RIA: Dynamics of Oscillatory Neural Systems

本项目探索基于哺乳动物视觉皮层和嗅球中神经元柱振荡行为的下一代神经计算。最近的发现，如兔子嗅球振荡的证据，帮助他们确定其他兔子的性别和年龄，这些发现支持了比信号量级更深入地观察的生物学基础。神经元的状态不会被认为是一个简单的水平或幅度，而是其输出相对于其他邻近神经元的幅度、频率、相位和其他属性的组合。本研究旨在通过数学推导动力学方程的封闭解和仿真来分析和表征耦合振荡系统的行为，耦合振荡柱的行为可以通过改变激励、自反馈增益、横向耦合和振荡频率参数来观察。高斯噪声对大型振荡柱网络的影响也将被研究。

This project explores next-generation neural computing based on oscillatory behavior of neuron columns found in the visual cortex and olfactory bulbs of mammals. The biological basis for looking further than magnitude of signals is sufficient as supported by recent discoveries such as evidence of oscillations in the olfactory bulbs of rabbits which helped them to determine the sex and age of other rabbits. That state of neuron would not be considered as a simple level or magnitude, but rather a combination of magnitude, frequency, phase, and perhaps other attributes, of its output relative to other neighboring neurons. This research seeks to analyze and characterize the behavior of coupled oscillatory systems by mathematically deriving closed-form solutions to the dynamic equations and simulation, the behavior of the coupled oscillatory columns can be observed by varying the stimulus, self-feedback gain, lateral coupling, and frequency parameter of oscillation. The effects of Gaussian noise on large networks of oscillatory columns will also be investigated.