Developmental Changes in Inspiratory Network Complexity and Burst Timing in Rat In Vivo

Hui Jing Yu1, 2, Xinnian Chen1, 2, and Irene C. Solomon2

1Department of Biomedical Engineering, State University of New York-Stony Brook, Stony Brook, NY11794

2Department of Physiology and Biophysics, State University of New York-Stony Brook, Stony Brook, NY11794

Abstract–Developmental changes in intrinsic membrane properties and synaptic transmission are present within the central respiratory neural network. The influence of maturation on the complex dynamics (i.e., complexity) underlying the central respiratory neural network as well as burst timing, however, remain to be examined. Therefore, we calculated the approximate entropy (ApEn; as an index of network complexity) of inspiratory motor discharges recorded from the diaphragm in spontaneously breathing urethane-anesthetized neonatal rats. Our findings demonstrate that changes in central inspiratory neural network complexity and burst timing occur with maturation, such that in the older neonatal rats, the neural controller exhibits higher ApEn (i.e., less system order) and longer inspiratory bursts. We suggest that these changes not only reflect the developmental reconfiguration of the central respiratory network but also provide quantitative insight into the extent of reconfiguration.

I. INTRODUCTION Numerous studies have examined maturational

changes in the expression levels of various neurotransmitter/neuromodulatory systems and neurotrophic factors involved in central respiratory control. Ongoing studies are focused on identifying developmentally regulated differences in the mechanisms of respiratory rhythm generation, pattern formation and chemoreception. The influence of these maturational changes on the complex dynamics of the central respiratory controller requires clarification. Since the complexity of a signal can be quantified using approximate entropy (ApEn), a statistical index that measures the regularity in a time series [1,2], we calculated the ApEn of inspiratory motor discharges recorded from neonatal rats. We reasoned that during

maturation, a greater degree of network interactions (both intrinsic and synaptically-mediated) would be established, and the inspiratory neural network would exhibit age-dependent increasing values of ApEn. Further, the enhanced complexity of this network would result in an increase in inspiratory (i.e., timing) activity.

II. MATERIALS AND METHODS Diaphragm electromyogram (EMG) activity was

recorded from spontaneously breathing urethane-anesthetized neonatal rats, postnatal (P) day 1-22; at least 50 inspiratory bursts were recorded from each. Signals were notch filtered at 60 Hz, band-pass filtered (0.01-1 KHz), and digitized (sampling rate 2 KHz) for off-line analysis. Data were segmented to lengths corresponding to the inspiratory burst, digitally band-pass filtered (10-50 Hz, 6-pole Butterworth), and re-sampled at 1 KHz. Inspiratory burst data were evaluated for temporal characteristics, and ApEn was calculated as follows [1]:

)()(),,(ApEn 1 rrNrm mm +Φ−Φ=

∑+−

=

−+−=Φ1

1

1 )(ln)1()( wheremN

i

mi

m rCmNr

)1/()()( and +−= mNiNrC mmi

rjXiXdiN m ≤= )](),([ of no.)( , where m is the embedding dimension, r is the tolerance level. X(i), X(j) are vectors defined by X(i) = [u(i), u(i +

1), ...,u(i + m – 1)] and X(j) = [u(j), u(j + 1), ..., u(j + m – 1)] from the original time series u(1), u(2), ..., u(N).

For these analyses, m = 2 and r = 0.25×SD (see [2]), and values for m were confirmed using Mutual Information and False Nearest Neighbor analyses. Animals were grouped into 4 age categories: P1-P5 (n=11), P6-P10 (n=14), P11-P15 (n=13), and P16-P22 (n=19). Data are reported as mean±SE, and the coefficient of variation (CV) was computed as an index

3131-4244-1033-9/07/$25.00 © 2007 IEEE.

of variability. Statistical analysis included one-way ANOVA, followed by Holm-Sidak post hoc analyses for multiple comparisons.

III. RESULTS AND DISCUSSION Previous work from our laboratory has shown that the inspiratory network of neonatal (P1-P5) preparations both in vivo and in vitro is more regular or predictable than that of adult preparations [3]. In the current investigation, analysis of the diaphragm EMG activity recorded from the in vivo neonatal rat preparation revealed differences in the timing and complexity of the inspiratory bursts with maturation. For the ages studied, younger neonatal rats exhibited shorter burst durations (TI) and longer expiratory pauses (TE) than those of older neonatal rats; these differences in timing resulted in higher burst frequencies as the rats matured (Fig. 1A). In addition, younger neonatal rats exhibited lower ApEn values (Fig. 1C). Linear regression analyses revealed a significant relationship between both TI and age (R2=0.74, P<0.001) and ApEn and age (R2=0.52, P<0.001). To further characterize the effects of maturation on inspiratory burst timing and complexity, the rats were grouped into 4 age categories. Based on these groupings, TI significantly increased as a function of age (P<0.001); however, TI values for the two youngest age groups were similar (Fig. 1B). With respect to inspiratory network complexity, ApEn values were significantly lower in the youngest age group as compared to all other groups (ApEn = 0.310±0.017, 0.351±0.010, 0.379±0.010, and 0.396±0.008 for increasing age groups, respectively; P<0.001); ApEn values were also significantly lower in the P6-P10 age group as compared to the P16-P22 age group (Fig. 1D). The highest degree of variability (i.e., greater CV) in both TI and ApEn were seen in the youngest age group (for TI, CV=30.5% vs. 9.8-11.4% in the remaining groups; for ApEn, CV=18.4% vs. 8.3-10.1% in the remaining groups).

Fig. 1. Effect of maturation on TI and ApEn underlying diaphragm EMG bursts. Data provided show 50-burst average for TI (A) and ApEn (C). Summary data showing group averages (mean±SE) for TI (B) and for ApEn (D). *P<0.001 for comparisons indicated; NS, not significant.

IV. CONCLUSIONS Our findings demonstrate (1) that ApEn and TI both

increase with maturation, (2) a significant relationship between ApEn and age as well as TI and age is observed, and (3) a greater degree of variability in both ApEn and TI is present in the youngest age group. These findings suggest that changes in central inspiratory neural network complexity and burst timing occur with maturation: in older neonatal rats, the inspiratory controller exhibits higher ApEn and longer inspiratory bursts. We suggest these changes not only reflect the developmental reconfiguration of the central respiratory network but also provide quantitative insight into the extent of reconfiguration.

ACKNOWLEDGMENT This work was supported by NIH grants NS045321 and

NS049310.

REFERENCES [1] S.M. Pincus. “Approximate entropy as a measure of

system complexity.” Proc. Natl. Acad. Sci. 88:2297-2301, 1991.

[2] S.M. Pincus, and A.L. Goldberger. “Physiological time-series analysis: what does regularity quantify?” Am. J. Physiol. 266:H1643-H1656, 1994.

[3] H.J. Yu, X. Chen, R.M. Foglyano, C.G. Wilson, and I.C. Solomon. “Respiratory network complexity in neonatal rat in vivo and in vitro.” Adv. Exp. Biol. Med. In Press.

314