归一化作为一种规范的神经计算。
Normalization as a canonical neural computation.
机构信息
UCL Institute of Ophtalmology, University College London, 11-43 Bath Street, London EC1V 9EL, UK. m.carandini@ucl. ac.uk
出版信息
Nat Rev Neurosci. 2011 Nov 23;13(1):51-62. doi: 10.1038/nrn3136.
There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.
越来越多的证据表明，大脑依赖于一组标准的神经计算，在不同的脑区和模态中重复这些计算，以便对不同的问题应用相似的操作。这种计算的一个有前途的候选者是归一化，其中神经元的响应除以一个常见的因子，该因子通常包括神经元池的总和活动。归一化是为了解释初级视觉皮层中的响应而开发的，现在被认为在整个视觉系统以及许多其他感觉模态和脑区中起作用。归一化可能是气味表示、视觉注意力的调制效应、价值编码和多感觉信息整合等操作的基础。它在从无脊椎动物到哺乳动物的多种物种的如此多样化的神经系统中存在，表明它是一种标准的神经计算。
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