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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
MODVIS Workshop
It is now common among visual scientists to make inferences about neural population coding of stimuli from indirect measures such as those provided by neuroimaging and psychophysics. The success of such studies depends strongly on simulation work using standard population encoding models extended with decoders (in psychophysics) and measurement models (in neuroimaging). However, not all studies are accompanied by simulation work, and those that are tend to vary widely in their assumptions about encoding, decoding, and measurement. To solve these issues, we designed a Python package (PEMGUIN) to assist computational modelling by providing simple ways to manage encoders' tuning functions, …
Modeling Distribution Learning In Visual Search, Andrey Chetverikov
Modeling Distribution Learning In Visual Search, Andrey Chetverikov
MODVIS Workshop
Chetverikov, Campana, and Kristjansson (2017) used visual search to demonstrate that human observers are able to extract statistical distributions of visual features. Observers searched for an odd-one-out target with distractors randomly drawn from the same distribution over the course of several “prime” trials. Then, on test trials parameters of the target and distractors changed and response times (RT) were analyzed as a function of the distance between the target position in feature space and the mean of distractor features during prime trials. The resulting RT curves followed the probability density of prime distractor distributions. This approach provides a detailed estimation …