Evidence map›Paper›PMID 40511684›Full record

ArticleeLife2025

Fingertip viscoelasticity enables human tactile neurons to encode loading history alongside current force.

Hannes P Saal, Ingvars Birznieks, Roland S Johansson

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hannes P SaalActive Touch Laboratory, School of Psychology, University of Sheffield, Sheffield, United Kingdom.ORCID https://orcid.org/0000-0002-7544-0196
Ingvars BirznieksSchool of Biomedical Sciences, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-4916-1254
Roland S JohanssonPhysiology Section, Department of Integrative and Medical Biology, Umeå University, Umeå, Sweden.ORCID https://orcid.org/0000-0003-3288-8326

Funding

Leverhulme Trust RPG-2022-031Vetenskapsrådet 08667
6 · The paper itself

Abstract

Human skin and its underlying tissues constitute a viscoelastic medium, implying that any deformation depends not only on the currently applied force, but also on the recent loading history. The extent to which this physical memory influences the signaling of first-order tactile neurons during natural hand use is not well understood. Here, we examined the effect of past loading on the responses of fast-adapting (FA-1) and slowly-adapting (SA-1 and SA-2) first-order tactile neurons innervating the human fingertip to loadings applied in different directions representative of object manipulation tasks. We found that variation in the preceding loading affected neurons' overall signaling of force direction. Some neurons kept signaling the current direction, while others signaled both the current and preceding direction, or even primarily the preceding direction. In addition, ongoing impulse activity in SA-2 neurons between loadings signaled information related to the fingertip's viscoelastic deformation state. We conclude that tactile neurons at the population level signal continuous information about the fingertip's viscoelastic deformation state, which is shaped by both its recent history and current loading. Such information might be sufficient for the brain to correctly interpret current force loading and help in computing accurate motor commands for interactions with objects in manipulation and haptic tasks.

Indexed as

ElasticityFingersNeuronsTouchTouch PerceptionAdultFemaleHumansMaleViscosityYoung Adulthumanneurosciencesensory afferentskin mechanicssomatosensation

Identifiers

PMID40511684
PMCPMC12165688

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.