Towards a computational psychiatry of juvenile obsessive-compulsive disorder

Abstract

Obsessive-Compulsive Disorder (OCD) most often emerges during adolescence, but we know little about the aberrant neural and cognitive developmental mechanisms that underlie its emergence during this critical developmental period. To move towards a computational psychiatry of juvenile OCD, we review studies on the computational, neuropsychological and neural alterations in juvenile OCD and link these findings to the adult OCD and cognitive neuroscience literature. We find consistent difficulties in tasks entailing complex decision making and set shifting, but limited evidence in other areas that are altered in adult OCD, such as habit and confidence formation. Based on these findings, we establish a neurocomputational framework that illustrates how cognition can go awry and lead to symptoms of juvenile OCD.We link these possible aberrant neural processes to neuroimaging findings in juvenile OCD and show that juvenile OCD is mainly characterised by disruptions of complex reasoning systems.

Consistency within change: Evaluating the psychometric properties of a widely-used predictive-inference task

“…Tracking participants' actions on each trial therefore allowed researchers to characterise learning 1,3,4,12,15,20 , arousal 2,6 , and neural mechanisms 7,8,11,19,21 in relation to these environmental changes. This cognitive flexibility is particularly relevant to psychiatric research, as cognitive inflexibility has been associated with several psychiatric disorders 13,18,[22][23][24][25][26][27][28][29][30][31][32] . For example, a study using this predictive-inference task showed that schizophrenic patients were prone to extreme forms of learning (i.e., little behavioural adaptation to new evidence and complete adaptation to it) 18 while patients with obsessive-compulsive disorder (OCD) have been seen to primarily over-emphasise new information at the cost of rashly discarding previously encountered evidence 13 .…”

Along the fringes of Agency: neurodevelopmental account of the obsessive mind

“…It is interesting to compare this neurodevelopmental model with recent computational models on OCD. Despite its developmental focus on developmental features, a recent computational account of juvenile OCD resulted in a top-down perspective, with origins of neurocognitive impairments in OCD putatively set at the level of complex reasoning systems, formation of meta-confidence for functioning systems arbitration process of the meta-controller 47 . Instead, it is possible to detect some affinities between our neurodevelopmental model and a recent computational model of OCD 48 .…”

“…Despite its developmental focus on developmental features, a recent computational account of juvenile OCD resulted in a top-down perspective, with origins of neurocognitive impairments in OCD putatively set at the level of complex reasoning systems, formation of meta-confidence for functioning systems arbitration process of the metacontroller. 47 Instead, it is possible to detect some affinities between our neurodevelopmental model and a recent computational model of OCD. 48 Indeed, the core of our model, reduced SoA ontogenetically emerging from an individual history of altered sensorimotor prediction, due to altered CD mechanisms, has affinities with the core of such computational model of OCD, that is, an excessive uncertainty regarding state transitions, especially action-dependent transition.…”

Computational Predictions for OCD Pathophysiology and Treatment: A Review

“…Most previous work focused on distinguishing between only two RL systems: model-based and model-free RL (14), as prototype extremes. Recent evidence shows that there are likely several parallel systems present in the brain, which are involved in OCD pathology and their dynamics is best captured by a mixture of RL algorithms (18,53). It has been suggested that model-free learning might simply be an imperfect formalization of habit-learning (1).…”

“…Thus, re-consideration is needed about this model-free/modelbased dichotomy. For example, it was found that model-free spatial-motor outcome-irrelevant learning generalized across distinct state features (31,53). In a meta-study of juvenile OCD (53), subjects had difficulties in model-based complex decision-making and set shifting.…”