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Mechanisms Leading to Rhythm Cessation in the Respiratory PreBötzinger Complex Due to Piecewise Cumulative Neuronal Deletions(1,2,3).

Song H, Hayes JA, Vann NC, Drew LaMar M, Del Negro CA - eNeuro (2015)

Bottom Line: When the recruitment rate drops below 1 neuron/ms the network stops spontaneous rhythmic activity.Neurons that play pre-eminent roles in rhythmogenesis include those that commence spiking during the quiescent phase between respiratory bursts and those with a high number of incoming synapses, which both play key roles in recruitment, i.e., recurrent excitation leading to network bursts.This study provides a theoretical framework for the operating mechanism of mammalian central pattern generator networks and their susceptibility to loss-of-function in the case of disease or neurodegeneration.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Applied Science, The College of William & Mary , Williamsburg, Virginia 23187-8795.

ABSTRACT
The mammalian breathing rhythm putatively originates from Dbx1-derived interneurons in the preBötzinger complex (preBötC) of the ventral medulla. Cumulative deletion of ∼15% of Dbx1 preBötC neurons in an in vitro breathing model stops rhythmic bursts of respiratory-related motor output. Here we assemble in silico models of preBötC networks using random graphs for structure, and ordinary differential equations for dynamics, to examine the mechanisms responsible for the loss of spontaneous respiratory rhythm and motor output measured experimentally in vitro. Model networks subjected to cellular ablations similarly discontinue functionality. However, our analyses indicate that model preBötC networks remain topologically intact even after rhythm cessation, suggesting that dynamics coupled with structural properties of the underlying network are responsible for rhythm cessation. Simulations show that cumulative cellular ablations diminish the number of neurons that can be recruited to spike per unit time. When the recruitment rate drops below 1 neuron/ms the network stops spontaneous rhythmic activity. Neurons that play pre-eminent roles in rhythmogenesis include those that commence spiking during the quiescent phase between respiratory bursts and those with a high number of incoming synapses, which both play key roles in recruitment, i.e., recurrent excitation leading to network bursts. Selectively ablating neurons with many incoming synapses impairs recurrent excitation and stops spontaneous rhythmic activity and motor output with lower ablation tallies compared with random deletions. This study provides a theoretical framework for the operating mechanism of mammalian central pattern generator networks and their susceptibility to loss-of-function in the case of disease or neurodegeneration.

No MeSH data available.


Active subnetwork properties for a sequence of inspiratory-like bursts given different ICAN thresholds. A, Active subnetwork size (number of neurons) for five representative ICAN thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. Color represents different threshold values. Arrows indicate deletions 0, 4, 10, and 20. B, Active subnetwork size (number of neurons) for five representative INa-P thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. C, Active subnetwork size (number of neurons) for five representative Isyn thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. D, Active subnetwork size (number of neurons) for five representative s thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation.
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Figure 4: Active subnetwork properties for a sequence of inspiratory-like bursts given different ICAN thresholds. A, Active subnetwork size (number of neurons) for five representative ICAN thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. Color represents different threshold values. Arrows indicate deletions 0, 4, 10, and 20. B, Active subnetwork size (number of neurons) for five representative INa-P thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. C, Active subnetwork size (number of neurons) for five representative Isyn thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. D, Active subnetwork size (number of neurons) for five representative s thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation.

Mentions: ICAN was formulated as a synaptically triggered inward current based on experimental evidence (Crowder et al., 2007; Pace et al., 2007b; Mironov, 2008, 2013; Pace and Del Negro, 2008; Rubin et al., 2009; Mironov and Skorova, 2011). Its activation depends proximally on cytosolic Ca2+, which rises because of synaptic drive from presynaptic partners. Once activated, ICAN generates postsynaptic bursts. Therefore ICAN is a cellular parameter whose magnitude depends both on the number of presynaptic partners and their activity (topology and dynamics). Taking the average value of ICAN for each neuron over an analytic time window centered at the peak of each inspiratory burst (see Materials and Methods for full definition), we generated a time series of active subnetwork snapshots spanning the simulation. All the constituent neurons whose average ICAN exceeded some threshold value comprised the active subnetwork. Figure 4A plots the size of the ICAN active subnetwork for five different thresholds (−2, −3, −3.5, −4, and −5 pA) during the course of one representative simulation. Note, ICAN may transiently exceed 9 nA, but its average over the entire analytic window is much lower, thus threshold is 1000-fold less than peak ICAN. Cumulative cell ablation caused the ICAN active subnetwork size to fluctuate and progressively diminish until the rhythm stopped. ICAN active subnetwork size often locked onto a particular value, and remained there despite ongoing cellular ablations, then fluctuated between levels, before finally locking onto a new smaller size. Although not illustrated in Figure 4, each decrement of the ICAN active subnetwork size was accompanied by a corresponding decrease in burst frequency (further explained below and in Fig. 5).


Mechanisms Leading to Rhythm Cessation in the Respiratory PreBötzinger Complex Due to Piecewise Cumulative Neuronal Deletions(1,2,3).

Song H, Hayes JA, Vann NC, Drew LaMar M, Del Negro CA - eNeuro (2015)

Active subnetwork properties for a sequence of inspiratory-like bursts given different ICAN thresholds. A, Active subnetwork size (number of neurons) for five representative ICAN thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. Color represents different threshold values. Arrows indicate deletions 0, 4, 10, and 20. B, Active subnetwork size (number of neurons) for five representative INa-P thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. C, Active subnetwork size (number of neurons) for five representative Isyn thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. D, Active subnetwork size (number of neurons) for five representative s thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4596029&req=5

Figure 4: Active subnetwork properties for a sequence of inspiratory-like bursts given different ICAN thresholds. A, Active subnetwork size (number of neurons) for five representative ICAN thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. Color represents different threshold values. Arrows indicate deletions 0, 4, 10, and 20. B, Active subnetwork size (number of neurons) for five representative INa-P thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. C, Active subnetwork size (number of neurons) for five representative Isyn thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation. D, Active subnetwork size (number of neurons) for five representative s thresholds (indicated above each trace) plotted versus sequential burst indices (1–213) for one simulation.
Mentions: ICAN was formulated as a synaptically triggered inward current based on experimental evidence (Crowder et al., 2007; Pace et al., 2007b; Mironov, 2008, 2013; Pace and Del Negro, 2008; Rubin et al., 2009; Mironov and Skorova, 2011). Its activation depends proximally on cytosolic Ca2+, which rises because of synaptic drive from presynaptic partners. Once activated, ICAN generates postsynaptic bursts. Therefore ICAN is a cellular parameter whose magnitude depends both on the number of presynaptic partners and their activity (topology and dynamics). Taking the average value of ICAN for each neuron over an analytic time window centered at the peak of each inspiratory burst (see Materials and Methods for full definition), we generated a time series of active subnetwork snapshots spanning the simulation. All the constituent neurons whose average ICAN exceeded some threshold value comprised the active subnetwork. Figure 4A plots the size of the ICAN active subnetwork for five different thresholds (−2, −3, −3.5, −4, and −5 pA) during the course of one representative simulation. Note, ICAN may transiently exceed 9 nA, but its average over the entire analytic window is much lower, thus threshold is 1000-fold less than peak ICAN. Cumulative cell ablation caused the ICAN active subnetwork size to fluctuate and progressively diminish until the rhythm stopped. ICAN active subnetwork size often locked onto a particular value, and remained there despite ongoing cellular ablations, then fluctuated between levels, before finally locking onto a new smaller size. Although not illustrated in Figure 4, each decrement of the ICAN active subnetwork size was accompanied by a corresponding decrease in burst frequency (further explained below and in Fig. 5).

Bottom Line: When the recruitment rate drops below 1 neuron/ms the network stops spontaneous rhythmic activity.Neurons that play pre-eminent roles in rhythmogenesis include those that commence spiking during the quiescent phase between respiratory bursts and those with a high number of incoming synapses, which both play key roles in recruitment, i.e., recurrent excitation leading to network bursts.This study provides a theoretical framework for the operating mechanism of mammalian central pattern generator networks and their susceptibility to loss-of-function in the case of disease or neurodegeneration.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Applied Science, The College of William & Mary , Williamsburg, Virginia 23187-8795.

ABSTRACT
The mammalian breathing rhythm putatively originates from Dbx1-derived interneurons in the preBötzinger complex (preBötC) of the ventral medulla. Cumulative deletion of ∼15% of Dbx1 preBötC neurons in an in vitro breathing model stops rhythmic bursts of respiratory-related motor output. Here we assemble in silico models of preBötC networks using random graphs for structure, and ordinary differential equations for dynamics, to examine the mechanisms responsible for the loss of spontaneous respiratory rhythm and motor output measured experimentally in vitro. Model networks subjected to cellular ablations similarly discontinue functionality. However, our analyses indicate that model preBötC networks remain topologically intact even after rhythm cessation, suggesting that dynamics coupled with structural properties of the underlying network are responsible for rhythm cessation. Simulations show that cumulative cellular ablations diminish the number of neurons that can be recruited to spike per unit time. When the recruitment rate drops below 1 neuron/ms the network stops spontaneous rhythmic activity. Neurons that play pre-eminent roles in rhythmogenesis include those that commence spiking during the quiescent phase between respiratory bursts and those with a high number of incoming synapses, which both play key roles in recruitment, i.e., recurrent excitation leading to network bursts. Selectively ablating neurons with many incoming synapses impairs recurrent excitation and stops spontaneous rhythmic activity and motor output with lower ablation tallies compared with random deletions. This study provides a theoretical framework for the operating mechanism of mammalian central pattern generator networks and their susceptibility to loss-of-function in the case of disease or neurodegeneration.

No MeSH data available.