Spinal Dorsal Horn Network Model (Medlock et al 2022)

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Accession:267056
To explore spinal dorsal horn (SDH) network function, we developed a computational model of the circuit that is tightly constrained by experimental data. Our model comprises conductance-based model neurons that reproduce the characteristic firing patterns of excitatory and inhibitory spinal neurons. Excitatory spinal neuron subtypes defined by calretinin, somatostatin, delta-opioid receptor, protein kinase C gamma, or vesicular glutamate transporter 3 expression or by transient/central spiking/morphology and inhibitory neuron subtypes defined by parvalbumin or dynorphin expression or by islet morphology were synaptically connected according to available qualitative data. Synaptic weights were adjusted to produce firing in projection neurons, defined by neurokinin-1 expression, matching experimentally measured responses to a range of mechanical stimulus intensities. Input to the circuit was provided by three types of afferents (Aß, Ad, and C-fibres) whose firing rates were also matched to experimental data.
Reference:
1 . Medlock L, Sekiguchi K, Hong S, Dura-Bernal S, Lytton WW, Prescott SA (2022) Multiscale computer model of the spinal dorsal horn reveals changes in network processing associated with chronic pain The Journal of Neuroscience [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Spinal cord lamina I neuron; Spinal cord lamina I-III interneuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NetPyNE; NEURON;
Model Concept(s): Sensory processing; Pain processing;
Implementer(s): Medlock, Laura [laura.medlock at mail.utoronto.ca]; Sekiguchi, Kazutaka [kazutaka.sekiguchi at shionogi.co.jp];
 
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SDHmodel
                            
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