A neural surveyor to map touch on the body

Abstract

Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Though it seems straightforward, this simple representation belies the complex link between an activation in somatosensory Area 3b and the associated touch location on the body. Any isolated activation is spatially ambiguous without a neural decoder that can read its position within the entire map, though how this is computed by neural networks is unknown.We propose that somatosensory cortex implements multilateration, a common computation used by surveying and GPS systems to localize objects. Specifically, to decode touch location on the body, the somatosensory system estimates the relative distance between the afferent input and the body's joints. We show that a simple feedforward neural network which captures the receptive field properties of somatosensory cortex implements a Bayes-optimal multilateral decoder via a combination of bell-shaped (Area 3b) and sigmoidal (Areas 1/2) tuning curves. Simulations demonstrated that this decoder produced a unique pattern of localization variability between two joints that was not produced by other known neural decoders. Finally, we identify this neural signature of multilateration in actual psychophysical experiments, suggesting that it is a candidate computational mechanism underlying tactile localization. take place in the frontal and parietal cortices (Burnod et al., 1999;Crawford et al., 2004;Medendorp et al., 2005;Pesaran et al., 2006).Equally crucial to localizing objects in the environment is localizing objects on the personal space of the body. Despite over 180 years of research on the sense of touch (Weber, 1834), the computations underlying tactile localization remain largely unknown. Recent accounts have suggested that tactile localization requires two computational steps Medina and Coslett, 2010). First, afferent input must be localized within a topographic map in

A somatosensory computation that unifies limbs and tools

“…(F(5,185)=0.21, p=.96). Crucially, the pattern of variable errors (Figure 1D) in both tasks displayed the hypothesized inverted U-shape, which was of similar magnitude to what we observed for touch on the arm (8,10). ously observed for localization on the arm (gray line and squares) in (10).…”

“…Analysis of the variable errors (2x6 repeated measures ANOVA) found a significant main effect of hit location (F(5,185)=36.1, p<.001) but no main effect of task (F(1,37)=0.39, p=.54) or an interaction (F(5,185)=0.21, p=.96). Crucially, the pattern of variable errors (Figure 1D) in both tasks displayed the hypothesized inverted U-shape, which was of similar magnitude to what we observed for touch on the arm (8,10). ously observed for localization on the arm (gray line and squares) in (10).…”

“…If tools are embodied by the sensorimotor system (2), we would expect that the brain repurposes its body-based sensorimotor computations to perform similar tasks with tools. Consistent with this hypothesis, we observed that localizing touch on the surface of a tool is characterized by perceptual anchors (9), suggesting that trilateration is the spatial computation employed by the somatosensory system to localize touch on body parts and tools alike (10).…”

“…we have observed for tactile localization on the arm and fingers (10). Our computational analyses implement this probabilistic model of trilateration (see below).…”

Alpha oscillations are involved in localizing touch on hand-held tools

“…Since it is essential to identify the position of a tactile object in order to interact with it, more than a century of research has characterized the perceptual processes underlying tactile localization at a behavioral level ((Badde et al, 2015;Cholewiak and Collins, 2003;Fuchs et al, 2019;Harrar and Harris, 2009;Ho and Spence, 2007;Liu and Medina, 2021;Mancini et al, 2011;Miller et al, 2020;Parrish, 1897;Sadibolova et al, 2018;Stevens, 1992;Weber, 1846); for a review see (Heed et al, 2015)). These studies have identified different spatial codes that are utilized to localize tactile stimuli.…”