Nieder Andreas, Merten Katharina
Department of Cognitive Neurology, Primate Neurocognition Laboratory, Hertie-Institute for Clinical Brain Research, University of Tuebingen, 72076 Tübingen, Germany.
J Neurosci. 2007 May 30;27(22):5986-93. doi: 10.1523/JNEUROSCI.1056-07.2007.
How single neurons represent information about the magnitude of a stimulus remains controversial. Neurons encoding purely sensory magnitude typically show monotonic response functions ("summation coding"), and summation units are usually implemented in models of numerosity representation. In contrast, cells representing numerical quantity exhibit nonmonotonic tuning functions that peak at their preferred numerosity ("labeled-line code"), but the restricted range of tested quantities in these studies did not permit a definite answer. Here, we analyzed both behavioral and neuronal representations of a broad range of numerosities from 1 to 30 in the prefrontal cortex of monkeys. Numerosity-selective neurons showed a clear and behaviorally relevant labeled-line code for all numerosities. Moreover, both the behavioral and neuronal tuning functions obeyed the Weber-Fechner Law and were best represented on a nonlinearly compressed scale. Our single-cell study is in good agreement with functional imaging data reporting peaked tuning functions in humans, demonstrating neuronal precursors for human number competence in a nonhuman primate. Our findings also emphasize that the manner in which neurons encode and maintain magnitude information may depend on the precise task at hand as well as the type of magnitude to represent and memorize.
单个神经元如何表征刺激强度的信息仍存在争议。编码纯感觉强度的神经元通常表现出单调响应函数（“求和编码”），并且求和单元通常在数量表征模型中实现。相比之下，表征数值量的细胞表现出非单调调谐函数，在其偏好的数量处达到峰值（“标记线编码”），但这些研究中测试数量的范围有限，无法给出明确答案。在这里，我们分析了猴子前额叶皮层中从1到30的广泛数量的行为和神经元表征。数量选择性神经元对所有数量都表现出清晰且与行为相关的标记线编码。此外，行为和神经元调谐函数都遵循韦伯-费希纳定律，并且在非线性压缩尺度上表现最佳。我们的单细胞研究与报告人类调谐函数峰值的功能成像数据高度一致，证明了非人类灵长类动物中人类数字能力的神经元前体。我们的发现还强调，神经元编码和维持强度信息的方式可能取决于手头的精确任务以及要表征和记忆的强度类型。
