩散张量成像（DTI）中获得了四个参数。采用配对t检验对所有测量值进行双边比较。基于连接纤维的数量和子区域之间的分数各向异性，构建了连接网络矩阵。结果表明，在右撇子优势群体中，我们观察到左半球LSAs的总数和长度超过右半球。在28个亚区中，有几个显示左侧体积优势，包括腹侧尾状核、苍白球、腹内侧壳核、内侧前额丘脑、枕侧丘脑和尾侧颞丘脑。相反，伏隔核、尾状背核、壳核背外侧、运动前丘脑、感觉丘脑、顶叶后丘脑和外侧额前丘脑的体积向右占优势。除腹侧内侧壳核（vmPu）外，所有其他亚核均显示至少三个DTI测量值，且左右差异。子区域之间的连通性在双侧半球显示出明显的模式，以左为主。总的来说，这些发现增强了我们对皮层下结构侧化的理解。

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引用次数: 0

Right inferior frontal cortex and preSMA in response inhibition: An investigation based on PTC model 基于PTC模型的右下额叶皮质和前脑区反应抑制研究。

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-02-01 DOI: 10.1016/j.neuroimage.2025.121004

Lili Wu , Mengjie Jiang , Min Zhao , Xin Hu , Jing Wang , Kaihua Zhang , Ke Jia , Fuxin Ren , Fei Gao

Response inhibition is an essential component of cognitive function. A large body of literature has used neuroimaging data to uncover the neural architecture that regulates inhibitory control in general and movement cancelation. The presupplementary motor area (preSMA) and the right inferior frontal cortex (rIFC) are the key nodes in the inhibitory control network. However, how these two regions contribute to response inhibition remains controversial. Based on the Pause-then-Cancel Model (PTC), this study employed functional magnetic resonance imaging (fMRI) to investigate the functional specificity of two regions in the stopping process. The Go/No-Go task (GNGT) and the Stop Signal Task (SST) were administered to the same group of participants. We used the GNGT to dissociate the pause process and both the GNGT and the SST to investigate the inhibition mechanism. Imaging data revealed that response inhibition produced by both tasks activated the preSMA and rIFC. Furthermore, an across-participants analysis showed that increased activation in the rIFC was associated with a delay in the go response in the GNGT. In contrast, increased activation in the preSMA was associated with good inhibition efficiency via the striatum in both GNGT and SST. These behavioral and imaging findings support the PTC model of the role of rIFC and preSMA, that the former is involved in a pause process to delay motor responses, whereas the preSMA is involved in the stopping of motor responses.

反应抑制是认知功能的重要组成部分。大量文献利用神经成像数据揭示了调节一般抑制控制和运动取消的神经结构。前辅助运动区（preSMA）和右侧额叶下皮层（rIFC）是抑制控制网络的关键节点。然而，这两个区域如何参与反应抑制仍然存在争议。本研究基于暂停-取消模型（Pause-then-Cancel Model， PTC），采用功能磁共振成像（functional magnetic resonance imaging, fMRI）研究两个区域在停止过程中的功能特异性。Go/No-Go任务（GNGT）和停止信号任务（SST）被分配给同一组参与者。我们使用GNGT来分离暂停过程，并使用GNGT和SST来研究抑制机制。成像数据显示，这两个任务产生的反应抑制激活了preSMA和rIFC。此外，跨参与者分析表明，rIFC激活的增加与GNGT的go反应延迟有关。相比之下，在GNGT和SST中，preSMA激活的增加与通过纹状体的良好抑制效率有关。这些行为和影像学研究结果支持了PTC模型中rIFC和preSMA的作用，即前者参与暂停过程以延迟运动反应，而preSMA参与停止运动反应。

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引用次数: 0

qPRF: A system to accelerate population receptive field modeling qPRF：一个加速群体接受场建模的系统。

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-02-01 DOI: 10.1016/j.neuroimage.2024.120994

Sebastian Waz , Yalin Wang , Zhong-Lin Lu

BOLD response can be fitted using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). Fitting the PRF model costs considerable time, often requiring days to analyze BOLD signals for a small cohort of subjects. We introduce the qPRF (“quick PRF”), a system for accelerated PRF modeling that reduced the computation time by a factor

> 1, 000

without losing goodness-of-fit when compared to another widely available PRF modeling package (Kay et al., 2013) on a benchmark of data from the Human Connectome Project (HCP; Van Essen et al. (2013). The system achieves this level of acceleration by pre-computing a tree-like data structure, which it rapidly searches during the fitting step for an optimal parameter combination. We tested the method on a constrained four-parameter version of the PRF model (Strategy 1 herein) and an unconstrained five-parameter PRF model, which the qPRF fitted at comparable speed (Strategy 2). We show how an additional search step can guarantee optimality of qPRF solutions with little additional time cost (Strategy 3). To assess the quality of qPRF solutions, we compared our Strategy 1 solutions to those provided by Benson et al. (2018) who performed a similar four-parameter fit. Both hemispheres of the 181 subjects in the HCP dataset (a total of 10,753,572 vertices, each with a unique BOLD time series of 1800 frames) were analyzed by qPRF in 12.82 h on an ordinary CPU. The absolute difference in

R^{2}

achieved by the qPRF compared to Benson et al. (2018) was negligible, with a median of 0.025% (

R^{2}

units being between 0% and 100%). In general, the qPRF yielded a slightly better fitting solution, achieving a greater

R^{2}

on 70.2% of vertices. We also assess the qPRF method’s model-recovery ability using a simulated dataset. The qPRF may facilitate the development and use of more elaborate models based on the PRF framework and may pave the way for novel clinical applications.

BOLD反应可以使用群体接受野（PRF）模型来拟合，以揭示视觉输入是如何在皮层上表示的（Dumoulin和Wandell， 2008）。拟合PRF模型需要相当长的时间，通常需要数天的时间来分析一小群受试者的BOLD信号。我们引入了qPRF（“快速PRF”），这是一个加速PRF建模的系统，与另一个广泛使用的PRF建模包（Kay等人，2013）相比，它在人类连接组项目(HCP；Van Essen et al.（2013）。该系统通过预先计算一个树状数据结构来实现这种程度的加速，并在拟合步骤中快速搜索最优参数组合。我们测试方法的约束的四个参数版本PRF模型(此处策略1)和一个不受约束的5个参数编码脉冲模型,其中qPRF安装速度可比(策略2)。我们展示一个额外的搜索步骤可以保证最优qPRF解决方案几乎没有额外时间成本(战略3)。评估qPRF解决方案的质量,我们比较我们的策略1解决方案提供的那些本森et al .(2018)执行一个类似的四个参数。在普通CPU上，使用qPRF在12.82 h内分析了HCP数据集中181名受试者的两个半球（共10,753,572个顶点，每个顶点具有唯一的1,800帧BOLD时间序列）。与Benson等人（2018）相比，qPRF实现的R2绝对差异可以忽略不计，中位数为0.025% （R2单位介于0%和100%之间）。一般来说，qPRF产生了稍微更好的拟合解决方案，在70.2%的顶点上实现了更大的R2。我们还使用模拟数据集评估了qPRF方法的模型恢复能力。qPRF可以促进基于PRF框架的更精细模型的开发和使用，并可能为新的临床应用铺平道路。

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引用次数: 0

The impact of channel density, inverse solutions, connectivity metrics and calibration errors on OPM-MEG connectivity analysis: A simulation study

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-31 DOI: 10.1016/j.neuroimage.2025.121056

Shengjie Qi , Xinda Song , Le Jia , Hongyu Cui , Yuchen Suo , Tengyue Long , Zhendong Wu , Xiaolin Ning

Magnetoencephalography (MEG) systems based on optically pumped magnetometers (OPMs) have rapidly developed in the fields of brain function, health, and disease. Functional connectivity analysis related to the resting-state has gained popularity as a field of research in recent years. Several studies have attempted to use OPM-based MEG (OPM-MEG) for brain network estimation research; however, the choice of source connectivity analysis pipeline may lead to outcome variability. Several methods and related parameters must be selected carefully at each step of the analysis. Therefore, this study assessed the effect of such analytical variability on the OPM-MEG connectivity analysis by conducting simulations. Synthetic MEG data corresponding to two default mode networks (DMN) with six or ten DMN regions were generated using the Gaussian Graphical Spectral (GGS) model. Six intersensor spacings were constructed, and six inverse algorithms and six functional connectivity measures were selected to assess their impact on the network reconstruction accuracy. Three potential sources of error – errors in the sensor gain, crosstalk, and angular errors of the sensitive axis of the OPM – were also assessed. Analytical variability with regard to the tested intersensor spacings, inverse solutions, and functional connectivity measures led to high result variability. Crosstalk exerted a significant impact on the accuracy, which may lead to network reconstruction failure. The accuracy improvement caused by an increase in the sensor density may be reduced by gain and angular errors. The minimum norm estimate (MNE) and weighted minimum norm estimate (wMNE) exhibited low robustness to sensor noise and calibration errors. Hence, a calibration workflow for accurate sensor parameters, such as the gain and direction of the sensitive axis, before commencing OPM-MEG measurement and a careful choice of different method combinations play crucial roles in ensuring that OPMs yield optimal results for functional connectivity analysis. A thorough framework for analyzing brain connectivity networks was provided herein.

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引用次数: 0

Reduced connection strength leads to enhancement of working memory capacity in cognitive training

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-30 DOI: 10.1016/j.neuroimage.2025.121055

Guiyang Lv , Tianyong Xu , Jinhang Li , Ping Zhu , Feiyan Chen , Dongping Yang , Guoguang He

It has been widely observed that cognitive training can enhance the working memory capacity (WMC) of participants, yet the underlying mechanisms remain unexplained. Previous research has confirmed that abacus-based mental calculation (AMC) training can enhance the WMC of subjects and suggested its possible association with changes in functional connectivity. With fMRI data, we construct whole brain resting state connectivity of subjects who underwent long-term AMC training and other subjects from a control group. Their working memory capacity is simulated based on their whole brain resting state connectivity and reservoir computing. It is found that the AMC group has higher WMC than the control group, and especially the WMC involved in the frontoparietal network (FPN), visual network (VIS) and sensorimotor network (SMN) associated with the AMC training is even higher in the AMC group. However, the advantage of the AMC group disappears if the connection strengths between brain regions are neglected. The effects on WMC from the connection strength differences between the AMC and control groups are evaluated. The results show that the WMC of the control group is enhanced and achieved consistency with or even better than that the AMC group if the connection strength of the control group are weakened. And the advantage of FPN, VIS and SMN is reproduced too. In conclusion, our work reveals a correlation between reduction in functional connection strength and enhancements in the WMC of subjects undergoing cognitive training.

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引用次数: 0

High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-30 DOI: 10.1016/j.neuroimage.2025.121070

Qinyang Shou , Chenyang Zhao , Xingfeng Shao , Megan M Herting , Danny JJ Wang

Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perfusion has been studied using multi-delay arterial spin labeling (MD-ASL) in adults but not in pediatric populations due to the challenge of small CP size in children. Here we present a high resolution (iso2 mm) MDASL protocol with 10-minute scan time and performed test-retest scans on 21 typically developing children aged 8 to 17 years. We further proposed a Transformer-based deep learning (DL) model with k-space weighted image average (KWIA) denoised images as reference for training the model. The performance of the model was evaluated by the SNR, bias and repeatability of the fitted perfusion parameters of the CP and gray matter. The proposed method was compared to several benchmark methods including KWIA, joint denoising and reconstruction with total generalized variation (TGV) regularization, as well as another self-supervised method termed Noise2Void. The results show that the proposed Transformer model with KWIA reference can effectively denoise multi-delay ASL images, not only improving the SNR for perfusion images of each delay, but also improving the SNR for the fitted perfusion maps for visualizing and quantifying CP perfusion in children. This may facilitate the use of MDASL in neurodevelopmental studies to characterize the development of CP and glymphatic system.

{"title":"High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI","authors":"Qinyang Shou , Chenyang Zhao , Xingfeng Shao , Megan M Herting , Danny JJ Wang","doi":"10.1016/j.neuroimage.2025.121070","DOIUrl":"10.1016/j.neuroimage.2025.121070","url":null,"abstract":"<div><div>Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perfusion has been studied using multi-delay arterial spin labeling (MD-ASL) in adults but not in pediatric populations due to the challenge of small CP size in children. Here we present a high resolution (iso2 mm) MDASL protocol with 10-minute scan time and performed test-retest scans on 21 typically developing children aged 8 to 17 years. We further proposed a Transformer-based deep learning (DL) model with k-space weighted image average (KWIA) denoised images as reference for training the model. The performance of the model was evaluated by the SNR, bias and repeatability of the fitted perfusion parameters of the CP and gray matter. The proposed method was compared to several benchmark methods including KWIA, joint denoising and reconstruction with total generalized variation (TGV) regularization, as well as another self-supervised method termed Noise2Void. The results show that the proposed Transformer model with KWIA reference can effectively denoise multi-delay ASL images, not only improving the SNR for perfusion images of each delay, but also improving the SNR for the fitted perfusion maps for visualizing and quantifying CP perfusion in children. This may facilitate the use of MDASL in neurodevelopmental studies to characterize the development of CP and glymphatic system.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121070"},"PeriodicalIF":4.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143075213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Different cortex activation between young and middle-aged people during different type problem-solving: An EEG&fNIRS study

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-30 DOI: 10.1016/j.neuroimage.2025.121062

Mevhibe Saricaoglu , Meryem Ayşe Yücel , Miray Budak , Ahmet Omurtag , Lutfu Hanoglu

Problem-solving strategies vary depending on the type of problem and aging. This study investigated the hemodynamic response measured by the changes in the oxyhemoglobin concentration (HbO), alpha frequency power, and their interrelation during problem-solving in healthy young and middle-aged individuals, employing combined electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recordings. The study included 39 young and 30 middle-aged subjects. The brain activation that occurred while answering different questions was recorded using combined EEG and fNIRS. During the EEG & fNIRS recording, four questions (arithmetic, general knowledge, insight, and basic operation) were used for problem-solving. Alpha power (8–13 Hz) and HbO changes were analyzed. The behavioral results indicated significant differences between age groups in various question types. While the middle-aged group performed better on the general knowledge questions, the older group performed better on the insight and four-process questions. The fNIRS results reveal significant differences in brain activation during problem-solving tasks, particularly in regions like DLPFC/TA, STG, pSSC/Wernicke, and STG/angular gyrus Wernicke's area. The young group with the highest HbO was recorded during arithmetic questions, general knowledge questions, and basic operation questions. In contrast, there was no significant highest HbO during insight questions. Similar findings were observed in the middle-aged group, with the highest HbO recorded during general knowledge questions. However, there was no significant HbO in other channels during the solving of other question types in this group. The alpha power varied across different electrodes for various question types in both young and middle-aged groups. The highest alpha frequency band power for different electrodes was recorded while solving general knowledge questions in the young group and insight questions in the middle-aged group. Finally, the EEG and fNIRS correlation results showed positive correlations between HbO and alpha frequency band power in specific brain regions while solving general knowledge questions, particularly in the middle-aged group.

The study reveals age-related differences in behavioral performance, brain activation patterns, and neural correlates during various cognitive tasks, showcasing distinct strengths between middle-aged and young individuals in specific question types.

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引用次数: 0

UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-30 DOI: 10.1016/j.neuroimage.2025.121064

Marco Capó , Silvia Vitali , Georgios Athanasiou , Nicole Cusimano , Daniel García , Garth Cruickshank , Bipin Patel , Alzheimer's Disease Neuroimaging Initiative

In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. Our analysis also includes established methodologies which have shown success in prior UK Biobank-related studies. For our analysis we used T1-weighted MRI scans and processed de novo all images via FastSurfer, transforming them into a conformed space for deep learning and extracting image-derived phenotypes for our machine learning approaches. We rigorously evaluated these approaches both as robust age predictors for healthy individuals and as potential biomarkers for various neurodegenerative conditions, leveraging data from the UK Biobank, ADNI, and NACC datasets. To this end we designed a statistical framework to assess age prediction performance, the robustness of the prediction across cohort variability (database, machine type and ethnicity) and its potential as a biomarker for neurodegenerative conditions. Results demonstrate that highly accurate brain age models, typically utilising penalised linear machine learning models adjusted with Zhang's methodology, with mean absolute errors under 1 year in external validation, can be achieved while maintaining consistent prediction performance across different age brackets and subgroups (e.g., ethnicity and MRI machine/manufacturer). Additionally, these models show strong potential as biomarkers for neurodegenerative conditions, such as dementia, where brain age prediction achieved an AUROC of up to 0.90 in distinguishing healthy individuals from those with dementia.

{"title":"UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases","authors":"Marco Capó , Silvia Vitali , Georgios Athanasiou , Nicole Cusimano , Daniel García , Garth Cruickshank , Bipin Patel , Alzheimer's Disease Neuroimaging Initiative","doi":"10.1016/j.neuroimage.2025.121064","DOIUrl":"10.1016/j.neuroimage.2025.121064","url":null,"abstract":"<div><div>In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. Our analysis also includes established methodologies which have shown success in prior UK Biobank-related studies. For our analysis we used T1-weighted MRI scans and processed de novo all images via FastSurfer, transforming them into a conformed space for deep learning and extracting image-derived phenotypes for our machine learning approaches. We rigorously evaluated these approaches both as robust age predictors for healthy individuals and as potential biomarkers for various neurodegenerative conditions, leveraging data from the UK Biobank, ADNI, and NACC datasets. To this end we designed a statistical framework to assess age prediction performance, the robustness of the prediction across cohort variability (database, machine type and ethnicity) and its potential as a biomarker for neurodegenerative conditions. Results demonstrate that highly accurate brain age models, typically utilising penalised linear machine learning models adjusted with Zhang's methodology, with mean absolute errors under 1 year in external validation, can be achieved while maintaining consistent prediction performance across different age brackets and subgroups (e.g., ethnicity and MRI machine/manufacturer). Additionally, these models show strong potential as biomarkers for neurodegenerative conditions, such as dementia, where brain age prediction achieved an AUROC of up to 0.90 in distinguishing healthy individuals from those with dementia.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121064"},"PeriodicalIF":4.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143075270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural damage-driven brain compensation among near-centenarians and centenarians without dementia

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-29 DOI: 10.1016/j.neuroimage.2025.121065

Hui Tang , Haichao Zhao , Hao Liu , Jiyang Jiang , Nicole Kochan , Jing Jing , Henry Brodaty , Wei Wen , Perminder S. Sachdev , Tao Liu

Compensation has been proposed as a mechanism to explain how individuals in very old age remain able to maintain normal cognitive functioning. Previous studies have provided evidence on the role of increasing functional connectivity as a compensatory mechanism for age-related white matter damage. However, we lack direct investigation into how these mechanisms contribute to the preservation of cognition in the very old population. We examined a cohort of near-centenarians and centenarians without dementia (aged 95-103 years, n=44). We constructed a structural disconnection matrix based on the disruption of white matter pathways caused by white matter hyperintensities (WMHs), aiming to explore the relationship between functional connections, cognitive preservation and white matter damage. Our results revealed that structural damage can reliably explain the variations of functional connections or cognitive maintenance. Notably, we found significant correlations between the weights in the functional connectivity model and the weights in the cognition model. We observed positive correlations between models for brain disconnections and cognitive function in near-centenarians and centenarians. The strongest effects were found between attention and somatomotor network (SMN) (r=0.397, p<0.001), memory and SMN (r=0.333 p<0.001), fluency and visual network (VIS) - control network (CN) (r=0.406, p<0.001), language and VIS (r=0.309, p<0.001), visuospatial ability and VIS-default mode network (DMN) (r=0.464, p<0.001), as well as global cognition and VIS-DMN (r=0.335, p<0.001). These findings suggest that enhancement of functional connectivity may serve as a compensatory mechanism, such that it mitigates the effects of white matter damage and contributes to preserved cognitive performance in very old age.

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引用次数: 0

A Test-Retest Study of Single- and Multi-Delay pCASL for Choroid Plexus Perfusion Imaging in Healthy Subjects Aged 19 to 87 Years

IF 4.7 2区医学 Q1 NEUROIMAGING

NeuroImage

Pub Date : 2025-01-29 DOI: 10.1016/j.neuroimage.2025.121048

Zixuan Liu , Qinyang Shou , Kay Jann , Chenyang Zhao , Danny JJ Wang , Xingfeng Shao

There is a growing interest in the choroid plexus (ChP) due to its critical role in cerebrospinal fluid (CSF) production and its involvement in neurodegenerative and cerebrovascular diseases. However, comprehensive studies comparing the accuracy and reliability of single- and multi-PLD (post-labeling delay) arterial spin labeling (ASL) techniques, specifically in relation to the ChP, remain limited. This study systematically evaluated the test-retest reliability and quantification accuracy of cerebral blood flow (CBF) measurements, focusing on the ChP, using single-delay and multi-delay 3D gradient-and-spin echo (GRASE) pseudo-continuous ASL (pCASL) on 28 subjects (aged 19 to 87 years, 14 males/14 females) at 3.0 tesla. Both single-delay (2 s) and 5-PLD (0.5 – 2.5 s) pCASL scans were repeated approximately one week apart with a spatial resolution of 2.5 × 2.5 × 3 mm³. Voxel-wise and regional CBF and arterial transit time (ATT) measurements were compared to assess test-retest reliability, with a particular focus on ChP perfusion changes with age. In this study, 12.15 % of ChP voxels exhibited ATTs longer than 2 s, potentially leading to a significant underestimation of CBF using single-delay ASL. Multi-delay ASL showed improved accuracy in estimating CBF values for the ChP compared to single-delay ASL when ATT > PLD. Additionally, ChP volume (mean ± std = 1.72± 0.85 ml) increased (p < 0.01) and ChP perfusion (43.07±14.18 mL/100 g/min) decreased (p = 0.04) with age. These findings underscore the robustness of multi-delay ASL with model-fitting quantification in assessing ChP perfusion, making it the preferred method for accurate CBF and ATT estimation, particularly in regions with prolonged transit time such as ChP.

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引用次数: 0