Cited by 280Tactile and Sensory InteractionsMultisensory perception and integrationMotor Control and Adaptation

Touch is a team effort: interplay of submodalities in cutaneous sensibility

Saal, Hannes P., Bensmaia, Sliman J.·2014·Trends in Neurosciences

Abstract

Traditionally, different classes of cutaneous mechanoreceptive afferents are ascribed different and largely non-overlapping functional roles (for example texture or motion) stemming from their different response properties. This functional segregation is thought to be reflected in cortex, where each neuron receives input from a single submodality. We summarize work that challenges this notion. First, while it is possible to design artificial stimuli that preferentially excite a single afferent class, most natural stimuli excite all afferents and most tactile percepts are shaped by multiple submodalities. Second, closer inspection of cortical responses reveals that most neurons receive convergent input from multiple afferent classes. We argue that cortical neurons should be grouped based on their function rather than on their submodality composition.

Integrity signals

Registry

Crossref · 10.1016/j.tins.2014.08.012

Cites

107 of 107 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Different populations of afferents can be activated through individual electrodes, which can have distinct receptive field locations and different sub-modality compositions of sensory afferents.

    “Different populations of afferents can be activated through these individual electrodes, which can have distinct receptive field locations (Saal and Bensmaia, 2014) and different sub-modality compositions of sensory afferents (mix of slowly adapting (SA), rapidly adapting (RA), and pacinian corpuscles (PC) afferents).”

    From Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. (2017) · cites this paper as Saal and Bensmaia, 2014

  • During natural contact with objects, all afferent types are activated and convey information about the objects' shape, size, texture and motion with respect to the skin.

    “During natural contact with objects, all afferent types are activated and convey information about the objects' shape, size, texture and motion with respect to the skin (Saal and Bensmaia, 2014).”

    From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014

  • Recent reinterpretation of extant data suggests that information about most tactile features is encoded synergistically by all afferent classes.

    “Indeed, while different afferent types were traditionally assumed to encode a single tactile feature, such as surface texture or tactile motion, recent reinterpretation of extant data suggests that information about most tactile features is encoded synergistically by all afferent classes (see Saal and Bensmaia, 2014 for a review).”

    From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014

  • Signals from multiple afferent types converge at the earliest stages of processing in somatosensory cortex (and perhaps even before).

    “Importantly, signals from multiple afferent types converge at the earliest stages of processing in somatosensory cortex (and perhaps even before) (Carter et al., 2014;Pei et al., 2009;Saal and Bensmaia, 2014), allowing for the possibility that mimicking naturalistic patterns of activation over small populations of afferents of mixed type will result in naturalistic patterns of cortical activation,”

    From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Saal, H. P., & Bensmaia, S. J.
Affiliations
University of Chicago (US)
Venue
Trends in Neurosciences
Publisher
Elsevier BV
Published
2014-12
Volume
37
Issue
12
Pages
689-697
ISSN
0166-2236 (ISSN-L)
OpenAlex
W2094721746
Cited by
280
References
107
Citations by year
2026: 33 · 2025: 23 · 2024: 23 · 2023: 24 · 2022: 31 · 2021: 27 · 2020: 21 · 2019: 22 · 2018: 26 · 2017: 16 · 2016: 18 · 2015: 15 · 2014: 1
FWCI
1.57
Type
journal article
Language
en
Open access
closed
Locations
  • Trends in Neurosciences (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Science Foundation
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
Keywords
cutaneous mechanoreceptors, tactile perception, afferent convergence, cortical neurons, functional segregation, texture perception, naturalistic stimuli, multisensory integration, somatosensory cortex
MeSH terms
Afferent Pathways, Brain Mapping, Humans, Mechanoreceptors, Neurons, Somatosensory Cortex, Touch

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review