Evidence map›Paper›PMID 34980661›Full record

ArticleeNeuro

Multivariate Analysis of Evoked Responses during the Rubber Hand Illusion Suggests a Temporal Parcellation into Manipulation and Illusion-Specific Correlates.

Placido Sciortino, Christoph Kayser

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In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

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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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

2 authors.

Placido SciortinoDepartment for Cognitive Neuroscience, Faculty of Biology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany placido.sciortino@uni-bielefeld.de.ORCID 0000-0002-9235-3086
Christoph KayserDepartment for Cognitive Neuroscience, Faculty of Biology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.ORCID 0000-0001-7362-5704

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The neurophysiological processes reflecting body illusions such as the rubber hand remain debated. Previous studies investigating the neural responses evoked by the illusion-inducing stimulation have provided diverging reports as to when these responses reflect the illusory state of the artificial limb becoming embodied. One reason for these diverging reports may be that different studies contrasted different experimental conditions to isolate potential correlates of the illusion, but individual contrasts may reflect multiple facets of the adopted experimental paradigm and not just the illusory state. To resolve these controversies, we recorded EEG responses in human participants and combined multivariate (cross-)classification with multiple Illusion and non-Illusion conditions. These conditions were designed to probe for markers of the illusory state that generalize across the spatial arrangements of limbs or the specific nature of the control object (a rubber hand or participant's real hand), hence which are independent of the precise experimental conditions used as contrast for the illusion. Our results reveal a parcellation of evoked responses into a temporal sequence of events. Around 125 and 275 ms following stimulus onset, the neurophysiological signals reliably differentiate the illusory state from non-Illusion epochs. These results consolidate previous work by demonstrating multiple neurophysiological correlates of the rubber hand illusion and illustrate how multivariate approaches can help pinpointing those that are independent of the precise experimental configuration used to induce the illusion.

Indexed as

IllusionsTouch PerceptionHandHumansMultivariate AnalysisProprioceptionVisual Perceptionbody consciousnessbody ownershipEEGrubber handrubber hand illusionself-consciousness

Identifiers

PMID34980661
PMCPMC8805188

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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.