PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly.

@article{Odic2016PsiMLEAM,
  title={PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly.},
  author={Darko Odic and Hee Yeon Im and Robert S Eisinger and Ryan Ly and Justin Halberda},
  journal={Behavior research methods},
  year={2016},
  volume={48 2},
  pages={445-62}
}
A simple and popular psychophysical model-usually described as overlapping Gaussian tuning curves arranged along an ordered internal scale-is capable of accurately describing both human and nonhuman behavioral performance and neural coding in magnitude estimation, production, and reproduction tasks for most psychological dimensions (e.g., time, space, number, or brightness). This model traditionally includes two parameters that determine how a physical stimulus is transformed into a… CONTINUE READING
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