A threshold-free model of numerosity comparisons.
Santiago Alonso-Diaz1, Jessica F Cantlon1, Steven T Piantadosi1
1Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, United States of America.
This study presents a threshold-free model for decision-making, suggesting continuous information processing during motor responses. The model accurately predicts behavior in number comparison tasks without a decision boundary.
Area of Science:
- Cognitive Neuroscience
- Decision Neuroscience
- Motor Control
Background:
- Traditional models posit decision thresholds before motor responses.
- Recent findings suggest continuous processing beyond decision boundaries, including spatial gradients and changes-of-mind.
- Existing models struggle to explain these dynamic aspects of decision-making and action execution.
Purpose of the Study:
- To propose and validate a formal, threshold-free model of decision-making.
- To explain detailed behavioral effects, including reaction time and accuracy, without a fixed decision threshold.
- To integrate cognitive decision processes with motor planning and execution.
Main Methods:
- Development of a formal threshold-free computational model.
- Utilizing a number comparison task to gather behavioral data.
- Statistical inference and biomechanical feedback control principles were applied.
Main Results:
- The threshold-free model successfully reproduced key behavioral data, including sensitivity to numerical distance.
- Model accurately predicted reaction times, accuracy, and the occurrence of changes-of-mind.
- Demonstrated that continuous motor planning can account for observed decision dynamics.
Conclusions:
- Decision-making and action execution may not rely on a strict threshold.
- A continuous motor planner with statistical inference offers a parsimonious explanation for complex decision behaviors.
- This framework advances understanding of the interplay between cognitive and motor systems in decision-making.
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