Collapsing bounds in HSSM; task structure

[Ben Jonathan Wagner]

Dear all,

i have a question regarding a decision-making task and the new HSSM toolbox. 

We have a reinforcement learning task where in some trials there is only learning of Q-values and sequence values (repetition of a policy) and in other trials participants have to make a binary choice that is modelled as a linear or non-linear function of Q-values and policy repetition and in some models other variables like e.g. a conflict term.

I did fit the data with a DDM programmed in JAGS and that worked fine. However, the task has a strict time-limit and thus the DDM likelihood function (with its long tails) is not suited very well. When you conduct PPCs it simulates RTs that are beyond this RT cutoff and would be invalid in the task. I guess it might be better to also fit a DDM with collapsing bounds to account for the urgency/time pressure.

Is it possible to fit such data using HSSM? As i outlined above It would be important that the model does learn different types of values in all trials, and that we can implement our own functions of how these values map on the different DDM parameters when decisions come up every 6 to 10 trials. Further the task has different conditions and days of participation which we all want to put in one model, plus its a relatively large dataset (for a decision-making task) with over 300.000 trials. If so, it would be great if you could shortly outline the key steps to do so. That would be a great help.

Thank you very much

Ben

Postdoc

Chair of Cognitive Computational Neuroscience

TU Dresden

[Michael J Frank]

Hi Ben, please start a discussion thread on the HSSM github rather than HDDM. Krishn Bera (cc'd) should be able to help here as we have some working examples of RL functions using blackbox likelihoods in HSSM which can be paired with any SSM (including collapsing bounds)

Michael

Michael J Frank, PhD | Edgar L. Marston Professor

Director, Carney Center for Computational Brain Science 

Laboratory of Neural Computation and Cognition  

Brown University
website 

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[Ben Jonathan Wagner]

Hi Michael and Krishn,

thank you very much, that sounds great. i will do that.

Bests,

Ben

 

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