论文标题
兴奋性和抑制性神经元网络中的接收领域的新兴组织
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons
论文作者
论文摘要
研究神经波的局部激发和抑制模式被研究为神经元调节组织的计算机制。提出了基于兴奋性和抑制性神经元网络的稀疏编码算法，该算法表现出地形图，因为接收场适应了输入刺激。由神经波的泄漏整合和火力模型的启发，我们提出了一个更典型的人工神经网络的激活模型。提出了使用自然图像和自然语言文本的激活模型进行的计算实验。在图像的情况下，出现了熟悉的“风车”模式。在文本的情况下，由此产生的地形图显示了粒度单词语义的二维表示。使用体感输入的合成模型的实验用于研究网络动力学如何影响输入变化下的神经元图的可塑性。
Local patterns of excitation and inhibition that can generate neural waves are studied as a computational mechanism underlying the organization of neuronal tunings. Sparse coding algorithms based on networks of excitatory and inhibitory neurons are proposed that exhibit topographic maps as the receptive fields are adapted to input stimuli. Motivated by a leaky integrate-and-fire model of neural waves, we propose an activation model that is more typical of artificial neural networks. Computational experiments with the activation model using both natural images and natural language text are presented. In the case of images, familiar "pinwheel" patterns of oriented edge detectors emerge; in the case of text, the resulting topographic maps exhibit a 2-dimensional representation of granular word semantics. Experiments with a synthetic model of somatosensory input are used to investigate how the network dynamics may affect plasticity of neuronal maps under changes to the inputs.
