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Laser ablation of Dbx1 neurons in the pre-Bötzinger complex stops inspiratory rhythm and impairs output in neonatal mice.

Wang X, Hayes JA, Revill AL, Song H, Kottick A, Vann NC, LaMar MD, Picardo MC, Akins VT, Funk GD, Del Negro CA - Elife (2014)

Bottom Line: To understand the neural origins of rhythmic behavior one must characterize the central pattern generator circuit and quantify the population size needed to sustain functionality.Breathing-related interneurons of the brainstem pre-Bötzinger complex (preBötC) that putatively comprise the core respiratory rhythm generator in mammals are derived from Dbx1-expressing precursors.These results demonstrate that a single canonical interneuron class generates respiratory rhythm and contributes in a premotor capacity, whereas these functions are normally attributed to discrete populations.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Science, The College of William and Mary, Williamsburg, United States.

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Numerical simulations of Dbx1 neuron laser ablation experiments.Networks of Dbx1 preBötC neurons parameterized by population size (n) and synaptic connection probability (p). Erdős-Rényi random directed graphs G(n,p) (Newman et al., 2006) determined the underlying connectivity structure. Each node in G(n,p) was populated by a Rubin-Hayes preBötC neuron model (Rubin et al., 2009) with dynamic excitatory synapses for links. Each block in the panels reports a measure of network performance. (A) The grey scale reports the percent of model networks that generated spontaneous rhythmic activity. Asterisks denote networks that generated respiratory-like cycle periods in ≥80% of individual realizations, which were then subjected to simulated laser ablation experiments (results in B and C). (B) The colorimetric scale reports the mean cycle period for 10 (or more) realizations of the network for each (n,p) pair (same as Figure 6A and panel C). Networks with asterisks (from Figure 6A and this figure's panel A) were subject to laser ablations in random sequence; the numbers in the blocks report the average final cycle period (in s) prior to rhythm cessation in the lesioned network at each (n,p) pair. (C) The numbers in the blocks report the average cell ablation tally at the point of rhythm cessation for five or more laser ablation simulations.DOI:http://dx.doi.org/10.7554/eLife.03427.014
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fig6s1: Numerical simulations of Dbx1 neuron laser ablation experiments.Networks of Dbx1 preBötC neurons parameterized by population size (n) and synaptic connection probability (p). Erdős-Rényi random directed graphs G(n,p) (Newman et al., 2006) determined the underlying connectivity structure. Each node in G(n,p) was populated by a Rubin-Hayes preBötC neuron model (Rubin et al., 2009) with dynamic excitatory synapses for links. Each block in the panels reports a measure of network performance. (A) The grey scale reports the percent of model networks that generated spontaneous rhythmic activity. Asterisks denote networks that generated respiratory-like cycle periods in ≥80% of individual realizations, which were then subjected to simulated laser ablation experiments (results in B and C). (B) The colorimetric scale reports the mean cycle period for 10 (or more) realizations of the network for each (n,p) pair (same as Figure 6A and panel C). Networks with asterisks (from Figure 6A and this figure's panel A) were subject to laser ablations in random sequence; the numbers in the blocks report the average final cycle period (in s) prior to rhythm cessation in the lesioned network at each (n,p) pair. (C) The numbers in the blocks report the average cell ablation tally at the point of rhythm cessation for five or more laser ablation simulations.DOI:http://dx.doi.org/10.7554/eLife.03427.014

Mentions: We used graph theory and simulations to investigate how Dbx1 neuron ablations affect preBötC structure and function. The Rubin–Hayes preBötC neuron model (Rubin et al., 2009) was assembled in Erdős-Rényi G(n,p) graphs (Newman et al., 2006) with population sizes n from 200–400 and connection probabilities p from 0.1 to 0.2. These parameter ranges encompass n = 325, an empirical estimate of the number of excitatory neurons in the perinatal mouse preBötC (Hayes et al., 2012) as well as p=0.13, the only experimentally determined connection probability among putatively rhythmogenic preBötC neurons in acute mouse slices (Rekling et al., 2000). Networks within the above n–p parameter range that generated respiratory-like cycle periods of ∼4 s are shown with asterisks in Figure 6A and Figure 6—figure supplement 1A. This set of model networks also generated network-wide bursts within 200–300 ms following brief focal glutamatergic stimulation of five or more constituent neurons (Figure 6B) in agreement with focal glutamate un-caging experiments in neonatal mouse slices, which showed that simultaneous stimulation of 4–9 preBötC neurons can trigger inspiratory bursts with similar latency (Kam et al., 2013b). These results substantiate that the model networks well represent the neonatal mouse preBötC in vitro.10.7554/eLife.03427.013Figure 6.Numerical simulations.


Laser ablation of Dbx1 neurons in the pre-Bötzinger complex stops inspiratory rhythm and impairs output in neonatal mice.

Wang X, Hayes JA, Revill AL, Song H, Kottick A, Vann NC, LaMar MD, Picardo MC, Akins VT, Funk GD, Del Negro CA - Elife (2014)

Numerical simulations of Dbx1 neuron laser ablation experiments.Networks of Dbx1 preBötC neurons parameterized by population size (n) and synaptic connection probability (p). Erdős-Rényi random directed graphs G(n,p) (Newman et al., 2006) determined the underlying connectivity structure. Each node in G(n,p) was populated by a Rubin-Hayes preBötC neuron model (Rubin et al., 2009) with dynamic excitatory synapses for links. Each block in the panels reports a measure of network performance. (A) The grey scale reports the percent of model networks that generated spontaneous rhythmic activity. Asterisks denote networks that generated respiratory-like cycle periods in ≥80% of individual realizations, which were then subjected to simulated laser ablation experiments (results in B and C). (B) The colorimetric scale reports the mean cycle period for 10 (or more) realizations of the network for each (n,p) pair (same as Figure 6A and panel C). Networks with asterisks (from Figure 6A and this figure's panel A) were subject to laser ablations in random sequence; the numbers in the blocks report the average final cycle period (in s) prior to rhythm cessation in the lesioned network at each (n,p) pair. (C) The numbers in the blocks report the average cell ablation tally at the point of rhythm cessation for five or more laser ablation simulations.DOI:http://dx.doi.org/10.7554/eLife.03427.014
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4129438&req=5

fig6s1: Numerical simulations of Dbx1 neuron laser ablation experiments.Networks of Dbx1 preBötC neurons parameterized by population size (n) and synaptic connection probability (p). Erdős-Rényi random directed graphs G(n,p) (Newman et al., 2006) determined the underlying connectivity structure. Each node in G(n,p) was populated by a Rubin-Hayes preBötC neuron model (Rubin et al., 2009) with dynamic excitatory synapses for links. Each block in the panels reports a measure of network performance. (A) The grey scale reports the percent of model networks that generated spontaneous rhythmic activity. Asterisks denote networks that generated respiratory-like cycle periods in ≥80% of individual realizations, which were then subjected to simulated laser ablation experiments (results in B and C). (B) The colorimetric scale reports the mean cycle period for 10 (or more) realizations of the network for each (n,p) pair (same as Figure 6A and panel C). Networks with asterisks (from Figure 6A and this figure's panel A) were subject to laser ablations in random sequence; the numbers in the blocks report the average final cycle period (in s) prior to rhythm cessation in the lesioned network at each (n,p) pair. (C) The numbers in the blocks report the average cell ablation tally at the point of rhythm cessation for five or more laser ablation simulations.DOI:http://dx.doi.org/10.7554/eLife.03427.014
Mentions: We used graph theory and simulations to investigate how Dbx1 neuron ablations affect preBötC structure and function. The Rubin–Hayes preBötC neuron model (Rubin et al., 2009) was assembled in Erdős-Rényi G(n,p) graphs (Newman et al., 2006) with population sizes n from 200–400 and connection probabilities p from 0.1 to 0.2. These parameter ranges encompass n = 325, an empirical estimate of the number of excitatory neurons in the perinatal mouse preBötC (Hayes et al., 2012) as well as p=0.13, the only experimentally determined connection probability among putatively rhythmogenic preBötC neurons in acute mouse slices (Rekling et al., 2000). Networks within the above n–p parameter range that generated respiratory-like cycle periods of ∼4 s are shown with asterisks in Figure 6A and Figure 6—figure supplement 1A. This set of model networks also generated network-wide bursts within 200–300 ms following brief focal glutamatergic stimulation of five or more constituent neurons (Figure 6B) in agreement with focal glutamate un-caging experiments in neonatal mouse slices, which showed that simultaneous stimulation of 4–9 preBötC neurons can trigger inspiratory bursts with similar latency (Kam et al., 2013b). These results substantiate that the model networks well represent the neonatal mouse preBötC in vitro.10.7554/eLife.03427.013Figure 6.Numerical simulations.

Bottom Line: To understand the neural origins of rhythmic behavior one must characterize the central pattern generator circuit and quantify the population size needed to sustain functionality.Breathing-related interneurons of the brainstem pre-Bötzinger complex (preBötC) that putatively comprise the core respiratory rhythm generator in mammals are derived from Dbx1-expressing precursors.These results demonstrate that a single canonical interneuron class generates respiratory rhythm and contributes in a premotor capacity, whereas these functions are normally attributed to discrete populations.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Science, The College of William and Mary, Williamsburg, United States.

Show MeSH
Related in: MedlinePlus