Institute of Neurology, University College London, London WC1N 3BG, UK.
Institute of Ophthalmology, University College London, London EC1V 9EL, UK.
Neuron. 2018 May 2;98(3):602-615.e8. doi: 10.1016/j.neuron.2018.03.037. Epub 2018 Apr 12.
Cortical computation arises from the interaction of multiple neuronal types, including pyramidal (Pyr) cells and interneurons expressing Sst, Vip, or Pvalb. To study the circuit underlying such interactions, we imaged these four types of cells in mouse primary visual cortex (V1). Our recordings in darkness were consistent with a "disinhibitory" model in which locomotion activates Vip cells, thus inhibiting Sst cells and disinhibiting Pyr cells. However, the disinhibitory model failed when visual stimuli were present: locomotion increased Sst cell responses to large stimuli and Vip cell responses to small stimuli. A recurrent network model successfully predicted each cell type's activity from the measured activity of other types. Capturing the effects of locomotion, however, required allowing it to increase feedforward synaptic weights and modulate recurrent weights. This network model summarizes interneuron interactions and suggests that locomotion may alter cortical computation by changing effective synaptic connectivity.
皮层计算源于多种神经元类型的相互作用,包括表达 Sst、Vip 或 Pvalb 的锥体 (Pyr) 细胞和中间神经元。为了研究这种相互作用的基础回路,我们在小鼠初级视觉皮层 (V1) 中对这四种类型的细胞进行了成像。我们在黑暗中的记录与“去抑制”模型一致,即运动激活 Vip 细胞,从而抑制 Sst 细胞并去抑制 Pyr 细胞。然而,当存在视觉刺激时,去抑制模型失败了:运动增加了 Sst 细胞对大刺激的反应和 Vip 细胞对小刺激的反应。一个递归网络模型成功地从其他类型的测量活动预测了每个细胞类型的活动。然而,要捕获运动的影响,需要允许它增加前馈突触权重并调节递归权重。该网络模型总结了中间神经元的相互作用,并表明运动可能通过改变有效突触连接来改变皮层计算。