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Infinite Horizon Control With Nonlinear Dynamics Models Reproduces Temporal Modulation of Reaching Movements
Antoine De Comite1, Hari Teja Kalidindi2,3,4, J Andrew Pruszynski5
1McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA adecomit@mit.edu.
Neural Computation
|April 7, 2026
Summary
Movement duration may not be preprogrammed but emerge from control policies. This framework explains human reaching behaviors and motor decisions, challenging previous assumptions in motor control research.
Area of Science:
- Motor control
- Computational neuroscience
- Biomechanics
Background:
- Movement duration is traditionally viewed as a preprogrammed parameter.
- An alternative perspective suggests movement duration arises from the control policy itself.
Purpose of the Study:
- To investigate if movement duration emerges from control policies.
- To model human reaching behavior using optimal feedback control and nonlinear dynamics.
Main Methods:
- Utilized infinite horizon optimal feedback control (IHOFC) with nonlinear limb dynamics.
- Extended the IHOFC framework to incorporate rewards and biomechanical costs.
Main Results:
- Successfully reproduced human reaching behaviors, including Fitts's law.
- Modeled temporal evolution of feedback responses and motor decisions in dynamic environments.
Conclusions:
- Movement duration can emerge from task-dependent control policies, not necessarily requiring a priori specification.
- This framework offers a candidate explanation for varied movement durations and challenges finite horizon formulations.
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