Estimating nerve excitation thresholds to cutaneous electrical stimulation by finite element modeling combined with a stochastic branching nerve fiber model

Abstract

Electrical stimulation of cutaneous tissue through surface electrodes is an often used method for evoking experimental pain. However, at painful intensities both non-nociceptive Aβ-fibers and nociceptive Aδ- and C-fibers may be activated by the electrical stimulation. This study proposes a finite element (FE) model of the extracellular potential and stochastic branching fiber model of the afferent fiber excitation thresholds. The FE model described four horizontal layers; stratum corneum, epidermis, dermis, and hypodermal used to estimate the excitation threshold of Aβ-fibers terminating in dermis and Aδ-fibers terminating in epidermis. The perception thresholds of 11 electrodes with diameters ranging from 0.2 to 20 mm were modeled and assessed on the volar forearm of healthy human volunteers by an adaptive two-alternative forced choice algorithm. The model showed that the magnitude of the current density was highest for smaller electrodes and decreased through the skin. The excitation thresholds of the Aδ-fibers were lower than the excitation thresholds of Aβ-fibers when current was applied through small, but not large electrodes. The experimentally assessed perception threshold followed the lowest excitation threshold of the modeled fibers. The model confirms that preferential excitation of Aδ-fibers may be achieved by small electrode stimulation due to higher current density in the dermoepidermal junction.

Volume conductor model of transcutaneous electrical stimulation with kilohertz signals

“…In TES, comfort can be an important factor for patient acceptance, and thus modeling studies have addressed the activation of superficial nerve endings (Kuhn et al 2010, Morch et al 2011). Our model could be used to study cutaneous activation by placing unmyelinated fibers in the skin layer in different orientations, but multiple layers of cutaneous tissue, as in Hartinger et al (2010), may be necessary as they can have substantially different dielectric properties.…”

Exploration of the conditioning electrical stimulation frequencies for induction of long-term potentiation-like pain amplification in humans

“…Indeed, in the rat spinal cord selective high frequency CES of Aδ-nociceptors induced LTD in nociceptive synaptic transmission rather than LTP (Randić et al, 1993;Liu et al, 1998). Electrical stimulation is less specific in activating specific nerve fibers, e.g., Aδ-or C-fibers (Nilsson and Schouenborg, 1999;Inui et al, 2002;Mørch et al, 2011). In addition, both C-fiber and Aδ-fiber pathways are found to be involved in the hyperalgesia at the conditioned site after high frequency CES (Hansen et al, 2007).…”

“…1A) (Biurrun Manresa et al, 2010). This electrode has been verified to induce a sensation of pain at a lower stimulation intensity compared with conventional cutaneous nerve stimulation because the diameter of the cathodes is smaller so a high current density is achieved in the epidermal layers where the nociceptive Aδ-and C fibers terminate (Kaube et al, 2000;Katsarava et al, 2006;Mouraux et al, 2010;Mørch et al, 2011). The individual electrical detection threshold (DTh) was determined according to the method of limits: a series of electrical pulses increasing and decreasing at step sizes of 3% of the stimulation intensity was repeated three times in each session.…”

A 3D Computational Model of Transcutaneous Electrical Nerve Stimulation for Estimating Aβ Tactile Nerve Fiber Excitability

“…Most of the previous computational work about TENS focused on nociceptive Aδ- or C-type fibers (Yang et al, 2015), or motor nerve fibers (Kuhn et al, 2010; Goffredo et al, 2014). Although some papers established TENS model considering tactile sensory nerve fiber (Kajimoto et al, 2004; Mørch et al, 2011), the fiber model is passive without explicit ion channel distribution. The active tactile sensory nerve fiber model is more comparable to neurophysiological properties and important for TENS modeling.…”