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Self-organization of repetitive spike patterns in developing neuronal networks in vitro

Authors

  • Jyh-Jang Sun,

    1. Institute of Physiology and Pathophysiology, University Medical Center of the Johannes Gutenberg University, Duesbergweg 6, D-55128 Mainz, Germany
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  • Werner Kilb,

    1. Institute of Physiology and Pathophysiology, University Medical Center of the Johannes Gutenberg University, Duesbergweg 6, D-55128 Mainz, Germany
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  • Heiko J. Luhmann

    1. Institute of Physiology and Pathophysiology, University Medical Center of the Johannes Gutenberg University, Duesbergweg 6, D-55128 Mainz, Germany
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Heiko J. Luhmann, as above.
E-mail: luhmann@uni-mainz.de

Abstract

The appearance of spontaneous correlated activity is a fundamental feature of developing neuronal networks in vivo and in vitro. To elucidate whether the ontogeny of correlated activity is paralleled by the appearance of specific spike patterns we used a template-matching algorithm to detect repetitive spike patterns in multi-electrode array recordings from cultures of dissociated mouse neocortical neurons between 6 and 15 days in vitro (div). These experiments demonstrated that the number of spiking neurons increased significantly between 6 and 15 div, while a significantly synchronized network activity appeared at 9 div and became the main discharge pattern in the subsequent div. Repetitive spike patterns with a low complexity were first observed at 8 div. The number of repetitive spike patterns in each dataset as well as their complexity and recurrence increased during development in vitro. The number of links between neurons implicated in repetitive spike patterns, as well as their strength, showed a gradual increase during development. About 8% of the spike sequences contributed to more than one repetitive spike patterns and were classified as core patterns. These results demonstrate for the first time that defined neuronal assemblies, as represented by repetitive spike patterns, appear quite early during development in vitro, around the time synchronized network burst become the dominant network pattern. In summary, these findings suggest that dissociated neurons can self-organize into complex neuronal networks that allow reliable flow and processing of neuronal information already during early phases of development.

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