Bonzon Pierre
Department of Information Systems, Faculty of HEC, University of Lausanne, Lausanne, Switzerland.
Front Comput Neurosci. 2019 Feb 12;13:1. doi: 10.3389/fncom.2019.00001. eCollection 2019.
A new computational framework implementing asynchronous neural dynamics is used to address the duality between synchronous vs. asynchronous processes, and their possible relation to conscious vs. unconscious behaviors. Extending previous results on modeling the first three levels of animal awareness, this formalism is used here to produce the execution traces of parallel threads that implement these models. Running simulations demonstrate how sensory stimuli associated with a population of excitatory neurons inhibit in turn other neural assemblies i.e., a kind of neuronal asynchronous wiring/unwiring process that is reflected in the progressive trimming of execution traces. Whereas, reactive behaviors relying on configural learning produce vanishing traces, the learning of a rule and its later application produce persistent traces revealing potential synchronous roots of animal awareness. In contrast, to previous formalisms that use analytical and/or statistical methods to search for patterns existing in a brain, this new framework proposes a tool for studying the emergence of brain structures that might be associated with higher level cognitive capabilities.
一种实现异步神经动力学的新计算框架被用于解决同步与异步过程之间的二元性，以及它们与有意识和无意识行为之间可能的关系。扩展先前关于对动物意识的前三个层次进行建模的结果，这里使用这种形式主义来生成实现这些模型的并行线程的执行轨迹。运行模拟展示了与一群兴奋性神经元相关的感觉刺激如何依次抑制其他神经集合，即一种神经元异步连接/断开连接的过程，这反映在执行轨迹的逐步修剪中。而依赖于构型学习的反应性行为会产生消失的轨迹，规则的学习及其随后的应用会产生持久的轨迹，揭示动物意识潜在的同步根源。相比之下，与以前使用分析和/或统计方法来寻找大脑中存在的模式的形式主义不同，这个新框架提出了一种工具，用于研究可能与更高层次认知能力相关的大脑结构的出现。
