Impaired error-likelihood prediction in medial prefrontal cortex in schizophrenia

Krawitz, Adam; Braver, Todd S.; Deanna, M; Brown, Joshua W.

doi:10.1016/j.neuroimage.2010.09.027

Cited by 26 publications

(24 citation statements)

References 59 publications

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“…There was also evidence of overall increased signaling to high risk/reward 'Success' outcomes in caudal ACC and increased signaling to low risk/reward 'Explode' outcomes in IFG and caudal ACC from baseline to follow-up. These results may be consistent with an increased surprise signal to unexpected outcomes (i.e., high risk successes and low risk explosions) in recovery which may, in turn, reflect formation of stronger expectancies based on previous outcomes (Alexander and Brown, 2010, 2011, 2014; Krawitz et al, 2011). However, we cannot exclude the possibility that this is a learning effect, unrelated to substance use recovery.…”

Section: Discussionsupporting

confidence: 62%

A preliminary study of longitudinal neuroadaptation associated with recovery from addiction

Förster

Finn

Brown

2016

Drug and Alcohol Dependence

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Background Few studies have explored longitudinal change in event-related brain responses during early recovery from addiction. Moreover, existing findings yield evidence of both increased and decreased signaling within reward and control centers over time. The current study explored reward- and control-related signals in a risky decision-making task and specifically investigated parametric modulations of the BOLD signal, rather than signal magnitude alone. It was hypothesized that risk-related signals during decision-making and outcome evaluation would reflect recovery and that change in specific signals would correspond with improved treatment outcomes. Methods Twenty-one substance dependent individuals were recruited upon enrollment in community-based substance use treatment programs, wherein they received treatment-as-usual. Participants completed functional neuroimaging assessments at baseline and 3-month follow-up while performing the Balloon Analogue Risk Task (BART). Risk- and reward-sensitive signals were identified using parametric modulators. Substance use was tracked throughout the 3-month study interval using the timeline follow-back procedure. Results Longitudinal contrasts of parametric modulators suggested improved formation of risk-informed outcome expectations at follow-up. Specifically, a greater response to high risk (low-likelihood) positive feedback was identified in caudal anterior cingulate cortex (ACC) and a greater response to low risk (low-likelihood) negative feedback was identified in caudal ACC and inferior frontal gyrus. In addition, attenuation of a ventromedial prefrontal cortex (vmPFC) “reward-seeking” signal (i.e., increasing response with greater reward) during risky decisions at follow-up was associated with less substance use during the study interval. Conclusions Changes in risk- and reward-related signaling in ACC/vmPFC appear to reflect recovery and may support sobriety.

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Section: Discussionsupporting

confidence: 62%

A preliminary study of longitudinal neuroadaptation associated with recovery from addiction

Förster

Finn

Brown

2016

Drug and Alcohol Dependence

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“…A similar argument based on a deficit in a neural comparator linking perception and action impairment has been made to extend this concept into cognitive systems to explain impaired theory of mind and emotional response deficits (Frith et al, 2000; Jeannerod, 2003). Indeed, a recent study has reported evidence for a deficit in error-likelihood prediction in the mPFC in schizophrenia patients in the context of a working-memory task (Krawitz et al, 2011). Additional behavioral evidence for breakdown of a comparator mechanism linking perception and action during self-other interactions is impaired gesture and movement imitation (Matthews et al, 2013) and emotional contagion (unconscious imitation of smiling and yawning – Haker and Rössler, 2009) in patients.…”

Section: Self-processing In Schizophreniamentioning

confidence: 99%

What Can Psychiatric Disorders Tell Us about Neural Processing of the Self?

Zhao

Luo

et al. 2013

Front. Hum. Neurosci.

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Many psychiatric disorders are associated with abnormal self-processing. While these disorders also have a wide-range of complex, and often heterogeneous sets of symptoms involving different cognitive, emotional, and motor domains, an impaired sense of self can contribute to many of these. Research investigating self-processing in healthy subjects has facilitated identification of changes in specific neural circuits which may cause altered self-processing in psychiatric disorders. While there is evidence for altered self-processing in many psychiatric disorders, here we will focus on four of the most studied ones, schizophrenia, autism spectrum disorder (ASD), major depression, and borderline personality disorder (BPD). We review evidence for dysfunction in two different neural systems implicated in self-processing, namely the cortical midline system (CMS) and the mirror neuron system (MNS), as well as contributions from altered inter-hemispheric connectivity (IHC). We conclude that while abnormalities in frontal-parietal activity and/or connectivity in the CMS are common to all four disorders there is more disruption of integration between frontal and parietal regions resulting in a shift toward parietal control in schizophrenia and ASD which may contribute to the greater severity and delusional aspects of their symptoms. Abnormalities in the MNS and in IHC are also particularly evident in schizophrenia and ASD and may lead to disturbances in sense of agency and the physical self in these two disorders. A better future understanding of how changes in the neural systems sub-serving self-processing contribute to different aspects of symptom abnormality in psychiatric disorders will require that more studies carry out detailed individual assessments of altered self-processing in conjunction with measurements of neural functioning.

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“…The current evidence of regional distinctions within the ACC suggests that these two signals may not only exist within ACC but also be spatially distinct. For example, several recent studies have outlined distinct subregions of the ACC based on probabilistic connectivity (Beckmann et al, 2009), dynamic causal modeling (Fan et al, 2008), motor representations (Amiez and Petrides, 2012), neural deficits in schizophrenia (Krawitz et al, 2011), and experimental paradigms incorporating error, conflict, and task-switching effects into a single design (Nee et al, 2011), highlighting the anatomical and functional heterogeneity of the ACC. The current study was designed to test whether a model-based analysis could identify these prediction and outcome processes in the ACC, and if so, whether these processes are spatially distinct or overlapping.…”

Section: Introductionmentioning

confidence: 99%

Distinct regions of anterior cingulate cortex signal prediction and outcome evaluation

Jahn

Nee²,

Alexander

et al. 2014

NeuroImage

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A number of theories have been proposed to account for the role of anterior cingulate cortex (ACC) and the broader medial prefrontal cortex (mPFC) in cognition. The recent Prediction of Response Outcome (PRO) computational model casts the mPFC in part as performing two theoretically distinct functions: learning to predict the various possible outcomes of actions, and then evaluating those predictions against the actual outcomes. Simulations have shown that this new model can account for an unprecedented range of known mPFC effects, but the central theory of distinct prediction and evaluation mechanisms within ACC remains untested. Using combined computational neural modeling and fMRI, we show here that prediction and evaluation signals are indeed each represented in the ACC, and furthermore, they are represented in distinct regions within ACC. Our task independently manipulated both the number of predicted outcomes and the degree to which outcomes violated expectancies, the former providing assessment of regions sensitive to prediction and the latter providing assessment of regions sensitive to evaluation. Using quantitative regressors derived from the PRO computational model, we show that prediction-based model signals load on a network including the posterior and perigenual ACC, but outcome evaluation model signals load on the mid-dorsal ACC. These findings are consistent with distinct prediction and evaluation signals as posited by the PRO model and provide new perspective on a large set of known effects within ACC.

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Impaired error-likelihood prediction in medial prefrontal cortex in schizophrenia

Cited by 26 publications

References 59 publications

A preliminary study of longitudinal neuroadaptation associated with recovery from addiction

A preliminary study of longitudinal neuroadaptation associated with recovery from addiction

What Can Psychiatric Disorders Tell Us about Neural Processing of the Self?

Distinct regions of anterior cingulate cortex signal prediction and outcome evaluation

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