David Akkurt et al 2009 J. Neural Eng. 6 056004 doi:10.1088/1741-2560/6/5/056004
David Akkurt, Yasemin M Akay and Metin Akay1
Show affiliationsIn this paper, we examined the effect of nicotine exposure and increased body temperature on the complexity (dynamics) of the genioglossus muscle (EMGg) and the diaphragm muscle (EMGdia) to explore the effects of nicotine and hyperthermia. Nonlinear dynamical analysis of the EMGdia and EMGg signals was performed using the approximate entropy method on 15 (7 saline- and 8 nicotine-treated) juvenile rats (P25–P35) and 19 (11 saline- and 8 nicotine-treated) young adult rats (P36–P44). The mean complexity values were calculated over the ten consecutive breaths using the approximate entropy method during mild elevated body temperature (38 °C) and severe elevated body temperature (39–40 °C) in two groups. In the first (nicotine) group, rats were treated with single injections of nicotine enough to produce brain levels of nicotine similar to those achieved in human smokers (2.5 (mg kg−1)/day) until the recording day. In the second (control) group, rats were treated with injections of saline, beginning at postnatal 5 days until the recording day. Our results show that warming the rat by 2–3 °C and nicotine exposure significantly decreased the complexity of the EMGdia and EMGg for the juvenile age group. This reduction in the complexity of the EMGdia and EMGg for the nicotine group was much greater than the normal during elevated body temperatures. We speculate that the generalized depressive effects of nicotine exposure and elevated body temperature on the respiratory neural firing rate and the behavior of the central respiratory network could be responsible for the drastic decrease in the complexity of the EMGdia and EMGg signals, the outputs of the respiratory neural network during early maturation.
87.85.Ng Biological signal processing
87.19.Pp Biothermics and thermal processes in biology
87.19.R- Mechanical and electrical properties of tissues and organs
Issue 5 (October 2009)
Received 19 April 2009, accepted for publication 3 August 2009
Published 27 August 2009
David Akkurt et al 2009 J. Neural Eng. 6 056004
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