Spike-timing-dependent plasticity (STDP) is a biological process in which the precise order and timing of neuronal spikes affect the degree of synaptic modification. While there has been numerous research focusing on the role of STDP in neural coding, the functional implications of STDP at the macroscopic level in the brain have not been fully explored yet. In this work, we propose that STDP in an ensemble of spiking neurons renders storing high dimensional information in the form of a `memory plane'. Neural activity based on STDP transforms periodic spatio-temporal input patterns into the corresponding memory plane, where the stored information can be dynamically revived with a proper cue. Using the dynamical systems theory that shows the analytic relation between the input and the memory plane, we were able to demonstrate a specific memory process for high-dimensional associative data sets. In the auto-associative memory task, a group of images that were continuously streamed to the system can be retrieved from the oscillating neural state. The second application deals with the process of semantic memory components that are embedded from sentences. The results show that words can recall multiple sentences simultaneously or one exclusively, depending on their grammatical relations. This implies that the proposed framework is apt to process multiple groups of associative memories with a composite structure.
翻译:具有刺刺性依赖性可塑性(STDP)是一个生物过程,在这个过程里,神经性钉钉的精确顺序和时间会影响合成改变的程度。虽然已经进行了许多研究,重点研究STDP在神经编码中的作用,但是尚未充分探讨STDP在大脑宏观层的功能影响。在这项工作中,我们建议STDP以神经神经元混合体的形式,以“模拟平面”的形式存储高维信息。基于STDP的神经活动将定期的瞬时输入模式转换成相应的记忆平面,在那里,存储的信息可以用适当的提示动态地恢复。利用能显示输入和记忆平面之间分析关系的动态系统理论,我们得以展示高维联动数据集的具体记忆过程。在自动感应存储任务中,一组连续流到系统的图像可以从感应状态中检索。第二个应用过程与多个记忆结构的组合,可以同时显示一个磁感应结构的组合结果。这个结构的第二个应用过程可以显示一个磁感应结构的组合,可以同时显示一个磁感应结构的组合。