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Dendritic Morphology Affects the Velocity and Amplitude of Back-propagating Action Potentials

摘要The back-propagating action potential(bpAP)is crucial for neuronal signal integration and synaptic plastic-ity in dendritic trees.Its properties(velocity and amplitude)can be affected by dendritic morphology.Due to limited spa-tial resolution,it has been difficult to explore the specific propagation process of bpAPs along dendrites and examine the influence of dendritic morphology,such as the dendrite diameter and branching pattern,using patch-clamp record-ing.By taking advantage of Optopatch,an all-optical elec-trophysiological method,we made detailed recordings of the real-time propagation of bpAPs in dendritic trees.We found that the velocity of bpAPs was not uniform in a single den-drite,and the bpAP velocity differed among distinct dendrites of the same neuron.The velocity of a bpAP was positively correlated with the diameter of the dendrite on which it prop-agated.In addition,when bpAPs passed through a dendritic branch point,their velocity decreased significantly.Similar to velocity,the amplitude of bpAPs was also positively corre-lated with dendritic diameter,and the attenuation patterns of bpAPs differed among different dendrites.Simulation results from neuron models with different dendritic morphology cor-responded well with the experimental results.These findings indicate that the dendritic diameter and branching pattern significantly influence the properties of bpAPs.The diversity among the bpAPs recorded in different neurons was mainly due to differences in dendritic morphology.These results may inspire the construction of neuronal models to predict the propagation of bpAPs in dendrites with enormous vari-ation in morphology,to further illuminate the role of bpAPs in neuronal communication.

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作者 Wu Tian [1] Luxin Peng [2] Mengdi Zhao [3] Louis Tao [4] Peng Zou [5] Yan Zhang [1] 学术成果认领
作者单位 State Key Laboratory of Membrane Biology,College of Life Sciences,Peking University,Beijing 100871,China [1] College of Chemistry and Molecular Engineering,Synthetic and Functional Biomolecules Center,Beijing National Laboratory for Molecular Sciences,Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education,Peking University,Beijing 100871,China [2] Center for Quantitative Biology,Academy for Advanced Interdisciplinary Studies,Peking University,Beijing 100871,China;Beijing Academy of Artificial Intelligence,Beijing 100084,China [3] Center for Quantitative Biology,Academy for Advanced Interdisciplinary Studies,Peking University,Beijing 100871,China;Center for Bioinformatics,National Laboratory of Protein Engineering and Plant Genetic Engineering,School of Life Sciences,Peking University,Beijing 100871,China [4] College of Chemistry and Molecular Engineering,Synthetic and Functional Biomolecules Center,Beijing National Laboratory for Molecular Sciences,Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education,Peking University,Beijing 100871,China;PKU-IDG/McGovern Institute for Brain Research,Peking University,Beijing 100871,China;Peking-Tsinghua Center for Life Sciences,Peking University,Beijing 100871,China;Chinese Institute for Brain Research(CIBR),Beijing 102206,China [5]
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发布时间 2023-02-06(万方平台首次上网日期,不代表论文的发表时间)
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神经科学通报(英文版)

神经科学通报(英文版)

2022年38卷11期

1330-1346页

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