Evidence map›Paper›PMID 39679272›Full record

ArticleArXiv2025

Predictive Strategies for the Control of Complex Motor Skills: Recent Insights into Individual and Joint Actions.

Marta Russo, Antonella Maselli, Dagmar Sternad, Giovanni Pezzulo

Abstract readPreprint
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

4 authors.

Marta RussoInstitute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via Giandomenico Romagnosi 18A, 00196 Rome, Italy.
Antonella MaselliInstitute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via Giandomenico Romagnosi 18A, 00196 Rome, Italy.
Dagmar SternadInstitute for Experiential Robotics, Department of Biology, Department of Electrical and Computer Engineering, Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.
Giovanni PezzuloInstitute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via Giandomenico Romagnosi 18A, 00196 Rome, Italy.

Funding

Predictability in complex object controlR37HD087089 · NICHD · NORTHEASTERN UNIVERSITY · PI Dagmar Sternad · 2022 to 2026
$3.0M
CRCNS Research Proposal: Collaborative Research: Neural Basis of Motor ExpertiseR01NS120579 · NINDS · NORTHEASTERN UNIVERSITY · PI BATISTA, AARON PAUL, STERNAD, DAGMAR · 2020 to 2025
$2.0M
Predictability in Complex Object ControlR01HD087089 · NICHD · NORTHEASTERN UNIVERSITY · PI STERNAD, DAGMAR · 2015 to 2020
$1.8M
NICHD NIH HHS R01 HD087089NICHD NIH HHS R37 HD087089NINDS NIH HHS R01 NS120579
6 · The paper itself

Abstract

Humans perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The "predictive brain" framework suggests that mastering these skills relies on predictive mechanisms, raising the question of how we deploy predictions for real-time control and coordination. This review highlights two research lines, showing that during the control of complex objects people make the interaction with 'tools' predictable; and that during dyadic coordination people make their behavior predictable and legible for their partners. These studies demonstrate that to achieve sophisticated motor skills, we play "prediction tricks": we select subspaces of predictable solutions and make sensorimotor interactions more predictable and legible by and for others. This synthesis underscores the critical role of predictability in optimizing control strategies across contexts. Furthermore, it emphasizes the need for novel studies on the scope and limits of predictive mechanisms in motor control.

Indexed as

closed-loop controljoint actionmotor controlobject interactionspredictionpredictive brain

Identifiers

PMID39679272
PMCPMC11643226

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.