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Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System
Journal of Signal Processing Systems ( IF 1.6 ) Pub Date : 2020-06-27 , DOI: 10.1007/s11265-020-01556-9
Johannes Partzsch , Christian Mayr , Massimiliano Giulioni , Marko Noack , Stefan Hänzsche , Stefan Scholze , Sebastian Höppner , Paolo Del Giudice , Rene Schüffny

Real-time coupling of cell cultures to neuromorphic circuits necessitates a neuromorphic network that replicates biological behaviour both on a per-neuron and on a population basis, with a network size comparable to the culture. We present a large neuromorphic system composed of 9 chips, with overall 2880 neurons and 144M conductance-based synapses. As they are realized in a robust switched-capacitor fashion, individual neurons and synapses can be configured to replicate with high fidelity a wide range of biologically realistic behaviour. In contrast to other exploration/heuristics-based approaches, we employ a theory-guided mesoscopic approach to configure the overall network to a range of bursting behaviours, thus replicating the statistics of our targeted in-vitro network. The mesoscopic approach has implications beyond our proposed biohybrid, as it allows a targeted exploration of the behavioural space, which is a non-trivial task especially in large, recurrent networks.



中文翻译:

在生物混合神经形态系统上配置种群动态的均值场方法

细胞培养物与神经形态电路的实时耦合需要一个神经形态网络,该网络能够在每个神经元和群体基础上复制生物学行为,其网络规模可与培养物媲美。我们提出了一个大型的神经形态系统,该系统由9个芯片组成,共有2880个神经元和基于144M电导的突触。由于它们以健壮的开关电容器方式实现,因此单个神经元和突触可配置为以高保真度复制各种生物学上的实际行为。与其他基于探索/启发式方法的方法相比,我们采用理论指导的介观方法将整个网络配置为一系列突发行为,从而复制我们的目标体外网络的统计信息。介观方法的含义超出了我们提出的生物混合,

更新日期:2020-06-27
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