CRCNS: Integrated Empirical and Multiscale Modeling of Human Sleep Spindles

描述（由申请人提供）：拟议研究的总体目标是确定人脑中生物物理水平的脑事件如何影响颅骨外的宏观记录。具体的重点是睡眠纺锤波，最好的研究睡眠节律，我们将获得同步EEG，MEG和深度电极记录。这些经验数据将被分析，以确定与纺锤波相关的皮层内电流的层流源，这些结果将与计算模型的预测相匹配。我们将开发三种类型的相关网络模型，以覆盖广泛的空间尺度。工作假设是，首先，纺锤波是由多个松耦合的皮质区域通过丘脑皮质传入神经的节律性激活产生的，从基质系统到达表层皮质层，从核心系统到达中层，第二，核心系统中限制性丘脑皮质区域中的纺锤波振荡通过基质系统传播。实验的具体目的和假设1）在睡眠纺锤波期间同时记录MEG和EEG。假设：脑磁图和脑电图在传感器水平和推断来源上记录的活动模式非常不同。差的相关性将是明显的，因为纺锤波放电内的不恒定的相位和振幅关系，以及只有松散的相关性，当纺锤波发生。2)在睡眠纺锤波期间从颅内EEG宏电极记录，同时进行头皮EEG和MEG记录。假设：来自不同皮层发生器的记录将仅彼此松散耦合，或与头皮EEG松散耦合，从而支持MEG提出的一般观点。3)睡眠纺锤波期间颅内微电极阵列的记录。假设：神经元发生器电流在表层和中层之间的每个纺锤体期间变化。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，并估计可能的核心和基质丘脑皮质投射的终止区。假设：人类的联合皮层和啮齿类动物的感觉皮层在解剖学上存在显著差异。建模特定目标和假设1）基于来自结构MRI的皮层重建构建准确、逼真的EEG/MEG正向解。假设：颅外EEG/MEG的基本参数可以通过模拟多个丘脑皮质区域来复制，这些区域之间具有不同的同步性。EEG/MEG的拟合参数值将与从颅内宏电极记录推断的值相匹配。2)使用主成分分析（PCA）分析记录的皮层电流源密度（CSD）。模型CSD模式预期从基质和核心丘脑皮质传入使用重建的颗粒上和颗粒下锥体细胞，其人口分布，和终止的基质和核心传入。假设：主要的时空CSD组件与PCA确定的主轴将对应的CSD组件建模，导致激活的矩阵和核心丘脑皮层传入。3)构建基于Hodgkin-Huxley离子电流的神经元模型，包括皮质细胞、丘脑网状核细胞、基质和核心丘脑中继细胞及其在微柱中的相互连接。假设：在不同皮层中预测的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生成EEG/MEG模式的空间精确的皮质模型。假设：从模型预测的EEG和MEG将与记录中观察到的那些相匹配，其中涉及与建模目标1中导出的参数相对应的基质与核心丘脑皮质系统。5)开发一个与放大模型的属性相匹配的统计模型，并使用统计物理学方法对其进行分析。假设：基质系统控制皮层有效连接，核心系统控制局部相关长度。来自人类的记录将在MGH（现金）进行，并在UCSD（Halgren和Sejnowski）进行分析和建模。这三个团队的PI，学生和博士后研究员将在研究期间每天进行互动，并将每年至少举行一次正式会议，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.