When More Control Means Better Choices: Cognitive Control Networks Drive Expected-Value Maximization Under Uncertainty

• Cognitive control capacity promotes maximizing choices under uncertainty. • High-CCC individuals show more expected-value maximizing responses. • High-CCC individuals adopt more cautious decision thresholds. • Cingulo-opercular connectivity links control capacity to optimal choice. Human decision-making under outcome uncertainty often deviates from rational expected-value maximization, frequently falling back on the suboptimal probability matching heuristic. The neurocomputational mechanisms determining individual differences in overcoming this heuristic remain elusive. Here, we investigated how cognitive control capacity (CCC) modulates decision-making under varying levels of outcome uncertainty. Participants with high and low CCC performed a predictive inference task during functional magnetic resonance imaging. Behaviorally, high CCC individuals consistently exhibited a significantly higher proportion of maximizing responses (PMR) across all uncertainty levels. Using hierarchical drift-diffusion modeling, we demonstrated that this optimal performance was driven by more cautious decision thresholds, indicating greater deliberation to resist intuitive shortcuts. At the neural level, while localized activations in the cingulo-opercular network (CON) and frontoparietal network (FPN) reflected the general cognitive burden of escalating uncertainty, functional connectivity analyses revealed a specific neural pathway supporting optimal choices. Crucially, the connectivity within the CON (anterior insula to middle frontal gyrus) acted as a specific neural amplifier, which was absolutely necessary for translating high cognitive capacity into optimal expected-value maximization. The FPN, while tracking uncertainty, did not modulate this capacity-performance link. Together, these findings provide an integrated neurocomputational framework demonstrating how specific cognitive control networks mobilize resources to overcome heuristic tendencies and achieve optimal decisions under uncertainty.

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Publication Details

Journal
NeuroImage
Published
2026-05-01
DOI
https://doi.org/10.1016/j.neuroimage.2026.121989
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
0.00

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article

When More Control Means Better Choices: Cognitive Control Networks Drive Expected-Value Maximization Under Uncertainty

Tingting Wu, Yunpeng Jiang, Yuning Geng, Fang Liu et al.
NeuroImage
Decision-Making and Behavioral Economics
article

When More Control Means Better Choices: Cognitive Control Networks Drive Expected-Value Maximization Under Uncertainty

Tingting Wu, Yunpeng Jiang, Yuning Geng, Fang Liu, Tianhao Liu, Qiang Wang, Shuoxian Zhang, Yan Chen, Shuaipeng You, Xia Wu
article en

Abstract

• Cognitive control capacity promotes maximizing choices under uncertainty. • High-CCC individuals show more expected-value maximizing responses. • High-CCC individuals adopt more cautious decision thresholds. • Cingulo-opercular connectivity links control capacity to optimal choice. Human decision-making under outcome uncertainty often deviates from rational expected-value maximization, frequently falling back on the suboptimal probability matching heuristic. The neurocomputational mechanisms determining individual differences in overcoming this heuristic remain elusive. Here, we investigated how cognitive control capacity (CCC) modulates decision-making under varying levels of outcome uncertainty. Participants with high and low CCC performed a predictive inference task during functional magnetic resonance imaging. Behaviorally, high CCC individuals consistently exhibited a significantly higher proportion of maximizing responses (PMR) across all uncertainty levels. Using hierarchical drift-diffusion modeling, we demonstrated that this optimal performance was driven by more cautious decision thresholds, indicating greater deliberation to resist intuitive shortcuts. At the neural level, while localized activations in the cingulo-opercular network (CON) and frontoparietal network (FPN) reflected the general cognitive burden of escalating uncertainty, functional connectivity analyses revealed a specific neural pathway supporting optimal choices. Crucially, the connectivity within the CON (anterior insula to middle frontal gyrus) acted as a specific neural amplifier, which was absolutely necessary for translating high cognitive capacity into optimal expected-value maximization. The FPN, while tracking uncertainty, did not modulate this capacity-performance link. Together, these findings provide an integrated neurocomputational framework demonstrating how specific cognitive control networks mobilize resources to overcome heuristic tendencies and achieve optimal decisions under uncertainty.

NeuroImage
Tianjin Normal University (CN), Capital Normal University (CN)
National Outstanding Youth Science Fund Project of National Natural Science Foundation of China
Openalex Percentile: Top 5%
Decision-Making and Behavioral Economics
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