English

Attachment: a predictive coding approach

Neurons and Cognition 2025-05-16 v2

Abstract

We introduce a novel predictive coding framework for studying attachment theory. Building off an established model of attachment, the dynamic-maturational model (DMM), as well as the neuroanatomical Embodied Predictive Interoception Coding (EPIC) model of interoception and emotion, we not only elucidate how neural processes can shape attachment strategies, but also explore how early attachment experiences can shape those processes in the first place.

Keywords

Cite

@article{arxiv.2505.05476,
  title  = {Attachment: a predictive coding approach},
  author = {Anthony Lin},
  journal= {arXiv preprint arXiv:2505.05476},
  year   = {2025}
}

Comments

27 pages; major revision to model, emphasizing the role of domain-general processes in the attachment system

R2 v1 2026-06-28T23:26:08.049Z