Memristor-Based FBM Circuit of Collaboration Among Multiple Brain Regions and Its Application in Rescue Robot
本文设计了一种基于忆阻器的多脑区协作FBM神经网络电路，模拟情绪对决策的影响，并在救援机器人中应用，具有低功耗和高集成度优势。
Current memristive circuits for biological decision-making only consider single-dimensional stimulus feedback and synaptic weight regulation without considering the influence of multiple factors interacting. This article designs a biological multibrain collaborative Fogg's behavior model (FBM) neural network circuit based on memristors and considers the influence of emotions on decision-making. The circuit includes the thalamus, dorsolateral prefrontal cortex, ventral tegmental area, hippocampus, amygdala, striatum system, and anterior cingulate cortex module. The circuit adopts a brain-like partitioned modular design, which provides a structural basis for its functional implementation, and it also has the advantages of low power consumption and high integration. The circuit can accurately simulate neural synaptic plasticity and realize learning reinforcement, natural forgetting, and dynamic modulation of synaptic strength under emotional regulation. PSpice simulations show that the integration of more brain region coordination mechanisms exhibits adaptive decision-making characteristics that are closer to the biological brain.