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Incentive motivation improves numerosity discrimination: Insights from pupillometry combined with drift-diffusion
Annika Dix1,2, Shu-Chen Li3,4
1Faculty of Psychology, Chair of Lifespan Developmental Neuroscience, Technische Universität Dresden, 01062, Dresden, Germany. annika.dix@tu-dresden.de.
Scientific Reports
|February 15, 2020
Summary
Incentive motivation enhances the approximate number system (ANS), improving numerosity discrimination accuracy and information processing. This suggests rewards boost cognitive precision in numerical tasks.
Area of Science:
- Cognitive Neuroscience
- Experimental Psychology
Background:
- The approximate number system (ANS) is crucial for symbolic math abilities.
- Incentive motivation's role in numerosity discrimination and its mechanisms require further investigation.
Purpose of the Study:
- To explore how incentive motivation affects numerosity discrimination.
- To elucidate the underlying neural and cognitive mechanisms.
Main Methods:
- Developed a novel incentivized dot comparison task for 32 young adults.
- Applied EZ-diffusion modeling to analyze decision-making processes.
- Measured phasic pupil dilation to assess salience network involvement.
Main Results:
- Reward conditions led to improved accuracy and faster information accumulation.
- Phasic pupil dilation indicated enhanced salience network engagement.
- Findings suggest incentive motivation boosts ANS precision.
Conclusions:
- Incentive motivation enhances numerosity perception and cognitive precision.
- Results align with Adaptive Gain Theory, implicating locus coeruleus-norepinephrine system.
- Reward-induced pupil dilation reflects modulated salience attention and response caution.
