CRCNS: Integrated Empirical and Multiscale Modeling of Human Sleep Spindles

描述(申请人提供)：拟议研究的总体目标是确定人脑生物物理水平上的大脑事件如何影响颅骨外的宏观记录。具体的焦点是睡眠纺锤波，这是研究最好的睡眠节律，为此，我们将获得同步的脑电，脑磁图和深度电极记录。这些经验数据将被分析以确定大脑皮质内与纺锤波相关的电流的层流来源，这些结果将与计算模型的预测相匹配。我们将开发三种相关的网络模型，以涵盖广泛的空间尺度。工作假说是，第一，纺锤波是由多个松散耦合的皮质区域通过丘脑皮质传入有节奏地激活而产生的，从基质系统到皮层浅层，再到核心系统的中间层，第二，核心系统中受限的丘脑皮质区域的纺锤波通过基质系统传播。实验的特定目标和假设1)同时记录睡眠纺锤波的脑磁图和脑电。假设：脑磁图和脑电波将在传感器水平和其推断的来源记录非常不同的活动模式。较差的相关性将是明显的，因为在纺锤形放电中存在不恒定的相位和幅度关系，以及只有在纺锤形波发生时的松散相关性。2)睡眠纺锤体内脑电宏观电极记录，同时记录头皮脑电和脑磁图。假设：来自不同皮质产生器的记录只会彼此松散地耦合，或与头皮EEG相耦合，从而支持MEG提出的一般观点。3)睡眠纺锤期脑微电极阵列记录。假设：在浅层和中层之间，每一个纺锤波的神经元产生电流都不同。4)从人类联合皮质重建颗粒上和颗粒下锥体细胞，确定它们的层状分布，并估计核心和基质丘脑皮质投射的可能终止区。假设：人类的联想皮质和啮齿动物的感觉皮质在解剖学上会有显著的差异。建模特定的目标和假设1)基于结构MRI的皮质重建，构建准确、现实的EEG/MEG正演解。假设：颅外脑电/脑磁图的基本参数可以通过建立多个丘脑皮质区域的模型来复制，这些区域之间具有不同的同步性。脑电/脑磁图的拟合参数值将与从脑内大电极记录推断的值相匹配。2)利用主成分分析(PCA)对记录到的皮层电流源密度(CSD)进行分析。使用颗粒上和颗粒下锥体细胞的重建、它们的种群分布以及基质和核心传入的终止来模拟预期来自基质和核心丘脑皮质传入的CSD模式。假设：主成分分析确定的构成纺锤波的主要时空CSD成分将与CSD成分相对应，这些CSD成分模拟为激活基质和核心丘脑皮质传入的结果。3)构建基于Hodgkin-Huxley离子流的神经元模型，该模型包括皮质细胞、丘脑网状核细胞、丘脑基质细胞和核心丘脑中继细胞，以及它们在一个小柱中的相互联系。假设：预测的不同皮质层电流的时空模式将与使用建模目标2中描述的方法获得的时空模式相匹配。4)使用简化的神经模型将皮质微柱网络模型放大到可以产生EEG/MEG模式的空间精确的皮质模型。假设：模型中预测的EEG和MEG将与记录中观察到的匹配，涉及与建模目标1中导出的参数相对应的矩阵和核心丘脑皮质系统。5)开发与放大模型的属性匹配的统计模型，并使用统计物理的方法对其进行分析。假设：矩阵系统控制有效的大脑皮层连通性，核心系统控制局部相关长度。来自人类的协作研究记录将在MGH(Cash)进行，并在UCSD(Halgren和Sejnowski)进行分析和建模。这三个由PI、学生和博士后研究员组成的团队将在研究期间每天进行互动，并将至少每年正式会面一次，以评估进展并计划新的实验。

DESCRIPTION (provided by applicant): The overall goal of the proposed research is to determine how brain events at the biophysical level in the human brain influence the macroscopic recordings outside the skull. The specific focus is on sleep spindles, the best studied sleep rhythm, for which we will obtain simultaneous EEG, MEG and depth electrode recordings. These empirical data will be analyzed to determine the laminar sources of the currents within the cortex associated with spindles and these results will be matched to predictions from computational models. We will develop three types of related network models to cover a wide range of spatial scales. The working hypotheses are, first, that spindles are generated by multiple loosely-coupled cortical regions through rhythmic activation of thalamocortical afferents, onto superficial cortical layers from the matrix system, and onto middle layers from the core system, and second, that spindle oscillations in restricted thalamocortical domains in the core system are spread via the matrix system. Empirical Specific Aims and Hypotheses 1) Record MEG and EEG simultaneously during sleep spindles. Hypothesis: MEG and EEG will record very different activity patterns at the sensor level and in their inferred sources. Poor correlation will be apparent as inconstant phase and amplitude relations within spindle discharges, as well as only loose correlations as to when spindles occur. 2) Record from intracranial EEG macro-electrodes during sleep spindles, with simultaneous scalp EEG and MEG recordings. Hypothesis: Recordings from different cortical generators will be only loosely coupled with each other, or with scalp EEG, thus supporting the general view suggested by MEG. 3) Record from intracranial microelectrode arrays during sleep spindles. Hypothesis: Neuronal generator currents vary during each spindle between superficial and middle layers. 4) Reconstruct supragranular and infragranular pyramidal cells from association cortex in humans, determine their laminar distribution, and estimate the likely termination zones of core and matrix thalamocortical projections. Hypothesis: Significant anatomical differences will be found between human association cortex and the rodent sensory cortex. Modeling Specific Aims and Hypotheses 1) Construct accurate, realistic EEG/MEG forward solutions based on cortical reconstruction from structural MRI. Hypothesis: Basic parameters of extracranial EEG/MEG can be replicated by modeling multiple thalamocortical domains with varying synchrony between domains. The values of the fit parameters to EEG/MEG will match those inferred from intracranial macroelectrode recordings. 2) Analyze the recorded cortical Current Source Density (CSD) using Principal Components Analysis (PCA). Model the CSD patterns expected from the matrix and core thalamocortical afferents using reconstructions of supragranular and infragranular pyramidal cells, their population distribution, and terminations of matrix and core afferents. Hypothesis: The main spatiotemporal CSD components contributing to the spindle identified with PCA will correspond to the CSD components modeled to result from activation of matrix and core thalamocortical afferents. 3) Construct neuronal models based on Hodgkin-Huxley ionic currents that include cortical cells, thalamic reticular nuclear cells, matrix and core thalamic relay cells, and their interconnections in a minicolumn. Hypothesis: The spatiotemporal patterns of currents predicted in different cortical layers will match those obtained using the methods described in modeling aim 2. 4) Scale up the cortical minicolumn network model using simplified neural models to a spatially accurate cortical model that can generate EEG/MEG patterns. Hypothesis: The predicted EEG and MEG from the model will match those observed in recordings, with the involvement of matrix vs core thalamocortical systems corresponding to the parameters derived in modeling aim 1. 5) Develop a statistical model that matches the properties of the scaled up model and analyze it with methods from statistical physics. Hypothesis: The matrix system controls the effective cortical connectivity and the core system controls the local correlation length. Collaborative research Recordings from humans will be performed at MGH (Cash), with analysis and modeling at UCSD (Halgren and Sejnowski). These 3 teams of PIs, students and postdoctoral fellows will interact on a daily basis during the research and will meet formally at least once a year to assess progress and plan new experiments.