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Updated: Jun 17, 2026
08:29
Standardized Induction and Assessment of Long-term Potentiation-like Cortical Plasticity Using Transcranial Magnetic Stimulation
Published on: November 7, 2025
High-definition transcranial random noise stimulation enhances fluid intelligence with increasing cortical
Tianyi Zheng1, Yunshan Huang1, Masato Sugino1
1Department of Human and Engineered Environmental Studies, The University of Tokyo, 277-0882 Chiba, Japan.
Journal of Neural Engineering
|June 15, 2026
Summary
High-definition, high-frequency transcranial random noise stimulation (HD/HF-tRNS) improved reasoning speed in adults. This brain stimulation technique enhanced cognitive performance by modulating neural activity, particularly during difficult tasks.
Area of Science:
- Neuroscience
- Cognitive Science
- Neuromodulation
Background:
- Fluid intelligence underpins complex reasoning.
- The impact of HD/HF-tRNS on demanding cognitive tasks and neural mechanisms is not well understood.
Purpose of the Study:
- To investigate the effects of offline HD/HF-tRNS on the right dorsolateral prefrontal cortex (DLPFC).
- To examine behavioral and neurophysiological changes during fluid intelligence tasks.
Main Methods:
- A double-blind, sham-controlled study with 26 healthy adults.
- Participants completed Raven's Progressive Matrices (RPM) before and after active or sham HD/HF-tRNS.
- Electroencephalography (EEG) recorded neural activity, analyzing high-gamma synchronization and aperiodic exponent.
Main Results:
- Active HD/HF-tRNS reduced reaction time on difficult RPM items, unlike sham stimulation.
- Increased high-gamma spatial phase synchronization and decreased aperiodic exponent were observed post-stimulation.
- Neurophysiological changes were primarily localized to the right hemisphere during task performance.
Conclusions:
- Offline HD/HF-tRNS over the right DLPFC enhances response speed in demanding reasoning tasks.
- The stimulation induced task-dependent alterations in EEG markers of cortical excitability.
- HD/HF-tRNS shows promise as a tool for investigating neural processes in complex cognition.
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