Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Department of Brain and Cognitive Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Cell Rep. 2023 Aug 29;42(8):112900. doi: 10.1016/j.celrep.2023.112900. Epub 2023 Jul 29.
The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, we propose a model in which neuronal tuning for quantity comparisons can arise spontaneously in completely untrained neural circuits. Using a biologically inspired model neural network, we find that single units selective to proportions and differences between visual quantities emerge in randomly initialized feedforward wirings and that they enable the network to perform quantity comparison tasks. Notably, we find that two distinct tunings to proportion and difference originate from a random summation of monotonic, nonlinear neural activities and that a slight difference in the nonlinear response function determines the type of measure. Our results suggest that visual quantity comparisons are primitive types of functions that can emerge spontaneously before learning in young brains.
即使在新生动物中，也能观察到用两种不同的度量标准（比例和差异）来比较视觉对象数量的能力。然而，在没有视觉经验的情况下，这种功能是如何在大脑中产生的，仍然未知。在这里，我们提出了一个模型，在这个模型中，即使在未经训练的神经网络中，神经元对数量比较的调谐也可以自发产生。使用受生物启发的模型神经网络，我们发现，对视觉数量之间的比例和差异有选择性的单个单元会出现在随机初始化的前馈布线中，并且它们使网络能够执行数量比较任务。值得注意的是，我们发现，对比例和差异的两种不同调谐源自单调、非线性神经活动的随机求和，而非线性响应函数的微小差异决定了度量的类型。我们的结果表明，视觉数量比较是原始类型的功能，可以在年轻大脑的学习之前自发产生。
