CNP RL

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Basic Task Description

The CNP "RL" task contains two tasks in one - a probabilistic selection task and a probabilistic reversal learning task. These tasks were designed to assess feedback sensitivity and behavioral flexibility, respectively. Both tasks have been widely used to determine reinforcement learning characteristics and behavioral flexibility in healthy and patient populations. The probabilistic selection task, initially designed by Michael Frank, is specifically used to determine participants' tendencies to learn either from positive or negative feedback (e.g., Frank et al., 2004). The probabilistic reversal learning task, originally developed by Trevor Robbins and Robert Rogers (

Task Procedure

For general testing procedure, please refer to LA2K General Testing Procedure [here?].

Task Structure Detail

This is what we had worked on before, but could use updating. We'd like to capture a schema that can handle each of the tasks in the CNP, so please think general when editing -fws

Task Schematic

Schematic of the RL task

Task Parameters Table

Dependent Variables

The primary dependent variable is ...

Table of all available variables.

Code/Algorithms

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History of Checking Scoring:

References

Frank MJ, Seeberger LC, O'Reilly RC. By carrot or by stick: cognitive reinforcement learning in Parkinsonism. Science 2004;306:1940-1943