A finite element modeling study of the differential effect of temporal interference stimulation on sequential motor learning

Healthy ageing often results in diminished motor and cognitive functions in humans. Non-invasive brain stimulation (NIBS) has the potential to restore the operation of deteriorated neural components, with important implications for improving cognitive functions in healthy older adults. Previous studies have shown heterogeneous effects of NIBS to enhance learning, which has hindered its establishment as an intervention to improve neural functions in humans. Recent studies show that individual characteristics can lead to differential stimulation effects, partially explaining the large heterogeneity in previous reports. Here, we expand on this individualized approach by assessing the relationship between the amount of energy injected into a critical hub of the motor network, and the magnitude of the resulting behavioral change. We applied transcranial temporal interference stimulation (tTIs) to the striatum in 29 healthy volunteers (14 young, 15 older) during a motor sequence learning task. Next, we generated individualized simulations of the induced electric fields at the target using finite element modeling, and associated the strength of the induced fields with the level of motor learning. Finally, we applied a clustering algorithm to group participants based on the magnitude of the electric field induced at the target. Our results show a differential effect of stimulation, with the largest behavioral change related to more intense electric fields (0.4 V/m and above), while weaker electric fields had smaller to no effect. The present work constitutes an additional step towards the individualization of NIBS, here tTIs to the striatum, essential for its future application as a therapeutic intervention.