Sparse coding and lateral inhibition arising from balanced and unbalanced dendrodendritic excitation and inhibition . Yu et al., J Neurosci. 2014 Oct 8;34(41):13701-13. doi: 10.1523/JNEUROSCI.1834-14.2014. 我们最近刚发表在《神经科学通讯》的这篇文章揭示了神经网络系统普遍存在的稀疏编码侧向抑制的突触机制。应用嗅球系统（因为嗅球内部兴奋性神经元（僧帽细胞）和抑制性神经元（颗粒细胞）非常规则组合成神经网络，易于研究）作为研究对象，构建了一个大尺度神经网络模型。通过研究兴奋性和抑制性突触强度在学习过程中动力学演化规律，和最终形成的稀疏编码状态和侧向抑制程度，我们发现，当兴奋性和抑制性突触强度达到最佳比例时（约为1:1.5和1:2这个范围），神经元集群的稀疏发放度最高。而与这些神经元相邻的没有直接接受信号输入的神经元的兴奋性和抑制性突触强度出现极大地比例失衡（1:100），这导致了侧向抑制这种现象。神经元的稀疏发放和侧向抑制共同作用使得神经网络出现最为高效的稀疏编码。 Abstract The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral-granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/ inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/ inhibition ( inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition . These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learning process, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb.
标签: 突触连接
