Paradigm constraints on moral decision space: a model fit to mouse-tracking data
Résumé
Background: A multitude of factors may influence moral decisions, leading to complex dynamics that call for nuance. Yet, experimental paradigms are often restricted to two-alternative forced choice tasks, with alternatives placed in opposite corners of the screen space.
Aim: Could paradigm response mode (two-alternatives or continuous scale) influence how morality is cognitively represented and processed, either relying on continuums or categories?
Methods: We built a computational model of (moral) decision-making based on differential equations (dynamic neural fields coupled with sensorimotor control, extending classical drift diffusion models) in which a 1D population of neuronal units maps a moral judgment scale (discrete or continuous). Neural fields usually operate on continuous spaces (e.g., sensorimotor), but allow the emergence of spatially localized attractors. Spatiotemporally coherent activity across the neural field reflects convergence in the decision space, while generating (mouse) trajectories aiming at on-screen response locations.
Results: Simulated data were fitted to mouse-tracking data previously collected on human participants, where the dynamics of participants’ judgments on moral statements was recorded using the computer mouse. Based on paradigmatic constraints implemented in the model, it successfully produced adequate mouse trajectories in both binary and continuous response modes, possibly reflecting how the spatial representation of responses impact decision-making.
Conclusion: Adjusting parameters in our model based on empirical data allowed us to bridge the gap between two-alternative forced choice and continuous scale paradigms, possibly giving insights into processes underlying human decision-making, and whether moral decision dynamics would differ depending on response mode.
Aim: Could paradigm response mode (two-alternatives or continuous scale) influence how morality is cognitively represented and processed, either relying on continuums or categories?
Methods: We built a computational model of (moral) decision-making based on differential equations (dynamic neural fields coupled with sensorimotor control, extending classical drift diffusion models) in which a 1D population of neuronal units maps a moral judgment scale (discrete or continuous). Neural fields usually operate on continuous spaces (e.g., sensorimotor), but allow the emergence of spatially localized attractors. Spatiotemporally coherent activity across the neural field reflects convergence in the decision space, while generating (mouse) trajectories aiming at on-screen response locations.
Results: Simulated data were fitted to mouse-tracking data previously collected on human participants, where the dynamics of participants’ judgments on moral statements was recorded using the computer mouse. Based on paradigmatic constraints implemented in the model, it successfully produced adequate mouse trajectories in both binary and continuous response modes, possibly reflecting how the spatial representation of responses impact decision-making.
Conclusion: Adjusting parameters in our model based on empirical data allowed us to bridge the gap between two-alternative forced choice and continuous scale paradigms, possibly giving insights into processes underlying human decision-making, and whether moral decision dynamics would differ depending on response mode.