Kohler Matthias, Bengtsson Fredrik, Stratmann Philipp, Röhrbein Florian, Knoll Alois, Albu-Schäffer Alin, Jörntell Henrik
Technical University of Munich, Department of Informatics, 85748 Garching, Germany.
German Aerospace Center, Institute of Robotics and Mechatronics, 82234 Weβling, Germany.
iScience. 2022 Mar 17;25(4):104083. doi: 10.1016/j.isci.2022.104083. eCollection 2022 Apr 15.
The spinal cord is engaged in all forms of motor performance but its functions are far from understood. Because network connectivity defines function, we explored the connectivity of muscular, tendon, and tactile sensory inputs among a wide population of spinal interneurons in the lower cervical segments. Using low noise intracellular whole cell recordings in the decerebrated, non-anesthetized cat , we could define mono-, di-, and trisynaptic inputs as well as the weights of each input. Whereas each neuron had a highly specific input, and each indirect input could moreover be explained by inputs in other recorded neurons, we unexpectedly also found the input connectivity of the spinal interneuron population to form a continuum. Our data hence contrasts with the currently widespread notion of distinct classes of interneurons. We argue that this suggested diversified physiological connectivity, which likely requires a major component of circuitry learning, implies a more flexible functionality.
脊髓参与各种形式的运动表现，但其功能远未被理解。由于网络连接性决定功能，我们研究了下颈段大量脊髓中间神经元之间肌肉、肌腱和触觉感觉输入的连接性。在去大脑、未麻醉的猫身上使用低噪声细胞内全细胞记录，我们可以定义单突触、双突触和三突触输入以及每个输入的权重。虽然每个神经元都有高度特异性的输入，而且每个间接输入都可以由其他记录的神经元中的输入来解释，但我们意外地还发现脊髓中间神经元群体的输入连接性形成了一个连续体。因此，我们的数据与目前广泛存在的不同类型中间神经元的概念形成对比。我们认为，这种多样化的生理连接性可能需要电路学习的一个主要组成部分，这意味着功能更加灵活。
