Developing a Diagnostic Brain Imaging Protocol for Recent Onset Psychosis which Embodies Principles of Predictive Coding and Free Energy

Although schizophrenia is usually conceptualized of as a disorder of well formed hallucinations and delusions, its onset is more typically characterized by heightened arousal, a vague but pervasive feeling of unease and poorly formed misperceptions. This unstable constellation of symptoms challenges clinical diagnosis at a time when properly guided interventions are most likely to have the greatest long-term benefits. It is possible to frame this clinical picture as a disturbance in the capacity of the cortex to optimally form predictive models of the environment, to appropriately sample visual scenes in order to estimate the likelihood of such models and to hence minimize surprise in a dynamic social landscape. This approach suggests that manipulating the relationship between visual search strategies and natural scene statistics might be a sensitive means of quantifying core neurobiological deficits early in the course of emerging psychotic disorders. We are developing a diagnostic tool for the prodromal phase of these disorders which involves experimentally disturbing the relationship between visual saccades and the stream of natural images in well directed films. I will outline the conceptual and computational bases and early experimental results thus far obtained, including a canonical example of paranoia and theory of mind in a spaghetti western.