Lamina specific loss of inhibition may lead to distinct neuropathic manifestations: a computational modeling approach

Abstract

Introduction: It has been reported that inhibitory control at the superficial dorsal horn (SDH) can act in a regionally distinct manner, which suggests that regionally specific subpopulations of SDH inhibitory neurons may prevent one specific neuropathic condition. Methods: In an attempt to address this issue, we provide an alternative approach by integrating neuroanatomical information provided by different studies to construct a network-model of the SDH. We use Neuroids to simulate each neuron included in that model by adapting available experimental evidence. Results: Simulations suggest that the maintenance of the proper level of pain sensitivity may be attributed to lamina II inhibitory neurons and, therefore, hyperalgesia may be elicited by suppression of the inhibitory tone at that lamina. In contrast, lamina III inhibitory neurons are more likely to be responsible for keeping the nociceptive pathway from the mechanoreceptive pathway, so loss of inhibitory control in that region may result in allodynia. The SDH network-model is also able to replicate non-linearities associated to pain processing, such as Aβ-fiber mediated analgesia and frequency-dependent increase of the neural response. Discussion: By incorporating biophysical accuracy and newer experimental evidence, the SDH network-model may become a valuable tool for assessing the contribution of specific SDH connectivity patterns to noxious transmission in both physiological and pathological conditions.

The Neuroid revisited: A heuristic approach to model neural spike trains

“…Still, this comparison would be a bit more complicated since the neural response varies between different populations. A previous study (Prada et al, 2015) found that the Neuroid might be used to predict the firing frequency of nociceptive primary afferent A-and C-fibers, but it could be insufficient to model spinal dorsal horn neurons. All this suggests that, in the absence of a quantitative index for the evaluation of the accuracy achieved by several neuron-models, the results obtained by previous (Izhikevich, 2004;Long and Fang, 2010;Skocik and Long, 2014;Wang et al, 2014) and the current study may not be absolutely conclusive.…”

“…An innovative alternative known as Neuroid (Prada et al, 2012) was introduced at the 34 th International Annual Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'12). Since then, this neuron-model has been utilized to aid in understanding how functionally different neural populations (e.g., low-threshold vs. high-threshold afferent fibers; normally silent vs. tonically active neurons) interact each other and how those differences affect the way that visual and tactile Prada et al, 2015) information is processed.…”