Equal evidence perceptual tasks suggest a key role for interactive competition in decision-making

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Decision Science

Background:

• Sequential sampling theory (SST) models decision-making as evidence accumulation.
• A key debate in SST is the dependency between accumulators: independent, fully dependent, or partially dependent.

Purpose of the Study:

• To determine the most plausible model of accumulator dependency in human decision-making.
• To investigate how evidence magnitude and trial variability affect decision dynamics.

Main Methods:

• Introduced novel equal-evidence conditions to classic perceptual tasks.
• Developed and tested a spectrum of models from independent to fully dependent accumulation.
• Examined within-trial and between-trial variability (BTV).

Main Results:

• Response times varied systematically with evidence magnitude in equal-evidence conditions.
• Response times increased as evidence difference decreased in unequal-evidence conditions.
• Models incorporating partial dependency provided the best fit to experimental data.

Conclusions:

• Partial dependency between accumulators is a more accurate representation of human decision-making.
• Mechanisms like lateral inhibition, inducing partial dependency, are crucial for understanding decision dynamics, even in simple tasks.