Detection of M-sequences from spike sequence in neuronal networks

  • Authors:

  • Yoshi Nishitani;Chie Hosokawa;Yuko Mizuno-Matsumoto;Tomomitsu Miyoshi;Hajime Sawai;Shinichi Tamura

  • Affiliations:

  • Graduate School of Medicine, Osaka University, Suita, Osaka, Japan;Health Research Institute, National Institute of Advanced Industrial Scientific and Technology, Ikeda, Osaka, Japan;Graduate School of Applied Informatics, University of Hyogo, Hyogo, Japan;Department of Integrative Physiology, Graduate School of Medicine, Osaka University, Osaka, Japan;Department of Integrative Physiology, Graduate School of Medicine, Osaka University, Osaka, Japan;Graduate School of Medicine, Osaka University, Suita and NBL Technovator Co., Ltd., Sennan, Osaka, Japan

  • Venue:
  • Computational Intelligence and Neuroscience - Special issue on Computational Intelligence in Biomedical Science and Engineering
  • Year:
  • 2012

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Abstract

In circuit theory, it is well known that a linear feedback shift register (LFSR) circuit generates pseudorandom bit sequences (PRBS), including an M-sequence with the maximum period of length. In this study, we tried to detect M-sequences known as a pseudorandom sequence generated by the LFSR circuit from time series patterns of stimulated action potentials. Stimulated action potentials were recorded from dissociated cultures of hippocampal neurons grown on a multielectrode array. We could find several M-sequences from a 3-stage LFSR circuit (M3). These results show the possibility of assembling LFSR circuits or its equivalent ones in a neuronal network. However, since the M3 pattern was composed of only four spike intervals, the possibility of an accidental detection was not zero. Then, we detected M-sequences from random spike sequences which were not generated from an LFSR circuit and compare the result with the number of M-sequences from the originally observed raster data. As a result, a significant difference was confirmed: a greater number of "0-1" reversed the 3-stage M-sequences occurred than would have accidentally be detected. This result suggests that some LFSR equivalent circuits are assembled in neuronal networks.