Spinal cord stimulation (SCS) is a clinical therapy for chronic, neuropathic pain, but an incomplete understanding of the mechanisms underlying SCS contributes to the lack of improvement in SCS efficacy over time. To study the mechanisms underlying SCS, we constructed a biophysically based network model of the dorsal horn circuit consisting of interconnected dorsal horn interneurons and a wide-dynamic range (WDR) projection neuron and representations of both local and surround receptive field inhibition. We validated the network model by reproducing cellular and network responses relevant to pain processing including wind-up, A fiber-mediated inhibition, and surround receptive field inhibition. We then simulated the effects of SCS on the activity of the WDR projection neuron and found that the response of the model WDR neuron to SCS depends on the SCS frequency; SCS frequencies of 30-100 Hz maximally inhibited the model WDR neuron, while frequencies under 30 Hz and over 100 Hz excited the model WDR neuron. We also studied the impacts on the effects of SCS of loss of inhibition due to the loss of either GABA or KCC2 function. Reducing the influence of local and surround GABAergic interneurons by weakening their inputs or their connections to the WDR neuron and shifting the anionic reversal potential of the WDR neurons upward each reduced the range of optimal SCS frequencies and changed the frequency at which SCS had a maximal effect. The results of this study provide insights into the mechanisms of SCS and pave the way for improved SCS parameter selection.
Keywords: computational modeling; dorsal horn network; spinal cord stimulation.
Copyright © 2014 the American Physiological Society.