Multiscale Oscillatory Dynamics in Cortical Function

项目摘要该项目旨在开发一个大脑皮质振荡模型，因为它们被认为可以精确地编码所有不同的大脑状态动态。如今，我们能够在多个尺度上获得神经活动的测量，从分子水平的详细化学相互作用开始，到细胞水平上的突触电流和放电动力学的局部记录，到神经元组件的记录的网络，到从多个皮质区域的大脑激活记录的系统。该模型将具有以下属性：1)它与特定大脑状态下的生理假设和实验记录一致，2)它是分层的，这个模型将进一步加深我们对大脑皮质动力学中几个明显现象的理解：1)它将从同步的角度解释大脑经历的招募过程，2)它将解释同步过程的稳健性，3)它将解释脑-状态转换动力学中的平稳性，4)它将解释同步细胞数量与同步频率之间的关系，5)解释基于内部刺激的自上而下的动态演化和自下而上的感觉信息处理的动力学和集成；5)解释执行中的时序特性和效率。然后，将推导出的详细的大脑皮层模型与我们现有的运动控制系统的系统级模型集成。特别是，我们的目标是研究振荡在组成皮质子系统之间的信息传递中的作用，并随后在头皮脑电记录中识别运动规划的独特特征。皮质振荡的模型将在各种方面具有实用价值。一方面，如果被用作预测者，它们可以指出旨在使模型无效的重要实验活动，这将导致我们对大脑过程的理解取得实质性进展。另一方面，这些模型作为一种诊断工具是至关重要的，例如，这些模型可以用于检测癫痫发作和脑肿瘤，校准麻醉过程中的药物作用，研究认知任务特征，以及研究智力低下。最后，它们可以为神经假体的正确设计提供适当的动力学描述。智力价值：拟议的研究通过开发一致的皮质活动计算模型，在神经生理学、神经解剖学和工程学之间架起了一座桥梁。这项研究是由一个多学科小组进行的，该小组在一般系统的建模、分析和设计以及神经系统的建模和分析方面都有专长，并有通过NSF支持进行合作的记录。通过我们与马萨诸塞州总医院的工作人员正在进行的电机系统控制合作，拟议的研究将增加一个实验部分。广泛影响：除了上述实用工具之外，这项研究正在系统性地缩小生物学家、统计学家、计算机科学家和系统理论家在了解神经系统方面的零散研究之间的差距。有了这种统一，计算生物学的发展将有助于理解并有可能治愈许多已知的神经疾病。这项研究的进展消除了科学和工程等高度隔离的领域之间的界限。这种多学科的研究需要具有不同专业领域的不同群体之间的完整互动。这项研究将导致博士论文涵盖这两个领域，正如我们的KDI项目所证明的那样。此外，跨学科的课程可以被组织起来，在本科水平上提供更好的多学科培训。

Project SummaryThe proposed project aims at developing a model of cortical oscillation in the brain as they arebelieved to encode in a precise way all the different brain-state dynamics. Nowadays, we are ableto obtain measurements of neural activities at multiple scales starting at the molecular level withdetailed chemical interactions, to cellular levels with localized recordings of synaptic currents andfiring dynamic, to networks with recordings from neuronal assemblies, to systems with recordingsof brain activation from multiple cortical areas.The model will have the following attributes: 1) it is consistent with physiological hypothesesand experimental recordings under specific brain states, 2) it is hierarchical, describing the brainactivity at multiple resolutions as well as describing brain state transitions as information-staterefinements and 3) it is amenable to efficient simulations.This model will further our understanding of several phenomena evident in the cortical dy-namics of the brain: 1) it will explain the recruitment process the brain undergoes in terms ofsynchronization, 2) it will explain the robustness of the synchronization process, 3) it will explainthe smoothness in the dynamics of brain-state transitions, 4) it will explain the relationship be-tween the number of synchronized cells and the frequency of synchronization, 5) it will explainthe dynamics and integration of the top-down dynamic evolution based on internal stimuli andthe bottom-up processing of sensory information, and 5) it will explain the timing properties andefficiency in execution.The derived detailed cortical model will then be integrated with our existing system-levelmodel of the motor control system. In particular, we aim to study the role of oscillations ininformation transfer across constituent cortical subsystems, and to subsequently identify uniquesignatures of motion planning in scalp EEG recordings.Models of cortical oscillations will have utility in various ways. On one hand, if used aspredictors, they can point to important experimental activities designed to invalidate the models,which will result in a substantial progress of our understanding of the brain processes. On theother hand, these models are critical as a diagnostic tool, for example, such models can be usedto detect seizures and brain tumors, to calibrate drug action during anesthesia, to study cognitivetask signatures, and to study mental retardation. Finally, they can provide the appropriatedynamic description for a proper design of neural prosthesis.Intellectual Merit: The proposed research provides a bridge between neurophysiology, neu-roanatomy, and engineering through the development of a consistent computational model ofcortical activities. The research is conducted by a multi-disciplinary group with expertise inboth modeling, analysis and design of systems in general, as well as modeling and analysis ofthe nervous system in particular, with a track record of collaboration through NSF support. Theproposed research will be augmented with an experimental component through our ongoing motorsystem control collaboration with workers in Massachusetts General Hospital.Broad Impact: Beyond the utility mentioned above, this research is systematically closing thegap between the fragmented research on understanding the nervous system conducted by biolo-gists, statisticians, computer scientists and system theorists. With this unification, computationalbiology developments will aid in understanding and potentially curing much of the neural diseasesknown.Progress in this research removes the boundaries between the strongly segregated fields such assciences and engineering. Such multi-disciplinary research requires complete interactions betweendifferent groups with different domains of expertise. This research will result in PhD theses cov-ering both such fields as demonstrated by our KDI project. In addition, courses across disciplinescan be structured to provide better multi-disciplinary training at the undergraduate level.