Abstract
Two prospective controllers of hand movements in catching-both based on required velocity control-were simulated. Under certain conditions, this required velocity control led to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint model. Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.
Original language | English |
---|---|
Pages (from-to) | 163-79 |
Number of pages | 17 |
Journal | Neural networks : the official journal of the International Neural Network Society |
Volume | 15 |
Issue number | 2 |
Publication status | Published - 2002 |
ASJC Scopus subject areas
- Artificial Intelligence
- General Neuroscience