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Sparse coding and high-order correlations in fine-scale cortical networks


Connectivity in the cortex is organized at multiple scales1,2,3,4,5, suggesting that scale-dependent correlated activity is particularly important for understanding the behaviour of sensory cortices and their function in stimulus encoding. We analysed the scale-dependent structure of cortical interactions by using maximum entropy models6,7,8,9 to characterize multiple-tetrode recordings from primary visual cortex of anaesthetized macaque monkeys (Macaca mulatta). We compared the properties of firing patterns among local clusters of neurons (<300 μm apart) with those of neurons separated by larger distances (600–2,500 μm). Here we report that local firing patterns are distinctive: whereas multi-neuronal firing patterns at larger distances can be predicted by pairwise interactions, patterns within local clusters often show evidence of high-order correlations. Surprisingly, these local correlations are flexible and rapidly reorganized by visual input. Although they modestly reduce the amount of information that a cluster conveys, they also modify the format of this information, creating sparser codes by increasing the periods of total quiescence, and concentrating information into briefer periods of common activity. These results imply a hierarchical organization of neuronal correlations: simple pairwise correlations link neurons over scales of tens to hundreds of minicolumns, but on the scale of a few minicolumns, ensembles of neurons form complex subnetworks whose moment-to-moment effective connectivity is dynamically reorganized by the stimulus.

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Figure 1: Analysis of multi-tetrode recordings.
Figure 2: A pairwise maximum entropy model frequently fails for local networks of neurons.
Figure 3: High-order stimulus dependent correlations in multi-neuron firing patterns.
Figure 4: Effect of correlations on stimulus encoding.


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We thank S. Nirenberg for comments on a draft of the manuscript. This work was supported by National Institutes of Health grants EY19454 and GM07739 (to I.E.O.) and EY09314 (to J.D.V.).

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Authors and Affiliations



I.E.O. conceived the project and carried out the data analysis. I.E.O. and J.D.V. wrote the manuscript. J.D.V. supervised the project. I.E.O., F.M., K.P.P., A.M.S., Q.H. and J.D.V. collected experimental data. F.M., K.P.P. and A.M.S. provided feedback on the manuscript.

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Correspondence to Ifije E. Ohiorhenuan.

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The authors declare no competing financial interests.

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Ohiorhenuan, I., Mechler, F., Purpura, K. et al. Sparse coding and high-order correlations in fine-scale cortical networks. Nature 466, 617–621 (2010).

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