Modeling Skin Blood Flow - A Neuro-physiological Approach

Introduction: In humans skin blood flow (SBF) plays a major role in body heat loss. Therefore the accuracy of models of human thermoregulation depends for a great deal on their ability to predict skin blood flow. Most SBF-models use body temperatures directly for calculation of skin perfusion. However, humans do not sense temperature directly, yet the information is coded into neuron fire rates. The aim of this study was to investigate whether SBF can be adequately modelled through simulation of temperature sensitive neurons and neuro-physiological pathways of excitation and inhibition. Methods: In this study a mathematical model for SBF was developed based on physiological knowledge on neural thermo-sensitivity and neural pathways. The model was fitted on human experimental data. Mean squared residuals (MSR) were estimated through k-fold cross-validation. Results: The model adequately explains the variance of the measurements (r=0.91). Furthermore the averaged MSR is close to the natural variation in the measurements (AMSR=0.087 vs. σ=0.080) indicating a small bias. Conclusion: In this study we developed a model for skin perfusion based on physiological evidence on thermo-reception and neural pathways. Given the highly explained variance this study shows that a neuro-physiological approach is applicable for modelling skin blood flow in thermoregulation.