涌现离子-神经元动力学的晶体管模拟。

Hfsp Journal Pub Date : 2008-06-01 Epub Date: 2008-04-18 DOI:10.2976/1.2905393
Guy Rachmuth, Chi-Sang Poon
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引用次数: 47

摘要

神经形态模拟金属氧化物硅(MOS)晶体管电路有望实现紧凑、低功耗和高速的离子神经元动力学模拟,其速度比数字模拟快几个数量级。然而,它们固有的有限输入电压动态范围与功耗和硅晶片面积权衡使得它们对由于制造不精确、器件噪声和其他非理想性而导致的晶体管失配高度敏感。这一限制阻碍了稳健的模拟大规模集成电路(aVLSI)实现紧急离子神经元动力学计算,而不仅仅是具有有限离子通道动力学的简单峰值。在这里,我们提出了多用途的神经形态模拟构建块电路,在低功耗MOS晶体管弱反转机制下提供接近最大电压动态范围,这是aVLSI实现或植入式仿生器件应用的理想选择。制造的微芯片可以实现动态离子神经元计算,如突触前尖峰或突触前和突触后活动的巧合检测。作为一个关键的性能基准,芯片上的高速和高度交互的离子神经元模拟能力使我们能够迅速发现混沌起搏器破裂的最小模型,这是一种具有基本生物学意义的紧急离子神经元行为,迄今为止尚未通过传统的数字或模拟模拟进行实验测试或计算探索。这些紧凑型和高能效的新兴离子神经元动力学晶体管模拟物为下一代神经形态、神经假肢和脑机接口应用开辟了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transistor analogs of emergent iono-neuronal dynamics.

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics. Here we present versatile neuromorphic analog building-block circuits that afford near-maximum voltage dynamic range operating within the low-power MOS transistor weak-inversion regime which is ideal for aVLSI implementation or implantable biomimetic device applications. The fabricated microchip allowed robust realization of dynamic iono-neuronal computations such as coincidence detection of presynaptic spikes or pre- and postsynaptic activities. As a critical performance benchmark, the high-speed and highly interactive iono-neuronal simulation capability on-chip enabled our prompt discovery of a minimal model of chaotic pacemaker bursting, an emergent iono-neuronal behavior of fundamental biological significance which has hitherto defied experimental testing or computational exploration via conventional digital or analog simulations. These compact and power-efficient transistor analogs of emergent iono-neuronal dynamics open new avenues for next-generation neuromorphic, neuroprosthetic, and brain-machine interface applications.

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Hfsp Journal
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