Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany.
Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zürich, Switzerland.
Science. 2024 Apr 19;384(6693):338-343. doi: 10.1126/science.adg8828. Epub 2024 Apr 18.
The computational capabilities of neuronal networks are fundamentally constrained by their specific connectivity. Previous studies of cortical connectivity have mostly been carried out in rodents; whether the principles established therein also apply to the evolutionarily expanded human cortex is unclear. We studied network properties within the human temporal cortex using samples obtained from brain surgery. We analyzed multineuron patch-clamp recordings in layer 2-3 pyramidal neurons and identified substantial differences compared with rodents. Reciprocity showed random distribution, synaptic strength was independent from connection probability, and connectivity of the supragranular temporal cortex followed a directed and mostly acyclic graph topology. Application of these principles in neuronal models increased dimensionality of network dynamics, suggesting a critical role for cortical computation.
神经元网络的计算能力从根本上受到其特定连接的限制。皮质连接的先前研究主要在啮齿动物中进行;其中建立的原则是否也适用于进化扩展的人类大脑皮层尚不清楚。我们使用手术获得的脑组织样本研究了人类颞叶皮层中的网络特性。我们分析了 2-3 层锥体神经元的多神经元膜片钳记录,与啮齿动物相比发现了显著差异。相互作用呈随机分布,突触强度与连接概率无关,而颗粒上颞叶皮质的连接遵循有向且大多非循环图拓扑结构。将这些原则应用于神经元模型增加了网络动力学的维数,表明皮质计算具有关键作用。