.MAT

results_map_t1.mat (1.17 MB)

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results_map_t2.mat (1.18 MB)

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results_map_t3.mat (1.19 MB)

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results_map_t4.mat (1.2 MB)

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results_map_t5.mat (1.2 MB)

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results_mle_t1.mat (1.16 MB)

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results_mle_t2.mat (1.17 MB)

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results_mle_t3.mat (1.18 MB)

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results_mle_t4.mat (1.19 MB)

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results_mle_t5.mat (1.2 MB)

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results_map_t1_sp.mat (1.11 MB)

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results_map_t2_sp.mat (1.1 MB)

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results_map_t3_sp.mat (1.12 MB)

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results_map_t4_sp.mat (1.11 MB)

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results_map_t5_sp.mat (1.11 MB)

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results_map_t5_13on.mat (1.09 MB)

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results_map_t5_13on_sp.mat (1007.5 kB)

.RDATA

fit_1lr1s1lapse1bias_ALL_t5.RData (138.72 MB)

.RDATA

fit_1lr1s1lapse1bias_HC_t5.RData (83.35 MB)

.RDATA

fit_1lr1s1lapse1bias_PA_t5.RData (56.53 MB)

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215 files

Reinforcement-learning in mood and anxiety disorders: a simulation meta-analysis

dataset

posted on 2021-08-20, 16:50 authored by Alex Pike, Oliver RobinsonOliver Robinson

These are the MCMC or MAP model fits estimated for different models fit to choices made on different synthetic benchmarking tasks in this simulation meta-analysis. From this data, we can estimate a) the best-fitting model to this meta-dataset; b) parameter values from either the best-fitting model, or from models in proportion to their fit to the data (Bayesian Model Averaging). These datasets are .RData files, so can be opened in R, or converted and uploaded into other settings.

For more details on the project please see the page at osf.io: OSF | Reinforcement-learning in mood and anxiety disorders: a simulation meta-analysis