Neuroimage-Clinical最新文献

英文中文

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01

引用次数: 0

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01

引用次数: 0

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01

引用次数: 0

Separating the forest from the palm trees: Individual variation in a presurgical language mapping task 从棕榈树中分离森林：手术前语言映射任务中的个体差异

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2026.103943

Natalie L. Voets , Oiwi Parker Jones , Mohamed L. Seghier , Puneet Plaha

Background

Selecting optimal tasks for language mapping in neurosurgical patients poses challenges that are exacerbated by mismatches in practice between presurgical and intraoperative evaluations. To help align practices, we evaluated a functional MRI version of a semantic association task increasingly used during intra-operative assessment of awake neurosurgery patients. Using a recently proposed consistency mapping approach, we characterise task fMRI activation reliability across individuals, visits, and scan cohorts.

Methods

FMRI data were acquired during an adapted Pyramids and Palm Trees Task (PPTT) in 15 healthy controls and 54 pre-surgical patients with a glioma. A new implementation of threshold-weighted overlap mapping (TWOM) was used to evaluate: 1. inter-individual variability in task activations among individuals; 2. test–retest variability in controls scanned twice (16 ± weeks apart); 3. between-scanner reliability across two patient cohorts scanned on a 3 T Siemens Prisma (n = 27) or Verio (n = 24) scanner using standard (TR = 3 s, voxel size 3 × 3 × 3 mm) or advanced (TR = 0.93 s, voxel size 2x2x2 mm) fMRI acquisitions, respectively.

Results

Task-related activations in the core language network were highly consistent between individuals and across test–retest sessions. Several brain regions showed variable activations, reflecting atypical language dominance (confirmed during neurosurgery), or differences in regional involvement during semantic processing.

Conclusion

The PPTT engaged widespread brain networks including but not limited to regions implicated in semantic processing. Overlap mapping is a powerful way to visualise meaningful variations in neural processing at the individual level, supporting alignment of pre- and intra-operative mapping for any given task.

为神经外科患者选择最佳的语言映射任务是一项挑战，而手术前和术中评估之间的不匹配加剧了这一挑战。为了帮助调整实践，我们评估了语义关联任务的功能性MRI版本，该任务越来越多地用于对清醒的神经外科患者进行术中评估。使用最近提出的一致性映射方法，我们描述了个体、访问和扫描队列之间任务fMRI激活的可靠性。方法采用金字塔和棕榈树任务（PPTT）对15名健康对照者和54名手术前胶质瘤患者进行sfmri数据采集。采用一种新的阈值加权重叠映射（TWOM）方法进行评价：个体间任务激活的个体间变异；2. 对照扫描两次（间隔16±周）的重测变异性；3. 两组患者分别在3t Siemens Prisma （n = 27）或Verio （n = 24）扫描仪上使用标准（TR = 3秒，体素大小为3 × 3 × 3mm）或高级（TR = 0.93秒，体素大小为2x2x2 mm）功能磁共振成像扫描的扫描仪间可靠性。结果核心语言网络的任务相关激活在个体之间和重复测试期间高度一致。几个大脑区域表现出不同的激活，反映了非典型的语言优势（在神经外科手术中得到证实），或者在语义处理过程中区域参与的差异。结论PPTT涉及广泛的大脑网络，包括但不限于涉及语义处理的区域。重叠映射是一种强大的方法，可以在个体层面上可视化神经处理的有意义的变化，支持对任何给定任务进行术前和术中映射的对齐。

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引用次数: 0

Resting-State EEG captures functional network correlates of plasma p-Tau-217 in Alzheimer’s disease 静息状态脑电图捕获阿尔茨海默病血浆p-Tau-217的功能网络相关

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2026.103947

Giordano Cecchetti , Jacopo Lanzone , Luca Zanchi , Giulia Rugarli , Silvia Basaia , Marco Cursi , Federico Coraglia , Edoardo G. Spinelli , Alma Ghirelli , Elisa Canu , Elisa Sibilla , Francesca Caso , Roberto Santangelo , Davide Curti , Giovanna Franca Fanelli , Anna Bellini , Giuseppe Magnani , Federica Agosta , Massimo Filippi

Background

Scalable biomarkers are needed for early Alzheimer’s disease (AD) detection. Plasma p-tau217 reflects AD pathology, while resting-state EEG captures functional brain alterations. Their relationship remains unclear.

Methods

We enrolled 128 patients with subjective cognitive decline (SCD), mild cognitive impairment due to AD (AD-MCI), or AD dementia (AD-DEM), who underwent 32-channel EEG and plasma biomarker assessment. EEG features included spectral, aperiodic, phase–amplitude coupling, and complexity metrics. Machine learning was used to classify p-tau217 positivity.

Results

AD-MCI and AD-DEM patients showed increased p-tau217 and spectral slowing (higher theta, lower alpha). While no correlations survived correction for multiple comparisons, stage-specific analyses revealed positive associations between theta power and p-tau217 in AD-MCI and AD-DEM. A random forest classifier achieved an AUC of 0.75 in predicting p-tau217 positivity.

Conclusions

EEG captures functional alterations reflecting AD pathology beyond molecular measures, supporting its value as a complementary, non-invasive biomarker for early stratification in clinical settings.

背景：早期阿尔茨海默病（AD）检测需要可扩展的生物标志物。血浆p-tau217反映AD病理，而静息状态脑电图捕捉功能性脑改变。他们的关系尚不清楚。方法我们招募了128例主观认知能力下降（SCD）、AD所致轻度认知障碍（AD- mci）或AD痴呆（AD- dem）患者，对他们进行了32通道脑电图和血浆生物标志物评估。脑电图特征包括频谱、非周期性、相幅耦合和复杂性指标。使用机器学习对p-tau217正性进行分类。结果ad - mci和AD-DEM患者p-tau217升高，波谱变慢（高θ，低α）。虽然多重比较校正后没有相关性，但特定阶段的分析显示AD-MCI和AD-DEM中theta功率与p-tau217之间存在正相关。随机森林分类器预测p-tau217阳性的AUC为0.75。结论seeg能够捕捉到分子测量之外反映AD病理的功能改变，支持其作为临床早期分层的补充、非侵入性生物标志物的价值。

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引用次数: 0

Investigating causal relations between brain morphology and genetic risk variants in Parkinson’s disease 研究脑形态与帕金森病遗传风险变异之间的因果关系

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2025.103928

Gabrielle Dagasso , Vibujithan Vigneshwaran , Anthony J Winder , Raissa Souza , Erik Y. Ohara , Matthias Wilms , Nils D. Forkert

Imaging genomics for Parkinson’s disease (PD) research aims to integrate genetic and imaging biomarkers to explore how genetic alterations influence brain morphology and function. However, traditional methods have been largely correlative, limiting their utility. Recent advances in machine learning offer potential for exploring causal relationships, although these have not yet been applied to investigate genetic variants and brain phenotypes in PD.

Thus, we employ a causal deep learning approach for genotype-phenotype analysis in PD using a novel method to assess the causal impact of genetic risk variants on brain structures.

A masked causal normalizing flow model was adapted to evaluate genetic variants associated with PD and their effects on brain structures. The Parkinson’s Progression Markers Initiative (PPMI) dataset was used for development and evaluation, we included 102 controls, 214 patients with PD, and 43 patients with prodromal PD (n = 359), with 223 males (age range 31–82) An additional testing on neurologically healthy participants from the UK Biobank for validation was done as well, with 16,861 participants (Male n = 7,747, age range: 44–82).

The causal deep learning model identified several significant causal relationships: the rs4073221 variant in SATB1 affects the right putamen volume (p-value = 6.8x10^-5) and the T408M (rs75548401) variant in GBA1 influences the right pars triangularis volume (p-value = 1x10^-13), aligning with known PD pathophysiology. Complex variant analysis of LRRK2 G2019S and GBA1 E365K showed individual-level volumetric changes. Similar trends were found in the UK Biobank and PPMI datasets, demonstrating reasonable generalization.

The proposed causal deep learning framework reveals promising results for investigating genetic-brain architectures in PD. It demonstrates feasibility for further imaging genomics studies in PD and other neurological disorders.

帕金森病（PD）成像基因组学研究旨在整合遗传和成像生物标志物，探索遗传改变如何影响大脑形态和功能。然而，传统方法在很大程度上是相互关联的，限制了它们的实用性。机器学习的最新进展为探索因果关系提供了潜力，尽管这些尚未应用于研究PD的遗传变异和大脑表型。因此，我们采用因果深度学习方法对PD进行基因型-表型分析，使用一种新的方法来评估遗传风险变异对大脑结构的因果影响。一个被掩盖的因果归一化流模型被用来评估与PD相关的遗传变异及其对大脑结构的影响。帕金森病进展标志物倡议（PPMI）数据集用于开发和评估，我们包括102名对照组，214名PD患者和43名前驱PD患者（n = 359），其中223名男性（年龄范围31-82岁）。此外，我们还对来自英国生物银行的神经健康参与者进行了额外的测试，共16,861名参与者（男性n = 7,747，年龄范围44-82岁）。因果深度学习模型确定了几个重要的因果关系：SATB1中的rs4073221变异影响右侧壳核体积（p值= 6.8x10-5）， GBA1中的T408M （rs75548401）变异影响右侧三角部体积（p值= 1x10-13），与已知的PD病理生理学一致。LRRK2 G2019S和GBA1 E365K的复杂变异分析显示个体水平的体积变化。在英国生物银行和PPMI数据集中也发现了类似的趋势，证明了合理的推广。提出的因果深度学习框架为研究帕金森病的遗传-大脑结构揭示了有希望的结果。它证明了PD和其他神经系统疾病进一步成像基因组学研究的可行性。

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引用次数: 0

Depression vulnerability involves brain activity and connectivity changes consistent with cholinergic deviancy 抑郁易感性涉及与胆碱能偏差一致的大脑活动和连通性变化。

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2025.103941

Peter Stiers, Zoe Samara, Kyran J.R. Kuijpers, Elisabeth A.T. Evers, Johannes G. Ramaekers

Behavioral and imaging studies suggests that emotional biases in the perception of faces associated with major depression disorder (MD) may be embedded within a broader sensory processing deficit. Increased cortical acetylcholine in MD suggest that this deficit may be related to abnormal attention modulation of sensory areas. It is not clear, however, whether these problems are a manifestation of the disease or whether they precede symptom onset. To investigate this, we applied functional magnetic resonance imaging (fMRI) to look for brain activity changes that participants with a family risk of MD (N = 30) shared with participant with MD (N = 28), compared to matched controls (N = 28). Participants were scanned while performing gender categorization of sad, happy, and neutral face pictures, as well as during a state of rest. Task-related activity changes, shared by participants at risk of and suffering from MD, were mostly seen in the posterior brain: increased activity in dorsal attention and visual association cortex, and decreased in lower visual areas. The changes did not differ between neutral faces and faces expressing an emotion. The at risk and MD participants additionally showed increased functional connectivity between the dorsal attention clusters and the lingual gyrus, and decreased connectivity with the lateral occipital complex (LOC). Lastly, they also had in common increased functional connectivity of magnocellular basal forebrain seeds with LOC and visual association cortex. These changes are consistent with an acetylcholine-mediated change in attention-guided sensory processing of all environmental events, which is discernable even before the first MD episode.

行为和影像学研究表明，与重度抑郁症（MD）相关的面部感知中的情绪偏差可能嵌入在更广泛的感觉加工缺陷中。MD的皮质乙酰胆碱增加表明这种缺陷可能与感觉区域的异常注意调节有关。然而，尚不清楚这些问题是疾病的表现，还是在症状出现之前。为了研究这一点，我们应用功能磁共振成像（fMRI）来寻找具有MD家族风险的参与者（N = 30）与MD参与者（N = 28）的大脑活动变化，并与匹配的对照组（N = 28）进行比较。在对悲伤、快乐和中性的人脸图片进行性别分类时，以及在休息状态下，对参与者进行扫描。与任务相关的活动变化，在有MD风险和患有MD的参与者中，主要出现在大脑后部：背侧注意力和视觉关联皮层的活动增加，而下视觉区域的活动减少。这些变化在中性的脸和表达情绪的脸之间没有区别。此外，高风险和MD参与者还表现出背侧注意簇和舌回之间的功能连通性增加，与外侧枕复合体（LOC）的连通性减少。最后，他们的大细胞基底前脑种子与LOC和视觉关联皮层的功能连通性也普遍增加。这些变化与乙酰胆碱介导的对所有环境事件的注意引导感觉加工的变化是一致的，甚至在第一次MD发作之前就可以辨别出来。

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引用次数: 0

The structural, functional, and neurophysiological connectome of mild traumatic brain injury: A DTI, fMRI and MEG multimodal clustering and data fusion study 轻度外伤性脑损伤的结构、功能和神经生理连接组：DTI、fMRI和MEG多模态聚类和数据融合研究。

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2026.103946

Jing Zhang , Kevin G. Solar , Kristina Safar , Rouzbeh Zamyadi , Marlee M. Vandewouw , Leodante Da Costa , Shawn G. Rhind , Rakesh Jetly , Benjamin T. Dunkley

The clinical presentation and neurobiology of mild traumatic brain injury (mTBI) − also referred to as concussion − are complex and multifaceted, and interrelationships between neurobiological measures derived from neuroimaging are poorly understood. This study applied machine learning (ML) to multimodal whole-brain functional connectomes from magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and structural connectomes from diffusion tensor imaging (DTI) in a test of discriminative accuracy in cases of mTBI. Resting state MEG (amplitude envelope correlations), fMRI (BOLD correlations), and DTI (fractional anisotropy, FA; streamline count, SC) connectome data was acquired in 26 controls without mTBI (all male; 27.6 ± 4.7 years) and 24 participants with mTBI (all male; 29.7 ± 6.7 years) in the acute-subacute phase of injury. ML with data fusion was used to optimally identify modalities and brain features for discriminating individuals with mTBI from those without. Univariate group differences were only found for MEG functional connectivity, while no differences were found for fMRI or DTI. Functional connectivity (fMRI and MEG) showed robust unimodal classification accuracy for mTBI, followed by structural connectivity (DTI), where FA showed marginally better classification performance than SC, but SC outperformed FA in data interpretation and fusion. Perfect, unsupervised separation of participants with and without mTBI was achieved through participant fusion maps featuring all three data modalities. Finally, the MEG-only full feature fusion map showed group differences, and this effect was eliminated upon integrating DTI and fMRI datasets. The markers identified here align well with prior multimodal findings in concussion and highlight modality-specific considerations for their use in understanding network abnormalities of mTBI.

轻度创伤性脑损伤（mTBI）的临床表现和神经生物学（也称为脑震荡）是复杂和多方面的，神经影像学得出的神经生物学测量之间的相互关系尚不清楚。本研究将机器学习（ML）应用于脑磁图（MEG）和功能磁共振成像（fMRI）的多模态全脑功能连接体，以及弥散张量成像（DTI）的结构连接体，以测试mTBI病例的判别准确性。静息状态MEG（振幅包膜相关性）、fMRI （BOLD相关性）和DTI（分数各向异性，FA；流线计数，SC）连接体数据在26例未患mTBI的对照组（均为男性，27.6±4.7岁）和24例急性-亚急性期mTBI患者（均为男性，29.7±6.7岁）中获得。使用数据融合的ML来最佳地识别mTBI患者和非mTBI患者的模式和大脑特征。单变量组差异仅存在于MEG功能连接上，而在fMRI或DTI上没有发现差异。功能连通性（fMRI和MEG）对mTBI显示出稳健的单峰分类准确性，其次是结构连通性（DTI），其中FA的分类性能略好于SC，但SC在数据解释和融合方面优于FA。通过具有所有三种数据模式的参与者融合图，实现了有和没有mTBI的参与者的完美无监督分离。最后，MEG-only全特征融合图显示出组间差异，在整合DTI和fMRI数据集时消除了这种影响。本研究发现的标记物与先前在脑震荡中的多模态发现很好地吻合，并强调了在理解mTBI网络异常时对特定模态的考虑。

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引用次数: 0

The effect of iron deposition on cognitive fatigue in multiple sclerosis 铁沉积对多发性硬化症认知疲劳的影响。

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01 DOI: 10.1016/j.nicl.2026.103953

Bing Yao , John DeLuca , Glenn R. Wylie

Cognitive fatigue (CF) is a prevalent and disabling symptom in multiple sclerosis (MS), but its neural underpinnings remain poorly understood. Emerging evidence suggests that iron accumulation in deep gray matter, particularly the basal ganglia, may contribute to CF by disrupting neural activity. This study examined the relationship between brain iron deposition and CF in individuals with MS using functional MRI (fMRI) and quantitative susceptibility mapping (QSM).

Seventy participants with relapsing-remitting MS (RRMS) and 30 matched healthy controls underwent a task-switching paradigm during fMRI, alternating between color and speed judgments to induce CF. Iron concentration in the caudate, putamen, and globus pallidus was measured using multi-echo gradient echo (ME-GRE) sequences. CF was evaluated with a visual analog scale (VAS-F), and behavioral performance was assessed by response time and accuracy.

MS participants showed significantly greater CF over time, with increasing VAS-F scores and slower, less accurate responses compared to controls. Higher iron levels in the left caudate correlated with steeper CF slopes and reduced activation in fatigue-related regions, including the dorsolateral and ventromedial prefrontal cortex and anterior cingulate cortex. A significant Group × Iron × CF interaction indicated opposite patterns of activation: while MS patients showed decreased activation with higher iron, controls exhibited increased activation, suggesting a compensatory response.

These findings suggest that abnormal iron accumulation contributes to CF in MS and may impair functional compensation. Iron-sensitive MRI may offer a promising biomarker to identify individuals at risk for debilitating fatigue and guide interventions targeting iron metabolism.

认知疲劳（CF）是多发性硬化症（MS）中一种普遍的致残症状，但其神经基础尚不清楚。新出现的证据表明，铁积聚在深部灰质，特别是基底神经节，可能通过破坏神经活动而导致CF。本研究利用功能磁共振成像（fMRI）和定量易感性制图（QSM）研究了MS患者脑铁沉积与CF之间的关系。70名患有复发缓解型多发性硬化（RRMS）的参与者和30名匹配的健康对照者在fMRI期间进行了任务转换范式，在颜色和速度判断之间交替以诱导CF。使用多回声梯度回声（ME-GRE）序列测量尾状核、壳核和苍白球中的铁浓度。用视觉模拟量表（VAS-F）评价CF，用反应时间和准确度评价行为表现。随着时间的推移，MS参与者表现出明显更大的CF，与对照组相比，VAS-F评分增加，反应更慢，更不准确。高铁水平的左尾状核与更陡峭的CF斜坡和疲劳相关区域的激活减少相关，包括背外侧和腹内侧前额叶皮层和前扣带皮层。显著的组×铁× CF相互作用表明相反的激活模式：MS患者在高铁条件下表现出活性降低，而对照组表现出活性增加，提示代偿反应。这些发现表明，异常铁积累有助于MS中的CF，并可能损害功能代偿。铁敏感MRI可能提供一种有前景的生物标志物，用于识别有衰弱性疲劳风险的个体，并指导针对铁代谢的干预。

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引用次数: 0

IF 3.6 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical

Pub Date : 2026-01-01

引用次数: 0

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