(a) AC and EA representations based on the drift-diffusion model (DDM) structure; we assumed that taste attribute construction (taste-AC) and health attribute construction (health-AC) signals in each trial integrated based on hierarchical multi-attribute drift diffusion model (HDDM) drfit rates (drift (t) = wtastiness * tastiness (t) + whealthiness * healthiness (t) + ValConst) and created the EA signal based on other DDM parameters. Model 1 computes the association of individually perceived tastiness and healthiness of each food with each of the taste-AC, health-AC, and EA signals. (b) Examples of time course of taste-AC (red), health-AC (blue), and EA (black) signals in two trials where a tasty but unhealthy (trial 1, solid lines) and a healthy but non-tasty (trial 2, dotted lines) food were presented. RT1 and RT2 are the reaction times on trial 1 and trial 2. Parameters used for these simulation examples are wtastiness = 0.7, whealthiness = 0.1, ValConst = 0.5, threshold = 0.9, spbias = 0.45, nondec = 0.462 s. (c) Model 1 coefficients showing the association between food tastiness ratings and the simulated taste-AC signal (solid red line), food tastiness ratings and the simulated EA signal (dashed red line), food healthiness ratings and the simulated health-AC signal (solid blue line), and food healthiness ratings and the simulated EA signal (dashed blue line) using individual HDDM parameters in NATURAL, HEALTH, and DECREASE conditions. Coefficients are averaged across subjects. Average RT in each condition is shown on the x-axes (mean RT = 0.98 s, 1.06 s, 1.05 s for NATURAL, HEALTH, and DECREASE, respectively). See Figure 2—figure supplement 1 and Figure 2—source data 1 for fitted model parameters.