Individual differences in how infants change behaviours from spontaneous to instrumental

Young infants can change their behaviour and learn through interactions with novel environments. This ability has been demonstrated through group-averaged analyses. However, it remains unclear whether averaged behavioural changes accurately capture the diverse changes occurring at the individual level. To address this, we measured limb movement alterations in 185 infants aged 2 to 3 months before and after their arm was tethered to an overhead mobile and analysed individual differences in addition to conventional group analyses. While the group-averaged data showed a gradual increase in arm movements, individual learning curves rarely exhibited such simple gradual increases and instead displayed more complex patterns. To disentangle the complex movement patterns, we applied time-series clustering and dynamical systems modelling to our large-scale dataset. As a result, the infants were divided into distinct clusters with significant differences in spontaneous movements before learning, rather than after. A dynamical systems model further demonstrated that only differences in spontaneous movements could explain the diversity of overall behavioural changes. These findings indicate that the varying degrees of behavioural change reflect infants' unique learning processes rather than their learning capabilities. Furthermore, learning, as a process that reduces individual difference, suggest that infants harness their unique spontaneous movements to acquire instrumental behaviours.

Authors

Institutions

Publication Details

Journal
Communications Psychology
Published
2025-11-20
DOI
https://doi.org/10.1038/s44271-025-00333-3
Primary Topic
Child and Animal Learning Development
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Individual differences in how infants change behaviours from spontaneous to instrumental

Gentaro Taga, Hama Watanabe, Ryo Fujihira
Communications Psychology
Child and Animal Learning Development
article

Individual differences in how infants change behaviours from spontaneous to instrumental

Gentaro Taga, Hama Watanabe, Ryo Fujihira
article en

Abstract

Young infants can change their behaviour and learn through interactions with novel environments. This ability has been demonstrated through group-averaged analyses. However, it remains unclear whether averaged behavioural changes accurately capture the diverse changes occurring at the individual level. To address this, we measured limb movement alterations in 185 infants aged 2 to 3 months before and after their arm was tethered to an overhead mobile and analysed individual differences in addition to conventional group analyses. While the group-averaged data showed a gradual increase in arm movements, individual learning curves rarely exhibited such simple gradual increases and instead displayed more complex patterns. To disentangle the complex movement patterns, we applied time-series clustering and dynamical systems modelling to our large-scale dataset. As a result, the infants were divided into distinct clusters with significant differences in spontaneous movements before learning, rather than after. A dynamical systems model further demonstrated that only differences in spontaneous movements could explain the diversity of overall behavioural changes. These findings indicate that the varying degrees of behavioural change reflect infants' unique learning processes rather than their learning capabilities. Furthermore, learning, as a process that reduces individual difference, suggest that infants harness their unique spontaneous movements to acquire instrumental behaviours.

Communications PsychologyVol. 3(1)
Tokyo Fuji University (JP), Japan Graduate School of Education University (JP), The University of Tokyo (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 61%
Child and Animal Learning Development
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.