Poirazi P, Mel B W
Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Neuron. 2001 Mar;29(3):779-96. doi: 10.1016/s0896-6273(01)00252-5.
We consider the combined effects of active dendrites and structural plasticity on the storage capacity of neural tissue. We compare capacity for two different modes of dendritic integration: (1) linear, where synaptic inputs are summed across the entire dendritic arbor, and (2) nonlinear, where each dendritic compartment functions as a separately thresholded neuron-like summing unit. We calculate much larger storage capacities for cells with nonlinear subunits and show that this capacity is accessible to a structural learning rule that combines random synapse formation with activity-dependent stabilization/elimination. In a departure from the common view that memories are encoded in the overall connection strengths between neurons, our results suggest that long-term information storage in neural tissue could reside primarily in the selective addressing of synaptic contacts onto dendritic subunits.
我们考虑了活跃树突和结构可塑性对神经组织存储容量的综合影响。我们比较了两种不同树突整合模式的容量:(1)线性模式,即突触输入在整个树突分支上进行求和;(2)非线性模式,即每个树突隔室充当一个单独阈值化的类神经元求和单元。我们计算出具有非线性亚基的细胞的存储容量要大得多,并表明这种容量可通过一种结构学习规则来实现,该规则将随机突触形成与活动依赖的稳定/消除相结合。与记忆编码于神经元之间整体连接强度的普遍观点不同,我们的结果表明神经组织中的长期信息存储可能主要在于突触接触对树突亚基的选择性寻址。