Attachment: a predictive coding approach

TL;DR

This paper presents a new predictive coding framework integrating attachment theory, neural processes, and early experiences to better understand how attachment strategies are formed and influenced by brain functions.

Contribution

It introduces a novel predictive coding approach that combines attachment theory with neuroanatomical models to explain the neural basis of attachment behaviors.

Findings

Neural processes influence attachment strategies.

Early attachment experiences shape neural mechanisms.

The framework links neuroanatomy with attachment behaviors.

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.