场定向聚合人工突触的结构演化和按需生长
Structural evolution and on-demand growth of artificial synapses via field-directed polymerization
摘要：
电路的互连性、容错和动态演化是生物启发工程长期追求的目标。在这里，我们提出了树枝状晶体管组成的有机半导体作为构建块的类脑计算。这些装置，由于它们的电压触发的生长和神经结构的相似性，响应动作电位，以实现复杂的类脑功能，如巴甫洛夫学习，模式识别，和尖峰时间依赖性可塑性。连接的动态形成让人想起一种称为突触发生的生物学习机制，它是通过我们命名为场定向聚合的电化学反应进行的。我们将其用于枝晶连接，并通过调节生长参数来控制材料特性，例如与塑性相关的电阻和时间常数。我们相信，这些结果将激发进一步的研究对复杂的整合聚合突触的脑启发计算。
英文摘要：
Interconnectivity, fault tolerance, and dynamic evolution of the circuitry are long sought-after objectives of bio-inspired engineering. Here, we propose dendritic transistors composed of organic semiconductors as building blocks for neuromorphic computing. These devices, owning to their voltage-triggered growth and resemblance to neural structures, respond to action potentials to achieve complex brain-like features, such as Pavlovian learning, pattern recognition, and spike-timing-dependent plasticity. The dynamic formation of the connections is reminiscent of a biological learning mechanism known as synaptogenesis, and it is carried out by an electrochemical reaction that we name field-directed polymerization. We employ it to dendritic connections and, by modulating the growth parameters, control material properties such as the resistance and the time constants relevant for plasticity. We believe these results will inspire further research towards the complex integration of polymerized synapses for brain-inspired computing.
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