Modeling sensory adaptation to peripheral nerve stimulation

Abstract

Neural adaptation is a well-known phenomenon of the human sensory systems. Prolonged stimulation of the sensory system causes the adaptation (e.g. reduced neural activity) of the afferent sensory inputs. Interestingly, the use of direct nerve stimulation using implanted electrodes has been shown as the promise for providing sensory feedback to amputees. Although this technique is proven to be able to convey several sensory information, sensory adaptation to the neural stimulation can cause some unwanted behavior (e.g., disappearing of the artificial sensation after few minutes, changes in the perceptual intensity over time). Here we present a computational model of the sensory adaptation to direct electrical nerve stimulation. The model considers important biological parameters (i.e. synaptic processes) together with the different stimulation parameters (i.e. stimulation amplitude and frequency). The model was fitted on experimental data collected in two human transfemoral amputees, who were implanted with four transverse intrafascicular multichannel electrodes (TIME) in their residual tibial nerve. This model is not only used to better understand the mechanisms of sensory adaptation to different neural stimulation strategies, but it could also be exploited in future in neuroprosthetic applications to predict and control sensory adaptation.