Center for Learning and Memory, University of Texas at Austin, Austin, Texas, USA.
Nat Neurosci. 2011 Sep 11;14(10):1330-7. doi: 10.1038/nn.2901.
Entorhinal grid cells in mammals fire as a function of animal location, with spatially periodic response patterns. This nonlocal periodic representation of location, a local variable, is unlike other neural codes. There is no theoretical explanation for why such a code should exist. We examined how accurately the grid code with noisy neurons allows an ideal observer to estimate location and found this code to be a previously unknown type of population code with unprecedented robustness to noise. In particular, the representational accuracy attained by grid cells over the coding range was in a qualitatively different class from what is possible with observed sensory and motor population codes. We found that a simple neural network can effectively correct the grid code. To the best of our knowledge, these results are the first demonstration that the brain contains, and may exploit, powerful error-correcting codes for analog variables.
哺乳动物的内嗅网格细胞根据动物的位置发射，具有空间周期性的反应模式。这种位置的非局部周期性表示是一种局部变量，与其他神经代码不同。没有理论解释为什么应该存在这样的代码。我们研究了带有噪声神经元的网格代码在多大程度上可以让理想观察者准确估计位置，结果发现这种代码是一种以前未知的群体代码，具有前所未有的抗噪能力。特别是，网格细胞在编码范围内达到的表示精度与从观察到的感觉和运动群体代码中获得的精度完全不同。我们发现，一个简单的神经网络可以有效地修正网格代码。据我们所知，这些结果首次证明了大脑中包含并可能利用强大的纠错代码来处理模拟变量。
