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On- and Off-centre Pathways in a Retino-Geniculate Spiking Neural Network on SpiNNaker

机译:在Teminaker的Retino-enciculate尖刺神经网络中的处于和离心路径

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We present a neural circuit inspired by the brain visual pathway simulated with neuromorphic hardware. The main recipient of the visual information from retinal ganglion cells is the dorsal part of the Lateral Geniculate Nucleus (LGN). Previously, we have implemented a Spiking Neural Network of the LGN on SpiNNaker receiving inputs from an electronic retina (e-retina) chip comprising a Dynamic Vision Sensor. Here, we incorporate a retinotopic structure in the existing LGN network emulating the on- and off-centre receptive fields of the retinal spiking neurons, which are well simulated by the e-retina output. We have parameterised the model to mimic the `push' (excitation) and `pull' (inhibition) dynamics observed in the LGN due to the centre-surround organisation of its receptive fields and synaptic connectivities. The model presented here lay the groundwork for research on building a biologically plausible spiking neural network of visual cognition.
机译:我们提出了一种由脑视觉途径的神经循环,其用神经形状硬件模拟。 视网膜神经节细胞的视觉信息的主要接受者是横向核状核(LGN)的背部部分。 以前,我们已经在旋转线机上实现了LGN的LGN的尖峰神经网络,从包括动态视觉传感器的电子视网膜(E-Retina)芯片接收输入。 这里,我们在现有的LGN网络中纳入视网膜运动结构,其模拟视网膜尖峰神经元的接触和偏离中心接收领域,这通过E-Retina输出良好地模拟。 我们已经参数化了模型以模拟LGN在LGN中观察到的“推动”(刺激)和“拉动”动态,因为其接受领域和突触结合性。 该模型介绍了在建立一种生物合理的视觉认知神经网络的基础上奠定了基础。

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