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Perceptual classification in a rapidly changing environment.

ABSTRACT: Humans and monkeys can learn to classify perceptual information in a statistically optimal fashion if the functional groupings remain stable over many hundreds of trials, but little is known about categorization when the environment changes rapidly. Here, we used a combination of computational modeling and functional neuroimaging to understand how humans classify visual stimuli drawn from categories whose mean and variance jumped unpredictably. Models based on optimal learning (Bayesian model) and a cognitive strategy (working memory model) both explained unique variance in choice, reaction time, and brain activity. However, the working memory model was the best predictor of performance in volatile environments, whereas statistically optimal performance emerged in periods of relative stability. Bayesian and working memory models predicted decision-related activity in distinct regions of the prefrontal cortex and midbrain. These findings suggest that perceptual category judgments, like value-guided choices, may be guided by multiple controllers.

SUBMITTER: Summerfield C

PROVIDER: S-EPMC3975575 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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Perceptual classification in a rapidly changing environment.

Summerfield Christopher C Behrens Timothy E TE Koechlin Etienne E

Neuron 20110801 4

Humans and monkeys can learn to classify perceptual information in a statistically optimal fashion if the functional groupings remain stable over many hundreds of trials, but little is known about categorization when the environment changes rapidly. Here, we used a combination of computational modeling and functional neuroimaging to understand how humans classify visual stimuli drawn from categories whose mean and variance jumped unpredictably. Models based on optimal learning (Bayesian model) a ...[more]

PMID: 21867887

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Project description:IntroductionAn overview of the requirements for the head of a surgical department in Germany should be given.Materials and methodsA retrospective literature research on surgical professional policy publications of the last 10 years in Germany was conducted.ResultsSurveys show that commercial influences on medical decisions in German hospitals have today become an everyday, predominantly negative, actuality. Nevertheless, in one survey, 82.9% of surgical chief physicians reported being very satisfied with their profession, compared with 61.5% of senior physicians and only 43.4% of hospital specialists. Here, the chief physician is challenged. Only 70% of those surveyed stated that they could rely on their direct superiors when difficulties arose at work, and only 34.1% regarded feedback on the quality of their work as sufficient. The high distress rate in surgery (58.2% for all respondents) has led to a lack in desirability and is reflected in a shortage of qualified applicants for resident positions. In various position papers, surgical residents (only 35% describe their working conditions as good) demand improved working conditions. Chief physicians are being asked to facilitate a suitable work-life balance with regular working hours and a corporate culture with participative management and collegial cooperation. Appreciation of employee performance must also be expressed. An essential factor contributing to dissatisfaction is that residents fill a large part of their daily working hours with non-physician tasks. In surveys, 70% of respondents stated that they spend up to ≥3 h a day on documentation and secretarial work.DiscussionThe chief physician is expected to relieve his medical staff by employing non-physician assistants to take care of non-physician tasks. Transparent and clearly structured training to achieve specialist status is essential. It has been shown that a balanced work-life balance can be achieved for surgeons. Family and career can be reconciled in appropriately organized departments by making use of part-time and shift models that exclude 24-h shifts and making working hours more flexible.

Dataset Information

Perceptual classification in a rapidly changing environment.

Publications

Perceptual classification in a rapidly changing environment.

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