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Proc Natl Acad Sci U S A. 2018 Jul 3;115(27):E6329-E6338. doi: 10.1073/pnas.1720995115. Epub 2018 Jun 22.

Sparse bursts optimize information transmission in a multiplexed neural code.

Author information

University of Ottawa Brain and Mind Research Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada;
Department of Physics, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany.
Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, 10587 Berlin, Germany.


Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.


cerebral cortex; dendritic computation; multiplexing; neural coding; short-term plasticity

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