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Entropy 2014, 16(8), 4677-4692; doi:10.3390/e16084677

Entropy-Complexity Characterization of Brain Development in Chickens

1
IFLYSIB, CONICET & Universidad Nacional de La Plata, La Plata, Argentina
2
Departamento de Física, Facultad de Ciencias Exactas, UNLP Calle 49 y 115. C.C. 67 (1900), La Plata, Argentina
3
Instituto de Física Universidade Federal de Alagoas (UFAL). BR 104 Norte km 97, 57072-970 Maceió, Alagoas, Brazil
4
Instituto Tecnológico Buenos Aires (ITBA), Av Eduardo Madero 399, C1106ACD Ciudad Autónoma de Buenos Aires, Argentina
*
Author to whom correspondence should be addressed.
Received: 21 July 2014 / Accepted: 20 August 2014 / Published: 21 August 2014
(This article belongs to the Special Issue Entropy and Electroencephalography)
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Abstract

Electroencephalography (EEG) reflects the electrical activity of the brain, which can be considered chaotic and ruled by a nonlinear dynamics. Chickens exhibit a protracted period of maturation, and this temporal separation of the synapse formation and maturation phases is analogous to human neural development, though the changes in chickens occur in weeks compared to years in humans. The development of synaptic networks in the chicken brain can be regarded as occurring in two broadly defined phases. We specifically describe the chicken brain development phases in the causality entropy-complexity plane H × C, showing that the complexity of the electrical activity can be characterized by estimating the intrinsic correlational structure of the EEG signal. This allows us to identify the dynamics of the developing chicken brain within the zone of a chaotic dissipative behavior in the plane H × C. View Full-Text
Keywords: EEG signals; statistical complexity measure; chicken brain; neural maturation EEG signals; statistical complexity measure; chicken brain; neural maturation
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Montani, F.; Rosso, O.A. Entropy-Complexity Characterization of Brain Development in Chickens. Entropy 2014, 16, 4677-4692.

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