The neural architecture of pragmatic processing
The neural architecture of pragmatic processing
批准号:
10406543
负责人:
Evelina Fedorenko
金额:
$23.26万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-05-21 至 2023-04-30
关键词:
AnatomyAnimal ModelArchitectureAreaAtlasesAwardBehaviorBrainBrain imagingBrain regionBroca&aposs areaCerebellumCognitionCommunicationComputer softwareDataDevelopmentFunctional Magnetic Resonance ImagingFutureHumanIndividualInferior frontal gyrusInvestigationLanguageLeadLesionLinguisticsLinkLiteratureLocationMapsMental ProcessesMeta-AnalysisMindModelingNetwork-basedNeurosciencesOnline SystemsOutputParentsParticipantPatientsPerceptionPopulationProbabilityResearchResearch PersonnelResortScanningScienceShort-Term MemorySignal TransductionStructure of superior temporal sulcusSurfaceassociation cortexbasebrain surgerycognitive abilitycognitive controlcognitive neurosciencecognitive processexecutive functionface perceptionimaging studyimprovedinter-individual variationinterestlanguage comprehensionlanguage processingparent grantrelating to nervous systemresponsesocialtheoriestool
中文摘要
项目总结
英文摘要
PROJECT SUMMARY
Functional magnetic resonance imaging (fMRI) has been invaluable for illuminating the brain’s functional
architecture. It has been especially important for cognitive abilities where animal models have limited utility, like
language. However, the field of human cognitive neuroscience has been struggling in that many findings are
not replicable, suffer from statistical flaws, or are difficult to compare across studies due to the use of divergent
analytic approaches. Many have now recognized the need for more robust, replicable, and meaningful science.
We here propose the development and dissemination of a powerful tool that can improve the field’s ability to
establish a robust and cumulative research enterprise. Leveraging the data collected in our lab over the last
ten years (>800 neurotypical participants across >1,200 scanning sessions), we propose to develop and
make publicly available probabilistic functional atlases for four brain networks critical for high-level
cognition: the language-selective network (which supports language processing; Fedorenko et al., 2010,
2011), the domain-general Multiple Demand (MD) network (which supports executive functions like cognitive
control; Duncan, 2010), the Default Mode network (DMN) (which supports internally-directed cognition and
construction of situation models; Buckner & DiNicola, 2019), and the Theory of Mind network (which supports
general social inference; Saxe & Kanwisher, 2003). These atlases will be created based on large numbers of
individual activation maps for well-established and extensively validated ‘localizer’ tasks targeting these
networks (700+ participants for the first three networks, and ~150 participants for the ToM network) and can be
used to estimate the probability that any given location in the common brain space belongs to a particular
functional network. In Aim 1, we will develop these probabilistic atlases. To do so, we will aggregate all the
relevant data for each of the localizer tasks, preprocess it through a uniform pipeline across two most
commonly used software packages (SPM, Friston, 1997; and FreeSurfer, Dale et al., 1999), and overlay the
individual activation maps in the relevant volume and surface spaces. We will additionally extract a set of key
individual-level neural markers, so that their distributions can be used normatively for comparisons with other
populations. In Aim 2, we will make the atlases (and constituent individual activation maps and neural markers)
publicly available. To do so, we will create a robust and interactive web-based platform for the dissemination of
the atlases. The proposed project is a critical step to bridge two fundamentally different and currently
disjoint analytic traditions in functional brain imaging—group-averaging approaches and functional
localization in individual brains—by providing common reference frames: probabilistic functional atlases based
on well-established and widely used localizers for four high-level brain networks. The ability to more
straightforwardly compare findings across diverse studies is bound to lead to more rigorous and transparent
science thus improving our understanding of human communication and related abilities.
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DOI:
10.1080/23273798.2018.1525494
发表时间:
2020
期刊:
Language, cognition and neuroscience
影响因子:
--
作者:
[Jacoby N, Fedorenko E]
通讯作者:
Fedorenko E
Agrammatic output in non-fluent, including Broca's, aphasia as a rational behavior.
不流利的语法输出,包括布罗卡失语症,是一种理性行为。
DOI:
10.1080/02687038.2022.2143233
发表时间:
2023
期刊:
Aphasiology
影响因子:
2
作者:
[Fedorenko,Evelina, Ryskin,Rachel, Gibson,Edward]
通讯作者:
Gibson,Edward
DOI:
10.1016/j.cortex.2020.06.013
发表时间:
2020-10
期刊:
Cortex; a journal devoted to the study of the nervous system and behavior
影响因子:
--
作者:
[Assem M, Blank IA, Mineroff Z, Ademoğlu A, Fedorenko E]
通讯作者:
Fedorenko E
Functionally distinct language and Theory of Mind networks are synchronized at rest and during language comprehension.
功能上不同的语言和心理理论网络在休息和语言理解过程中是同步的。
DOI:
10.1152/jn.00619.2018
发表时间:
2019
期刊:
Journal of neurophysiology
影响因子:
2.5
作者:
[Paunov,AlexanderM, Blank,IdanA, Fedorenko,Evelina]
通讯作者:
Fedorenko,Evelina
Do domain-general executive resources play a role in linguistic prediction? Re-evaluation of the evidence and a path forward.
领域通用执行资源在语言预测中发挥作用吗?
DOI:
10.1016/j.neuropsychologia.2019.107258
发表时间:
2020
期刊:
Neuropsychologia
影响因子:
2.6
作者:
[Ryskin,Rachel, Levy,RogerP, Fedorenko,Evelina]
通讯作者:
Fedorenko,Evelina
共 20 条
Computational neuroscience of language processing in the human brain
-
批准号:10199330
-
项目类别:
-
资助金额:$66.26万
-
财政年份:2021
-
负责人:Evelina Fedorenko
-
依托单位:
Computational Neuroscience of Language Processing in the Human Brain
-
批准号:10584494
-
项目类别:
-
资助金额:$68.79万
-
财政年份:2021
-
负责人:Evelina Fedorenko
-
依托单位:
Computational neuroscience of language processing in the human brain
-
批准号:10380789
-
项目类别:
-
资助金额:$64.44万
-
财政年份:2021
-
负责人:Evelina Fedorenko
-
依托单位:
Functional reorganization of the language and domain-general multiple demand systems in aphasia
-
批准号:10374793
-
项目类别:
-
资助金额:$62.42万
-
财政年份:2019
-
负责人:Evelina Fedorenko
-
依托单位:
Functional reorganization of the language and domain-general multiple demand systems in aphasia
-
批准号:9888346
-
项目类别:
-
资助金额:$62.42万
-
财政年份:2019
-
负责人:Evelina Fedorenko
-
依托单位:
Functional reorganization of the language and domain-general multiple demand systems in aphasia
-
批准号:10604322
-
项目类别:
-
资助金额:$62.42万
-
财政年份:2019
-
负责人:Evelina Fedorenko
-
依托单位:
The neural architecture of pragmatic processing
-
批准号:10395450
-
项目类别:
-
资助金额:$39.75万
-
财政年份:2018
-
负责人:Evelina Fedorenko
-
依托单位:
The neural architecture of pragmatic processing
-
批准号:9916718
-
项目类别:
-
资助金额:$43.69万
-
财政年份:2018
-
负责人:Evelina Fedorenko
-
依托单位:
fMRI investigations of the functional architecture of the language system
-
批准号:9054139
-
项目类别:
-
资助金额:$24.6万
-
财政年份:2014
-
负责人:Evelina Fedorenko
-
依托单位:
fMRI investigations of the functional architecture of the language system
-
批准号:8754821
-
项目类别:
-
资助金额:$24.89万
-
财政年份:2014
-
负责人:Evelina Fedorenko
-
依托单位:
fMRI investigations of the functional architecture of the language system
-
批准号:7533677
-
项目类别:
-
资助金额:$7.93万
-
财政年份:2009
-
负责人:Evelina Fedorenko
-
依托单位:
海外基金