Handedness between bodies: toward a relational account of manual laterality

Papadatou-Pastou and colleagues’ rapid review maps 47 named tasks comparing the relative skill of the two hands. From a relational perspective, most tasks assess a person acting alone. This provides a baseline, but not a complete account of how manual asymmetry is expressed. Evidence that hand choice and attributed handedness vary with target animacy, communicative purpose, partner role, emotional context, or viewpoint raises a further question: can relative hand performance also change when the same or a matched action is embedded in a social context? We use relational handedness to denote systematic variation in hand choice or relative hand performance generated or modulated by an actor’s relation to a partner or observer, given a social goal and spatial arrangement. Attributed handedness addresses the neighboring question of how the observer–agent relation shapes perceived manual laterality and helps identify relational variables to manipulate. Relational handedness is not a third score alongside preference and skill, but a testing condition potentially assessing their contextual stability. Future batteries could pair validated individual tasks with matched social and nonsocial conditions and test the hand-by-condition interaction. This would preserve the distinction between preference and skill while separating task noise from meaningful relational modulation.

Authors

Institutions

Publication Details

Journal
Laterality Asymmetries of Body Brain and Cognition
Published
2026-09-25
DOI
https://doi.org/10.1080/1357650x.2026.2738687
Primary Topic
Hemispheric Asymmetry in Neuroscience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Handedness between bodies: toward a relational account of manual laterality

Luca Tommasi, Gianluca Malatesta
Laterality Asymmetries of Body Brain and Cognition
Hemispheric Asymmetry in Neuroscience
article

Handedness between bodies: toward a relational account of manual laterality

Luca Tommasi, Gianluca Malatesta
article en

Abstract

Papadatou-Pastou and colleagues’ rapid review maps 47 named tasks comparing the relative skill of the two hands. From a relational perspective, most tasks assess a person acting alone. This provides a baseline, but not a complete account of how manual asymmetry is expressed. Evidence that hand choice and attributed handedness vary with target animacy, communicative purpose, partner role, emotional context, or viewpoint raises a further question: can relative hand performance also change when the same or a matched action is embedded in a social context? We use relational handedness to denote systematic variation in hand choice or relative hand performance generated or modulated by an actor’s relation to a partner or observer, given a social goal and spatial arrangement. Attributed handedness addresses the neighboring question of how the observer–agent relation shapes perceived manual laterality and helps identify relational variables to manipulate. Relational handedness is not a third score alongside preference and skill, but a testing condition potentially assessing their contextual stability. Future batteries could pair validated individual tasks with matched social and nonsocial conditions and test the hand-by-condition interaction. This would preserve the distinction between preference and skill while separating task noise from meaningful relational modulation.

Laterality Asymmetries of Body Brain and Cognition
University of Chieti-Pescara (IT)
Reduced inequalities
Openalex Percentile: Top 10%
Hemispheric Asymmetry in Neuroscience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.