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From rubber hands to neuroprosthetics: Neural correlates of embodiment

2023· review· en· W4385605096 on OpenAlexaff
F. Castro, Bigna Lenggenhager, Daniel Zeller, Giovanni Pellegrino, Marco D’Alonzo, Giovanni Di Pino

Bibliographic record

VenueNeuroscience & Biobehavioral Reviews · 2023
Typereview
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsWestern University
FundersH2020 European Research CouncilEuropean Research CouncilIstituto Nazionale per l'Assicurazione Contro Gli Infortuni sul LavoroMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsNeuroprostheticsIllusionPsychologyCognitive psychologyVariety (cybernetics)Focus (optics)Phantom limbCognitive scienceAmputationNeuroscienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Our interaction with the world rests on the knowledge that we are a body in space and time, which can interact with the environment. This awareness is usually referred to as sense of embodiment. For the good part of the past 30 years, the rubber hand illusion (RHI) has been a prime tool to study embodiment in healthy and people with a variety of clinical conditions. In this paper, we provide a critical overview of this research with a focus on the RHI paradigm as a tool to study prothesis embodiment in individuals with amputation. The RHI relies on well-documented multisensory integration mechanisms based on sensory precision, where parietal areas are involved in resolving the visuo-tactile conflict, and premotor areas in updating the conscious bodily representation. This mechanism may be transferable to prosthesis ownership in amputees. We discuss how these results might transfer to technological development of sensorised prostheses, which in turn might progress the acceptability by users.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.298
GPT teacher head0.442
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2023
Admission routes1
Has abstractyes

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