Contention scheduling and the control of routine activities.

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Neuropsychology

Background:

• Routine action control is complex, prone to errors in healthy individuals and severe deficits in neurological conditions.
• Previous research has empirically studied action breakdown in patients and linked findings to psychological theories.

Purpose of the Study:

• To present a computational model of routine action selection.
• To simulate action control using a hierarchical network of action schemas with competitive activation.
• To compare model behavior to patient data.

Main Methods:

• Developed a computational model based on a hierarchical network of action schemas.
• Utilized competitive activation mechanisms for action selection.
• Performed simulations in a complex naturalistic domain and simulated neurological damage ('lesioning').

Main Results:

• The model successfully demonstrated organized sequential action selection in complex scenarios.
• Simulated lesioning in the model produced behavior qualitatively similar to the action disorganization syndrome observed in patients.
• The model provides a theoretical framework for understanding action control and breakdown.

Conclusions:

• The computational model effectively captures aspects of routine action control.
• The model's ability to simulate patient behavior supports its validity in explaining action disorganization syndromes.
• This work offers insights into the neural mechanisms underlying action selection and control.