Neuromorphic technologies typically employ a point neuron model, neglecting the spatiotemporal nature of neuronal computation. Dendritic morphology and synaptic organization are structurally tailored for spatiotemporal information processing, such as visual perception. Here we report a neuromorphic computational model that integrates synaptic organization with dendritic tree-like morphology. Based on the physics of multigate silicon nanowire transistors with ion-doped sol–gel films, our model—termed dendristor—performs dendritic computation at the device and neural-circuit level. The dendristor offers the bioplausible nonlinear integration of excitatory/inhibitory synaptic inputs and silent synapses with diverse spatial distribution dependency, emulating direction selectivity, which is the feature that reacts to signal direction on the dendrite. We also develop a neuromorphic dendritic neural circuit—a network of interconnected dendritic neurons—that serves as a building block for the design of a multilayer network system that emulates three-dimensional spatial motion perception in the retina.

神经形态技术通常采用点神经元模型，忽略神经元计算的时空性质。树突形态和突触组织在结构上是为时空信息处理（例如视觉感知）量身定制的。在这里，我们报告了一种将突触组织与树突树状形态相结合的神经形态计算模型。基于具有离子掺杂溶胶凝胶薄膜的多栅极硅纳米线晶体管的物理原理，我们的模型（称为树状晶体）在器件和神经电路级别执行树状计算。树突提供了具有不同空间分布依赖性的兴奋性/抑制性突触输入和沉默突触的生物合理的非线性集成，模拟方向选择性，这是对树突上的信号方向做出反应的特征。我们还开发了一种神经形态树突神经回路——一种互连的树突神经元网络——作为设计多层网络系统的构建块，模拟视网膜中的三维空间运动感知。