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Jahansa, P.

Publications and source records attributed to Jahansa, P..

2 recordsLinked to original sources

Effect of dependency and tail behavior on a probability inequality occurring in modeling cognitive processes

A central idea in modeling performance in cognitive tasks is dynamic competition among processes in separate channels, known as "race model". This model implies a certain inequality between associated probability distributions under rather general conditions. The inequality represents an important empirical test of the race model, but its usefulness is limited since it requires the assumption of stochastic independence between the channels. Using the stop signal paradigm as reference, we investigate more general forms of stochastic dependence that still imply the inequality using the concepts of copula and heavy-tailed marginal distributions.

neuroscience↗

Mixture-models for stimulus-selective stopping

Stimulus-selective stopping extends the standard stop signal task by occasionally presenting an ignore signal instead of a stop signal, in which case participants are instructed to continue responding to the go signal. Here we present several model classes that are based on the idea that responses observed under an ignore signal are the result of a probabilistic mixture from the processing distributions of the go and the ignore signal. Earlier work ensures that the mixture hypothesis is statistically testable. We derive quantitative predictions and parameter estimation for model classes that differ in the way the mixture is introduced. The results are illustrated with an application to a published dataset for stimulus-selective stopping.

neuroscience↗