Distilling noise characteristics and prior expectations in multisensory causal inference
Fig 14
Unisensory model recovery results.
Rows correspond to different simulated datasets (groups of 15 simulated participants), each named after their ground-truth generative model. Within each row, the columns are different candidate models fitted to the same simulated group (row and column orders are identical, hence omitted). Within each row, the matrix entries are NLL/AIC/BIC differences between each fitted model to the ground-truth model (the row’s diagonal entry, which is always the baseline of 0). Color indicates whether the NLL/AIC/BIC difference is positive (green) or negative (pink), visualized in log scale (colorbar). Successful model recovery implies that the diagonal entries have lowest AIC/BIC within their row, and thus all matrix entries should be positive (green). (A) NLL differences. (B) AIC differences, (C) BIC differences.