Pouget Alexandre, Bavelier Daphné
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA.
Neuron. 2007 Feb 15;53(4):473-5. doi: 10.1016/j.neuron.2007.02.004.
Traditional theories of attention rely on the idea that when we search for a target in a visual display the brain boosts the activity of neurons optimally tuned for the target features. In this issue of Neuron, Navalpakkam and Itti take a computational approach to show that this strategy is actually very inefficient when the target is surrounded by distractors with similar features. Instead, the optimal strategy is to boost the activity of neurons that best discriminate between target and distractors, while essentially ignoring the neurons that respond best to the target.
传统的注意力理论基于这样一种观点，即当我们在视觉场景中搜索目标时，大脑会增强对目标特征进行最优调谐的神经元的活动。在本期《神经元》杂志中，纳瓦尔帕卡姆和伊蒂采用一种计算方法表明，当目标被具有相似特征的干扰物包围时，这种策略实际上效率非常低。相反，最优策略是增强那些能最好地区分目标和干扰物的神经元的活动，而基本上忽略那些对目标反应最佳的神经元。
