Personalized Network‐Guided Neuromodulation Enhances Human Working Memory

The next frontier in cognitive neuromodulation is defined by personalized and adaptive protocols, necessitating approaches tailored to individual functional neuroanatomy and brain‐state fluctuations. Here, we introduce an adaptive neuromodulation framework that integrates individualized network targeting with real‐time decoding of brain states to precisely target working memory functional networks. Using concurrent transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI), we first mapped participant‐specific networks and identified personalized targets. A real‐time decoder then tracked stimulation‐evoked neural dynamics to empirically determine the optimal frequency (i.e., the best‐performing within a tested set of 5, 10, and 20 Hz) and a corresponding suboptimal frequency for each individual. In a multi‐session crossover study, only the optimal‐frequency stimulation significantly improved working memory, with the decoder's output predicting behavioral gains. A key finding is the substantial inter‐individual variability in the optimal frequency, providing evidence against the notion of a universal “best” frequency. Our results demonstrate that cognitive enhancement is governed by the precise interaction between stimulation target and frequency. This work provides a causal demonstration of personalized, network‐based neuromodulation and offers proof of concept for a generalizable, biomarker‐driven framework, representing a step toward advancing cognitive therapeutics. Trial Registration : This study is registered at ClinicalTrials.gov (identifier: NCT04402294).