Neural Dynamics: Their Nonlinear Basis and Computational Consequences

大脑使用动作电位或尖峰信号对信息进行编码，动作电位或尖峰信号是由单个神经元产生的短脉冲电。知觉、认知和运动控制都依赖于正确处理的尖峰编码信息。想象一下，如果你大脑中的神经元开始错误地产生尖峰信号会发生什么。知觉可能会扭曲，思维受损，运动控制丧失。也就是说，理解神经元如何产生尖峰信号是理解大脑如何工作的关键。 我们的研究重点是破译神经元如何产生尖峰。不同的神经元以非常不同的方式做到这一点，并且可以基于此在操作上被分类为积分器或符合检测器。 重要的是，每个神经元都是一个更大网络的一部分，网络的运作方式在很大程度上取决于组成神经元的运作方式。另一个重要的考虑因素是没有两个神经元是完全相同的。在这里，我们研究神经元之间细微差异的基础和后果。所有积分器都以或多或少相同的方式产生尖峰，但它们以完全相同的方式产生尖峰是否重要？同样的问题也适用于符合探测器。细微的细胞差异对网络编码重要吗？另一方面，这些差异从何而来？阐明这些基本问题将有助于解释大脑如何处理信息的关键方面，以及这种处理在某些神经系统疾病中如何出错。

The brain encodes information using action potentials, or spikes, which are short pulses of electricity generated by individual neurons. Perception, cognition, and motor control all rely on spike-encoded information being properly processed. Just imagine what would happen if the neurons in your brain started producing spikes incorrectly... perceptions could become distorted, thinking impaired, and motor control lost. This to say that understanding how neurons produce spikes is key to understanding how the brain works. Our research focusses on deciphering how neurons generate spikes. Different neurons do this in very different ways, and can be operationally classified as integrators or coincidence detectors on the basis thereof. Importantly, each neuron is part of a larger network, and how the network operates depends heavily upon how the component neurons operate. Another important consideration is that no two neurons are exactly alike. Here, we investigate the basis for and consequences of subtle differences between neurons. All integrators generate spikes in more or less the same way, but is it important that they do not do so in exactly the same way? The same question applies to coincidence detectors. Are subtle cellular differences important for network coding? On the other hand, from where do these differences originate? Answering those fundamental questions will help explain key aspects of how the brain processes information, and how that processing may go awry in certain neurological diseases.