Dividing up the pie: Allocating attention across dual tasks

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Decision Science

Background:

• Daily life demands divided attention, leading to cognitive exhaustion.
• Existing psychological theories lack direct investigation into the cognitive mechanisms of resource allocation.
• Previous modeling approaches have not fully integrated decision-making under attentional constraints.

Purpose of the Study:

• To present a novel joint-computational approach for understanding attentional resource allocation in dual-task environments.
• To quantify the subjective and latent processes involved in divided attention.
• To provide a framework for predicting cognitive performance under varying workloads.

Main Methods:

• Conducted two paired experiments involving participants completing a Multiple Object Tracking task and a Detection Response Task simultaneously.
• Developed a unified computational framework integrating separate decision-making models.
• The framework's single allocation process was designed to predict performance across different cognitive demands.

Main Results:

• The joint-computational model accurately predicted participant performance across a range of cognitive demands.
• The framework successfully unified separate decision-making models under a single attentional allocation process.
• Demonstrated the model's ability to quantify subjective and latent processes in divided attention.

Conclusions:

• Attentional resource allocation plays a central role in dual-task performance.
• The proposed computational framework offers a flexible method for analyzing divided attention.
• Decision-makers exhibit adaptability in allocating cognitive resources based on shifting workloads.