.png){kind=icon}
返回
Simple networks for spike-timing-based computation, with application to olfactory processing
.png){kind=icon}
OA
AI
DOI：10.1016/S0896-6273(03)00120-X.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Spike synchronization across neurons can be selective for the situation where neurons are driven at similar firing rates, a many are equal computation. This can be achieved in the absence of synaptic interactions between neurons, through phase locking to a common underlying oscillatory potential. Based on this principle, we instantiate an algorithm for robust odor recognition into a model network of spiking neurons whose main features are taken from known properties of biological olfactory systems. Here, recognition of odors is signaled by spike synchronization of specific subsets of mitral cells. This synchronization is highly odor selective and invariant to a wide range of odor concentrations. It is also robust to the presence of strong distractor odors, thus allowing odor segmentation within complex olfactory scenes. Information about odors is encoded in both the identity of glomeruli activated above threshold (1 bit of information per glomerulus) and in the analog degree of activation of the glomeruli (approximately 3 bits per glomerulus).
Keyword:
BULB
REPRESENTATIONS
OSCILLATIONS
RECOGNITION
INTEGRATION
SYNCHRONY
RESPONSES
MIXTURES
ODORANTS
NEURONS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
15
论文数:
1.4W
被引数:
9.9W
机构
暂无机构信息
引用论文
分享收藏Valence, arousal, familiarity, concreteness, and imageability ratings for 292 two-character Chinese nouns in Cantonese speakers in Hong Kong.png)
PLOS ONEOAAI
PLOS ONEIF0
OAAI分享收藏
查看更多内容