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Understanding decision-making deficits in neurological conditions: insights from models of natural action selection.

ABSTRACT: Models of natural action selection implicate fronto-striatal circuits in both motor and cognitive 'actions'. Dysfunction of these circuits leads to decision-making deficits in various populations. We review how computational models provide insights into the mechanistic basis for these deficits in Parkinson's patients and those with ventromedial frontal damage. We then consider implications of the models for understanding behaviour and cognition in attention-deficit/hyperactivity disorder (ADHD). Incorporation of cortical noradrenaline function into the model improves action selection in noisy environments and accounts for response variability in ADHD. We close with more general clinical implications.

SUBMITTER: Frank MJ

PROVIDER: S-EPMC2440777 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

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Understanding decision-making deficits in neurological conditions: insights from models of natural action selection.

Frank Michael J MJ Scheres Anouk A Sherman Scott J SJ

Philosophical transactions of the Royal Society of London. Series B, Biological sciences 20070901 1485

Models of natural action selection implicate fronto-striatal circuits in both motor and cognitive 'actions'. Dysfunction of these circuits leads to decision-making deficits in various populations. We review how computational models provide insights into the mechanistic basis for these deficits in Parkinson's patients and those with ventromedial frontal damage. We then consider implications of the models for understanding behaviour and cognition in attention-deficit/hyperactivity disorder (ADHD). ...[more]

PMID: 17428775

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Project description:BackgroundThere is sparse high-level evidence to guide treatment decisions for severe, acute cholecystitis (inflammation of the gallbladder). Therefore, treatment decisions depend heavily on individual surgeon judgment, which is highly variable and potentially amenable to personalized, data-driven decision support. We test the hypothesis that surgeons' treatment recommendations misalign with perceived risks and benefits for laparoscopic cholecystectomy (surgical removal) vs. percutaneous cholecystostomy (image-guided drainage).MethodsSurgery attendings, fellows, and residents applied individual judgement to standardized case scenarios in a live, web-based survey in estimating the quantitative risks and benefits of laparoscopic cholecystectomy vs. percutaneous cholecystostomy for both moderate and severe acute cholecystitis, as well as the likelihood that they would recommend cholecystectomy.ResultsSurgeons predicted similar 30-day morbidity rates for laparoscopic cholecystectomy and percutaneous cholecystostomy. However, a greater proportion of surgeons predicted low (<50%) likelihood of full recovery following percutaneous cholecystostomy compared with cholecystectomy for both moderate (30% vs. 2%, p < 0.001) and severe (62% vs. 38%, p < 0.001) cholecystitis. Ninety-eight percent of all surgeons were likely or very likely to recommend cholecystectomy for moderate cholecystitis; only 32% recommended cholecystectomy for severe cholecystitis (p < 0.001). There were no significant differences in predicted postoperative morbidity when respondents were stratified by academic rank or self-reported ability to predict complications or make treatment recommendations.ConclusionsSurgeon recommendations for severe cholecystitis were discordant with perceived risks and benefits of treatment options. Surgeons predicted greater functional recovery after cholecystectomy but less than one-third recommended cholecystectomy. These findings suggest opportunities to augment surgical decision-making with personalized, data-driven decision support.

Dataset Information

Understanding decision-making deficits in neurological conditions: insights from models of natural action selection.

Publications

Understanding decision-making deficits in neurological conditions: insights from models of natural action selection.

Similar Datasets

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