Propagation of spiking moments in linear Hawkes networks
Universitat Pompeu Fabra（庞培法布拉大学）；Institute of Neuroinformatics and Neuroscience Center Zurich, University of Zurich/ETH Zurich（苏黎世大学/苏黎世联邦理工学院苏黎世神经信息学与神经科学中心）；University of Bern（伯尔尼大学）
The present paper provides exact mathematical expressions for the high-order moments of spiking activity in a recurrently-connected network of linear Hawkes processes. It extends previous studies that have explored the case of a (linear) Hawkes network driven by deterministic intensity functions to the case of a stimulation by external inputs (rate functions or spike trains) with arbitrary correlation structure. Our approach describes the spatio-temporal filtering induced by the afferent and recurrent connectivities (with arbitrary synaptic response kernels) using operators acting on the input moments. This algebraic viewpoint provides intuition about how the network ingredients shape the input-output mapping for moments, as well as cumulants. We also show using numerical simulation that our results hold for neurons with refractoriness implemented by self-inhibition, provided the corresponding negative feedback for each neuron only mildly alters its mean firing probability.
Optimal interplay between synaptic strengths and network structure enhances activity fluctuations and information propagation in hierarchical modular networks
Event-driven eligibility propagation in large sparse networks: efficiency shaped by biological realism
Institute for Advanced Simulation 6 (IAS-6), Jülich Research Centre（先进模拟研究所第六所（IAS-6），于利希研究中心）；RWTH Aachen University（亚琛工业大学）；University of Wuppertal（伍珀塔尔大学）；University of Bern（伯尔尼大学）；Norwegian University of Life Sciences（挪威生命科学大学）；Käte Hamburger Kolleg, RWTH Aachen University（凯特·汉伯格学院，亚琛工业大学）；Institute of Zoology, University of Cologne（科隆大学动物学研究所）
Scalable Construction of Spiking Neural Networks using up to thousands of GPUs
University of Cagliari（卡利亚里大学）；Istituto Nazionale di Fisica Nucleare (INFN)（意大利国家核物理研究所）；Jülich Research Centre（于利希研究中心）；RWTH Aachen University（亚琛工业大学）
ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks
Department of Data Science and AI, Monash University（墨尔本大学数据科学与人工智能系）；School of Computer Science and Engineering, Southeast University（东南大学计算机科学与工程学院）；School of Software, Northeastern University（东北大学软件学院）
