Self-regulated complexity in cultured neuronal networks

Eyal Hulata; Itay Baruchi; Ronen Segev; Yoash Shapira; Eshel Ben-Jacob

doi:10.1103/PhysRevLett.92.198105

Self-regulated complexity in cultured neuronal networks

Eyal Hulata, Itay Baruchi, Ronen Segev, Yoash Shapira, Eshel Ben-Jacob

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Abstract

The quantified observables of self-regulated complexity in cultured neuronal networks were studied. The sequence was mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The new observables are utilized to identify self-regulation motifs in observed complex network activity. It is found that for hierarchical sequences, the variance of the VF exhibits a maximum for a specific word length.

Original language	English
Article number	198105
Pages (from-to)	198105-1-198105-4
Journal	Physical Review Letters
Volume	92
Issue number	19
DOIs	https://doi.org/10.1103/PhysRevLett.92.198105
State	Published - 14 May 2004
Externally published	Yes

ASJC Scopus subject areas

General Physics and Astronomy

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10.1103/PhysRevLett.92.198105

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title = "Self-regulated complexity in cultured neuronal networks",

abstract = "The quantified observables of self-regulated complexity in cultured neuronal networks were studied. The sequence was mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The new observables are utilized to identify self-regulation motifs in observed complex network activity. It is found that for hierarchical sequences, the variance of the VF exhibits a maximum for a specific word length.",

author = "Eyal Hulata and Itay Baruchi and Ronen Segev and Yoash Shapira and Eshel Ben-Jacob",

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AU - Shapira, Yoash

AU - Ben-Jacob, Eshel

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Y1 - 2004/5/14

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AB - The quantified observables of self-regulated complexity in cultured neuronal networks were studied. The sequence was mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The new observables are utilized to identify self-regulation motifs in observed complex network activity. It is found that for hierarchical sequences, the variance of the VF exhibits a maximum for a specific word length.

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M3 - Article

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Self-regulated complexity in cultured neuronal networks

Abstract

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