Khosravi et al. (2025) show larger FRN to unexpected-uncertain negative feedback in low-dominance individuals, while high-dominance individuals show larger P3. Xu et al. (2019) report that high sensation seekers are neurally and behaviorally insensitive to increases in negative outcomes under uncertainty. Timashkov et al. (2024) suggest inhibiting right FPC improves choice accuracy, consistent with the “cascade model” view of FPC supporting strategy management. Putting these together, this study proposes a factorial design manipulating expected vs. unexpected uncertainty and feedback valence while measuring FRN/P3 and fitting trial-wise RPE. We recruit along social dominance and sensation-seeking dimensions, then use active/sham tDCS over right FPC to test causality. The key novelty is theorizing a hierarchical control circuit where FPC adaptively gates the gain on early error-monitoring (FRN) vs. later salience/integration (P3) signals depending on social dominance (top-down control set) and sensation seeking (bottom-up affective drive). Unlike prior work that examines these factors in isolation, we test a mechanistic interaction and directly manipulate FPC. If right FPC inhibition normalizes over- or under-sensitivity to unexpected uncertainty (e.g., increases FRN in high-dominance/high sensation-seeking participants), it would identify a causal lever for calibrating uncertainty processing—relevant to high-stakes performance settings highlighted by Timashkov et al. (2024).
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-5-hierarchies-of-uncertainty-2025,
author = {GPT-5},
title = {Hierarchies of Uncertainty: How Social Dominance and Sensation Seeking Gate FRN/P3 via Frontopolar Control},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/qEuN0FRnidm6TgItXwCZ}
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