Circuit Mechanisms Governing the Default Mode Network
管理默认模式网络的电路机制
基本信息
- 批准号:10380898
- 负责人:
- 金额:$ 73.29万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-01 至 2026-01-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAlzheimer&aposs DiseaseAnteriorAreaAttentionAttention deficit hyperactivity disorderAttenuatedAuditoryBehaviorBehavioralBrainBrain DiseasesBrain regionDataDisinhibitionEntropyEventExhibitsFiberFrequenciesFunctional Magnetic Resonance ImagingFunctional disorderGoalsHumanImageImaging TechniquesInsula of ReilInterneuronsInvestigationKnowledgeLightLinkMagnetic Resonance ImagingMeasurementMeasuresMedialMethodologyMusNeuronsOutputPhasePhotometryPrefrontal CortexPublic HealthRepetitive SequenceResearchRestRodentSchizophreniaSignal TransductionSpace ModelsStimulusStressStudy modelsSystemTimeTranslational ResearchTranslationsautism spectrum disorderawakecausal modelcell typecingulate cortexcognitive controldeviantexcitatory neuronhemodynamicsindexinginnovationinsightnervous system disordernetwork architectureneural circuitneuromechanismneuronal circuitryneurophysiologyneuropsychiatric disorderneuropsychiatrynew technologynoveloptogeneticspreventresponsetime use
项目摘要
PROJECT SUMMARY
Non-invasive functional magnetic resonance imaging (fMRI) has revolutionized our
understanding of macroscopic functional brain networks. However, inherent constraints of current fMRI
methodologies in humans limit our ability to probe the mechanisms underlying these networks. The
overarching goal of this project is to shed light on cellular and circuit mechanisms underlying the
functional organization of the default-mode network (DMN) – a large-scale brain network that is crucial
for a wide range of behaviors. While the new technologies in rodents allows us to experimentally reveal
causal control of DMN, rodent DMN topology has only been defined using resting-state fMRI, but not
functionally in terms of activation or suppression of brain activity in response to behaviorally relevant
salient stimuli. This represents a critical barrier preventing any straightforward translation between
rodent and human DMN research findings. To address this, we developed a novel silent zero-echo-
time (ZTE) fMRI technique, enabling awake rodent imaging and the use of an auditory oddball
paradigm, wherein deviant oddball stimuli presented amongst a sequence of repetitive control stimuli
can drive attention and suppress DMN. We also developed an MR-compatible, four-channel,
spectrally-resolved fiber-photometry system, allowing concurrent recording of ground-truth neuronal
activities during fMRI. To shed light on the circuit mechanisms governing the DMN, we proposed
two complementary research Aims building on our rigorous prior research. In Aim 1, we will determine
how attention to salient stimuli alters DMN activity and connectivity using the novel ZTE-photometry
platform. In Aim 2, we will introduce time-locked optogenetics on defined cell types to causally
manipulate the activity of anterior insula – the brain region assumed to be responsible for DMN dynamic
switching in numerous fMRI causal modeling studies. Functionally dissecting the rodent DMN
architecture is critical to the understanding of DMN transition mechanisms, which will enable us to
causally model, and make predictions about brain states, bringing insight into the network basis of
human behavior and neuropsychiatric/neurological disorders.
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项目总结
项目成果
期刊论文数量(0)
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VINOD MENON其他文献
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{{ truncateString('VINOD MENON', 18)}}的其他基金
Circuit Mechanisms Governing the Default Mode Network
管理默认模式网络的电路机制
- 批准号:
10576946 - 财政年份:2021
- 资助金额:
$ 73.29万 - 项目类别:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法
- 批准号:
10200653 - 财政年份:2019
- 资助金额:
$ 73.29万 - 项目类别:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法
- 批准号:
10631143 - 财政年份:2019
- 资助金额:
$ 73.29万 - 项目类别:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法
- 批准号:
10425350 - 财政年份:2019
- 资助金额:
$ 73.29万 - 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
- 批准号:
10468844 - 财政年份:2018
- 资助金额:
$ 73.29万 - 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
- 批准号:
9769805 - 财政年份:2018
- 资助金额:
$ 73.29万 - 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: Outcomes and Trajectories
数学障碍的纵向神经认知研究:结果和轨迹
- 批准号:
10842461 - 财政年份:2018
- 资助金额:
$ 73.29万 - 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
- 批准号:
10259850 - 财政年份:2018
- 资助金额:
$ 73.29万 - 项目类别:
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and disease
新颖的——贝叶斯——线性——动态——基于系统的——方法——用于发现——人类——大脑——电路——健康和疾病的动力学
- 批准号:
9170593 - 财政年份:2016
- 资助金额:
$ 73.29万 - 项目类别:
Computational modeling of dynamic causal brain circuits underlying cognitive dysfunction in Alzheimer's disease
阿尔茨海默病认知功能障碍的动态因果脑回路的计算模型
- 批准号:
10301331 - 财政年份:2014
- 资助金额:
$ 73.29万 - 项目类别: