Florey Department of Neuroscience and Mental Health - Research Publications

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    Modelling of synaptic interactions between two brainstem half-centre oscillators that coordinate breathing and swallowing
    Tolmachev, P ; Dhingra, RR ; Manton, JH ; Dutschmann, M ( 2021)
    Abstract Respiration and swallowing are vital orofacial motor behaviours that require the coordination of the activity of two brainstem central pattern generators (r-CPG, sw-CPG). Here, we use computational modelling to further elucidate the neural substrate for breathing-swallowing coordination. We progressively construct several computational models of the breathing-swallowing circuit, starting from two interacting half-centre oscillators for each CPG. The models are based exclusively on neuronal nodes with spike-frequency adaptation, having a parsimonious description of intrinsic properties. These basic models undergo a stepwise integration of synaptic connectivity between central sensory relay, sw- and r-CPG neuron populations to match experimental data obtained in a perfused brainstem preparation. In the model, stimulation of the superior laryngeal nerve (SLN, 10s) reliably triggers sequential swallowing with concomitant glottal closure and suppression of inspiratory activity, consistent with the motor pattern in experimental data. Short SLN stimulation (100ms) evokes single swallows and respiratory phase resetting yielding similar experimental and computational phase response curves. Subsequent phase space analysis of model dynamics provides further understanding of SLN-mediated respiratory phase resetting. Consistent with experiments, numerical circuit-busting simulations show that deletion of ponto-medullary synaptic interactions triggers apneusis and eliminates glottal closure during sequential swallowing. Additionally, systematic variations of the synaptic strengths of distinct network connections predict vulnerable network connections that can mediate clinically relevant breathing-swallowing disorders observed in the elderly and patients with neurodegenerative disease. Thus, the present model provides novel insights that can guide future experiments and the development of efficient treatments for prevalent breathing-swallowing disorders. Key points The coordination of breathing and swallowing depends on synaptic interactions between two functionally distinct central pattern generators (CPGs) in the dorsal and ventral brainstem. We model both CPGs as half-centre oscillators with spike-frequency adaptation to identify the minimal connectivity sufficient to mediate physiologic breathing-swallowing interactions. The resultant computational model(s) can generate sequential swallowing patterns including concomitant glottal closure during simulated 10s stimulation of the superior laryngeal nerve (SLN) consistent with experimental data. In silico, short (100 ms) SLN stimulation triggers a single swallow which modulates the respiratory cycle duration consistent with experimental recordings. By varying the synaptic connectivity strengths between the two CPGs and the sensory relay neurons, and by inhibiting specific nodes of the network, the model predicts vulnerable network connections that may mediate clinically relevant breathing-swallowing disorders.
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    Modeling the respiratory central pattern generator with resonate-and-fire Izhikevich-Neurons
    Tolmachev, P ; Dhingra, RR ; Pauley, M ; Dutschmann, M ; Manton, JH ; Cheng, L ; Leung, ACS ; Ozawa, S (Springer Nature, 2018-01-01)
    Computational models of the respiratory central pattern generator (rCPG) are usually based on biologically-plausible Hodgkin Huxley neuron models. Such models require numerous parameters and thus are prone to overfitting. The HH approach is motivated by the assumption that the biophysical properties of neurons determine the network dynamics. Here, we implement the rCPG using simpler Izhikevich resonate-and-fire neurons. Our rCPG model generates a 3-phase respiratory motor pattern based on established connectivities and can reproduce previous experimental and theoretical observations. Further, we demonstrate the flexibility of the model by testing whether intrinsic bursting properties are necessary for rhythmogenesis. Our simulations demonstrate that replacing predicted mandatory bursting properties of pre-inspiratory neurons with spike adapting properties yields a model that generates comparable respiratory activity patterns. The latter supports our view that the importance of the exact modeling parameters of specific respiratory neurons is overestimated.