dsGrid: a dual-site TMS grid-search method for personalized targeting of motor network connectivity

Brain targets for transcranial magnetic stimulation (TMS) are often derived from anatomical landmarks or group-level neuroimaging data, which lack precision or personalization, contributing to the variability in TMS responses. Personalized functional magnetic resonance imaging (fMRI) may improve accuracy but remains resource-intensive and not widely accessible.

To determine whether a new dual-site targeting method (dsGrid), based on dual-coil TMS mapping of motor connectivity, aligns with individual motor network connectivity derived from fMRI and validate its use.

Forty-seven participants underwent resting-state and task-based fMRI, followed by dual-coil TMS during a goal-directed action task. Motor network connectivity was quantified using fMRI, both resting-state and task-based connectivity, and task-evoked BOLD activity was also quantified. The strength of fMRI-derived motor features was assessed at the TMS target sites identified by dsGrid and compared with the strength of these measures at a conventional group-based target (e.g., the P3 electrode from a 10-20 EEG system) and registered to individual anatomy.

Targets identified by dsGrid are more accurate in terms of individualized motor network connectivity and activation across all three fMRI modalities than group-based P3 coordinates mapped to individual MRI space.

dsGrid enables precise, individualized TMS targeting of functional motor circuits, supporting its use in both research and clinical neuromodulation.