Liu Guosong
Picower Centre for Learning and Memory, RIKEN-MIT Neuroscience Research Center, Department of Brain & Cognitive Sciences, MIT, Cambridge, Massachusetts 02139, USA.
Nat Neurosci. 2004 Apr;7(4):373-9. doi: 10.1038/nn1206. Epub 2004 Mar 7.
Theoretical and experimental studies on the computation of neural networks suggest that neural computation results from a dynamic interplay of excitatory and inhibitory (E/I) synaptic inputs. Precisely how E/I synapses are organized structurally and functionally to facilitate meaningful interaction remains elusive. Here we show that E/I synapses are regulated across dendritic trees to maintain a constant ratio of inputs in cultured rat hippocampal neurons. This structural arrangement is accompanied by an E/I functional balance maintained by a 'push-pull' feedback regulatory mechanism that is capable of adjusting E/I efficacies in a coordinated fashion. We also found that during activity, inhibitory synapses can determine the impact of adjacent excitatory synapses only if they are colocalized on the same dendritic branch and are activated simultaneously. These fundamental relationships among E/I synapses provide organizational principles relevant to deciphering the structural and functional basis for neural computation within dendritic branches.
关于神经网络计算的理论和实验研究表明,神经计算源于兴奋性和抑制性(E/I)突触输入之间的动态相互作用。目前仍不清楚E/I突触在结构和功能上是如何组织以促进有意义的相互作用的。在此,我们表明,在培养的大鼠海马神经元中,E/I突触在整个树突树上受到调节,以维持输入的恒定比例。这种结构排列伴随着一种由“推挽”反馈调节机制维持的E/I功能平衡,该机制能够以协调的方式调节E/I效能。我们还发现,在活动期间,抑制性突触只有在与相邻兴奋性突触共定位在同一树突分支上并同时被激活时,才能决定其对相邻兴奋性突触的影响。E/I突触之间的这些基本关系为解读树突分支内神经计算的结构和功能基础提供了相关的组织原则。
Neuroscience. 2008-7-31
J Neurophysiol. 2005-3
bioRxiv. 2025-6-3
Int J Mol Sci. 2023-4-12
Front Comput Neurosci. 2023-3-24