Difference between revisions of "CNP RL"
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The CNP "RL" task contains two tasks embedded in one - a probabilistic selection task (PST) and a probabilistic reversal learning task (PRLT). These tasks were designed to assess feedback sensitivity and behavioral flexibility, respectively. Both have been extensively used to determine reinforcement learning biases and behavioral flexibility in both healthy and patient populations. Initially designed by Michael Frank, the probabilistic selection task 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 (Lawrence et al, 1999; Swainson et al., 2000), examines participants' ability to adapt to changes in learned contingencies. Both tasks involve initial training periods in which participants must learn appropriate responses given probabilistic feedback ("noisy" feedback). | The CNP "RL" task contains two tasks embedded in one - a probabilistic selection task (PST) and a probabilistic reversal learning task (PRLT). These tasks were designed to assess feedback sensitivity and behavioral flexibility, respectively. Both have been extensively used to determine reinforcement learning biases and behavioral flexibility in both healthy and patient populations. Initially designed by Michael Frank, the probabilistic selection task 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 (Lawrence et al, 1999; Swainson et al., 2000), examines participants' ability to adapt to changes in learned contingencies. Both tasks involve initial training periods in which participants must learn appropriate responses given probabilistic feedback ("noisy" feedback). | ||
| − | Probabilistic Selection Task | + | ''Probabilistic Selection Task'' |
| − | + | In the typical PST, three pairs of cards are presented and participants must learn the "correct" card in each pair. Each pair is associated with different probabilities. For pair AB, choosing A is associated with positive feedback 80% of the time (B 20% of the time). For CD, choosing C leads to positive feedback 70% of the time, and E in EF 60% of the time. Over time, participants learn to choose the higher probability cards - choosing A, C, and E most of the time. Learning may be achieved either by choosing the card associated with positive feedback or by avoiding the card associated with negative feedback. After training, to assess whether participants learn more from positive or negative feedback, the cards are recombined in a "probe" phase, such that each card is paired with every other card. Participants are required to make a choice given these novel pairs without receiving feedback. A bias towards learning from positive feedback is determined by the number of times participants choose the highest probability card (the card receiving the most positive feedback) relative to the others (A vs. B, A vs. C, A vs. D, A vs. E), and a bias towards learning from negative feedback is derived by the number times that the lowest probability card is avoided (B vs. C, B vs. E, B vs. F). The tendency to choose A versus avoiding B is associated with several neuropsychiatric phenotypes, most notably observed in Parkinson's patients (Frank et al., 2004), and evidence for genetic associations has been observed (Frank et al., 2007). | |
| − | In the typical PST, three pairs of cards are presented and participants must learn the "correct" card in each pair. Each pair is associated with different probabilities. For pair AB, choosing A is associated with positive feedback 80% of the time (B 20% of the time). For CD, choosing C leads to positive feedback 70% of the time, and E in EF 60% of the time. Over time, participants learn to choose the higher probability cards - choosing A, C, and E most of the time. Learning may be achieved either by choosing the card associated with positive feedback or by avoiding the card associated with negative feedback. After training, to assess whether participants learn more from positive or negative feedback, the cards are recombined in a "probe" phase, such that each card is paired with every other card. Participants are required to make a choice given these novel pairs without receiving feedback. A bias towards learning from positive feedback is determined by the number of times participants choose the highest probability card (the card receiving the most positive feedback) relative to the others (A vs. B, A vs. C, A vs. D, A vs. E), and a bias towards learning from negative feedback is derived by the number times that the lowest probability card is avoided (B vs. C, B vs. E, B vs. F). | + | |
C and D may have a 60%/40% probability. This feedback is probabilistic in that a given response may be correct for a certain percentage of trials (e.g., 80% of trials). Participants are typically informed that the feedback may be "unreliable". | C and D may have a 60%/40% probability. This feedback is probabilistic in that a given response may be correct for a certain percentage of trials (e.g., 80% of trials). Participants are typically informed that the feedback may be "unreliable". | ||
Revision as of 17:06, 1 June 2011
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Contents
Basic Task Description
The CNP "RL" task contains two tasks embedded in one - a probabilistic selection task (PST) and a probabilistic reversal learning task (PRLT). These tasks were designed to assess feedback sensitivity and behavioral flexibility, respectively. Both have been extensively used to determine reinforcement learning biases and behavioral flexibility in both healthy and patient populations. Initially designed by Michael Frank, the probabilistic selection task 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 (Lawrence et al, 1999; Swainson et al., 2000), examines participants' ability to adapt to changes in learned contingencies. Both tasks involve initial training periods in which participants must learn appropriate responses given probabilistic feedback ("noisy" feedback).
Probabilistic Selection Task In the typical PST, three pairs of cards are presented and participants must learn the "correct" card in each pair. Each pair is associated with different probabilities. For pair AB, choosing A is associated with positive feedback 80% of the time (B 20% of the time). For CD, choosing C leads to positive feedback 70% of the time, and E in EF 60% of the time. Over time, participants learn to choose the higher probability cards - choosing A, C, and E most of the time. Learning may be achieved either by choosing the card associated with positive feedback or by avoiding the card associated with negative feedback. After training, to assess whether participants learn more from positive or negative feedback, the cards are recombined in a "probe" phase, such that each card is paired with every other card. Participants are required to make a choice given these novel pairs without receiving feedback. A bias towards learning from positive feedback is determined by the number of times participants choose the highest probability card (the card receiving the most positive feedback) relative to the others (A vs. B, A vs. C, A vs. D, A vs. E), and a bias towards learning from negative feedback is derived by the number times that the lowest probability card is avoided (B vs. C, B vs. E, B vs. F). The tendency to choose A versus avoiding B is associated with several neuropsychiatric phenotypes, most notably observed in Parkinson's patients (Frank et al., 2004), and evidence for genetic associations has been observed (Frank et al., 2007).
C and D may have a 60%/40% probability. This feedback is probabilistic in that a given response may be correct for a certain percentage of trials (e.g., 80% of trials). Participants are typically informed that the feedback may be "unreliable".
In the CNP version of these tasks, participants undergo an two training stages in which they must learn which of two stimuli are correct given probabilistic feedback. After initial training
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
Stimuli
Dependent Variables
The primary dependent variable is ...
Table of all available variables.
Cleaning Rules
Code/Algorithms
History of Checking Scoring:
Data Distributions
References
Frank MJ, Seeberger LC, O'Reilly RC. By carrot or by stick: cognitive reinforcement learning in Parkinsonism. Science 2004;306:1940-1943
Lawrence AD, Sahakian BJ, Rogers RD, Hodges JR, Robbins TW. Discrimination, reversal, and shift learning in Huntington's disease: mechanisms of impaired response selection. Neuropsychologia 1999;37:1359-1374.
Swainson R, Rogers RD, Sahakian BJ, Summers BA, Polkey CE, Robbins TW. Probabilistic learning and reversal deficits in patients with Parkinson's disease or frontal or temporal lobe lesions: possible adverse effects of dopaminergic medication. Neuropsychologia 2000;38:596-612
