A neural surveyor to map touch on the body

Abstract

Significance Perhaps the most recognizable “sensory map” in neuroscience is the somatosensory homunculus. Although the homunculus suggests a direct link between cortical territory and body part, the relationship is actually ambiguous without a decoder that knows this mapping. How the somatosensory system derives a spatial code from an activation in the homunculus is a longstanding mystery we aimed to solve. We propose that touch location is disambiguated using multilateration, a computation used by surveying and global positioning systems to localize objects. We develop a Bayesian formulation of multilateration, which we implement in a neural network to identify its computational signature. We then detect this signature in psychophysical experiments. Our results suggest that multilateration provides the homunculus-to-body mapping necessary for localizing touch.