TY - GEN A1 - Hoxha, Isabelle A1 - Chevallier, Sylvain A1 - Ciarchi, Matteo A1 - Glasauer, Stefan A1 - Delorme, Arnaud A1 - Amorim, Michel‐Ange T1 - Accounting for endogenous effects in decision‐making with a non‐linear diffusion decision model T2 - Scientific Reports N2 - The Drift‐Diffusion Model (DDM) is widely accepted for two‐alternative forced‐choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter‐trial dynamics at the single‐ trial level and endogenous influences. We propose a novel model, the non‐linear Drift‐Diffusion Model (nl‐DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non‐linear model performs better than the drift‐diffusion model for an equivalent complexity. To give better intuition on the meaning of nl‐DDM parameters, we compare the DDM and the nl‐DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl‐DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across‐trial variability for perceptual decisions and accounts for peri‐stimulus influences. Y1 - 2023 U6 - https://doi.org/10.1038/s41598-023-32841-9 SN - 2045-2322 VL - 13 ER - TY - JOUR A1 - Polezhaeva, Olga A1 - Glasauer, Stefan A1 - Amorim, Michel-Ange T1 - Prediction of uncertain visual trajectories is biased toward motion continuity JF - Attention, perception, & psychophysics : AP&P N2 - Visual motion prediction under uncertainty must rely on both statistical and kinematic properties of the stimulus. Here, we investigated how decision-making processes and psychophysical parameters are modulated during extrapolation of random trajectories with different noise characteristics (Random Walk, RDW, or Independently and Identically Distributed, IID). Noise was applied to the horizontal position of a dot moving downward with constant vertical speed and vanishing before reaching the edge of the screen. Participants had to judge whether the dot would reach the edge right or left of the center. In Experiment 1 we varied the side of the last visible horizontal position, optimal for RDW extrapolation, and the mean of all visible positions, optimal for IID, to be either on the same or on opposite sides of the screen center. Experiment 2 investigated how the final segment of an IID path impacts the trajectory extrapolation when the last visible position and the mean of the last segment are on opposite sides of the center. Experiment 3 focused on assessing the accuracy of trajectory perception amid varying levels of noise. Behavioral and DDM (Diffusion Decision Model) analyses revealed that for RDW trajectories, participants relied on the last visible position, reflecting the temporal continuity of the path and leading to faster and more accurate decision making. IID trajectories showed greater variability in prediction strategies, with participants also focusing more on the last segment, as with RDW, rather than the mean position of the whole previous trajectory. However, this strategy works well even for IID paths despite being a suboptimal solution. These findings suggest that the perceptual system favors smooth motion for visual interpretation, aiding in the prediction of uncertain visual trajectories. KW - Motion extrapolation KW - Diffusion decision model KW - Perception Y1 - 2026 U6 - https://doi.org/10.3758/s13414-025-03210-7 SN - 1943-3921 VL - 88 IS - 3 SP - 1 EP - 21 PB - Springer Science and Business Media LLC CY - New York, NY ER -