论文标题
由抗波利晶体管制成的生物现实和多功能人造树突
Bio-realistic and versatile artificial dendrites made of anti-ambipolar transistors
论文作者
论文摘要
对神经网络作为神经元的二进制二进制的理解已成为神经科学的基础,因此,从大脑中汲取灵感的新兴神经形态计算技术。然而,最近,由于最近的神经科学研究,这种教条越来越受到挑战,在这些研究中,发现淡化的树突是活跃的,动态独特且在计算上强大的。迄今为止,对人工树突的研究很少,现有的少数设备仍然远离通用或(和)生物现实主义。主流设备体系结构中可用的物理机制有限的物理机制阻碍了突破。在这里,我们在实验上证明了由WSE2/MOS2异径 - 渠道 - 通道抗波拉晶体管制成的生物真实和多功能人造树突,可以密切模仿实验记录的非单调树突状CA2+动作潜力,从而使各种精液计算构成了各种复杂的计算。尖峰神经网络模拟表明,这种非惯例但生物现实的树突状激活的结合增强了网络在非平稳环境中的鲁棒性和代表性。通过进一步利用循环效应,树突状抗波尔晶体管可以自然模仿树突状脊柱上突触可变性(元塑性)的调节,这是树突状的重要稳态现象,这是由于树突状调节引起的。树突状抗极性晶体管的发明完成了神经形态晶体管的家族,并代表了多样化晶体管功能的重大进步。
The understanding of neural networks as neuron-synapse binaries has been the foundation of neuroscience, and therefore, the emerging neuromorphic computing technology that takes inspiration from the brain. This dogma, however, has been increasingly challenged by recent neuroscience research in which the downplayed dendrites were found to be active, dynamically unique and computationally powerful. To date, research on artificial dendrites is scarce and the few existing devices are still far from versatile or (and) bio-realistic. A breakthrough is hampered by the limited available physical mechanisms in mainstream device architectures. Here, we experimentally demonstrate a bio-realistic and versatile artificial dendrite made of WSe2/MoS2 heterojunction-channel anti-ambipolar transistor, which can closely mimic the experimentally recorded non-monotonic dendritic Ca2+ action potential that underpins various sophisticated computations. Spiking neural network simulations reveal that the incorporation of this nonconventional but bio-realistic dendritic activation enhances the robustness and representational capability of the network in non-stationary environments. By further exploiting the memristive effect, dendritic anti-ambipolar transistor can naturally mimic Ca2+-mediated regulation of synaptic plasticity (meta-plasticity) at dendritic spine, an important homeostatic phenomenon due to dendritic modulation. The invention of dendritic anti-ambipolar transistor completes the family of neuromorphic transistors and represents a major advance in diversifying the functionality of transistors.