Heterosynaptic plasticity plays a key role in addressing the interactions between local and global neuromodulation and the implementation of more complex biological functions. However, conventional heterosynaptic devices suffer from high energy consumption, high operating voltages and a lack of multi-modal regulation, which hinder the development of next-generation neuromorphic computing. Here, we report a heterogeneous ion-modulated 2D-WS four-terminal heterosynaptic memtransistor (Na@WSHMT) with typical heterosynaptic plasticity at low stimulation voltage (200 mV) and ultra-low energy consumption (150 aJ). Moreover, the potential of four-terminal heterosynaptic memtransistors is demonstrated for enhancing the digit recognition with an increased recognition accuracy from 90.5 % to 93.3 % by stimulating the heterosynaptic terminal (light). Furthermore, convolutional image processing such as feature extraction is successfully performed by a convolutional neural network based on the multi-conductance characteristic of Na@WSHMT. The ion-modulated heterosynaptic memtransistor provide a promising strategy for energy-efficient and controllable neuromorphic computing.

中文翻译：

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用于可控突触调制和节能神经形态计算的异质离子调制 2D-WS2 异质突触记忆晶体管


异质突触可塑性在解决局部和整体神经调节之间的相互作用以及更复杂的生物功能的实现方面发挥着关键作用。然而，传统的异质突触设备存在高能耗、高工作电压和缺乏多模态调节等问题，阻碍了下一代神经形态计算的发展。在这里，我们报告了一种异质离子调制的 2D-WS 四端异质突触记忆晶体管 (Na@WSHMT)，在低刺激电压 (200 mV) 和超低能耗 (150 aJ) 下具有典型的异质突触可塑性。此外，四端异质突触记忆晶体管具有增强数字识别的潜力，通过刺激异质突触末端（光），识别准确度从 90.5% 提高到 93.3%。此外，基于Na@WSHMT的多电导特性的卷积神经网络成功地进行了特征提取等卷积图像处理。离子调制异质突触记忆晶体管为节能且可控的神经形态计算提供了一种有前景的策略。