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• W2896567555 abstract "Abstract Many skills rely on performing noisy mental computations on noisy sensory measurements. Bayesian models suggest that humans compensate for measurement noise and reduce behavioral variability by biasing perception toward prior expectations. Whether a similar strategy is employed to compensate for noise in downstream mental and sensorimotor computations is not known. We tested humans in a battery of tasks and found that tasks which involved more complex mental transformations resulted in increased bias, suggesting that humans are able to mitigate the effect of noise in both sensorimotor and mental transformations. These results indicate that humans delay inference in order to account for both measurement noise and noise in downstream computations." @default.
• W2896567555 created "2018-10-26" @default.
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• W2896567555 date "2018-10-24" @default.
• W2896567555 modified "2023-10-02" @default.
• W2896567555 title "Late Bayesian inference in mental transformations" @default.
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• W2896567555 doi "https://doi.org/10.1038/s41467-018-06726-9" @default.
• W2896567555 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6200789" @default.
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