Imaging input and output of neocortical networks in vivo

被引:353
作者
Kerr, JND [1 ]
Greenberg, D [1 ]
Helmchen, F [1 ]
机构
[1] Max Planck Inst Med Res, Dept Cell Physiol, D-69120 Heidelberg, Germany
关键词
bulk loading; population imaging; presynaptic; sparse coding;
D O I
10.1073/pnas.0506029102
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Neural activity manifests itself as complex spatiotemporal activation patterns in cell populations. Even for local neural circuits, a comprehensive description of network activity has been impossible so far. Here we demonstrate that two-photon calcium imaging of bulk-labeled tissue permits dissection of local input and output activities in rat neocortex in vivo. Besides astroglial and neuronal calcium transients, we found spontaneous calcium signals in the neuropil that were tightly correlated to the electrocorticogram. This optical encephalogram (OEG) is shown to represent bulk calcium signals in axonal structures, thus providing a measure of local input activity. Simultaneously, output activity in local neuronal populations could be derived from action potential-evoked calcium transients with single-spike resolution. By using these OEG and spike activity measures, we characterized spontaneous activity during cortical Up states. We found that (i) spiking activity is sparse (< 0.1 Hz); (it) on average, only approximate to 10% of neurons are active during each Up state; (iii) this active subpopulation constantly changes with time; and (iv) spiking activity across the population is evenly distributed throughout the Up-state duration. Furthermore, the number of active neurons directly depended on the amplitude of the OEG, thus optically revealing an input-output function for the local network. We conclude that spontaneous activity in the neocortex is sparse and heterogeneously distributed in space and time across the neuronal population. The dissection of the various signal components in bulk-loaded tissue as demonstrated here will enable further studies of signal flow through cortical networks.
引用
收藏
页码:14063 / 14068
页数:6
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