Paradox resolved: Stop signal race model with negative dependence.

Area of Science:

• Cognitive psychology
• Neuroscience
• Computational modeling

Background:

• Voluntary response inhibition is a key aspect of cognitive control.
• The stop-signal paradigm is widely used to investigate response inhibition.
• Existing models, like the independent race model, face challenges linking behavioral data to neural findings of interacting neural networks.

Purpose of the Study:

• To propose a dependent race model for response inhibition.
• To reconcile behavioral modeling with neurophysiological evidence of interacting neural processes.
• To provide a framework for understanding the mechanisms of cognitive control.

Main Methods:

• Development of a dependent race model with perfect negative stochastic dependence between go and stop processes.
• Comparison of the dependent model with the independent race model.
• Analysis of behavioral data from the stop-signal paradigm.

Main Results:

• The dependent race model is consistent with interacting neural processes.
• For mean data, the dependent model yields identical predictions to the independent race model.
• This resolves an apparent paradox, advancing response inhibition research.

Conclusions:

• The dependent race model offers a parsimonious yet neurobiologically plausible account of response inhibition.
• It bridges the gap between behavioral measures and neural network dynamics.
• The model facilitates future research into more complex cognitive control scenarios.