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Sleep-spindles as a marker of attention and intelligence in dogs 作为狗的注意力和智力标志的睡眠锭。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-11-05 DOI: 10.1016/j.neuroimage.2024.120916
Ivaylo Borislavov Iotchev , Dóra Szabó , Borbála Turcsán , Zsófia Bognár , Eniko Kubinyi
The sleep spindle-generating thalamo-cortical circuitry supports attention capacity in awake humans and animals, but using sleep spindles to predict differences in attention has not been tried in either. Of the more commonly examined cognitive correlates of spindle occurrence and amplitude, post-sleep recall, and general intelligence, only post-sleep recall had been studied in dogs, rats and mice. Here, we examined a sample of companion dogs (N = 58) for whom polysomnographic recordings and several cognitive tests were performed on two occasions each, with a three-month break in-between. Five of the tests were used to extract a factor analogous to human g (general mental ability). A sixth test in the battery measured sustained attention. Both attention and g-factor scores were linked to higher slow spindle occurrence and absolute sigma power detected in polysomnographic recordings over the central electrode. These effects persisted across measurement occasions. Higher intrinsic spindle frequency was, in turn, linked to lower g-factor scores but displayed no relationship with attention scores. The overlap in localization and direction for the effects of slow spindle density (spindles/minute) and sigma power supports that they tap into the same underlying cognition-relevant aspects of spindling. Given earlier large sample and meta-analysis validations of sigma power as a reliable predictor of cognitive performance in humans, we thus conclude that the currently handled method for quantifying spindle density in dogs indeed measures cognition-relevant spindle activity by virtue of its agreement with the sigma power alternative.
产生睡眠纺锤体的丘脑-皮层回路支持清醒的人类和动物的注意力能力,但利用睡眠纺锤体来预测注意力的差异在人类和动物中都没有尝试过。在对睡眠纺锤体发生和振幅、睡后回忆和一般智力的认知相关性进行的较常见研究中,只有睡后回忆在狗、大鼠和小鼠中进行过研究。在此,我们对伴侣犬(58 只)进行了抽样调查,对它们分别进行了两次多导睡眠图记录和几项认知测试,中间休息了三个月。其中五项测试用于提取与人类 g(一般智力)类似的因子。第六项测试用于测量持续注意力。在中央电极的多导睡眠图记录中检测到较高的慢纺锤体发生率和绝对西格玛功率,从而预测了注意力和 g 因子的得分。这些效应在不同的测量场合持续存在。较高的内在纺锤体频率反过来又与较低的 g 因子得分有关,但与注意力得分没有关系。慢速纺锤体密度(纺锤体/分钟)和σ功率效应在定位和方向上的重叠证明,它们挖掘了纺锤体与认知相关的相同方面。鉴于早先的大样本和荟萃分析验证了西格玛功率是人类认知能力的可靠预测指标,我们由此得出结论,目前在狗身上使用的纺锤体密度量化方法确实测量了与认知相关的纺锤体活动,因为它与西格玛功率替代方法一致。
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引用次数: 0
Decoding cortical chronotopy—Comparing the influence of different cortical organizational schemes 解码皮层时序--比较不同皮层组织方案的影响
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-11-02 DOI: 10.1016/j.neuroimage.2024.120914
Falko Mecklenbrauck , Jorge Sepulcre , Jana Fehring , Ricarda I. Schubotz
The brain's diverse intrinsic timescales enable us to perceive stimuli with varying temporal persistency. This study aimed to uncover the cortical organizational schemes underlying these variations, revealing the neural architecture for processing a wide range of sensory experiences. We collected resting-state fMRI, task-fMRI, and diffusion-weighted imaging data from 47 individuals. Based on this data, we extracted six organizational schemes: (1) the structural Rich Club (RC) architecture, shown to synchronize the connectome; (2) the structural Diverse Club architecture, as an alternative to the RC based on the network's module structure; (3) the functional uni-to-multimodal gradient, reflected in a wide range of structural and functional features; and (4) the spatial posterior/lateral-to-anterior/medial gradient, established for hierarchical levels of cognitive control. Also, we explored the effects of (5) structural graph theoretical measures of centrality and (6) cytoarchitectural differences. Using Bayesian model comparison, we contrasted the impact of these organizational schemes on (1) intrinsic resting-state timescales and (2) inter-subject correlation (ISC) from a task involving hierarchically nested digit sequences. As expected, resting-state timescales were slower in structural network hubs, hierarchically higher areas defined by the functional and spatial gradients, and thicker cortical regions. ISC analysis demonstrated hints for the engagement of higher cortical areas with more temporally persistent stimuli. Finally, the model comparison identified the uni-to-multimodal gradient as the best organizational scheme for explaining the chronotopy in both task and rest. Future research should explore the microarchitectural features that shape this gradient, elucidating how our brain adapts and evolves across different modes of processing.
大脑的内在时间尺度多种多样,这使我们能够感知具有不同时间持续性的刺激。本研究旨在揭示这些变化背后的大脑皮层组织方案,揭示处理各种感官体验的神经架构。我们收集了 47 人的静息态 fMRI、任务-fMRI 和扩散加权成像数据。基于这些数据,我们提取了六种组织方案:(1)结构性富俱乐部(RC)架构,该架构显示了连接组的同步性;(2)结构性多样化俱乐部架构,该架构是基于网络模块结构的 RC 架构的替代方案;(3)功能性单模态到多模态梯度,该梯度反映在广泛的结构和功能特征中;以及(4)空间性后部/外侧到前部/内侧梯度,该梯度建立在认知控制的分层水平上。此外,我们还探讨了(5)中心性结构图理论测量和(6)细胞结构差异的影响。利用贝叶斯模型比较法,我们对比了这些组织方案对(1)内在静息态时间尺度和(2)涉及分层嵌套数字序列任务的受试者间相关性(ISC)的影响。正如预期的那样,在结构网络中心、由功能和空间梯度定义的分层较高区域以及较厚的皮层区域,静息状态时标较慢。ISC 分析表明,更高的皮层区域会受到时间上更持久的刺激。最后,通过模型比较发现,单模态到多模态梯度是解释任务和休息时序的最佳组织方案。未来的研究应该探索形成这种梯度的微观结构特征,阐明我们的大脑是如何在不同的处理模式中适应和进化的。
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引用次数: 0
Neurophysiological dynamics of metacontrol states: EEG insights into conflict regulation 元控制状态的神经生理学动态:脑电图对冲突调节的启示
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-11-02 DOI: 10.1016/j.neuroimage.2024.120915
Xi Wang , Nasibeh Talebi , Xianzhen Zhou , Bernhard Hommel , Christian Beste
Understanding the neural mechanisms underlying metacontrol and conflict regulation is crucial for insights into cognitive flexibility and persistence. This study employed electroencephalography (EEG), EEG-beamforming and directed connectivity analyses to explore how varying metacontrol states influence conflict regulation at a neurophysiological level. Metacontrol states were manipulated by altering the frequency of congruent and incongruent trials across experimental blocks in a modified flanker task, and both behavioral and electrophysiological measures were analyzed. Behavioral data confirmed the experimental manipulation's efficacy, showing an increase in persistence bias and a reduction in flexibility bias during increased conflict regulation. Electrophysiologically, theta band activity paralleled the behavioral data, suggesting that theta oscillations reflect the mismatch between expected metacontrol bias and actual task demands. Alpha and beta band dynamics differed across experimental blocks, though these changes did not directly mirror behavioral effects. Post-response alpha and beta activity were more pronounced in persistence-biased states, indicating a neural reset mechanism preparing for future cognitive demands. By using a novel artificial neural networks method, directed connectivity analyses revealed enhanced inter-regional communication during persistence states, suggesting stronger top-down control and sensorimotor integration. Overall, theta band activity was closely tied to metacontrol processes, while alpha and beta bands played a role in resetting the neural system for upcoming tasks. These findings provide a deeper understanding of the neural substrates involved in metacontrol and conflict monitoring, emphasizing the distinct roles of different frequency bands in these cognitive processes.
了解元控制和冲突调节的神经机制对于深入了解认知的灵活性和持久性至关重要。本研究采用脑电图(EEG)、脑电波束成形和定向连接分析来探讨不同的元控制状态如何在神经生理水平上影响冲突调节。元控制状态是通过改变改良的侧翼任务中各实验块的一致和不一致试验频率来操纵的,并对行为和电生理测量进行了分析。行为数据证实了实验操作的有效性,显示在冲突调节增加时,持久性偏差增加,灵活性偏差减少。在电生理方面,θ波段活动与行为数据一致,表明θ振荡反映了预期的元控制偏差与实际任务需求之间的不匹配。α和β波段的动态变化在不同的实验区块有所不同,但这些变化并不直接反映行为效应。反应后的α和β活动在持续偏差状态下更为明显,这表明神经复位机制正在为未来的认知需求做准备。通过使用一种新的人工神经网络方法,定向连接分析表明在持续状态下区域间交流增强,这表明自上而下的控制和感觉运动整合更强。总体而言,θ波段活动与元控制过程密切相关,而α和β波段则在为即将到来的任务重置神经系统方面发挥作用。这些发现加深了对元控制和冲突监控所涉及的神经基底的理解,强调了不同频段在这些认知过程中的不同作用。
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引用次数: 0
MQGA: A quantitative analysis of brain network hubs using multi-graph theoretical indices MQGA:利用多图理论指数对大脑网络枢纽进行定量分析。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-11-01 DOI: 10.1016/j.neuroimage.2024.120913
Hongzhou Wu , Zhenzhen Yang , Qingquan Cao , Pan Wang , Bharat B. Biswal , Benjamin Klugah-Brown
Recent advancements in large-scale network studies have shown that connector hubs and provincial hubs are vital for coordinating complex cognitive tasks by facilitating information transfer between and within specialized modules. However, current methods for identifying these hubs often lack standardized measurement criteria, hindering quantitative analysis. This study proposes a novel computational method utilizing multi-graph theoretical index calculations to quantitatively analyze hub attributes in brain networks. Using benchmark network, random simulation network (N = 100), resting fMRI data from the ADHD-200 NYU dataset (HC = 110, ADHD = 146), and the Peking dataset (HC = 120, ADHD = 83), we introduce the Multi-criteria Quantitative Graph Analysis (MQGA) method, which employs betweenness centrality, degree centrality, and participation coefficient to determine the connector (con) hub index and provincial (pro) hub index. The method's accuracy, reliability, and stability were validated through correlation analysis of hub indices and labels, vulnerability tests, and consistency analysis across subjects. Results indicate that as network sparsity increases, the con hub index increases while the pro hub index decreases, with the optimal hub node index at 4 % sparsity. Vulnerability tests revealed that removing con nodes had a greater impact on network integrity than removing pro nodes. Both con and pro exhibited stability in consistency analyses, but con was more stable. The stability of hub scores in disease groups was significantly lower than in the healthy control group. High con values were found in the precuneus, postcentral gyrus, and precentral gyrus, whereas high pro values were identified in the precentral gyrus, postcentral gyrus, superior parietal lobule, precuneus, and superior temporal gyrus. This approach enhances the accuracy and sensitivity of hub node identification, facilitating precise comparisons and producing consistent, replicable results, advancing our understanding of brain network hub nodes, their roles in cognitive processes, and their implications for brain disease research.
大规模网络研究的最新进展表明,连接器枢纽和省枢纽通过促进专门模块之间和内部的信息传递,对于协调复杂的认知任务至关重要。然而,目前识别这些枢纽的方法往往缺乏标准化的测量标准,从而阻碍了定量分析。本研究提出了一种新颖的计算方法,利用多图论指数计算来定量分析大脑网络中的枢纽属性。利用基准网络、随机模拟网络(N = 100)、ADHD-200 纽约大学数据集(HC = 110,ADHD = 146)和北京数据集(HC = 120,ADHD = 83)的静息 fMRI 数据,我们介绍了多标准定量图分析(MQGA)方法,该方法利用间度中心性、度中心性和参与系数来确定连接器(con)枢纽指数和省(pro)枢纽指数。该方法的准确性、可靠性和稳定性通过集线器指数和标签的相关性分析、易损性测试和跨受试者的一致性分析得到了验证。结果表明,随着网络稀疏度的增加,省中心指数(con hub index)增加,而省中心指数(pro hub index)减少,在稀疏度为 4% 时达到最佳中心节点指数。脆弱性测试表明,移除 con 节点比移除 pro 节点对网络完整性的影响更大。在一致性分析中,Con 和 Pro 都表现出稳定性,但 Con 更稳定。疾病组的 hub 分数稳定性明显低于健康对照组。在楔前回、中央后回和中央前回发现了高 con 值,而在中央前回、中央后回、顶叶上小叶、楔前回和颞上回发现了高 pro 值。这种方法提高了中枢节点识别的准确性和灵敏度,有助于进行精确比较,并产生一致的、可复制的结果,从而推进我们对大脑网络中枢节点、它们在认知过程中的作用以及它们对大脑疾病研究的影响的理解。
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引用次数: 0
Feasibility of using toroidal transceivers for acquiring intraoperative MR images around deep brain stimulation electrodes 使用环形收发器获取围绕脑深部刺激电极的术中磁共振图像的可行性。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-31 DOI: 10.1016/j.neuroimage.2024.120912
Nur Izzati Huda Zulkarnain, Alireza Sadeghi-Tarakameh, Russell L. Lagore, Dee M. Koski, Gregory J. Metzger, Zuzan Cayci, Noam Harel, Yigitcan Eryaman

Introduction

Magnetic resonance imaging (MRI) provides excellent soft tissue contrast for visualizing of deep brain stimulation (DBS) targets, allowing validation of the electrode placement, and assessing complications such as microhemorrhage and edema. However, the presence of the electrodes can introduce challenges such as radiofrequency (RF) induced current artifacts and excessive heating of the electrode contacts. Additionally, extended procedure times are also considered a disadvantage when using MRI as an intraoperative imaging modality following DBS electrode placement.

Method

We propose a novel approach of using toroidal resonators to inductively couple the shaft of the electrode to the scanner's transmit-receive chain thereby utilizing it as a localized imaging antenna. The small extent of the field generated by the electrode antenna allows fast imaging with smaller field-of-views (FOVs) spanning only a few centimeters. Furthermore, we present a fast and accurate safety monitoring strategy that can be used to predict the temperature increase at the electrical contacts of the electrode.

Results and Discussion

Imaging with the toroidal transceiver yields a higher signal-to-noise ratio (SNR) efficiency in proximity to the electrodes. This approach reduced the RF induced current artifacts around the electrode which enhanced the visibility of the shaft and improved electrode localization. Moreover, the limited sensitivity around the electrode can be exploited to perform fast scans with small FOVs. The predicted heating around DBS contacts was in quantitative agreement with the experimental heating in swine studies with a normalized root-mean-square error (NRMSE) ≤ 0.09.
简介磁共振成像(MRI)为脑深部刺激(DBS)靶点的可视化提供了极佳的软组织对比度,可以验证电极的放置位置,并评估微出血和水肿等并发症。然而,电极的存在会带来一些挑战,如射频(RF)引起的电流伪影和电极触点的过度加热。此外,在使用磁共振成像作为 DBS 电极置入术中成像方式时,手术时间延长也被认为是一个不利因素:我们提出了一种新方法,即使用环形谐振器将电极轴与扫描仪的发射接收链感应耦合,从而将其用作局部成像天线。电极天线产生的磁场范围较小,可在仅几厘米的较小视场(FOV)内快速成像。此外,我们还提出了一种快速准确的安全监控策略,可用于预测电极电触点的温度升高:使用环形收发器成像可在靠近电极的地方获得更高的信噪比(SNR)效率。这种方法减少了电极周围的射频感应电流伪影,从而提高了轴的可见度,改善了电极定位。此外,还可以利用电极周围有限的灵敏度,以较小的视野进行快速扫描。在猪的研究中,DBS 触点周围的预测加热与实验加热在数量上是一致的,归一化均方根误差 (NRMSE) ≤ 0.09。
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引用次数: 0
Enhancing prediction of human traits and behaviors through ensemble learning of traditional and novel resting-state fMRI connectivity analyses 通过对传统和新型静息状态 fMRI 连接性分析的集合学习,加强对人类特质和行为的预测。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-31 DOI: 10.1016/j.neuroimage.2024.120911
Takaaki Yoshimoto , Kai Tokunaga , Junichi Chikazoe
Recent advances in cognitive neuroscience have focused on using resting-state functional connectivity (RSFC) data from fMRI scans to more accurately predict human traits and behaviors. Traditional approaches generally analyze RSFC by correlating averaged time-series data across regions of interest (ROIs) or networks, which may overlook important spatial signal patterns. To address this limitation, we introduced a novel linear regression technique that estimates RSFC by predicting spatial brain activity patterns in a target ROI from those in a seed ROI. We applied both traditional and our novel RSFC estimation methods to a large-scale dataset from the Human Connectome Project and the Brain Genomics Superstruct Project, analyzing resting-state fMRI data to predict sex, age, personality traits, and psychological task performance. To enhance prediction accuracy, we developed an ensemble learner that combines these qualitatively different methods using a weighted average approach. Our findings revealed that hierarchical clustering of RSFC patterns using our novel method displays distinct whole-brain grouping patterns compared to the traditional approach. Importantly, the ensemble model, integrating these diverse weak learners, outperformed the traditional RSFC method in predicting human traits and behaviors. Notably, the predictions from the traditional and novel methods showed relatively low similarity, indicating that our novel approach captures unique and previously undetected information about human traits and behaviors through fine-grained local spatial patterns of neural activation. These results highlight the potential of combining traditional and innovative RSFC analysis techniques to enrich our understanding of the neural basis of human traits and behaviors.
认知神经科学的最新进展主要集中在利用来自 fMRI 扫描的静息态功能连接(RSFC)数据来更准确地预测人类的特征和行为。传统的方法一般是通过对感兴趣区(ROI)或网络的平均时间序列数据进行相关性分析,这可能会忽略重要的空间信号模式。为了解决这一局限性,我们引入了一种新型线性回归技术,通过预测种子区域中的空间活动模式来估算目标区域的 RSFC。我们将传统的和新型的 RSFC 估算方法应用于人类连接组计划和脑基因组超级结构计划的大规模数据集,通过分析静息态 fMRI 数据来预测性别、年龄、个性特征和心理任务表现。为了提高预测准确性,我们开发了一种集合学习器,利用加权平均方法将这些定性不同的方法结合起来。我们的研究结果表明,与传统方法相比,使用我们的新方法对 RSFC 模式进行分层聚类可显示出独特的全脑分组模式。重要的是,整合了这些不同弱学习者的集合模型在预测人类特征和行为方面优于传统的 RSFC 方法。值得注意的是,传统方法和新方法的预测结果显示出相对较低的相似性,这表明我们的新方法通过神经激活的细粒度局部空间模式捕捉到了有关人类特征和行为的独特的、以前未被发现的信息。这些结果凸显了将传统和创新的 RSFC 分析技术相结合来丰富我们对人类特征和行为的神经基础的理解的潜力。
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引用次数: 0
Reconstruction of intra- and extra-neurite conductivity tensors via conductivity at Larmor frequency and DWI data patterns 通过拉莫尔频率电导率和 DWI 数据模式重建神经元内和神经元外电导率张量。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-30 DOI: 10.1016/j.neuroimage.2024.120900
Munbae Lee , Geon-Ho Jahng , Oh-In Kwon
The developed magnetic resonance electrical properties tomography (MREPT) techniques visualize the internal conductivity distribution at Larmor frequency by measuring the B1 transceive phase data. In biological tissues, electrical conductivity is influenced by ion concentrations and mobility. To visualize the anisotropic conductivity tensor of biological tissues, we use the Einstein–Smoluchowski equation, which links the diffusion coefficient to particle mobility. By assuming a correlation between ion mobility and water diffusivity, we aim to decompose the internal isotropic conductivity at Larmor frequency into anisotropic conductivity tensors within the intra- and extra-neurite compartments. The multi-compartment spherical mean technique (MC-SMT), utilizing both high and low b-value diffusion-weighted imaging (DWI) data, characterizes the diffusion of water molecules within and across the intra- and extra-neurite compartments by analyzing the microstructural intricacies and the foundational architectural arrangement of the brain’s tissues. By analyzing the relationships between the measured DWI data, the microscopic diffusion signal, and the fiber orientation distribution function, we predict the DWI data for the intra- and extra-neurite compartments using spherical harmonic decomposition. Using the predicted DWI data for the intra- and extra-neurite compartments, we develop a conductivity tensor imaging method that operates specifically within the separated compartments. Human brain experiments, involving four healthy volunteers and a brain tumor patient, were performed to assess and confirm the reliability of the proposed method.
所开发的磁共振电特性断层成像(MREPT)技术通过测量 B1 收发相位数据,可视化拉莫尔频率下的内部电导率分布。在生物组织中,电导率受离子浓度和迁移率的影响。为了可视化生物组织的各向异性电导张量,我们使用了爱因斯坦-斯莫卢霍夫斯基方程,该方程将扩散系数与粒子迁移率联系起来。通过假定离子迁移率与水扩散率之间的相关性,我们旨在将拉莫尔频率下的内部各向同性电导率分解为神经元内和神经元外区室的各向异性电导率张量。多室球面均值技术(MC-SMT)利用高和低 b 值扩散加权成像(DWI)数据,通过分析大脑组织的微观结构错综复杂性和基础结构排列,描述了水分子在神经元内和神经元外室内部和之间的扩散特征。通过分析测得的 DWI 数据、微观扩散信号和纤维取向分布函数之间的关系,我们利用球形谐波分解法预测了神经元内和神经元外区块的 DWI 数据。利用预测的神经元内和神经元外分区的 DWI 数据,我们开发了一种电导张量成像方法,该方法专门在分离的分区中运行。我们对四名健康志愿者和一名脑肿瘤患者进行了人脑实验,以评估和确认所提方法的可靠性。
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引用次数: 0
Quantifying neurovascular coupling through a concurrent assessment of arterial, capillary, and neuronal activation in humans: A multimodal EEG-fNIRS-TCD investigation 通过同时评估人体动脉、毛细血管和神经元的激活来量化神经血管耦合:多模式 EEG-fNIRS-TCD 研究。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-30 DOI: 10.1016/j.neuroimage.2024.120910
Joel S. Burma , Ibukunoluwa K. Oni , Andrew P. Lapointe , Selina Rattana , Kathryn J. Schneider , Chantel T. Debert , Jonathan D. Smirl , Jeff F. Dunn

Background

This study explored a novel multimodal neuroimaging approach to assess neurovascular coupling (NVC) in humans using electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and transcranial Doppler ultrasound (TCD).

Methods

Fifteen participants (nine females; age 19–32) completed concurrent EEG-fNIRS-TCD imaging during motor (finger tapping) and visual (“Where's Waldo?”) tasks, with synchronized monitoring of blood pressure, capnography, and heart rate. fNIRS assessed microvascular oxygenation within the frontal, motor, parietal, and occipital cortices, while the middle and posterior cerebral arteries (MCA/PCA) were insonated using TCD. A 16-channel EEG set-up was placed according to the 10–20 system. Wilcoxon signed-rank tests were used to compare physiological responses between the active and resting phases of the tasks, while cross-correlations with zero legs compared cerebral and systemic hemodynamic responses across both tasks.

Results

Time-frequency analysis demonstrated a reduction in alpha and low beta band power in electrodes C3/C4 during finger tapping (p < 0.045) and all electrodes during the Waldo task (all p < 0.001). During Waldo, cross-correlation analysis demonstrated the change in oxygenated hemoglobin and cerebral blood velocity had a moderate-to-strong negative correlation with systemic physiological influences, highlighting the measured change resulted from neuronal input. Deoxygenated hemoglobin displayed the greatest negative cross-correlation with the MCA/PCA within the motor cortices and visual during the motor and visual tasks, respectively (range:0.54, -0.82).

Conclusions

This investigation demonstrated the feasibility of the proposed EEG-fNIRS-TCD response to comprehensively assess the NVC response within human, specifically quantifying the real-time temporal synchrony between neuronal activation (EEG), microvascular oxygenation changes (fNIRS), and conduit artery velocity alterations (TCD).
研究背景这项研究探索了一种新颖的多模态神经成像方法,利用脑电图(EEG)、功能性近红外光谱(fNIRS)和经颅多普勒超声(TCD)来评估人类的神经血管耦合(NVC):15 名参与者(9 名女性;年龄 19-32 岁)在完成运动(手指敲击)和视觉("沃尔多在哪里?")任务时同时完成了脑电图-fNIRS-TCD 成像,并同步监测了血压、血氧饱和度和心率。fNIRS 评估了额叶、运动、顶叶和枕叶皮层内的微血管氧饱和度,同时使用 TCD 对大脑中动脉和后动脉(MCA/PCA)进行了电刺激。根据 10-20 系统设置了 16 通道脑电图。Wilcoxon 符号秩检验用于比较任务活跃期和静止期的生理反应,而零脚交叉相关检验则用于比较两项任务中的大脑和全身血液动力学反应:结果:时频分析表明,在手指敲击过程中,C3/C4电极上的α和低β波段功率降低(p结论:这项研究证明了 "α和低β波段功率 "疗法的可行性:这项研究证明了提议的脑电图-fNIRS-TCD 反应全面评估人体内 NVC 反应的可行性,特别是量化神经元激活(脑电图)、微血管氧合变化(fNIRS)和导管动脉速度变化(TCD)之间的实时时间同步性。
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引用次数: 0
Spherical-deconvolution informed filtering of tractograms changes laterality of structural connectome 以球形解卷积为基础的阶梯图过滤改变了结构连接组的侧向性。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-28 DOI: 10.1016/j.neuroimage.2024.120904
Yifei He , Yoonmi Hong , Ye Wu
Diffusion MRI-driven tractography, a non-invasive technique that reveals how the brain is connected, is widely used in brain lateralization studies. To improve the accuracy of tractography in showing the underlying anatomy of the brain, various tractography filtering methods were applied to reduce false positives. Based on different algorithms, tractography filtering methods are able to identify the fibers most consistent with the original diffusion data while removing fibers that do not align with the original signals, ensuring the tractograms are as biologically accurate as possible. However, the impact of tractography filtering on the lateralization of the brain connectome remains unclear. This study aims to investigate the relationship between fiber filtering and laterality changes in brain structural connectivity. Three typical tracking algorithms were used to construct the raw tractography, and two popular fiber filtering methods(SIFT and SIFT2) were employed to filter the tractography across a range of parameters. Laterality indices were computed for six popular biological features, including four microstructural measures (AD, FA, RD, and T1/T2 ratio) and two structural features (fiber length and connectivity) for each brain region. The results revealed that tractography filtering may cause significant laterality changes in more than 10% of connections, up to 25% for probabilistic tracking, and deterministic tracking exhibited minimal laterality changes compared to probabilistic tracking, experiencing only about 6%. Except for tracking algorithms, different fiber filtering methods, along with the various biological features themselves, displayed more variable patterns of laterality change. In conclusion, this study provides valuable insights into the intricate relationship between fiber filtering and laterality changes in brain structural connectivity. These findings can be used to develop improved tractography filtering methods, ultimately leading to more robust and reliable measurements of brain asymmetry in lateralization studies.
弥散核磁共振成像(MRI)驱动的牵引成像是一种非侵入性技术,可揭示大脑的连接方式,被广泛应用于大脑侧化研究。为了提高束成像在显示大脑潜在解剖结构方面的准确性,人们采用了各种束成像过滤方法来减少假阳性。基于不同的算法,束流成像滤波方法能够识别与原始扩散数据最一致的纤维,同时去除与原始信号不一致的纤维,确保束流图在生物学上尽可能准确。然而,束图过滤对大脑连接组侧向化的影响仍不清楚。本研究旨在探讨纤维过滤与大脑结构连接侧向性变化之间的关系。研究使用了三种典型的追踪算法来构建原始牵引图,并采用了两种流行的纤维过滤方法(SIFT和SIFT2)来过滤一系列参数范围内的牵引图。计算了六种流行生物特征的侧向性指数,包括每个脑区的四种微结构测量(AD、FA、RD和T1/T2比值)和两种结构特征(纤维长度和连接性)。结果表明,牵引滤波可能会导致10%以上的连接发生明显的侧向变化,概率追踪可达25%,而确定性追踪与概率追踪相比,侧向变化极小,仅为6%左右。除跟踪算法外,不同的纤维过滤方法以及各种生物特征本身都显示出更多不同的侧向变化模式。总之,这项研究为了解纤维过滤与大脑结构连接侧向变化之间的复杂关系提供了宝贵的见解。这些发现可用于开发改进的束成像过滤方法,最终在侧向化研究中对大脑不对称性进行更稳健可靠的测量。
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引用次数: 0
Atypical prefrontal neural activity during an emotional interference control task in adolescents with autism spectrum disorder: A functional near-infrared spectroscopy study 自闭症谱系障碍青少年在情绪干扰控制任务中的非典型前额叶神经活动:功能性近红外光谱研究。
IF 4.7 2区 医学 Q1 NEUROIMAGING Pub Date : 2024-10-28 DOI: 10.1016/j.neuroimage.2024.120907
Tingting Chen , Jiarui Jiang , Mingchao Xu , Yuanfu Dai , Xiaoyan Gao , Changhao Jiang
Autism spectrum disorder (ASD) is typically characterized by impairments in social interaction and communication, which may be associated with a failure to naturally orient to social stimuli, particularly in recognizing and responding to facial emotions. As most previous studies have used nonsocial stimuli to investigate inhibitory control in children and adults with ASD, little is known about the behavioral and neural activation patterns of emotional inhibitory control in adolescent with ASD. Functional neuroimaging studies have underscored the key role of the prefrontal cortex (PFC) in inhibitory control and emotional face processing. Thus, this study aimed to examine whether adolescent with ASD exhibited altered PFC processing during an emotional Flanker task by using non-invasive functional near-infrared spectroscopy (fNIRS). Twenty-one adolescents with high-functioning ASD and 26 typically developing (TD) adolescents aged 13–16 years were recruited. All participants underwent an emotional Flanker task, which required to decide whether the centrally positioned facial emotion is consistent with the laterally positioned facial emotion. TD adolescents exhibited larger RT and mean O2Hb level in the incongruent condition than the congruent condition, evoking cortical activations primarily in right PFC regions in response to the emotional Flanker effect. In contrast, ASD adolescents failed to exhibit the processing advantage for congruent versus incongruent emotional face in terms of RT, but showed cortical activations primarily in left PFC regions in response to the emotional Flanker effect. These findings suggest that adolescents with ASD rely on different neural strategies to mobilize PFC neural resources to address the difficulties they experience when inhibiting the emotional face.
自闭症谱系障碍(ASD)的典型特征是社会交往和沟通障碍,这可能与无法自然地适应社会刺激有关,尤其是在识别和应对面部情绪方面。由于以往的研究大多使用非社交刺激来研究 ASD 儿童和成人的抑制控制能力,因此人们对 ASD 青少年情绪抑制控制的行为和神经激活模式知之甚少。功能神经影像学研究强调了前额叶皮层(PFC)在抑制控制和情绪面孔处理中的关键作用。因此,本研究旨在通过非侵入性功能性近红外光谱(fNIRS)检查患有自闭症的青少年在完成情绪侧翼任务时是否表现出前额叶皮层处理的改变。研究人员招募了21名患有高功能自闭症的青少年和26名发育典型(TD)青少年,年龄在13-16岁之间。所有参与者都接受了情绪侧翼任务,该任务要求他们判断中心位置的面部情绪是否与侧面位置的面部情绪一致。TD青少年在不一致条件下的RT和平均O2Hb水平均高于一致条件下,主要是右侧PFC区域的皮质激活对情绪Flanker效应做出了反应。与此相反,ASD 青少年在处理一致与不一致的情绪面孔时,在反应时间上没有表现出优势,但在对情绪侧翼效应做出反应时,主要在左侧前脑皮层区域表现出皮层激活。这些研究结果表明,患有ASD的青少年在抑制情绪面孔时,会依靠不同的神经策略来调动PFC神经资源,以解决他们遇到的困难。
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