Skin and Mechanoreceptor Contribution to Tactile Input for Perception: A Review of Simulation Models.

Area of Science:

• Computational neuroscience
• Robotics
• Sensorimotor science
• Psychology

Background:

• Traditional methods for studying skin and tactile neurons have limitations.
• Understanding mechanoreceptor response is crucial for fields like robotics and neuroscience.
• Quantitative models offer a way to study skin-nerve interactions.

Purpose of the Study:

• To review four computational models of mechanoreceptor response to tactile stimuli.
• To guide researchers in psychology, sensorimotor science, and robotics on model implementation.
• To highlight the advantages of computational modeling over traditional measurement techniques.

Main Methods:

• Overview of selected computational models.
• Simulation of stimulus application to neuronal spiking response.
• Evaluation of models against existing experimental data.
• Assessment of model applicability to human tactile perception.

Main Results:

• The reviewed models simulate mechanoreceptor responses to tactile stimulation.
• Models provide insights into the combined effects of skin properties on tactile neuron activity.
• The models allow examination of different neural coding strategies.

Conclusions:

• Computational models offer a valuable approach to understanding tactile sensation.
• These models can bridge the gap between skin mechanics and neural activity.
• The reviewed models are applicable to research in human tactile perception and robotics.