Department of Epileptology, University of Bonn Medical Center, Sigmund-Freud-Str. 25, 53105 Bonn, Germany; Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, 72076 Tübingen, Germany.
Department of Neurosurgery, University of Bonn Medical Center, Sigmund-Freud-Str. 25, 53105 Bonn, Germany.
Neuron. 2018 Nov 7;100(3):753-761.e4. doi: 10.1016/j.neuron.2018.08.036. Epub 2018 Sep 20.
Our human-specific symbolic number skills that underpin science and technology spring from nonsymbolic set size representations. Despite the significance of numerical competence, its single-neuron mechanisms in the human brain are unknown. We therefore recorded from single neurons in the medial temporal lobe of neurosurgical patients that performed a calculation task. We found that distinct groups of neurons represented either nonsymbolic or symbolic number, but not both number formats simultaneously. Numerical information could be decoded robustly from the population of neurons tuned to nonsymbolic number and with lower accuracy also from the population of neurons selective to number symbols. The tuning characteristics of selective neurons may explain why set size is represented only approximately in behavior, whereas number symbols allow exact assessments of numerical values. Our results suggest number neurons as neuronal basis of human number representations that ultimately give rise to number theory and mathematics.
我们人类特有的、支撑科学技术的象征性数字技能源于非象征性集合大小的表示。尽管数字能力意义重大，但它在人类大脑中的单个神经元机制尚不清楚。因此，我们记录了在执行计算任务的神经外科患者的内侧颞叶中的单个神经元。我们发现，不同的神经元群体代表非象征性或象征性的数字，但不能同时代表两种数字格式。可以从对非符号数字敏感的神经元群体中，以及从对数字符号敏感的神经元群体中，以较低的准确性，对数值信息进行稳健解码。选择性神经元的调谐特性可以解释为什么集合大小仅在行为中被近似表示，而数字符号则可以对数值进行精确评估。我们的结果表明，神经元作为人类数字表示的神经元基础，最终产生了数论和数学。
