Recent Developments in the Habit Hypothesis of OCD and Compulsive Disorders

Gillan, Claire M.

doi:10.1007/7854_2020_199

Cited by 10 publications

(14 citation statements)

References 92 publications

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“…However, it is of great interest to understand how automatic habitual control operates in the normal circumstances of everyday life. It is also important to understand how brain disorders such as Parkinson’s disease 7, 8 , obsessive-compulsive disorder 9 , and drug addictions 10 lead to clinically dysfunctional patterns of habitual use of behaviour. Despite the importance of habitual control in daily life and clinical pathology, formal investigation of the inherent stimulus-response associations established in everyday life is in its infancy.…”

Section: Introductionmentioning

confidence: 99%

“…However, the relationship between these newly acquired stimulus-response associations and those acquired naturally over a lifetime when conducting everyday activities, is uncertain. It is equally important to understand how these important functional systems might malfunction, as reflected in brain disorders such as Parkinson’s disease (Bannard et al, 2019; Redgrave et al, 2010b), obsessive-compulsive disorder (Gillan, 2021), and drug addictions (Sjoerds et al, 2013), where dysfunctional patterns of habits are evident. Despite the obvious importance of habitual control, formal investigations of stimulus-response associations established in everyday-life are notably absent.…”

Section: Introductionmentioning

confidence: 99%

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An fMRI meta-analysis of the role of the striatum in everyday-life vs laboratory-developed habits

Guida

Michiels

Redgrave

et al. 2021

Preprint

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The dorsolateral striatum plays a major role in stimulus-response habits that are learned in the experimental laboratory. Here, we use meta-analytic procedures to identify the neural circuits activated during the execution of stimulus-response behaviours acquired in everyday-life and those activated by habits acquired in the laboratory. In the case of everyday-life habits we dissociated motor and associative components. We found that motor-dominant stimulus-response associations developed outside the laboratory engaged posterior dorsal putamen, supplementary motor area (SMA) and cerebellum. Associative components were also represented in the posterior putamen. Meanwhile, newly learned habits relied more on the anterior putamen with activation expanding to caudate and nucleus accumbens. Importantly, common neural representations for both naturalistic and laboratory based habits were found in posterior left and anterior right putamen. Our findings suggest a common striatal substrate for behaviours with significant stimulus-response associations, independently of whether they were acquired in the laboratory or everyday-life.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An fMRI meta-analysis of the role of the striatum in everyday-life vs laboratory-developed habits

Guida

Michiels

Redgrave

et al. 2021

Preprint

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“…Although it is challenging to move from a phenomenologically based thought process to a dynamical approach, we claim that a phase transition in understanding psychiatric disease as dynamical pathologies is inevitable. To this end, computational/theoretical frameworks have been synthesized to capture how OCD symptoms can be further analyzed from a trans-diagnostic and computational perspective (1).…”

Section: Discussionmentioning

confidence: 99%

“…Obsessions and compulsions might independently contribute to the pathophysiology (1,16). An alternative possibility posits that rather than goal-directed avoidance behaviors, compulsions derive from manifestations of excessive habit formation (50,51), thus obsessive thoughts may develop as a result of compulsive behavior.…”

Section: Co-morbidity and Trans-dimensional Analysismentioning

confidence: 99%

“…In this review, we assessed the evolution of the computational modeling efforts that aim to study some aspects of obsessive compulsive disorder (OCD) pathophysiology. The computational and theoretical investigations support the move from the currently used nosological classification toward trans-dimensional approaches (1). This trend is motivated by a necessity to gain a deeper and more biologically grounded understanding of the disease in order to develop personalized interventions.…”

Section: Introductionmentioning

confidence: 99%

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Computational Predictions for OCD Pathophysiology and Treatment: A Review

Szalisznyó

Silverstein

2021

Front. Psychiatry

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Obsessive compulsive disorder (OCD) can manifest as a debilitating disease with high degrees of co-morbidity as well as clinical and etiological heterogenity. However, the underlying pathophysiology is not clearly understood. Computational psychiatry is an emerging field in which behavior and its neural correlates are quantitatively analyzed and computational models are developed to improve understanding of disorders by comparing model predictions to observations. The aim is to more precisely understand psychiatric illnesses. Such computational and theoretical approaches may also enable more personalized treatments. Yet, these methodological approaches are not self-evident for clinicians with a traditional medical background. In this mini-review, we summarize a selection of computational OCD models and computational analysis frameworks, while also considering the model predictions from a perspective of possible personalized treatment. The reviewed computational approaches used dynamical systems frameworks or machine learning methods for modeling, analyzing and classifying patient data. Bayesian interpretations of probability for model selection were also included. The computational dissection of the underlying pathology is expected to narrow the explanatory gap between the phenomenological nosology and the neuropathophysiological background of this heterogeneous disorder. It may also contribute to develop biologically grounded and more informed dimensional taxonomies of psychopathology.

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