Table 4.
Connectivity for the network model
| Conduction Times |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Source Population | Target Population | Synaptic Type | Min | Max | Number of Terminals | Synaptic Strength | Source Population, n | Target Population, n | Divergence | Mean Number of Terminals | Convergence |
| E-Dec P‡ | E-Aug-late (#2) | Inh_1 | 2 | 4 | 150 | 0.02 | 300 | 600 | 132.51 ± 3.36 | 1.13 | 66.26 ± 7.63 |
| I-Dec‡ | E-Aug late (#2) | Inh_2 | 0 | 5 | 115 | 1.0 | 300 | 600 | 104.77 ± 2.71 | 1.10 | 52.39 ± 6.40 |
| E-Aug early‡ | E-Aug late (#2) | Inh_1 | 0 | 2 | 50 | 0.001 | 300 | 600 | 48.01 ± 1.32 | 1.04 | 24.00 ± 4.83 |
| E-Aug late (#1)* | I-Dec | Inh_1 | 0 | 4 | 55 | 0.01 | 300 | 300 | 50.33 ± 1.87 | 1.09 | 50.33 ± 6.68 |
| E-Aug late (#2)‡ | I-Dec | Inh_1 | 0 | 4 | 100 | 0.05 | 600 | 300 | 85.21 ± 3.03 | 1.17 | 170.43 ± 10.33 |
| Second-order cough*§ | I-Dec | Ex_1 | 0 | 3 | 100 | 0.038 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough*§ | I-Aug | Ex_1 | 0 | 3 | 100 | 0.02 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough*§ | VRC IE | Inh_1 | 0 | 3 | 100 | 0.2 | 100 | 99 | 63.13 ± 3.05 | 1.58 | 63.77 ± 5.20 |
| Second-order cough*§ | E-Dec P | Ex_1 | 0 | 3 | 100 | 0.015 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough*§ | E-Aug early | Ex_1 | 0 | 3 | 100 | 0.1 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough*§ | E-Aug late (#1) | Ex_1 | 0 | 3 | 100 | 0.06 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough*§ | E-Aug BS | Ex_1 | 0 | 4 | 125 | 0.001 | 100 | 300 | 102.81 ± 3.59 | 1.22 | 34.27 ± 4.61 |
| Second-order cough*§ | Pump- | Inh_1 | 0 | 4 | 250 | 0.4 | 100 | 300 | 170.45 ± 4.98 | 1.47 | 56.82 ± 4.58 |
| Second-order cough*§ | PRG cIE | Ex_1 | 0 | 3 | 100 | 0.001 | 100 | 100 | 63.59 ± 3.21 | 1.57 | 63.59 ± 5.84 |
| Second-order cough*§ | PRG rIE | Ex_1 | 0 | 3 | 100 | 0.001 | 100 | 100 | 63.59 ± 3.21 | 1.57 | 63.59 ± 5.84 |
| Second-order cough*§ | PRG I | Ex_1 | 0 | 3 | 100 | 0.001 | 100 | 100 | 63.59 ± 3.21 | 1.57 | 63.59 ± 5.84 |
| Second-order cough*§ | PRG E | Ex_1 | 0 | 3 | 100 | 0.001 | 100 | 100 | 63.59 ± 3.21 | 1.57 | 63.59 ± 5.84 |
| Second-order cough*§ | PRG EI | Ex_1 | 0 | 3 | 100 | 0.001 | 100 | 100 | 63.59 ± 3.21 | 1.57 | 63.59 ± 5.84 |
| Second-order cough*§ | E-Dec Pre | Ex_1 | 0 | 3 | 100 | 0.0025 | 100 | 300 | 85.14 ± 3.15 | 1.11 | 28.38 ± 3.97 |
| Second-order cough (insp)‡§ | I-Dec | Ex_1 | 0 | 3 | 100 | 0.038 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough (insp)‡§ | I-Aug | Ex_1 | 0 | 3 | 100 | 0.02 | 100 | 300 | 85.25 ± 2.83 | 1.17 | 28.42 ± 5.15 |
| Second-order cough (insp)‡§ | VRC IE | Inh_1 | 0 | 3 | 100 | 0.2 | 100 | 99 | 63.13 ± 3.05 | 1.58 | 63.77 ± 5.20 |
| Second-order cough (insp)‡§ | E-Aug late (#2) | Ex_1 | 0 | 3 | 100 | 0.07 | 100 | 600 | 92.11 ± 2.37 | 1.09 | 15.35 ± 4.27 |
| Second-order cough (exp)‡§ | E-Dec P | Ex_1 | 0 | 3 | 100 | 0.015 | 250 | 300 | 85.23 ± 2.93 | 1.17 | 71.02 ± 9.02 |
| Second-order cough (exp)‡§ | E-Aug early | Ex_1 | 0 | 3 | 100 | 0.1 | 250 | 300 | 85.23 ± 2.93 | 1.17 | 71.02 ± 9.02 |
| Second-order cough (exp)‡§ | E-Aug late (#1) | Ex_1 | 0 | 3 | 100 | 0.06 | 250 | 300 | 85.23 ± 2.93 | 1.17 | 71.02 ± 9.02 |
| Second-order cough (exp)‡§ | E-Aug BS | Ex_1 | 0 | 4 | 125 | 0.001 | 250 | 300 | 102.33 ± 3.45 | 1.22 | 85.28 ± 6.85 |
| Second-order cough (exp)‡§ | Pump- | Inh_1 | 0 | 4 | 250 | 0.4 | 250 | 300 | 170.67 ± 4.79 | 1.46 | 142.23 ± 7.14 |
| Second-order cough (exp)‡§ | PRG cIE | Ex_1 | 0 | 3 | 100 | 0.001 | 250 | 100 | 63.42 ± 3.05 | 1.58 | 158.54 ± 10.15 |
| Second-order cough (exp)‡§ | PRG rIE | Ex_1 | 0 | 3 | 100 | 0.001 | 250 | 100 | 63.42 ± 3.05 | 1.58 | 158.54 ± 10.15 |
| Second-order cough (exp)‡§ | PRG I | Ex_1 | 0 | 3 | 100 | 0.001 | 250 | 100 | 63.42 ± 3.05 | 1.58 | 158.54 ± 10.15 |
| Second-order cough (exp)‡§ | PRG E | Ex_1 | 0 | 3 | 100 | 0.001 | 250 | 100 | 63.42 ± 3.05 | 1.58 | 158.54 ± 10.15 |
| Second-order cough (exp)‡§ | PRG EI | Ex_1 | 0 | 3 | 100 | 0.001 | 250 | 100 | 63.42 ± 3.05 | 1.58 | 158.54 ± 10.15 |
| Second-order cough (exp)‡§ | E-Dec Pre | Ex_1 | 0 | 3 | 100 | 0.0025 | 250 | 300 | 85.08 ± 3.08 | 1.18 | 70.90 ± 6.53 |
| Second-order cough feed-forward inhibition† | Second-order cough | Inh_1 | 0 | 2 | 500 | 0.02 | 100 | 250 | 215.94 ± 3.74 | 2.32 | 86.38 ± 3.09 |
| Second-order cough feed-forward inhibition‡ | Second-order cough (exp) | Inh_1 | 0 | 2 | 500 | 0.02 | 100 | 250 | 215.94 ± 3.74 | 2.32 | 86.38 ± 3.09 |
| Second-order cough feed-forward inhibition‡ | Second-order cough (insp) | Inh_1 | 0 | 2 | 500 | 0.02 | 100 | 100 | 99.33 ± 0.91 | 5.03 | 99.33 ± 0.85 |
Symbols indicate connections present in the base model from Poliaček et al. (48) and version 1 that were removed from version 2 (
) and connections added to the base model (48) to create version 1 (
) and version 2 (
) of the computational model.
Connection relaying a perturbation to the network model. Connections between individual neurons were made according to a sequence of pseudorandom numbers calculated from a unique seed number for each source-to-target connection. Targets were chosen with replacement. This table includes the mean ± SD of the number of neurons in each target population innervated by each source neuron in each population. Corresponding values are also shown for source neurons that innervated each target neuron in each population. These data indicate the extent of divergence and convergence, respectively. Most neurons in each source population made a single terminal connection with each target neuron. Mean number of terminals, the mean number of terminals from each source neuron innervating each target neuron. The efficacy of connections between populations of neurons was influenced by the change in conductance associated with each action potential at a synapse (synaptic strength) and the number of terminals for each axon. Synaptic types were distinguished by their equilibrium potentials and time constants. The time constant of some synapses was slightly longer than others because troughs in cross-correlograms from which the particular synaptic connections were inferred tended to have longer durations. Six types of synapses were used in the simulation: type 1 excitatory (Ex_1, equilibrium potential of 115.0 mV; time constant, 1.5 ms), type 3 excitatory (Ex_3, equilibrium potential, 115.0 mV; time constant, 5.0 ms), type 1 inhibitory (Inh_1, equilibrium potential, −25.0 mV; time constant, 1.5 ms), type 2 inhibitory (Inh_2, equilibrium potential, −25.0 mV; time constant, 2.0 ms), type 4 inhibitory (Inh_4, equilibrium potential, −25.0 mV; time constant, 5.0 ms), and presynaptic modulation (Pre, time constant, 1.5 ms). If the value of the presynaptic modulatory strength parameter (synaptic strength) was <1.0, the strength of the connection it modulates was reduced to the product of the presynaptic synaptic strength parameter and target synapse conductance. If the presynaptic synaptic strength parameter was >1.0, the amount by which it was >1 is added to its target synapse's conductance. Minimum and maximum conduction times are expressed in 0.5-ms simulation clock ticks for each source-to-target axon population. Number of terminals, number of terminals from source neuron; cIE, caudal IE; rIE, rostral IE.