An Introduction to Adaptive Narrative Control Theory
Every so often as a researcher, I come across a theoretical paper that aligns so well with my own thinking that I can’t help but want to share it. Last week, I read “The computational unconscious: Adaptive narrative control, psychopathology, and subjective well-being” by George Deane and colleagues, which was one such paper. In this blog post, I want to describe the main ideas in the paper, which center around a model of the origin and persistence of psychopathology called Adaptive Narrative Control Theory (ANC). My motivation for writing this is twofold. Firstly, I think that the concept is extremely useful colloquially for thinking about how we acquire certain “unhealthy” mental habits of thought. Secondly, I wanted to ensure that I understood the theory well myself, and I have found that it is indeed the case that the best way to ensure that you have learned something is to try to teach it.
The authors build on the conceptual framework of active inference which is a computational way of understanding how and why living organisms form minds that I have previously written about here. As a quick introduction, active inference views the brain as a sophisticated prediction machine. Our brains constantly build and refine internal ‘generative models’ to understand and anticipate both the world around us and our own internal states. When reality doesn’t match these predictions, a ‘prediction error’ occurs — a surprise signal that the brain tries to minimize. We primarily do this in two ways: either by acting to make our predictions come true, or by updating our internal models to better reflect reality. When we typically think of action, we think of acting externally to change the world, but it is also possible to act internally on our own mental models as well. It is this latter kind of action that is of interest to us here.
Adaptive Narrative Control is the idea that during the course of our lives we learn to take mental actions in order to avoid negative affect and steer our experience towards positive affect. From an active inference perspective, this involves selecting actions to minimize the prediction error associated with aversive states and maximize evidence for preferred states of being. We can break this down a bit further. The “narrative control” part of the term corresponds to the fact that we learn to take sequences of mental actions that go on to make up a coherent narrative flow of our everyday experience — essentially, we are trying to maintain a consistent, predictable story about ourselves and the world. The “adaptive” part of the term refers to the fact that doing so ideally allows us to accomplish our goals in life and experience on average more positive affect than negative affect. Paradoxically, as the authors of the paper point out, trying to avoid negative affect in the short term can actually make it more difficult for us to do so in the long term, sometimes catastrophically so. This forms the primary insight of the paper.
To back up a bit, though, what exactly is a mental action? It is a manipulation of how and to what we direct our attention during conscious experience. In active inference terms, attention can be thought of as a way to select and weigh information, increasing the precision or confidence with which we represent it to ourselves. At any given moment, we can direct our attention to aspects of our sensory world, but we can also direct attention to our thoughts, memories, emotions, bodily sensations, or any piece of qualitative information that we have access to. For example, right now I am engaged in the mental action of attending to the words on the screen as I type them. For every object that we attend to, we are necessarily actively excluding myriad other potential objects of attention at the same time. In my case I am avoiding attending to the pain in my lower back (or at least I was until I wrote this sentence). In reality, mental actions are never taken in isolation, but are part of a sequence of actions making up a larger attentional strategy our brain deploys. These strategies for sequences of actions are called policies.
As we learn to take certain mental actions and to avoid others, we slowly develop certain habits of attention, which then become habits of thought and emotion. These habits form at the neural level, through the reinforcement of certain sequences of mental action which get wired into our brains through synaptic plasticity. Due to this process, what begins as a mental action that we took intentionally may eventually become a mental action that we take almost automatically without thinking about it. This occurs because the selected policy has consistently led to a reduction in prediction error (e.g., successfully avoided a negative feeling) in specific contexts, reinforcing its future selection. This would not be a problem if every mental action that we learn were completely optimal in all situations. Often what happens is that in the context we initially learn some policy for mental action that is indeed adaptive for that time and place. Our lives change however, and we later find ourselves in a different context in which that policy is no longer adaptive, failing to minimize long-term prediction error or leading us away from our overall goals, yet we’ve learned a habit of it that we simply repeat automatically, to our disadvantage.
Let’s take the example of a bright pre-med college student taking an important test in their biology class. The student has studied hard for the test and expects to do well on it. To their dismay, they find that the test is much more difficult than expected. Once the test is graded and returned to them, they find that they failed it by a few points. This realization is incredibly painful for them, generating significant prediction error that clashes with their model of themselves as a successful student and future doctor, and interferes with their sense of self-worth and identity. In response to this revelation, they deploy a sequence of mental actions (a policy) which enable them to avoid thinking about the failed test and its implications for their desired career. In the short term they are able to relieve their stress and enjoy their college activities and time with other students. In the long term however, their intentional inattention to the failed test results in them not putting as much effort into the next biology exam, and this time they do even worse than before. In response, they ignore this bad score too, and soon find that they are completely unprepared and unqualified for medical school.
What went wrong with this student? The problem is that although their mental action policy was adaptive on a short timescale (sparing their sense of self-worth as a college student by temporarily reducing distressing prediction errors), it was ultimately maladaptive at the longer timescale (sacrificing their career aspirations as an adult). By taking mental actions to ignore the negative affect associated with the reality of their failed exam, the student denied themselves the critical epistemic value that was associated with that failure. Namely, the information that they needed to update their internal model and adopt a more effective studying strategy for the subsequent college exams. It isn’t just information about the world that the student misses out on. According to ANC, the student also fails to learn a more nuanced understanding of their own affective states, meaning their generative model of their own emotions remains imprecise. What should be a granular differentiation between negative affect states, such as “failing a test is bad but not the end of the world” becomes generalized to “all bad things are the end of the world.” This makes the student much less capable of managing their emotions in the long term when other inevitable stressors present themselves.
The solution to the student’s problem seems clear: they need to attend to the reality of their situation head-on and learn from it appropriately, allowing the prediction errors to update their model of themselves and their strategies. Of course, this is easier said than done. Depending on how entrenched a certain policy is, it may be hard for someone to even be aware that they are engaging in it. Furthermore, although it may be maladaptive, it still likely provides some level of psychological relief (short-term prediction error reduction), otherwise it wouldn’t have been learned in the first place. We find that, from one perspective, the entirety of the field of psychotherapy can be understood as helping people to do just this: attend to things that they had previously trained themselves to avoid. More concretely, what a psychotherapeutic relationship enables is for the client to learn to take the mental actions necessary to encounter difficult emotions, thoughts, and memories that they had previously learned to avoid at some point earlier in their life, facilitating the revision of maladaptive generative models.
Beyond psychotherapy, meditation and the use of psychedelics are two other broad techniques which can be used to accomplish a similar goal of modifying the attentional policy to become less avoidant. In the case of meditation, an individual will actively practice keeping their attention on the object of meditation (i.e. the breath, a flame, etc.). At the same time, they avoid taking any other mental actions, including those avoidant ones which had become habitual. This can be seen as a process of observing prediction errors related to internal states without reflexively deploying old policies to suppress them, thereby increasing the precision of ascending sensory information about one’s internal state. Psychedelics on the other hand make it more likely that we will take mental actions that we might not have in the past, including those that bring us into closer contact with previously avoided mental content. They might achieve this by temporarily reducing the precision of high-level priors (strong beliefs or predictions), allowing for a greater exploration of alternative models and policies. MDMA-assisted therapy in particular has demonstrated impressive success with enabling individuals with PTSD to attend to and process difficult traumatic memories that would otherwise be near-impossible to deal with and overwhelming to the nervous system.
At this point, readers with a background in psychology might find all this a little familiar, and for good reason. Although the authors of ANC frame it using the formalisms of computational psychiatry, they readily admit that the theory is in many ways simply a modernized version of Sigmund Freud’s theory of repression. For Freud, experiences which were too difficult for us to deal with consciously are actively repressed into the unconscious where they no longer can directly interfere with the daily life of the individual. The role of psychoanalysis is then to perform a kind of diving expedition to find those repressed contents and bring them to the surface, making them consciously accessible once again. ANC takes these ideas and grounds them in the language of modern scientific theory, specifically the frameworks of predictive processing and active inference. In doing so, it is able to adeptly bridge the century-wide gap, both providing concrete, computationally plausible mechanisms through which to understand repression as well as enabling the generalization of the theory to new forms of therapeutic practice. I think it is a valuable contribution, and I am looking forward to engaging with it in my own theoretical work going forward.
