Andrew K McVea, A. DiFilippo, Max McLachlan, Matthew D. Zammit, B. Bendlin, Sterling C. Johnson, T. Betthauser, Bradley T. Christian
Abstract [F-18]MK6240 is a Positron Emission Tomography (PET) radioligand with favorable imaging characteristics for measuring tau aggregation in Alzheimer’s disease (AD). In this study, we investigated the impact of extra-cerebral off-target binding (ECB) in the meninges and sinus present in [F-18]MK6240 PET scans on quantifying tau burden in preclinical AD. Based on large cohort data from 433 [F-18]MK6240 scans acquired at the University of Wisconsin-Madison, simulations were conducted to examine the range of effects of ECB by varying the ECB profile and input radiotracer concentration curves on areas of early tau accumulation in AD. The range and patterning of ECB in the imaging cohort had high variability between participants; however, 35% revealed moderate to high meningeal signal that could influence quantification. Partial volume effects, which can lead to measured PET signal from neighboring regions influencing signal in adjacent areas of interest, were examined in the simulated images. The simulations demonstrate that signal from the sinus increases the neighboring entorhinal cortex region (ERC) signal and activity detected from the meninges can similarly influence the inferior cerebellar grey matter reference region. ECB effects from the sinus were the most prevalent in our cohort, and simulations with the average ECB profile had ERC uptake (SUV) 23% higher than simulations with no ECB. Spill-in effects from the sinus, which increases the medial and ventral temporal cortex standardized uptake value ratio (SUVR), and spill-in from the meninges into the cerebellar reference region, which leads to a reduction in global SUVR, act in opposite directions, complicating the interpretation of the derived SUVR of [F-18]MK6240 images. These simulation results quantify the effects of ECB in [F-18]MK6240 scans and introduce correction factors to minimize bias of the SUVR measure.
摘要 [F-18]MK6240是一种正电子发射断层扫描（PET）放射性配体，具有良好的成像特性，可用于测量阿尔茨海默病（AD）中的tau聚集。在本研究中，我们研究了[F-18]MK6240 PET 扫描中出现的脑膜和窦的脑外脱靶结合（ECB）对量化临床前 AD 中 tau 负担的影响。根据威斯康星大学麦迪逊分校获得的 433 次 [F-18]MK6240 扫描的大量队列数据，通过改变 ECB 曲线和输入放射性示踪剂浓度曲线来检查 ECB 对 AD 早期 tau 累积区域的影响范围。成像队列中ECB的范围和模式在参与者之间有很大的变异性；然而，35%的ECB显示出中等到较高的脑膜信号，这可能会影响量化。部分容积效应会导致相邻区域的 PET 信号影响相邻相关区域的信号，模拟图像对这种效应进行了研究。模拟结果表明，来自静脉窦的信号会增加邻近内侧皮质区域（ERC）的信号，而从脑膜检测到的活动同样会影响小脑下部灰质参考区域。在我们的队列中，窦的ECB效应最为普遍，具有平均ECB特征的模拟的ERC摄取量（SUV）比没有ECB的模拟高23%。窦的溢入效应会增加颞叶内侧和腹侧皮层的标准化摄取值比（SUVR），而脑膜溢入小脑参考区域则会导致总体 SUVR 降低，这两种效应的作用方向相反，从而使[F-18]MK6240 图像的 SUVR 解释变得复杂。这些模拟结果量化了[F-18]MK6240扫描中ECB的影响，并引入了校正因子以尽量减少SUVR测量的偏差。
{"title":"Evaluating the effect of extra-cerebral off-target binding in [F-18]MK6240 PET scans in early-stage Alzheimer’s disease","authors":"Andrew K McVea, A. DiFilippo, Max McLachlan, Matthew D. Zammit, B. Bendlin, Sterling C. Johnson, T. Betthauser, Bradley T. Christian","doi":"10.1162/imag_a_00135","DOIUrl":"https://doi.org/10.1162/imag_a_00135","url":null,"abstract":"Abstract [F-18]MK6240 is a Positron Emission Tomography (PET) radioligand with favorable imaging characteristics for measuring tau aggregation in Alzheimer’s disease (AD). In this study, we investigated the impact of extra-cerebral off-target binding (ECB) in the meninges and sinus present in [F-18]MK6240 PET scans on quantifying tau burden in preclinical AD. Based on large cohort data from 433 [F-18]MK6240 scans acquired at the University of Wisconsin-Madison, simulations were conducted to examine the range of effects of ECB by varying the ECB profile and input radiotracer concentration curves on areas of early tau accumulation in AD. The range and patterning of ECB in the imaging cohort had high variability between participants; however, 35% revealed moderate to high meningeal signal that could influence quantification. Partial volume effects, which can lead to measured PET signal from neighboring regions influencing signal in adjacent areas of interest, were examined in the simulated images. The simulations demonstrate that signal from the sinus increases the neighboring entorhinal cortex region (ERC) signal and activity detected from the meninges can similarly influence the inferior cerebellar grey matter reference region. ECB effects from the sinus were the most prevalent in our cohort, and simulations with the average ECB profile had ERC uptake (SUV) 23% higher than simulations with no ECB. Spill-in effects from the sinus, which increases the medial and ventral temporal cortex standardized uptake value ratio (SUVR), and spill-in from the meninges into the cerebellar reference region, which leads to a reduction in global SUVR, act in opposite directions, complicating the interpretation of the derived SUVR of [F-18]MK6240 images. These simulation results quantify the effects of ECB in [F-18]MK6240 scans and introduce correction factors to minimize bias of the SUVR measure.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"123 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140782888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maximillian K. Egan, Cyril Costines, Mark D’Esposito, Sepideh Sadaghiani
Abstract It is increasingly recognized that cognitive control requires integration across large-scale brain networks anchored in frontal and parietal cortices. While the functional role of individual networks has been studied extensively, their cross-network interactions in the service of cognitive control are poorly understood. Beyond in-the-moment regulation of goal-relevant information processing (e.g., of sensory information), cognitive control encompasses preparatory processes in anticipation of upcoming stimuli and actions. Such preparatory control is often endogenous, that is, it is based on internal representations without relying on external cues or events. Here, we assessed network interactions that support such endogenously driven preparatory control. We recorded fMRI (N = 25) during a perceptual decision task with highly variable intertrial intervals. In half of the blocks, trial onset was cued, while in the remaining blocks, participants maintained readiness without relying on cues. We studied endogenous preparatory control in the intertrial period preceding uncued (vs. cued) trials. Behavioral outcomes confirmed heavier cognitive control demands in the uncued condition. Endogenous preparatory control was associated with increased activity of the dorsal attention network (DAN). This contrasted with in-the-moment control over stimulus-response processing during the trial itself, which was supported foremost by the right-hemispheric fronto-parietal network (FPN). Cross-network interactions were strengthened exclusively during endogenous preparatory control; the default mode network (DMN) showed more positive connectivity with the DAN and to a lesser degree the cingulo-opercular network (CON). Our results demonstrate that cross-networks interactions are particularly important for endogenously driven preparatory control. They further suggest that the DMN may be implicated in internally harnessing resources for cognitive control. This notion extends the DMN’s known role in internally-oriented processing to the domain of cognitive control when preparation cannot be aided by external events.
摘要 人们越来越认识到，认知控制需要以额叶和顶叶皮层为基础的大规模大脑网络的整合。虽然人们对单个网络的功能作用进行了广泛研究，但对它们在认知控制过程中的跨网络互动却知之甚少。除了对目标相关信息处理（如感官信息）的即时调节外，认知控制还包括对即将到来的刺激和行动进行预测的准备过程。这种准备性控制通常是内源性的，也就是说，它基于内部表征，而不依赖于外部线索或事件。在这里，我们评估了支持这种内生驱动的准备控制的网络交互作用。我们在具有高度可变试验间隔的知觉决策任务中记录了 fMRI（N = 25）。在一半的区块中，试验开始时有提示，而在其余的区块中，参与者不依赖提示而保持准备状态。我们研究了无提示（与有提示）试验前的试验间歇期的内源性准备控制。行为结果证实，在无提示条件下，认知控制要求更高。内源性准备控制与背侧注意网络（DAN）活动的增加有关。这与在试验过程中对刺激-反应处理的即时控制形成了鲜明对比，后者主要得到了右半球前顶叶网络（FPN）的支持。只有在内源性准备控制过程中，交叉网络的相互作用才会得到加强；默认模式网络（DMN）显示出与 DAN 更多的正连接性，其次是与小脑丘网络（CON）的连接性。我们的研究结果表明，跨网络互动对于内源性驱动的准备控制尤为重要。它们进一步表明，DMN可能与内部利用资源进行认知控制有关。这一概念将DMN在内部导向处理中的已知作用扩展到了认知控制领域，即当准备工作无法得到外部事件的帮助时。
{"title":"Endogenous preparatory control is associated with increased interaction between default mode and dorsal attention networks","authors":"Maximillian K. Egan, Cyril Costines, Mark D’Esposito, Sepideh Sadaghiani","doi":"10.1162/imag_a_00124","DOIUrl":"https://doi.org/10.1162/imag_a_00124","url":null,"abstract":"Abstract It is increasingly recognized that cognitive control requires integration across large-scale brain networks anchored in frontal and parietal cortices. While the functional role of individual networks has been studied extensively, their cross-network interactions in the service of cognitive control are poorly understood. Beyond in-the-moment regulation of goal-relevant information processing (e.g., of sensory information), cognitive control encompasses preparatory processes in anticipation of upcoming stimuli and actions. Such preparatory control is often endogenous, that is, it is based on internal representations without relying on external cues or events. Here, we assessed network interactions that support such endogenously driven preparatory control. We recorded fMRI (N = 25) during a perceptual decision task with highly variable intertrial intervals. In half of the blocks, trial onset was cued, while in the remaining blocks, participants maintained readiness without relying on cues. We studied endogenous preparatory control in the intertrial period preceding uncued (vs. cued) trials. Behavioral outcomes confirmed heavier cognitive control demands in the uncued condition. Endogenous preparatory control was associated with increased activity of the dorsal attention network (DAN). This contrasted with in-the-moment control over stimulus-response processing during the trial itself, which was supported foremost by the right-hemispheric fronto-parietal network (FPN). Cross-network interactions were strengthened exclusively during endogenous preparatory control; the default mode network (DMN) showed more positive connectivity with the DAN and to a lesser degree the cingulo-opercular network (CON). Our results demonstrate that cross-networks interactions are particularly important for endogenously driven preparatory control. They further suggest that the DMN may be implicated in internally harnessing resources for cognitive control. This notion extends the DMN’s known role in internally-oriented processing to the domain of cognitive control when preparation cannot be aided by external events.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"47 21","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140765741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. F. Deschwanden, Alba López Piñeiro, Isabel Hotz, Brigitta Malagurski, S. Mérillat, Lutz Jäncke
Abstract Introduction: There is accumulating cross-sectional evidence of decreased within-network resting-state functional connectivity (RSFC) and increased between-network RSFC when comparing older to younger samples, but results from longitudinal studies with healthy aging samples are sparse and less consistent. Some of the variability might occur due to differences in network definition and the fact that most atlases were trained on young adult samples. Applying these atlases to older cohorts implies the generalizability of network definitions to older individuals. However, because age is linked to a less segregated network architecture, this assumption might not be valid. To account for this, the Atlas55+ (A55) was recently published. The A55 was trained on a sample of people over the age of 55, making the network solutions suitable for studies on the aging process. Here, we want to compare the A55 to the popular Yeo-Krienen atlas to investigate whether and to what extent differences in network definition influence longitudinal changes of RSFC. For this purpose, the following networks were investigated: the occipital network (ON, “visual network”), the pericentral network (PN, “somatomotor network”), the medial frontoparietal network (M-FPN, “default network”), the lateral frontoparietal network (L-FPN, “control network”), and the midcingulo-insular network (M-CIN, “salience network”). Methods: Analyses were performed using longitudinal data from cognitively healthy older adults (N = 228, mean age at baseline = 70.8 years) with five measurement points over 7 years. To define the five networks, we used different variants of the two atlases. The spatial overlap of the networks was quantified using the dice similarity coefficient (DSC). RSFC trajectories within networks were estimated with latent growth curve models. Models of varying complexity were calculated, ranging from a linear model without interindividual variability in intercept and slope to a quadratic model with variability in intercept and slope. In addition, regressions were calculated in the models to explain the potential variance in the latent factors by baseline age, sex, and education. Finally, the regional homogeneity and the silhouette coefficient were computed, and the spin test and Wilcoxon-Mann-Whitney test were used to evaluate how well the atlases fit the data. Results: Median DSC across all comparisons was 0.67 (range: 0.20–0.93). The spatial overlap was higher for primary processing networks in comparison to higher-order networks and for intra-atlas comparisons versus inter-atlas comparisons. Three networks (ON, PN, M-FPN) showed convergent shapes of trajectories (linear vs. quadratic), whereas the other two networks (L-FPN, M-CIN) showed differences in change over time depending on the atlas used. The 95% confidence intervals of the estimated time and age effects overlapped in most cases, so that differences were mainly evident regarding the p-value. The evaluation of
{"title":"Influence of atlas-choice on age and time effects in large-scale brain networks in the context of healthy aging","authors":"P. F. Deschwanden, Alba López Piñeiro, Isabel Hotz, Brigitta Malagurski, S. Mérillat, Lutz Jäncke","doi":"10.1162/imag_a_00127","DOIUrl":"https://doi.org/10.1162/imag_a_00127","url":null,"abstract":"Abstract Introduction: There is accumulating cross-sectional evidence of decreased within-network resting-state functional connectivity (RSFC) and increased between-network RSFC when comparing older to younger samples, but results from longitudinal studies with healthy aging samples are sparse and less consistent. Some of the variability might occur due to differences in network definition and the fact that most atlases were trained on young adult samples. Applying these atlases to older cohorts implies the generalizability of network definitions to older individuals. However, because age is linked to a less segregated network architecture, this assumption might not be valid. To account for this, the Atlas55+ (A55) was recently published. The A55 was trained on a sample of people over the age of 55, making the network solutions suitable for studies on the aging process. Here, we want to compare the A55 to the popular Yeo-Krienen atlas to investigate whether and to what extent differences in network definition influence longitudinal changes of RSFC. For this purpose, the following networks were investigated: the occipital network (ON, “visual network”), the pericentral network (PN, “somatomotor network”), the medial frontoparietal network (M-FPN, “default network”), the lateral frontoparietal network (L-FPN, “control network”), and the midcingulo-insular network (M-CIN, “salience network”). Methods: Analyses were performed using longitudinal data from cognitively healthy older adults (N = 228, mean age at baseline = 70.8 years) with five measurement points over 7 years. To define the five networks, we used different variants of the two atlases. The spatial overlap of the networks was quantified using the dice similarity coefficient (DSC). RSFC trajectories within networks were estimated with latent growth curve models. Models of varying complexity were calculated, ranging from a linear model without interindividual variability in intercept and slope to a quadratic model with variability in intercept and slope. In addition, regressions were calculated in the models to explain the potential variance in the latent factors by baseline age, sex, and education. Finally, the regional homogeneity and the silhouette coefficient were computed, and the spin test and Wilcoxon-Mann-Whitney test were used to evaluate how well the atlases fit the data. Results: Median DSC across all comparisons was 0.67 (range: 0.20–0.93). The spatial overlap was higher for primary processing networks in comparison to higher-order networks and for intra-atlas comparisons versus inter-atlas comparisons. Three networks (ON, PN, M-FPN) showed convergent shapes of trajectories (linear vs. quadratic), whereas the other two networks (L-FPN, M-CIN) showed differences in change over time depending on the atlas used. The 95% confidence intervals of the estimated time and age effects overlapped in most cases, so that differences were mainly evident regarding the p-value. The evaluation of","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"41 1","pages":"1-24"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140771702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Cloos, E. Selingue, Shota Hodono, Romain Gaudin, Luisa Ciobanu
Abstract Recently, a new method was introduced to detect neuronal activity using Magnetic Resonance Imaging (MRI). The method, referred to as DIANA, showed MRI signals with millisecond temporal resolution that correlated with local field potentials measured invasively in mice. Troublingly, attempts by other groups to detect the DIANA signals in humans at 7 Tesla and mice at 15.2 Tesla have failed. So far, attempts to reproduce DIANA in small rodents have focused on paradigms using whisker pad stimulation, which were expected to produce a 0.1–0.15% signal change. However, the Supplementary Material accompanying the original DIANA paper showed that visual stimulation produced a three times larger signal, which should be much easier to detect. Therefore, we attempted to find the DIANA signal in rats using a visual stimulation paradigm. Experiments were performed at 17.2 Tesla but also at 7.0 Tesla to see if the DIANA signal appears at a lower field strength where T2 is longer and BOLD contributions are reduced. In addition, simulations were performed to investigate the theoretical detectability of synthetic DIANA signals in noisy data. Although our data indicated that a 0.1% signal change would have been detectable, we did not observe a DIANA signal. We did observe neuronally driven hemodynamic signal variations that were much larger than the anticipated DIANA signal. The amplitude of these signal changes was relatively similar at 7.0 and 17.2 Tesla (0.7% vs 1.1%). Numerical simulations indicated, however, that the measured hemodynamic signal changes would not interfere with the detection of DIANA signals. Therefore, it is reasonable to expect that measurements at higher field strength with improved SNR would have a better chance to detect the DIANA signal. Yet, we, among others, were unable to find it.
{"title":"No observation of DIANA signals in rats at 7.0 and 17.2 Tesla","authors":"M. Cloos, E. Selingue, Shota Hodono, Romain Gaudin, Luisa Ciobanu","doi":"10.1162/imag_a_00136","DOIUrl":"https://doi.org/10.1162/imag_a_00136","url":null,"abstract":"Abstract Recently, a new method was introduced to detect neuronal activity using Magnetic Resonance Imaging (MRI). The method, referred to as DIANA, showed MRI signals with millisecond temporal resolution that correlated with local field potentials measured invasively in mice. Troublingly, attempts by other groups to detect the DIANA signals in humans at 7 Tesla and mice at 15.2 Tesla have failed. So far, attempts to reproduce DIANA in small rodents have focused on paradigms using whisker pad stimulation, which were expected to produce a 0.1–0.15% signal change. However, the Supplementary Material accompanying the original DIANA paper showed that visual stimulation produced a three times larger signal, which should be much easier to detect. Therefore, we attempted to find the DIANA signal in rats using a visual stimulation paradigm. Experiments were performed at 17.2 Tesla but also at 7.0 Tesla to see if the DIANA signal appears at a lower field strength where T2 is longer and BOLD contributions are reduced. In addition, simulations were performed to investigate the theoretical detectability of synthetic DIANA signals in noisy data. Although our data indicated that a 0.1% signal change would have been detectable, we did not observe a DIANA signal. We did observe neuronally driven hemodynamic signal variations that were much larger than the anticipated DIANA signal. The amplitude of these signal changes was relatively similar at 7.0 and 17.2 Tesla (0.7% vs 1.1%). Numerical simulations indicated, however, that the measured hemodynamic signal changes would not interfere with the detection of DIANA signals. Therefore, it is reasonable to expect that measurements at higher field strength with improved SNR would have a better chance to detect the DIANA signal. Yet, we, among others, were unable to find it.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"221 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140789059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Amunts, M. Axer, L. Bitsch, J. Bjaalie, A. Brovelli, S. Caspers, I. Costantini, E. D’Angelo, G. Bonis, J. DeFelipe, A. Destexhe, Timo Dickscheid, M. Diesmann, S. Eickhoff, Andreas K. Engel, J. Fousek, S. Furber, R. Goebel, Onur Günterkün, J. Kotaleski, C. Hilgetag, S. Hölter, Y. Ioannidis, V. Jirsa, W. Klijn, J. Kämpfer, T. Lippert, A. Meyer-Lindenberg, M. Migliore, Yannick Morel, F. Morin, Lena Oden, F. Panagiotaropoulos, P. Paolucci, C. Pennartz, S. Petkoski, Mihai A. Petrovici, P. Ritter, S. Rotter, Andreas Rowald, S. Ruland, Philippe Ryvlin, Arleen Salles, M. Sanchez-Vives, J. Schemmel, B. Thirion
Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.
{"title":"The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing","authors":"K. Amunts, M. Axer, L. Bitsch, J. Bjaalie, A. Brovelli, S. Caspers, I. Costantini, E. D’Angelo, G. Bonis, J. DeFelipe, A. Destexhe, Timo Dickscheid, M. Diesmann, S. Eickhoff, Andreas K. Engel, J. Fousek, S. Furber, R. Goebel, Onur Günterkün, J. Kotaleski, C. Hilgetag, S. Hölter, Y. Ioannidis, V. Jirsa, W. Klijn, J. Kämpfer, T. Lippert, A. Meyer-Lindenberg, M. Migliore, Yannick Morel, F. Morin, Lena Oden, F. Panagiotaropoulos, P. Paolucci, C. Pennartz, S. Petkoski, Mihai A. Petrovici, P. Ritter, S. Rotter, Andreas Rowald, S. Ruland, Philippe Ryvlin, Arleen Salles, M. Sanchez-Vives, J. Schemmel, B. Thirion","doi":"10.1162/imag_a_00137","DOIUrl":"https://doi.org/10.1162/imag_a_00137","url":null,"abstract":"Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"32 1","pages":"1-35"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140785473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joseph A. Behnke, V. Ahluwalia, Jeremy L. Smith, Benjamin B. Risk, Jianna Lin, Russell K. Gore, Jason W. Allen
Abstract Vestibular symptoms, such as dizziness and balance impairment, are frequently reported following mild traumatic brain injury (mTBI) and are associated with a protracted recovery, yet the underlying neuroanatomical substrates remain unclear. The present study utilized advanced diffusion MRI (dMRI) techniques including both conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to investigate microstructural white matter integrity in individuals with postconcussive vestibular dysfunction (PCVD) within the subacute injury period (median of 35 days from injury; IQR of 23). Study participants included 23 individuals with subacute PCVD and 37 healthy control subjects who underwent imaging and comprehensive clinical vestibular testing. Between-group voxelwise analysis of differences in white matter revealed areas of higher intra-neurite volume fraction (VIn) and isotropic volume fraction (VIso) within PCVD subjects compared to controls, which involved overlapping regions within the left hemisphere of the brain. Affected areas of higher VIn and VIso included the superior longitudinal fasciculus (SLF) and superior and posterior corona radiata (SCR and PCR, respectively). We examined the relationship between clinical vestibular measures and diffusion metrics including DTI (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD] and axial diffusivity [AD]) and NODDI (intraneurite volume fraction [VIn], isotropic volume fraction [VIso], dispersion anisotropy [DA], orientation dispersion indexTotal/Primary/Secondary [ODIT/P/S]) within 32 regions-of-interest. Clinical vestibular measures included self-reported measures, including the Dizziness Handicap Inventory, Visual Vertigo Analog Scale, and Vestibular/Ocular-Motor Screening, as well as objective vestibular testing using the sensory organization test. Significant correlations were found with clinical measures across all diffusion maps (except DA), within various regions of interest (ROIs), including SLF, SCR, and PCR. These results implicate several important association bundles that may potentiate sensory processing dysfunction related to PCVD. Whether these neuroanatomical differences found within the subacute phase of PCVD are in response to injury or represent preexisting structural variations that increase vulnerability to sensory processing dysfunction is unclear and remains an active area of study.
{"title":"Assessment of white matter microstructure integrity in subacute postconcussive vestibular dysfunction using NODDI","authors":"Joseph A. Behnke, V. Ahluwalia, Jeremy L. Smith, Benjamin B. Risk, Jianna Lin, Russell K. Gore, Jason W. Allen","doi":"10.1162/imag_a_00147","DOIUrl":"https://doi.org/10.1162/imag_a_00147","url":null,"abstract":"Abstract Vestibular symptoms, such as dizziness and balance impairment, are frequently reported following mild traumatic brain injury (mTBI) and are associated with a protracted recovery, yet the underlying neuroanatomical substrates remain unclear. The present study utilized advanced diffusion MRI (dMRI) techniques including both conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to investigate microstructural white matter integrity in individuals with postconcussive vestibular dysfunction (PCVD) within the subacute injury period (median of 35 days from injury; IQR of 23). Study participants included 23 individuals with subacute PCVD and 37 healthy control subjects who underwent imaging and comprehensive clinical vestibular testing. Between-group voxelwise analysis of differences in white matter revealed areas of higher intra-neurite volume fraction (VIn) and isotropic volume fraction (VIso) within PCVD subjects compared to controls, which involved overlapping regions within the left hemisphere of the brain. Affected areas of higher VIn and VIso included the superior longitudinal fasciculus (SLF) and superior and posterior corona radiata (SCR and PCR, respectively). We examined the relationship between clinical vestibular measures and diffusion metrics including DTI (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD] and axial diffusivity [AD]) and NODDI (intraneurite volume fraction [VIn], isotropic volume fraction [VIso], dispersion anisotropy [DA], orientation dispersion indexTotal/Primary/Secondary [ODIT/P/S]) within 32 regions-of-interest. Clinical vestibular measures included self-reported measures, including the Dizziness Handicap Inventory, Visual Vertigo Analog Scale, and Vestibular/Ocular-Motor Screening, as well as objective vestibular testing using the sensory organization test. Significant correlations were found with clinical measures across all diffusion maps (except DA), within various regions of interest (ROIs), including SLF, SCR, and PCR. These results implicate several important association bundles that may potentiate sensory processing dysfunction related to PCVD. Whether these neuroanatomical differences found within the subacute phase of PCVD are in response to injury or represent preexisting structural variations that increase vulnerability to sensory processing dysfunction is unclear and remains an active area of study.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"109 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140786356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Dorso-medial prefrontal cortex (dmPFC) plays a vital role in social cognition and behavior among humans. Enhanced responses in dmPFC when viewing social scenes predict increased levels of sociability in adults. The current longitudinal study examined the association between dmPFC response and sociability in early development. Brain responses were measured in response to social smiles and frowns using functional near-infrared spectroscopy (fNIRS) at 11 months. Individual differences in sociability were measured using the Early Childhood Behavior Questionnaire (ECBQ) at 18 months. Our longitudinal results show that greater engagement of the dmPFC when processing social smiles, but not frowns, at 11 months predicts higher levels of sociability at 18 months. This demonstrates that early variability in dmPFC response during positive social interactions is linked to individual differences in overtly displayed social behavior. This supports the view that dmPFC plays an important role in social cognition and behavior from early in human ontogeny.
{"title":"Dorso-medial prefrontal cortex responses to social smiles predict sociability in early human development","authors":"Tobias Grossmann, Olivia Allison","doi":"10.1162/imag_a_00129","DOIUrl":"https://doi.org/10.1162/imag_a_00129","url":null,"abstract":"Abstract Dorso-medial prefrontal cortex (dmPFC) plays a vital role in social cognition and behavior among humans. Enhanced responses in dmPFC when viewing social scenes predict increased levels of sociability in adults. The current longitudinal study examined the association between dmPFC response and sociability in early development. Brain responses were measured in response to social smiles and frowns using functional near-infrared spectroscopy (fNIRS) at 11 months. Individual differences in sociability were measured using the Early Childhood Behavior Questionnaire (ECBQ) at 18 months. Our longitudinal results show that greater engagement of the dmPFC when processing social smiles, but not frowns, at 11 months predicts higher levels of sociability at 18 months. This demonstrates that early variability in dmPFC response during positive social interactions is linked to individual differences in overtly displayed social behavior. This supports the view that dmPFC plays an important role in social cognition and behavior from early in human ontogeny.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"209 2","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140780434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Taco Goedemans, Francisca Ferreira, Thomas Wirth, Lonneke van der Weerd, Flavia V. Massey, Marie T. Krüger, Vanessa Milanese, A. Pakzad, T. Foltynie, P. Limousin, M. Bot, P. Munckhof, Rick Schuurman, L. Zrinzo, H. Akram
Abstract Patient-specific targeting of the Ventral intermediate nucleus (Vim) of the thalamus can be achieved with MR connectivity. Nevertheless, there are several drawbacks to using tractography-based targeting methods to visualise distinct thalamic nuclei (e.g., subjective region of interest selection, and thresholding of resulting tracts and clusters). Fractional anisotropy (FA) mapping, another product of diffusion MRI (dMRI), does not rely on tractography, and could thus be clinically more viable for discerning thalamic anatomy for stereotactic surgery. The aim of this study is to develop and present a hybrid, high-resolution, and high-fidelity imaging modality that combines contrast from FA maps as well as anatomical T1 sequences (FAT1 imaging); and to evaluate FAT1 based Vim-target definition. Imaging and outcome data of 35 consecutive refractory tremor patients who had undergone 43 connectivity guided deep brain stimulation (DBS) and/or radiofrequency thermocoagulation (RF-T) between 2013 and 2021 were included. First, the pre-operatively acquired dMRI and MPRAGE sequences were used to create FAT1 maps in retrospect. Then, an FAT1 based Vim-target was planned by an experienced functional neurosurgeon who was blinded for patient outcome. Finally, to investigate FAT1 based targeting, a post-hoc analysis was carried out of the degree of overlap between the newly created FAT1 based Vim-target, and the volume of tissue activation (VTA, in case of DBS) or lesion volume (in case of RF-T). This degree of overlap was compared between favourable and unfavourable outcome groups: outcomes were measured by experts blinded for imaging data at the last follow-up using a Clinical Global Impression-Improvement score (CGI-I), where a CGI-I score of 1-2 (i.e., FTMTRS improvement of ≥50%) was considered favourable. In 36 of the 43 (84%) performed surgeries (24 DBS and 19 RF-T), FAT1 based Vim-targeting was possible. For the group showing favourable outcome (71% of the patients at a median follow-up of 13 months), the mean amount of overlap between the FAT1 based Vim-target and the VTA or lesion was 42% (±13), versus 17% (±15) for patients with an unfavourable outcome (MD 25%, 95% CI 14–35, p < 0.0001). Retrospective use of FAT1 based Vim-targeting as a tool to predict outcome had a sensitivity of 90%, specificity of 80%, positive predictive value of 90%, and negative predictive value of 80%. In conclusion, FAT1 imaging is a new, high-resolution, and high-fidelity modality that combines diffusion and anatomical MRI. It provides a fast and efficacious way of targeting the ventral intermediate nucleus of the thalamus. In this study, FAT1 based targeting was highly accurate in predicting outcomes after deep brain stimulation and radiofrequency thalamotomy.
{"title":"FAT1 weighted MRI: Diffusion meets anatomical imaging and application in thalamic surgery for tremor","authors":"Taco Goedemans, Francisca Ferreira, Thomas Wirth, Lonneke van der Weerd, Flavia V. Massey, Marie T. Krüger, Vanessa Milanese, A. Pakzad, T. Foltynie, P. Limousin, M. Bot, P. Munckhof, Rick Schuurman, L. Zrinzo, H. Akram","doi":"10.1162/imag_a_00139","DOIUrl":"https://doi.org/10.1162/imag_a_00139","url":null,"abstract":"Abstract Patient-specific targeting of the Ventral intermediate nucleus (Vim) of the thalamus can be achieved with MR connectivity. Nevertheless, there are several drawbacks to using tractography-based targeting methods to visualise distinct thalamic nuclei (e.g., subjective region of interest selection, and thresholding of resulting tracts and clusters). Fractional anisotropy (FA) mapping, another product of diffusion MRI (dMRI), does not rely on tractography, and could thus be clinically more viable for discerning thalamic anatomy for stereotactic surgery. The aim of this study is to develop and present a hybrid, high-resolution, and high-fidelity imaging modality that combines contrast from FA maps as well as anatomical T1 sequences (FAT1 imaging); and to evaluate FAT1 based Vim-target definition. Imaging and outcome data of 35 consecutive refractory tremor patients who had undergone 43 connectivity guided deep brain stimulation (DBS) and/or radiofrequency thermocoagulation (RF-T) between 2013 and 2021 were included. First, the pre-operatively acquired dMRI and MPRAGE sequences were used to create FAT1 maps in retrospect. Then, an FAT1 based Vim-target was planned by an experienced functional neurosurgeon who was blinded for patient outcome. Finally, to investigate FAT1 based targeting, a post-hoc analysis was carried out of the degree of overlap between the newly created FAT1 based Vim-target, and the volume of tissue activation (VTA, in case of DBS) or lesion volume (in case of RF-T). This degree of overlap was compared between favourable and unfavourable outcome groups: outcomes were measured by experts blinded for imaging data at the last follow-up using a Clinical Global Impression-Improvement score (CGI-I), where a CGI-I score of 1-2 (i.e., FTMTRS improvement of ≥50%) was considered favourable. In 36 of the 43 (84%) performed surgeries (24 DBS and 19 RF-T), FAT1 based Vim-targeting was possible. For the group showing favourable outcome (71% of the patients at a median follow-up of 13 months), the mean amount of overlap between the FAT1 based Vim-target and the VTA or lesion was 42% (±13), versus 17% (±15) for patients with an unfavourable outcome (MD 25%, 95% CI 14–35, p < 0.0001). Retrospective use of FAT1 based Vim-targeting as a tool to predict outcome had a sensitivity of 90%, specificity of 80%, positive predictive value of 90%, and negative predictive value of 80%. In conclusion, FAT1 imaging is a new, high-resolution, and high-fidelity modality that combines diffusion and anatomical MRI. It provides a fast and efficacious way of targeting the ventral intermediate nucleus of the thalamus. In this study, FAT1 based targeting was highly accurate in predicting outcomes after deep brain stimulation and radiofrequency thalamotomy.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"157 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140793603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Early life adversity is associated with differences in brain function and an elevated risk for poor mental health. Using data from children aged 10 (N = 5,798) from the Adolescent Brain Cognitive Development (ABCD) cohort, we investigated how adversity relates to functional brain organisation using a network neuroscience approach. We derived four data-driven categories of adversity by fitting a mixed graphical model: household/community instability, physical/sexual abuse, parental neglect, and financial difficulties. Analyses revealed that multiple forms of adversity were associated with reduced clustering and increased assortativity across the entire brain and that these local measures of organisation captured greater adversity-related variance than mesoscale measures like modularity. The most pronounced effects were in the somatosensory and subcortical networks. Financial difficulties showed the strongest and most widespread associations with brain organisation, with evidence of a mediating effect of assortativity on the association between financial difficulties and internalising symptoms. Adding race as a covariate attenuated most brain-adversity relationships, suggesting that experiences of adversity are strongly related to race/ethnicity in the ABCD sample. These results demonstrate that different forms of adversity are associated with both shared and unique variations in functional brain organisation, highlighting its potential significance for explaining individual differences in mental health outcomes following early life adversity.
{"title":"Dimensions of early life adversity and their associations with functional brain organisation","authors":"Maria Vedechkina, Duncan E. Astle, Joni Holmes","doi":"10.1162/imag_a_00145","DOIUrl":"https://doi.org/10.1162/imag_a_00145","url":null,"abstract":"Abstract Early life adversity is associated with differences in brain function and an elevated risk for poor mental health. Using data from children aged 10 (N = 5,798) from the Adolescent Brain Cognitive Development (ABCD) cohort, we investigated how adversity relates to functional brain organisation using a network neuroscience approach. We derived four data-driven categories of adversity by fitting a mixed graphical model: household/community instability, physical/sexual abuse, parental neglect, and financial difficulties. Analyses revealed that multiple forms of adversity were associated with reduced clustering and increased assortativity across the entire brain and that these local measures of organisation captured greater adversity-related variance than mesoscale measures like modularity. The most pronounced effects were in the somatosensory and subcortical networks. Financial difficulties showed the strongest and most widespread associations with brain organisation, with evidence of a mediating effect of assortativity on the association between financial difficulties and internalising symptoms. Adding race as a covariate attenuated most brain-adversity relationships, suggesting that experiences of adversity are strongly related to race/ethnicity in the ABCD sample. These results demonstrate that different forms of adversity are associated with both shared and unique variations in functional brain organisation, highlighting its potential significance for explaining individual differences in mental health outcomes following early life adversity.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"58 35","pages":"1-25"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140795685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Noble, Joshua Curtiss, Luiz Pessoa, Dustin Scheinost
Abstract Human neuroscience research remains largely preoccupied with mapping distinct brain areas to complex psychological processes and features of mental health disorders. While this reductionist and localizationist perspective has resulted in several substantive contributions to the field, it has long been viewed as only a piece of the puzzle. Emerging evidence now empirically demonstrates how a historical reliance on localizationist techniques may underlie recent challenges to reproducibility and translation in human neuroscience. To advance discovery, we must collectively better incorporate complex systems and machine-learning approaches that better capture the multidimensional, dynamic, and interacting nature of the brain. Moreover, we must begin to contend with how to best integrate complementary modalities beyond the brain to better understand complex mental processes.
{"title":"The tip of the iceberg: A call to embrace anti-localizationism in human neuroscience research","authors":"S. Noble, Joshua Curtiss, Luiz Pessoa, Dustin Scheinost","doi":"10.1162/imag_a_00138","DOIUrl":"https://doi.org/10.1162/imag_a_00138","url":null,"abstract":"Abstract Human neuroscience research remains largely preoccupied with mapping distinct brain areas to complex psychological processes and features of mental health disorders. While this reductionist and localizationist perspective has resulted in several substantive contributions to the field, it has long been viewed as only a piece of the puzzle. Emerging evidence now empirically demonstrates how a historical reliance on localizationist techniques may underlie recent challenges to reproducibility and translation in human neuroscience. To advance discovery, we must collectively better incorporate complex systems and machine-learning approaches that better capture the multidimensional, dynamic, and interacting nature of the brain. Moreover, we must begin to contend with how to best integrate complementary modalities beyond the brain to better understand complex mental processes.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"117 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140789857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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