Mapping Brain Activity with High Spatiotemporal Resolution using Graphene Probes
使用石墨烯探针以高时空分辨率绘制大脑活动图
基本信息
- 批准号:10244939
- 负责人:
- 金额:$ 37.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-30 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:ActinsAddressAlzheimer&aposs DiseaseAmacrine CellsAreaAxonBehaviorBrainBrain MappingCalciumCarbonCategoriesCell membraneCell physiologyCellsCentral Nervous System DiseasesCoculture TechniquesCognitiveComplexCouplingDataDendritesDendritic SpinesDevicesDiseaseDown SyndromeEffectivenessElectrodesElectronsElectrophysiology (science)EnvironmentEpilepsyExcitatory SynapseExposure toFragile X SyndromeFrequenciesGasesGlaucomaGoalsImaging TechniquesIn SituIn VitroIndividualLightMaintenanceMapsMeasuresMechanicsMediatingMembraneMicroelectrodesMicrofluidicsMicroscopyMorphologyMotorMusMyosin ATPaseNatureNeuraxisNeurobiologyNeuronsNeurosciencesNeurotransmittersOpticsPathologicPhysiologicalPopulationPropertyProteinsResearchResolutionRetinaRetinal Ganglion CellsSamplingScanningSchemeSchizophreniaSideSignal TransductionSiliconSiteSliceStimulusStretchingStructureSurfaceSynapsesSystemTechnologyTimeTissuesTransistorsVertebral columnVisual evoked cortical potentialWild Type Mouseautism spectrum disorderbasebiomaterial compatibilitychemokinedesignfallsflexibilityfluorescence imaginggrapheneimplantationin vivomicromanipulatormillisecondmonolayernervous system disorderneurotechnologyoperationoptical imagingpatch clamppostsynapticresponsesensorspatiotemporalsynaptogenesistemporal measurementtwo-dimensionalvisual mapvoltagevoltage sensitive dye
项目摘要
Project Summary
The central nervous system (CNS), the most complex and dynamic network found in nature, is composed
of billions of neurons with trillions of dendritic spines and synapses, including pre- and postsynaptic terminals.
The postsynaptic side of synapses can take the form of dendritic spines, which are small, actin-rich protrusions
that serve as sites of postsynaptic contact and signal integration for most of the excitatory synapses in the CNS.
Synapses relay signals between neighboring neurons in large neuronal networks, underscoring their vital
function in the CNS. Not surprisingly, abnormalities in dendritic spines/synapses are associated with a number
of CNS disorders, including Fragile-X syndrome, Down’s syndrome, Alzheimer’s disease, autism, schizophrenia,
and epilepsy, glaucoma, and intellectual disorders. It is, therefore, crucial to understand the relationships
between the functional connectivity map of neuronal networks and the physiological or pathological functions of
individual synapses and neurons. To address this challenge, we propose to integrate two-dimensional flexible
graphene membranes with scanning photocurrent microscopy to probe electrical activities of individual synapses
and neurons in the retina and brain, two of the three components of the CNS. A unique advantage of graphene
is that its whole volume is exposed to the environment, which maximizes its sensitivity to local electrochemical
potential change. For example, graphene transistors are capable of detecting individual gas molecules, due to
its high surface-area-to-volume ratio and high electron mobility (100 to 1000 times higher than silicon). The high
electron mobility also enables graphene transistors to operate at very high frequencies (up to 500 GHz), leading
to high temporal resolution. Because of its strength and flexibility, graphene membranes can adhere to cell
membranes or tissue slices to achieve high electrical sensitivity. Furthermore, monolayer graphene transmits
more than 97% of incident light, making it ideal to be used as transparent electrical devices that are compatible
with optical imaging techniques. In addition, graphene transistors and electrodes have demonstrated the
capability of stable operation at stretching up to 9%. As such, we propose to create an unprecedented
neurotechnology through a rare combination of flexible graphene transistors and scanning photocurrent
microscopy to simultaneously study the electrical activities of a large population of synapses and neurons in
vitro, in situ, and in vivo. This technology will allow us to decipher the functional connectivity map of neuronal
networks with high spatiotemporal resolution and high throughput.
项目摘要
中枢神经系统(CNS)是自然界中发现的最复杂,最动态的网络
数十亿个神经元,具有数万亿个树突状刺和突触,包括突触前和突触后末端。
突触的突触后一侧可以采用小树突状的形式,这些刺是小的,富含肌动蛋白的突起的
对于中枢神经系统中的大多数兴奋突触,它充当突触后接触和信号积分的部位。
大型神经元网络中相邻神经元之间的突触中继信号,强调了它们的重要
CNS的功能。毫不奇怪,树突状刺/突触中的异常与数字有关
中枢神经系统疾病,包括脆弱X综合征,唐氏综合症,阿尔茨海默氏病,自闭症,精神分裂症,精神分裂症,
和癫痫,青光眼和肠道疾病。因此,了解关系至关重要
在神经元网络的功能连接图与物理或病理功能之间
个体突触和神经元。为了应对这一挑战,我们建议整合二维灵活性
用扫描光电流显微镜探测单个突触的电活动的石墨烯膜
和视网膜和大脑中的神经元,这是中枢神经系统的三个组成部分中的两个。石墨烯的独特优势
是它的整体体积暴露于环境,这最大化了其对局部电化学的敏感性
潜在的变化。例如,石墨烯晶体管能够检测到单个气体分子,因此
其高表面区域体积比和高电子迁移率(比硅高100至1000倍)。高
电子迁移率还使石墨烯晶体管以非常高的频率(最高500 GHz)运行,领先
高临时分辨率。由于其强度和柔韧性,石墨烯膜可以粘附在细胞上
膜或组织切片以达到高电敏感性。此外,单层石墨烯传输
超过97%的入射光,使其理想用作兼容的透明电动设备
使用光学成像技术。此外,石墨烯晶体管和电极已证明
稳定操作的能力高达9%。因此,我们建议创建一个前所未有的
神经技术通过柔性石墨烯晶体管和扫描光电流的罕见组合
显微镜可以轻松研究大量突触和神经元的电活动
体外,原位和体内。这项技术将使我们能够破译神经元的功能连接图
具有高时空分辨率和高吞吐量的网络。
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Dynamic Observation of Retinal Response to Pressure Elevation in a Microfluidic Chamber.
- DOI:10.1021/acs.analchem.1c05652
- 发表时间:2022-09-13
- 期刊:
- 影响因子:7.4
- 作者:Esteban-Linares, Alberto;Wareham, Lauren K.;Walmsley, Thayer S.;Holden, Joseph M.;Fitzgerald, Matthew L.;Pan, Zhiliang;Xu, Ya-Qiong;Li, Deyu
- 通讯作者:Li, Deyu
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Deyu Li其他文献
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{{ truncateString('Deyu Li', 18)}}的其他基金
Inhibitory Effect of Nitric Oxide on DNA Repair Enzymes
一氧化氮对DNA修复酶的抑制作用
- 批准号:
9232253 - 财政年份:2017
- 资助金额:
$ 37.99万 - 项目类别:
Exploring synaptic remodeling with graphene optoelectronic probes
用石墨烯光电探针探索突触重塑
- 批准号:
9234603 - 财政年份:2016
- 资助金额:
$ 37.99万 - 项目类别:
Exploring synaptic remodeling with graphene optoelectronic probes
用石墨烯光电探针探索突触重塑
- 批准号:
9025171 - 财政年份:2016
- 资助金额:
$ 37.99万 - 项目类别:
Imaging synapse formation using novel microfluidic platforms
使用新型微流体平台对突触形成进行成像
- 批准号:
8094187 - 财政年份:2011
- 资助金额:
$ 37.99万 - 项目类别:
Imaging synapse formation using novel microfluidic platforms
使用新型微流体平台对突触形成进行成像
- 批准号:
8306755 - 财政年份:2011
- 资助金额:
$ 37.99万 - 项目类别:
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