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Delusions and prediction error: clarifying the roles of behavioural and brain responses.

Corlett PR, Fletcher PC - Cogn Neuropsychiatry (2015)

Bottom Line: As well as reviewing the central ideas and concluding that the existing evidence base is broadly supportive of the model, they provide a detailed critique of some of the experiments that we have performed to study it.Though they conclude that the shortcomings that they identify in these experiments do not fundamentally challenge the prediction error model, we nevertheless respond to these criticisms.We defend the neuroimaging contrasts that we used to explore this model of psychosis arguing that, while any single contrast entails some ambiguity, our assumptions have been justified by our extensive background work before and since.

View Article: PubMed Central - PubMed

Affiliation: a Department of Psychiatry, Ribicoff Research Facility , Yale University , 34 Park Street, New Haven , CT , USA.

ABSTRACT
Griffiths and colleagues provided a clear and thoughtful review of the prediction error model of delusion formation [Cognitive Neuropsychiatry, 2014 April 4 (Epub ahead of print)]. As well as reviewing the central ideas and concluding that the existing evidence base is broadly supportive of the model, they provide a detailed critique of some of the experiments that we have performed to study it. Though they conclude that the shortcomings that they identify in these experiments do not fundamentally challenge the prediction error model, we nevertheless respond to these criticisms. We begin by providing a more detailed outline of the model itself as there are certain important aspects of it that were not covered in their review. We then respond to their specific criticisms of the empirical evidence. We defend the neuroimaging contrasts that we used to explore this model of psychosis arguing that, while any single contrast entails some ambiguity, our assumptions have been justified by our extensive background work before and since.

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Related in: MedlinePlus

Relating behavioural predictions to delusion-like ideas.Note: Scatterplot depicting the relationship between subjects' behavioural predictions about the blocked cue and their self-reported magical ideation measured with the Chapman scale (Eckblad & Chapman, 1983).
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f0001: Relating behavioural predictions to delusion-like ideas.Note: Scatterplot depicting the relationship between subjects' behavioural predictions about the blocked cue and their self-reported magical ideation measured with the Chapman scale (Eckblad & Chapman, 1983).

Mentions: When we examined brain responses to AB trials, we found that on average, dorsolateral prefrontal cortex (DLPFC) was less active than on control trials (Stage 1, C–, Stage 2, CD+). However, some subjects engaged DLPFC (and hence prediction error signalling) more than others in response to AB+ trials. This was manifest as behavioural learning about B, subjects with inappropriate prediction error responses at Stage 2, learned that B caused the allergy (Corlett & Fletcher, 2012). In response to Griffiths et al.'s concerns that we do not discuss behavioural data sufficiently, we returned to this data-set, examining the relationship between this inappropriate learning about redundant stimuli and the extent of subjects' odd beliefs (as measured by the magical ideation subscale scores from the Chapman Schizotypy scale). There was a significant correlation between subject's learning about the redundant stimuli (B?) and their odd-beliefs (n = 17, r = 0.5, p = 0.03, see Figure 1). We take Griffiths et al.'s point here, clearly simpler designs are easier to communicate and it is easier to use them to link inappropriate prediction error brain signal to delusion-like ideation unambiguously.


Delusions and prediction error: clarifying the roles of behavioural and brain responses.

Corlett PR, Fletcher PC - Cogn Neuropsychiatry (2015)

Relating behavioural predictions to delusion-like ideas.Note: Scatterplot depicting the relationship between subjects' behavioural predictions about the blocked cue and their self-reported magical ideation measured with the Chapman scale (Eckblad & Chapman, 1983).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4305467&req=5

f0001: Relating behavioural predictions to delusion-like ideas.Note: Scatterplot depicting the relationship between subjects' behavioural predictions about the blocked cue and their self-reported magical ideation measured with the Chapman scale (Eckblad & Chapman, 1983).
Mentions: When we examined brain responses to AB trials, we found that on average, dorsolateral prefrontal cortex (DLPFC) was less active than on control trials (Stage 1, C–, Stage 2, CD+). However, some subjects engaged DLPFC (and hence prediction error signalling) more than others in response to AB+ trials. This was manifest as behavioural learning about B, subjects with inappropriate prediction error responses at Stage 2, learned that B caused the allergy (Corlett & Fletcher, 2012). In response to Griffiths et al.'s concerns that we do not discuss behavioural data sufficiently, we returned to this data-set, examining the relationship between this inappropriate learning about redundant stimuli and the extent of subjects' odd beliefs (as measured by the magical ideation subscale scores from the Chapman Schizotypy scale). There was a significant correlation between subject's learning about the redundant stimuli (B?) and their odd-beliefs (n = 17, r = 0.5, p = 0.03, see Figure 1). We take Griffiths et al.'s point here, clearly simpler designs are easier to communicate and it is easier to use them to link inappropriate prediction error brain signal to delusion-like ideation unambiguously.

Bottom Line: As well as reviewing the central ideas and concluding that the existing evidence base is broadly supportive of the model, they provide a detailed critique of some of the experiments that we have performed to study it.Though they conclude that the shortcomings that they identify in these experiments do not fundamentally challenge the prediction error model, we nevertheless respond to these criticisms.We defend the neuroimaging contrasts that we used to explore this model of psychosis arguing that, while any single contrast entails some ambiguity, our assumptions have been justified by our extensive background work before and since.

View Article: PubMed Central - PubMed

Affiliation: a Department of Psychiatry, Ribicoff Research Facility , Yale University , 34 Park Street, New Haven , CT , USA.

ABSTRACT
Griffiths and colleagues provided a clear and thoughtful review of the prediction error model of delusion formation [Cognitive Neuropsychiatry, 2014 April 4 (Epub ahead of print)]. As well as reviewing the central ideas and concluding that the existing evidence base is broadly supportive of the model, they provide a detailed critique of some of the experiments that we have performed to study it. Though they conclude that the shortcomings that they identify in these experiments do not fundamentally challenge the prediction error model, we nevertheless respond to these criticisms. We begin by providing a more detailed outline of the model itself as there are certain important aspects of it that were not covered in their review. We then respond to their specific criticisms of the empirical evidence. We defend the neuroimaging contrasts that we used to explore this model of psychosis arguing that, while any single contrast entails some ambiguity, our assumptions have been justified by our extensive background work before and since.

Show MeSH
Related in: MedlinePlus