By-participant model fits replicate the continuous DR, flexible RB result for most individual learners¶

Claim · All claims
Evidence · 1 study · associational r1 · q3
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? When models were fit to each participant separately, the continuous DR flexible RB parameterization was best for 19/21 participants by LOOIC and 15/21 by Bayes factor, with high correspondence of point estimates. → Cochrane 2023

Evidence¶

Cochrane 2023¶

Cochrane, A., Sims, C. R., Bejjanki, V. R., Green, C. S., & Bavelier, D. (2023). Multiple timescales of learning indicated by changes in evidence-accumulation processes during perceptual decision-making. npj Science of Learning 8:19. https://doi.org/10.1038/s41539-023-00168-9

q3 · i? · associational · r1

The same six models were fit without the mixed-effects structure to each of the 21 participants' data separately; the continuous DR flexible RB model won in 19/21 (LOOIC) and 15/21 (Bayes factor) participants, and parameter point estimates correlated with the mixed-effects fits (e.g., asymptotic DR r = 0.85).

"The continuous DR flexible RB parameterization was the best- fitting model in 19/21 participants using LOOIC comparisons and 15/21 participants using Bayes Factor comparisons."

Discussion¶

Related Claims¶

• Model comparison favors continuous drift rate with flexible response boundary over constant, fully continuous, and day-resetting alternatives — related
• Drift rate increases as a continuous exponential function of cumulative trial number across four days of perceptual training — related
• Accuracy-only logistic psychometric fits support a two-timescale model but cannot identify which decision component changed — related