Predictability of object motion trajectory modulates information integration for continuous manual tracking

• DOI: 10.1167/jov.23.9.6004
• Publication Date: 2023-08-29T19:35:02Z
• Authors: Zhongting Chen; Yuqi You
• Keywords: Tracking (education); Position (finance)

Kalman filter models have been proposed to analyze integration of information in manual tracking human beings. The idea optimal control behind models, however, insights us further investigate whether the predictability object motion trajectories, as a kind prior knowledge, can modulate during continuous tracking. Specifically, we hypothesize that gain, which refers relative contribution visual input at current time step integration, would decrease when trajectories become more predictable. In study, generated three kinds 2D namely Gaussian noise phase-free sinusoidal-wave and phase-locked respectively. For displacements target position each followed distribution, N (0, σ2), where σ equaled 2px. So, this condition, were theoretically unpredictable. two other they both additions 7 nonharmonic sinusoidal waves with different periods (0.058s - 5s). amplitudes carefully adjusted so match displacement point. 36 subjects participated experiment performances on trial fitted by model separately. We used Gibbs sampling method estimate posterior distributions gain conditions found estimated decreased 2% for than perceptual inputs comparable conditions. This finding demonstrates people modulates their even without change suggests an should not only take but knowledge them into account well.