Functionalities Emerging in Adaptive Brain Networks through Selective Synchronization of Neurons by Targeted Feedback

大脑的两个普遍方面激发了这个项目：大脑节律和反馈连接。脑电图和其他技术在大脑中无处不在地观察到表明部分同步的节律，即神经元一致行动。但它们的功能仍然没有得到很好的理解；当动物注意环境的特定方面时，某些节律往往会增强。大脑网络的第二个特点是其广泛的反馈连接，这使得一个大脑区域对信息的处理可以被接收信息的大脑区域调节。该项目将研究具有反馈连接的神经元网络中的节律，调查这种有针对性的反馈是否允许特定神经元的选择性同步以及从中产生的功能。预计选择性同步有助于解决类似于鸡尾酒会问题的任务，即在许多人同时说话中跟随特定说话者的声音。研究将集中在嗅觉系统上。在那里，一个相应的具有挑战性的任务是，例如，让狗在许多其他气味中追踪毒品或地雷的微弱气味。该项目将为加强复杂刺激场景的生物驱动、事件驱动技术传感器输出的处理提供信息。对研究生和本科生在应用数学、神经科学和跨学科沟通技巧方面的培训是这个项目的一个组成部分。该研究将开发一种用于嗅球和梨状皮质的联合神经网络模型。结合嗅觉系统广泛的结构可塑性，网络将是自适应的，允许反馈连接反映以前的经验。将采用生物物理上详细的神经元模型以及高度简化的神经网络。在数学上，研究将使用和进一步使用各种分析和计算动力系统方法：混合模振荡器和延迟诱导振荡器的弱耦合；多时滞作用下神经元群的弱非线性分析谐振、延迟诱导Hopf分岔的分岔分析数值分支延拓。这些方法将由直接模拟加以补充。

Two pervasive aspects of the brain motivate this project: brain rhythms and feedback connectivity. Rhythms indicating partial synchronization, neurons acting in unison, are ubiquitously observed in the brain by EEG and other techniques. But their function is still not well understood; certain rhythms tend to be enhanced when an animal pays attention to specific aspects of its environment. A second characteristic aspect of brain networks is their extensive feedback connectivity, which allows the processing of information in a brain area to be modulated by the very brain area that receives that information. This project will study rhythms in neuronal networks with feedback connectivity, investigating whether such targeted feedback allows selective synchronization of specific neurons and what functionalities emerge from it. It is expected that selective synchronization contributes to solving tasks similar to the cocktail-party problem of following the voice of a specific speaker among many people talking simultaneously. The research will focus on the olfactory system. There, a corresponding challenging task is, e.g., for a dog to track the faint smell of a drug or landmine amidst many other smells. The project will inform efforts to enhance the processing of the outputs of biologically motivated, event-driven technological sensors for complex stimulus scenes. The training of graduate and undergraduate students in applied mathematics, neuroscience, and interdisciplinary communication skills is an integral part of this project. The research will develop a combined neuronal network model for the olfactory bulb and the piriform cortex. Incorporating aspects of the extensive structural plasticity of the olfactory system, the network will be adaptive, allowing the feedback connections to reflect previous experience. Biophysically detailed neuron models as well as highly simplified neuronal networks will be employed. Mathematically, the research will use and further various analytical and computational dynamical systems methods: weak coupling of mixed-mode oscillators and of delay-induced oscillators; weakly nonlinear analysis of neuronal populations interacting with multiple delays; bifurcation analysis of resonant, delay-induced Hopf bifurcations; numerical branch continuation. These approaches will be complemented by direct simulations.