Generalization in vision and motor control

被引:229
作者
Poggio, T [1 ]
Bizzi, E
机构
[1] MIT, McGovern Inst,Ctr Biol & Computat Learning, Dept Brain & Cognit Sci, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02142 USA
[2] European Brain Res Inst, I-00143 Rome, Italy
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
D O I
10.1038/nature03014
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Learning is more than memory. It is not simply the building of a look-up table of labelled images, or a phone-directory-like list of motor acts and the corresponding sequences of muscle activation. Central to learning and intelligence is the ability to predict, that is, to generalize to new situations, beyond the memory of specific examples. The key to generalization, in turn, is the architecture of the system, more than the rules of synaptic plasticity. We propose a specific architecture for generalization for both the motor and the visual systems, and argue for a canonical microcircuit underlying visual and motor learning.
引用
收藏
页码:768 / 774
页数:7
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