The impact of orbitofrontal dysfunction on cocaine addiction

Lucantonio, Federica; Stalnaker, Thomas A.; Shaham, Yavin; Niv, Yaron; Schoenbaum, Geoffrey

doi:10.1038/nn.3014

Cited by 185 publications

(182 citation statements)

References 99 publications

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“…A dual-system learning model ) has been combined with human brain imaging to examine specific ways an imbalance of these two systems might lead to maladaptive choice behavior in mental illness. Using this framework, it was found that repeated exposure to addictive drugs shifts behavior from model-based to model-free emphasis (Kurth-Nelson and Redish 2011, Lucantonio et al 2012. Likewise, data fitting by the dual-system model revealed that subjects diagnosed with obsessivecompulsive disorder display a bias towards model-free habit acquisition (Voon et al 2014).…”

Section: Endophenotypes Across Brain Disorder Categoriesmentioning

confidence: 99%

Computational Psychiatry

2016

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Psychiatric disorders such as autism and schizophrenia arise from abnormalities in brain systems that underlie cognitive, emotional and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically-realistic modeling bridging cellular and synaptic mechanisms with behavior, model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field. © 2014 Elsevier Inc. All rights reserved. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Neither Dr. Wang nor Dr. Krystal has any financial interests relevant to the advancement of computational psychiatry. to and engage with psychiatric research. Second, it will be important to develop a cadre of young psychiatrists who learn computational modeling, lest computational psychiatry.

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Section: Endophenotypes Across Brain Disorder Categoriesmentioning

confidence: 99%

Computational Psychiatry

2016

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“…In the former case, the increase in information that would occur from engaging the model-based system would be reduced. This could occur due to a general cognitive impairment (D. Schad, M. Rapp and Q. Huys, unpublished observations), perhaps due to deficits in prefrontal function, especially as a result of exposure to neurotoxic substances such as alcohol or cocaine (Goldstein et al, 2004;Briand et al, 2008;Lucantonio et al, 2012) but may also be characteristic of other populations (e.g. Darke et al 2000), and does involve the prefrontal cortex (Goldstein et al 2004; see also Volkow et al 2009).…”

Section: Shifts Towards Model-free Learning In Addictionmentioning

confidence: 99%

The role of learning-related dopamine signals in addiction vulnerability

Huys

Tobler

Hasler

et al. 2014

Progress in Brain Research

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Psychostimulants such as methylphenidate (MPH) and antidepressants such as fluoxetine (FLX) are widely used in the treatment of various mental disorders or as cognitive enhancers. These medications are often combined, for example, to treat comorbid disorders. There is a considerable body of evidence from animal models indicating that individually these psychotropic medications can have detrimental effects on the brain and behavior, especially when given during sensitive periods of brain development. However, almost no studies investigate possible interactions between these drugs. This is surprising given that their combined neurochemical effects (enhanced dopamine and serotonin neurotransmission) mimic some effects of illicit drugs such as cocaine and amphetamine. Here, we summarize recent studies in juvenile rats on the molecular effects in the mid-and forebrain and associated behavioral changes, after such combination treatments. Our findings indicate that these combined MPH + FLX treatments can produce similar molecular changes as seen after cocaine exposure while inducing behavioral changes indicative of dysregulated mood and motivation, effects that often endure into adulthood. Tables: 2 References: 254 ABSTRACT Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signalling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical and experimental accounts of phasic dopamine signalling, with implications for the role of learning-related dopamine signalling in addiction and related disorders. We describe the theoretical and behavioural characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction. CONTENTS

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“…Confirmant ces observations, l'inhibition optogéné-tique de l'OFC lors des sessions d'autostimulation avec punition réduit significativement la proportion d'individus compulsifs par rapport à des sessions sans inhibition de l'OFC 11 (Figure 2). Ces résultats confirment que l'activité neuronale dans l'OFC contribue à la transition vers une consommation compulsive en dépit des conséquences négatives, donc dans le développement de l'addiction [13,14]. Toutefois, de futures recherches devront déterminer si ces 11 Cette étude a été réalisée chez des souris exprimant le récepteur modifié DREADD (designer receptors exclusively activated by designer drugs) sensible au ligand CNO (clozapine-nitric oxide).…”

Section: Consommation Compulsive : Rôle Du Cortex Orbitofrontalunclassified