The golden age of online readout: EEG-informed TMS from manual probing to closed-loop neuromodulation

The integration of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) has markedly enhanced our ability to probe cortical excitability and monitor the brain's electrophysiological responses to external perturbations. In recent decades, this combination has become a widely used and important tool in both basic neuroscience and clinical research. However, persistent challenges remain, particularly the limited reliability of early TMS-evoked potentials (TEPs), contamination from stimulus-locked and induced artifacts (e.g., coil discharge, electrode polarization, cranial muscle activity), and reliance on non-individualized stimulation protocols. This review outlines the evolution of the TMS-EEG methodology in four key implementations: (i) EEG-blind TMS, where stimulation parameters are fixed without EEG-based adjustments; (ii) EEG-informed TMS, which leverages online EEG readouts to optimize stimulation settings prior to acquisition; (iii) EEG-triggered TMS, employing feedforward algorithms to align stimulation with ongoing neural oscillations; and (iv) closed loop TMS, where real-time feedback dynamically adapts stimulation parameters during the session. We examine the electrophysiological and technical foundations of each approach, highlighting their benefits and limitations. Emerging closed-loop systems represent a shift toward adaptive, data-driven neuromodulation, unlocking promising avenues for personalized brain stimulation. Further refinement of these approaches will be critical to improving their precision, reliability, and applicability in diverse clinical and research settings. Collectively, these developments demonstrate a field-wide progression toward increasingly precise and individualized brain stimulation strategies, enabled by real-time electrophysiological feedback and customizable stimulation protocols.