mlsanityData to 13 Oct 2026

Re-assessing the evidence for mental rotation abilities in children using computational models

arXiv 2512.17972 ↗First posted 19 Dec 2025q-bio.NC cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

There is strong and diverse evidence for mental rotation (MR) abilities in adults. However, current evidence for MR in children rests on just a few behavioral paradigms adapted from the adult literature. Here, we leverage recent computational models of the development of children's object recognition abilities to re-assess the evidence for MR in children. The computational models simulate infants' acquisition of object representations during embodied interactions with objects. We consider two different object recognition strategies, different from MRs, and assess their ability to replicate results from three classical MR tasks assigned to children between the ages of 6 months and 5 years. Our results show that MR may play no role in producing the results obtained from children younger than 5 years. In fact, we find that a simple recognition strategy that reflects a pixel-wise comparison of stimuli is sufficient to model children's behavior in the most used MR task. Thus, our study reopens the debate on how and when children develop genuine MR abilities.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 8 of its 61 references that are in the map. First posted on arXiv 19 Dec 2025.

Builds on

8 of 61 references.

References · 8

  1. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,009
  2. 2023TD-MPC2: Scalable, Robust World Models for Continuous Controlcited by 491
  3. 2024DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planningcited by 369
  4. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 326
  5. 2023MVImgNet: A Large-scale Dataset of Multi-view Imagescited by 219
  6. 2022Time to augment self-supervised visual representation learningcited by 15
  7. 2024Self-supervised visual learning from interactions with objectscited by 10
  8. 2023Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Playcited by 5

Built on by

Not cited yet.