Attachment: a predictive coding approach

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. Returning to John Bowlby's original vision for attachment theory, our framework is based on four simple, empirically-supported principles that can easily be interpreted with predictive coding. We apply our framework to further our understanding of the attachment strategies in the DMM. Specifically, we propose that the type A strategies (analogous to "avoidant" or "dismissive" attachment) involve the suppression of interoceptive prediction errors as an adaptive response to maltreatment, relieving stress in the short-term at the cost of interoceptive awareness and conceptual knowledge in the long-term. Furthermore, we propose that type C strategies (analogous to "ambivalent/resistant" or "preoccupied" attachment) involve the suppression 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, making several novel hypotheses that could have implications for the treatment of attachment-related psychopathology.