.png){kind=icon}
返回
Dendritic computation
.png){kind=icon}
PRE
AI
DOI：10.1146/annurev.neuro.28.061604.135703.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
One of the central questions in neuroscience is how particular tasks, or computations, are implemented by neural networks to generate behavior. The prevailing view has been that information processing in neural networks results primarily from the properties of synapses and the connectivity of neurons within the network, with the intrinsic excitability of single neurons playing a lesser role. As a consequence, the contribution of single neurons to computation in the brain has long been underestimated. Here we review recent work showing that neuronal dendrites exhibit a range of linear and nonlinear mechanisms that allow them to implement elementary computations. We discuss why these dendritic properties may be essential for the computations performed by the neuron and the network and provide theoretical and experimental examples to support this view.
Keyword:
dendrites
coding
synaptic integration
spikes
ion channels
期刊
IF:
13.2
论文数:
930
被引数:
1.3W
机构
暂无机构信息
引用论文
.png){kind=icon}
Human Neutrophil Heterogeneity Identified Using Flow Microfluorometry to Monitor Membrane Potential
OAAI
OAAI分享收藏分享收藏
查看更多内容