Attachment: a predictive processing approach

We introduce a novel predictive processing framework for studying attachment-related phenomena. Building off an established theory 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.Specifically, we propose that the type A strategies (analogous to "avoidant" or "dismissive" attachment) involve the attenuation of interoceptive prediction errors as an adaptive response to maltreatment, relieving stress in the short-term at the cost of interoceptive awareness in the long-term. Furthermore, we propose that type C strategies (analogous to "ambivalent/resistant" or "preoccupied" attachment) involve the attenuation of exteroceptive prediction errors to reflect the unreliability of external cues, motivating the obsessive seeking of information through increased vigilance and histrionic displays of affect. Finally, we explore the implications of our proposals for both interpreting the results of fMRI studies of attachment, and we make a few novel hypotheses that could have implications for the treatment of attachment-related psychopathology.