Evidence map›Paper›PMID 42266202›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

Neurophysiological mechanisms of optimized graphomotor performance in biscriptuals.

Yitong Zuo, Gaëlle Alhaddad, Víctor J López-Madrona, Laure Spieser, Antonella Iannotta, Jean-Claude Gilhodes, Benjamin Morillon, Marieke Longcamp

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yitong ZuoAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.ORCID https://orcid.org/0009-0004-7510-7088
Gaëlle AlhaddadAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.
Víctor J López-MadronaAix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France.
Laure SpieserAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.
Antonella IannottaAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.
Jean-Claude GilhodesAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.
Benjamin MorillonAix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France.
Marieke LongcampAix Marseille Université, CNRS, CRPN, Centre de Recherche en Psychologie et Neurosciences, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many literate adults master two writing systems: a phenomenon termed biscriptuality. Biscriptuals do not just juggle two scripts-their graphomotor coordination also generally outperforms that of monoscriptuals, suggesting that some components of their motor system have been optimized. To uncover the neurocognitive foundations of this biscriptual advantage, we synchronized a loop-tracing task on a digitizing tablet with electroencephalographical (EEG) recordings. Theta (4-7 Hz) and beta (13-30 Hz) oscillatory dynamics were analyzed to test whether biscriptuals display better optimized planning and monitoring, and/or better sensorimotor control. At the behavioral level, biscriptuals displayed a robust advantage in tracing frequency and stability compared to monoscriptuals. At the neural level, biscriptuals showed lower frontal theta power than monoscriptuals, with frontal theta power positively correlated with behavioral variability. Optimization of predictive inference mediated by midfrontal theta oscillations thus stands out as a hallmark of the biscriptual advantage. Biscriptuals also displayed a lower degree of beta synchronization over parieto-occipital electrodes than monoscriptuals, with beta power being less correlated with kinematic dynamics. Similar effects in the beta band were observed for all participants when task difficulty decreased. These effects suggest higher reliance on sensory feedback when graphomotor execution is more demanding. Overall, these results call for a model of handwriting control where prefrontal and sensorimotor components contribute to implementing internal predictive models, whose accuracy and reliability depend on the type of expertise acquired when learning to write.

Indexed as

biscriptualityEEGgraphomotor controlhandwritingneural oscillationspredictive coding

Identifiers

PMID42266202
PMCPMC13245215

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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.