Periodicity, mixed-mode oscillations, and quasiperiodicity in a rhythm-generating neural network

We studied patterns of oscillatory neural activity in the network that generates respiratory rhythm in mammals. When isolated in vitro, this network spontaneously generates an inspiratory-related motor rhythm, with stable amplitude from cycle to cycle. We show that progressively elevating neuronal e...

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Bibliographic Details
Published in:Biophysical journal 2002-01, Vol.82 (1 Pt 1), p.206-214
Main Authors: Del Negro, Christopher A, Wilson, Christopher G, Butera, Robert J, Rigatto, Henrique, Smith, Jeffrey C
Format: Article
Language:English
Subjects:
Animals
Animals, Newborn
Biochemistry
Brain Stem - physiology
Cellular biology
Electromyography
In Vitro Techniques
Inhalation - physiology
Mammals
Medulla Oblongata - physiology
Models, Neurological
Nerve Net - physiology
Neurons
Neurophysiology
Periodicity
Rats
Respiratory Mechanics - physiology
Respiratory system
Vagotomy
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Summary:We studied patterns of oscillatory neural activity in the network that generates respiratory rhythm in mammals. When isolated in vitro, this network spontaneously generates an inspiratory-related motor rhythm, with stable amplitude from cycle to cycle. We show that progressively elevating neuronal excitability in vitro causes periodic modulation of this inspiratory rhythm, evoking (in order): mixed-mode oscillations, quasiperiodicity, and ultimately disorganized aperiodic activity. Thus, the respiratory network oscillator follows a well defined sequence of behavioral states characterized by dynamical systems theory, which includes discrete stages of periodic and quasiperiodic amplitude modulation and progresses (according to theory) to aperiodic chaos-like behavior. We also observed periodic, mixed-mode periodic, and quasiperiodic breathing patterns in neonatal rodents and human infants in vivo, suggesting that breathing patterns generated by the intact nervous system reflect deterministic neural activity patterns in the underlying rhythm-generating network.
ISSN:0006-3495
1542-0086
DOI:10.1016/S0006-3495(02)75387-3