Spatiotemporal Network Dynamics in a Rat Model of Schizophrenia
精神分裂症大鼠模型中的时空网络动力学
基本信息
- 批准号:8720463
- 负责人:
- 金额:$ 41.93万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-04-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAdolescenceAdultAffectAgonistAnatomyAnimal ModelAnimalsAreaAutistic DisorderBehaviorBrainChronicCognitionCognitiveCommunicationComputational TechniqueCouplingDataDeep Brain StimulationDevelopmentElementsEquilibriumFrequenciesGenetic MarkersGoalsGrowthHippocampus (Brain)HumanImageImpaired cognitionIndividualLeadLengthLongitudinal StudiesMeasuresMental disordersModelingNMDA receptor antagonistNeuronsPathologyPathway interactionsPatientsPatternPerformancePharmaceutical PreparationsPharmacologyPhenotypePhysiologyPlayPrefrontal CortexProcessPublic HealthRattusRelative (related person)ResearchResistanceRodent ModelRoleSchizophreniaSpatial DistributionStructureSymptomsTechniquesTemporal LobeTestingTimebehavior measurementcognitive functiondopamine D4 receptoremerging adultimprovedinnovationlongitudinal designneurodevelopmentnovelnovel strategiesprenatalpublic health relevanceresearch studyspatiotemporal
项目摘要
DESCRIPTION (provided by applicant): Oscillatory network dynamics provide an intermediate phenotype that, in some human imaging studies, has proven to be a more fruitful correlation target than behavioral measures for identifying genetic biomarkers of psychiatric disorders. Using rodent models, we propose to study oscillatory long-range synchronization and its alterations in schizophrenia, as well as disturbances in developmental trajectories of oscillatory networks from adolescence to adulthood. The primary focus is the impaired rhythmic coordination between activities in the hippocampus (HC) and prefrontal cortex (PFC) which is particularly important for specific cognitive functions in the adult and was also shown to play an important role in early neurodevelopment. Abnormal functional connectivity between HC and PFC has been demonstrated in schizophrenic patients and in chronic animal models of schizophrenia. Since pathological alterations of the key elements of neuronal oscillatory networks are present in both HC and PFC, impaired cortico-hippocampal synchronization can originate from the pathology of either or both structures. We propose to examine this issue using a novel approach that can precisely define the spatial distribution of rhythmic generators and quantify their interactions, including the essential directional influences. We will systematically investigate the spectral structure, the anatomy, physiology, and pharmacology of these interactions in normal rats and in pharmacological models of schizophrenia. We further hypothesize that impaired oscillations also adversely affect the maturation of cortical networks and their long-range connections. Understanding the ontogeny of temporal dynamics and their control is a severe gap area in the field, because oscillations are critical for normal cognition ad seem to be impaired not just in schizophrenia, but also in autism, and other mental illnesses. Thus we will also investigate the normal development of HC-PFC relationship through adolescence and early adulthood and its pathological alterations in a neurodevelopmental model of schizophrenia using daily electrophysiological recordings; such a longitudinal design has not been attempted in prior studies. Specific Aim 1 is to establish the pattern of PFC- HC interactions including directional information. We propose that long-range influences synchronizing neuronal activity and gamma oscillations between HC and PFC are active in both directions, with an overall HC dominance. We will investigate the anatomical substrate of these bidirectional interactions and their role in a cognitive task which requires dynamic PFC-HC coupling. Specific Aim 2 is to examine the impaired PFC-HC interactions in pharmacological models of schizophrenia using NMDA receptor antagonists and dopamine D4 receptor agonists which, besides schizophrenia-relevant symptoms, are known to significantly alter brain oscillations and to reduce performance on cognitive tasks requiring functional PFC and HC networks. Specific Aim 3 is to define how oscillation networks develop through the periadolescent period in normal rats and in a neurodevelopmental model of schizophrenia. We propose a longitudinal study to investigate how the adult pattern of oscillatory synchronization develops and when and how the developmental trajectories in the schizophrenia model diverge from normal.
描述(由申请人提供):振荡网络动力学提供了一种中间表型,在一些人类成像研究中,已证明其是比用于鉴定精神疾病的遗传生物标志物的行为测量更有成效的相关性目标。使用啮齿动物模型,我们建议研究振荡远程同步和精神分裂症的改变,以及从青春期到成年期的振荡网络的发展轨迹的干扰。主要焦点是海马(HC)和前额叶皮层(PFC)活动之间的节律协调受损,这对成年人的特定认知功能特别重要,也被证明在早期神经发育中发挥重要作用。HC和PFC之间的异常功能连接已在精神分裂症患者和慢性精神分裂症动物模型中得到证实。由于神经元振荡网络的关键要素的病理改变是目前在HC和PFC,受损的皮质-海马同步可以起源于病理的任一或两个结构。我们建议使用一种新的方法来研究这个问题,该方法可以精确地定义节奏发生器的空间分布并量化它们的相互作用,包括基本的方向影响。我们将系统地研究正常大鼠和精神分裂症药理学模型中这些相互作用的光谱结构、解剖学、生理学和药理学。我们进一步假设受损的振荡也会对皮层网络的成熟及其长距离连接产生不利影响。理解时间动力学的个体发生及其控制是该领域的一个严重空白领域,因为振荡对正常认知至关重要,而且似乎不仅在精神分裂症中受损,而且在自闭症和其他精神疾病中也是如此。因此,我们也将调查正常发展的HC-PFC的关系,通过青春期和成年早期和精神分裂症的神经发育模型,使用日常电生理记录的病理改变,这样的纵向设计还没有尝试在以前的研究。具体目标1是建立包含方向信息的PFC- HC相互作用模式。我们建议,长程影响同步HC和PFC之间的神经元活动和γ振荡是积极的在两个方向上,与整体HC的优势。我们将研究这些双向相互作用的解剖学基础及其在需要动态PFC-HC耦合的认知任务中的作用。具体目标2是检查受损的PFC-HC的相互作用,在精神分裂症的药理学模型中使用NMDA受体拮抗剂和多巴胺D4受体激动剂,除了精神分裂症相关的症状,已知显着改变脑振荡,并降低性能的认知任务需要功能PFC和HC网络。具体目标3是定义振荡网络如何通过正常大鼠和精神分裂症的神经发育模型中的青少年期发育。我们提出了一个纵向研究,探讨如何振荡同步的成人模式的发展,以及何时以及如何在精神分裂症模型的发展轨迹偏离正常。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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10459607 - 财政年份:2021
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Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging
对威胁的注意偏差的获得、消除和回忆:计算模型和多模态脑成像
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10629385 - 财政年份:2021
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$ 41.93万 - 项目类别:
Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging
对威胁的注意偏差的获得、消除和回忆:计算模型和多模态脑成像
- 批准号:
10296986 - 财政年份:2021
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$ 41.93万 - 项目类别:
Mechanisms of attentional control: Structure and dynamics from simultaneous EEG-fMRI and machine learning
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10368957 - 财政年份:2018
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Mechanisms of attentional control: Structure and dynamics from simultaneous EEG-fMRI and machine learning
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9883648 - 财政年份:2017
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Spatiotemporal Network Dynamics in a Rat Model of Schizophrenia
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