High-definition transcranial random noise stimulation enhances fluid intelligence with increasing cortical excitability

Published in Journal of Neural Engineering, 2026

Objective. Fluid intelligence is a core component of higher-order cognition, yet whether high-definition high-frequency transcranial random noise stimulation (HD/HF-tRNS) can enhance demanding reasoning performance and modulate its neural correlates remains unclear. Approach. We investigated the after-effects of offline HD/HF-tRNS targeting the right dorsolateral prefrontal cortex (DLPFC). In a double-blind, sham-controlled, between-groups design, 26 healthy adults completed Raven’s progressive matrices (RPM) before and after receiving active or sham stimulation. Electroencephalography (EEG) was recorded during task and resting-state sessions. Behavioral outcomes were accuracy and reaction time; neurophysiological outcomes were high-gamma mean spatial phase synchronization and the aperiodic exponent of neural power spectra. Main results. Active HD/HF-tRNS did not significantly alter accuracy but selectively reduced reaction time on the most difficult RPM items. During hard-level trials, reaction time decreased after active stimulation but not after sham stimulation, and post-stimulation reaction time was lower in the active group than in the sham group. High-gamma spatial phase synchronization increased after active stimulation, and the aperiodic exponent decreased during medium- and hard-level trials, with effects predominantly over the right hemisphere. No significant stimulation-related changes were observed during resting state. Significance. Offline HD/HF-tRNS over the right DLPFC facilitated response speed during demanding fluid-intelligence performance and induced task-dependent changes in EEG-derived correlates of cortical excitability.

Recommended citation: Zheng, T., Huang, Y., Sugino, M., Shimba, K., Jimbo, Y., & Kotani, K. (2026). High-definition transcranial random noise stimulation enhances fluid intelligence with increasing cortical excitability. Journal of Neural Engineering, 23(4), 046002. https://doi.org/10.1088/1741-2552/ae7d58
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