TY - JOUR TI - TMS-evoked responses are driven by recurrent large-scale network dynamics AU - Momi, Davide AU - Wang, Zheng AU - Griffiths, John D A2 - Fornito, Alex A2 - Frank, Michael J A2 - Meier, Jil A2 - Pigorini, Andrea VL - 12 PY - 2023 DA - 2023/04/21 SP - e83232 C1 - eLife 2023;12:e83232 DO - 10.7554/eLife.83232 UR - https://doi.org/10.7554/eLife.83232 AB - A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research. KW - transcranial magnetic stimulation KW - electroencephalography KW - computational model KW - connectome KW - neural mass model KW - recurrence JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -