Development and validation of empirical models of the neuronal population activity underlying non-invasive human brain measurements
开发和验证非侵入性人脑测量中神经元群活动的经验模型
基本信息
- 批准号:9975889
- 负责人:
- 金额:$ 75.07万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-22 至 2023-06-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAnimal ExperimentationAnimal ModelAnimalsBackBehaviorBlood VesselsBrainBrain regionCaliberCharacteristicsCollectionCommunitiesComplexComputer ModelsDataDevelopmentDiseaseDisease modelElectrodesElectroencephalographyElectrophysiology (science)EventFosteringFunctional ImagingFunctional Magnetic Resonance ImagingGoalsHemodynamic PhenomenaHumanHuman ActivitiesImageImaging TechniquesIndividualLearningLinkMeasurementMeasuresMetabolicMethodsMicroscopicModalityModelingMotorMotor CortexNervous system structureNeuronsNeurosciencesOpticsPatientsPatternPerceptionPhasePhysiologyPopulationPositioning AttributePropertyResearchResolutionRodentScalp structureScientistSensorySeriesSignal TransductionSoftware ToolsSomatosensory CortexSpecialistStimulusSumSystemTactileTechnologyTestingTimeTissuesTranslatingValidationVisualVisual CortexWorkbasebrain cellcapillary bedcrosslinkdensityexperimental studyfallsfunctional magnetic resonance imaging/electroencephalographyhemodynamicshuman imagingimprovedinsightinstrumentintraoperative optical imagingmathematical modelmodel developmentmultimodal datamultimodalityneuroimagingneuronal circuitryneurotransmissionnon-invasive imagingoptical imagingreceptive fieldresponsesensory cortexsensory inputsensory stimulussensory systemsomatosensoryspatiotemporaltheoriestoolvolunteer
项目摘要
Project Summary / Abstract
A major obstacle in the study of human brain function is that we currently have limited understanding of
how the measurements made by different instruments, such as fMRI and EEG, relate to one another and to the
underlying neuronal circuitry. Significant efforts have led to development of models within various specialist
fields, but fragmentation has held us back from advancing our interpretation of the spatiotemporal
characteristics of non-invasive imaging signals. Bringing together the various models that pertain to signal
interpretation would constitute a significant advance in what we can learn from non-invasive neuroimaging. In
this project we take such an integrative approach to the study of cortical sensory systems. We intend to
develop a set of connecting, empirically driven models that will predict how sensory stimuli are encoded in
neuronal population activity underlying electrophysiological measures (AIM 1), and hemodynamic measures
(AIM 2), leading to a comprehensive integrative model (AIM 3). The pivotal integrative model (AIM 3) will
improve our understanding of, and revolutionize the information we can obtain from fMRI, the modality with the
highest potential for mapping detailed functions non-invasively in humans. To achieve this we will combine
hemodynamic and electrophysiological measurements at multiple spatial scales in humans, and in rodents at
very high resolutions. This will include non-invasive (fMRI at 3T and 7T, MEG and EEG) and invasive (optical
imaging, ECoG) modalities obtained from healthy humans. By obtaining multiple modality recordings from the
same individuals, using the same stimuli and tasks, we will be able to unequivocally link clear and specific
electrophysiological information to widely used fMRI technology, while significantly improving our
understanding of the electrical and hemodynamic phenomena underlying brain activity.
The research constitutes a multicenter endeavor to A) develop a comprehensive model to link external
inputs to neuronal population physiology to non-invasive imaging measures, B) obtain state of the art
multimodal recordings from the same individuals in order to bridge modalities and inform the models, C)
validate the models with data from multiple modalities (ECoG, fMRI, MEG/EEG, optical recordings) and brain
systems (visual, somatosensory and motor), and D) make algorithms and data available to the neuroscience
community to foster further development beyond the project's lifetime. Moreover, the research will foster
reconciliation of different theories about the relation between electrophysiology and fMRI and will lead to
`breakthroughs in understanding the dynamic activity of the human brain'. Such breakthroughs will be essential
in improving disease models of the nervous system, which rely on inferences about neuronal population
activity from non-invasive imaging of human brain activity.
项目总结/摘要
人类大脑功能研究的一个主要障碍是,我们目前对大脑功能的了解有限。
不同仪器(如fMRI和EEG)的测量结果如何相互关联,
潜在的神经回路重大的努力导致了各种专家模型的发展
但是碎片化阻碍了我们对时空的解释
非侵入性成像信号的特征。将与信号相关的各种模型汇集在一起
解释将使我们从非侵入性神经成像中了解到的信息取得重大进展。在
本计画我们采取整合的方法来研究皮质感觉系统。我们打算
开发一套连接,经验驱动的模型,将预测感官刺激是如何编码的,
神经元群体活动的基础电生理措施(AIM 1),和血液动力学措施
(AIM 2),导致一个全面的综合模型(AIM 3)。关键综合模型(AIM 3)将
提高我们的理解,并彻底改变我们可以从fMRI获得的信息,
最有可能在人类中非侵入性地绘制详细的功能。为了实现这一目标,我们将联合收割机
血液动力学和电生理学测量在多个空间尺度在人类,并在啮齿动物,
高分辨率。这将包括非侵入性(3 T和7 T的fMRI,MEG和EEG)和侵入性(光学
成像,ECoG)模式。通过获得多模态记录,
同样的人,使用同样的刺激和任务,我们将能够明确地联系起来,明确和具体的,
电生理信息与广泛使用的fMRI技术相结合,同时显着改善我们的
理解大脑活动背后的电和血液动力学现象。
该研究构成了一个多中心的奋进,A)开发一个综合模型,将外部
输入神经元群体生理学到非侵入性成像测量,B)获得最新技术水平
来自相同个体的多模态记录,以便桥接模态并告知模型,C)
使用来自多种模态(ECoG,fMRI,MEG/EEG,光学记录)和大脑的数据验证模型
系统(视觉,体感和运动),以及D)使算法和数据可用于神经科学
社区,以促进项目生命周期之外的进一步发展。此外,该研究将促进
关于电生理学和功能磁共振成像之间关系的不同理论的和解,将导致
“在理解人脑动态活动方面的突破”。这些突破将是必不可少的
在改善神经系统疾病模型方面,
非侵入性的人脑活动成像。
项目成果
期刊论文数量(26)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields.
- DOI:10.1371/journal.pcbi.1009955
- 发表时间:2022-04
- 期刊:
- 影响因子:4.3
- 作者:
- 通讯作者:
FMRI and intra-cranial electrocorticography recordings in the same human subjects reveals negative BOLD signal coupled with silenced neuronal activity.
- DOI:10.1007/s00429-021-02342-4
- 发表时间:2022-05
- 期刊:
- 影响因子:3.1
- 作者:Fracasso, Alessio;Gaglianese, Anna;Vansteensel, Mariska J.;Aarnoutse, Erik J.;Ramsey, Nick F.;Dumoulin, Serge O.;Petridou, Natalia
- 通讯作者:Petridou, Natalia
Laminar processing of numerosity supports a canonical cortical microcircuit in human parietal cortex.
数量的层流处理支持人类顶叶皮层中的典型皮层微电路。
- DOI:10.1016/j.cub.2021.07.082
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:vanDijk,JelleA;Fracasso,Alessio;Petridou,Natalia;Dumoulin,SergeO
- 通讯作者:Dumoulin,SergeO
A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex.
- DOI:10.1016/j.neuroimage.2021.118655
- 发表时间:2021-12-15
- 期刊:
- 影响因子:5.7
- 作者:Kupers ER;Benson NC;Winawer J
- 通讯作者:Winawer J
The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth.
- DOI:10.1177/0271678x221133972
- 发表时间:2023-03
- 期刊:
- 影响因子:6.3
- 作者:Schellekens, Wouter;Bhogal, Alex A.;Roefs, Emiel C. A.;Baez-Yanez, Mario G.;Siero, Jeroen C. W.;Petridou, Natalia
- 通讯作者:Petridou, Natalia
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Orrin Devinsky其他文献
Orrin Devinsky的其他文献
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{{ truncateString('Orrin Devinsky', 18)}}的其他基金
Machine learning approaches for improving EEG data utility in SUDEP research
用于提高 SUDEP 研究中脑电图数据效用的机器学习方法
- 批准号:
10593406 - 财政年份:2021
- 资助金额:
$ 75.07万 - 项目类别:
Advancing SUDEP risk prediction using a multicenter case-control approach
使用多中心病例对照方法推进 SUDEP 风险预测
- 批准号:
10290017 - 财政年份:2021
- 资助金额:
$ 75.07万 - 项目类别:
Advancing SUDEP risk prediction using a multicenter case-control approach
使用多中心病例对照方法推进 SUDEP 风险预测
- 批准号:
10463739 - 财政年份:2021
- 资助金额:
$ 75.07万 - 项目类别:
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