A mechanism for spatial perception on human skin

Fardo, Francesca; Beck, Brianna; Cheng, Tony; Haggard, Patrick

doi:10.1016/j.cognition.2018.05.024

Cited by 32 publications

(29 citation statements)

References 32 publications

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“…Further, the dominant source of error during path integration is noise that accumulates with distance travelled (Stangl et al, 2020). Interesting, similar errors are found for path integration in the tactile domain (Fardo et al, 2018;Moscatelli et al, 2014), suggesting that they may involve multilateration as well.…”

Section: Is Multilateration a General Spatial Computation?mentioning

confidence: 59%

A neural surveyor to map touch on the body

Miller

Fabio

Beers

et al. 2020

Preprint

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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

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Section: Is Multilateration a General Spatial Computation?mentioning

confidence: 59%

A neural surveyor to map touch on the body

Miller

Fabio

Beers

et al. 2020

Preprint

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“…S-space may be understood as a tactile analogue of a visual field: it allows computations of spatial relations between various points on the body on the basis of topological information stemming from neighboring relations between receptive fields. Cheng and Haggard (2018) suggest that such a space may be sufficient for body spatiality to arise.…”

Section: Multisensory Integration Hypothesis Vs Thementioning

confidence: 99%

“…In other words, the emergence of RHI depends on the degree of discrepancy between locations of sensory signals in external space, but the degree of discrepancy on the body is deemed irrelevant (or rather, assumed to be equal to 0). Recently, the term "skin space" ("S-space") has been coined (Haggard, Cheng, Beck, & Fardo, 2017;Cheng & Haggard, 2018;Fardo, Beck, Cheng, & Haggard, 2018) to describe a spatial representation allowing tactile localization on the surface of the skin. S-space may be understood as a tactile analogue of a visual field: it allows computations of spatial relations between various points on the body on the basis of topological information stemming from neighboring relations between receptive fields.…”

Section: Multisensory Integration Hypothesis Vs Thementioning

confidence: 99%

Rubber Hand Illusion does not arise from comparisons with internal body models: a new multisensory integration account of the sense of ownership

Litwin

2018

Preprint

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Human body sense is surprisingly flexible – precisely administered multisensory stimulation may result in the illusion that an external object is part of one’s body. There seems to be a general consensus that there are certain top-down constraints on which objects may be incorporated: in particular, to-be-embodied objects should be structurally similar to a visual representation stored in an internal body model for a shift in one’s body image to occur. However, empirical evidence contradicts the body model hypothesis: the sense of ownership may be spread over objects strikingly distinct in morphology and structure (e.g., robotic arms or empty space) and direct empirical support for the theory is currently lacking. As an alternative, based on the example of the rubber hand illusion (RHI), I propose a multisensory integration account of how the sense of ownership is induced. In this account, the perception of one’s own body is a regular type of multisensory perception and multisensory integration processes are not only necessary but also sufficient for embodiment. In this paper, I propose how RHI can be modeled with the use of Maximum Likelihood Estimation and natural correlation rules. I also discuss how Bayesian Coupling Priors and idiosyncrasies in sensory processing render prior distributions interindividually variable, accounting for large interindividual differences in susceptibility to RHI. Taken together, the proposed model accounts for exceptional malleability of human body perception, fortifies existing bottom-up multisensory integration theories with top-down models of relatedness of sensory cues, and generates testable and disambiguating predictions.

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“…Different cues contribute to the perception of motion in touch, including the spatiotemporal pattern of local deformation, as for example the one generated by the tip of a pencil moving across the skin, high-frequency skin vibrations occurring during slip motion, and the gross skin deformation, such as the stretch generated by a shear force applied to the fingertip [32,11,13,18,29,1]. The role of the first two motion cues, local indentation and vibrations, was deeply investigated in recent studies [5,9,15,31,23,8]. Here, we evaluate the role of shear deformation for the discrimination of speed.…”

Section: Introductionmentioning

confidence: 99%

“…The indentation produced by traceable surface elements, like moving raised dots or ridges, provide a salient motion cue in touch [32,5,15]. Recently, a model based on the spatiotemporal pattern of skin deformation reproduced the tactile afferent signals quite accurately [29].…”

Section: Introductionmentioning

confidence: 99%

Discriminating tactile speed in absence of raised texture elements: Role of deformation and vibratory cues

Moscatelli

Ryan

Ciotti

et al. 2019

Preprint

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Motion encoding in touch relies on multiple cues, such as displacements of traceable texture elements, friction-induced vibrations, and gross fingertip deformations by shear force. We evaluated the role of deformation and vibration cues in tactile speed discrimination. To this end, we tested the discrimination of speed of a moving smooth glass plate, and compared the precision of the responses when the same task was performed with a plate having a fine texture. Participants performed the task with and without masking vibrations. Speed discrimination was nearly as precise among the two surface types, as assessed by the steep slope of the psychometric function. Consistent with our previous work, high-frequency vibrations impaired the ability of the participants in discriminating surface speed. Results of the current study showed that it is possible to discriminate motion speed even in absence of a raised texture. Highlights 1 • On a smooth surface, humans are able to discriminate the speed of a 2 moving surface by frictional motion cues 3 • The precision of speed discrimination is nearly the same with smooth 4 and fine-textured surface types 5 • High frequency vibrations impair the ability to discriminate speed of 6 moving surfaces 7 It provides feedback for the manipulation of handheld objects [2], and for 11 guiding hand reaching towards a target goal while touching a surface [3, 12 4]. During grasping tasks, our sensorimotor system rapidly adjusts the grip 13 force based on the small slips between the object and the skin, revealed as 14 vibrations [5]. 15Different cues contribute to the perception of motion in touch, includ-16 ing the spatiotemporal pattern of skin indentation, as for example the one 17 generated by the tip of a pencil moving across the skin, high-frequency vi-18 brations caused by frictional slips, and the gross deformation of the skin 19 and subcutaneous tissues, such as the stretch generated by a shear force 20 applied to the fingertip [6, 7, 8, 9, 10]. The role of the first two motion 21 cues, local indentation and vibrations, was investigated in several studies 22 [11, 12, 13, 14, 15, 16, 17, 18]. Here, we investigated the discrimination of 23 speed of a smooth movable surface (i.e., a glass plate for microscope slide). 24Because of the lack of fine and coarse texture, shear deformation cues may 25 play an important role for this type of stimuli. Before introducing our study, 26 we will summarize recent findings about different cues in tactile motion per-27 ception. 28The indentation produced by traceable surface elements, like raised ridges 29 of the tip of a pen, provide a salient motion cue in touch [6, 11, 13]. For 30 instance, the perceived speed of a ridged surface depends on the distance 31 between its ridges, such as the closer the texture elements, the faster is 32 the perceived speed [12, 19]. In accordance with behavioral studies, a model 33 based on the spatiotemporal pattern of skin deformation, as the one produced 34 by a coarse texture, accurately reproduced tactile affere...

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A mechanism for spatial perception on human skin

Cited by 32 publications

References 32 publications

A neural surveyor to map touch on the body

A neural surveyor to map touch on the body

Rubber Hand Illusion does not arise from comparisons with internal body models: a new multisensory integration account of the sense of ownership

Discriminating tactile speed in absence of raised texture elements: Role of deformation and vibratory cues

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