SpiNNaker上海马CA3区生物启发记忆的棘波计算模型
Spike-based computational models of bio-inspired memories in the hippocampal CA3 region on SpiNNaker
摘要：
人脑是当今最强大、最高效的机器，在许多方面超越了现代计算机的能力。目前，神经形态工程的研究方向正在试图开发能够模仿大脑功能的硬件，以获得这些优越的能力。其中一个仍在开发中的领域是生物启发记忆的设计，海马体在其中起着重要作用。大脑的这个区域充当短期记忆，能够存储来自大脑中不同感觉流的信息关联，并在以后回忆它们。这是可能的，这要归功于构成海马主要子区域CA3的循环侧支网络结构。在这项工作中，我们开发了两个基于尖峰的计算模型的全功能海马生物启发的记忆的存储和召回的复杂模式实现与脉冲神经网络的SpiNNaker硬件平台。这些模型呈现了不同层次的生物抽象，第一个模型具有更接近生物模型的恒定振荡活动，第二个模型具有能量有效的调节活动，尽管它仍然是生物启发的，但选择了更多的功能方法。对每个模型进行了不同的实验，以测试它们的学习/回忆能力。所提出的模型的功能和生物相容性之间进行了全面的比较，显示它们的优点和缺点。这两个模型可供研究人员公开使用，可以为未来基于尖峰的实现和应用铺平道路。
英文摘要：
The human brain is the most powerful and efficient machine in existence today, surpassing in many ways the capabilities of modern computers. Currently, lines of research in neuromorphic engineering are trying to develop hardware that mimics the functioning of the brain to acquire these superior capabilities. One of the areas still under development is the design of bio-inspired memories, where the hippocampus plays an important role. This region of the brain acts as a short-term memory with the ability to store associations of information from different sensory streams in the brain and recall them later. This is possible thanks to the recurrent collateral network architecture that constitutes CA3, the main sub-region of the hippocampus. In this work, we developed two spike-based computational models of fully functional hippocampal bio-inspired memories for the storage and recall of complex patterns implemented with spiking neural networks on the SpiNNaker hardware platform. These models present different levels of biological abstraction, with the first model having a constant oscillatory activity closer to the biological model, and the second one having an energy-efficient regulated activity, which, although it is still bio-inspired, opts for a more functional approach. Different experiments were performed for each of the models, in order to test their learning/recalling capabilities. A comprehensive comparison between the functionality and the biological plausibility of the presented models was carried out, showing their strengths and weaknesses. The two models, which are publicly available for researchers, could pave the way for future spike-based implementations and applications.
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