Motor plans under uncertainty reflect a trade-off between maximizing reward and success

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# Go-Before-You-Know with reward and likelihood manipulation <br> Data and analysis code for 3 versions of the Go-Before-You-Know task: - Reward vs Frequency (https://github.com/CML-lab/KINARM_GBYK_RwdFreq) - Reward vs Probability (https://github.com/CML-lab/KINARM_GBYK_RwdProb) - Direct/Intermediate Discrete Choice (https://github.com/CML-lab/KINARM_GBYK_DiscreteChoice)

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