Robotic induction of neuromodulation via paired brain stimulation with mechanical stimulation

Abstract

Recent studies indicate that neural plasticity may contribute to functional recovery after a stroke where long-term potentiation (LTP) has been regarded as a contributor to motor learning as it strengthens excitatory synapses. There is an intervention that is known to induce LTP by applying transcranial magnetic stimulation (TMS) and peripheral stimulation. It is only when TMS and peripheral stimulation is repeatedly applied with an appropriate inter-stimulus interval (ISI) between them, that the LTP can be induced in the human motor cortex. Despite the promise of this intervention, tight time synchronization constraints and large variability in effective ISI among individuals still remain problems. In this study, the combination of TMS and mechanical stimulation as peripheral stimulation is used to understand the instantaneous neuromodulation of this intervention. This paired brain stimulation with mechanical stimulation was named mPBS. This mPBS intervention is similar to the intervention in paired associative stimulation (PAS), whereas PAS usually uses electrical stimulation as peripheral stimulation. The mechanical stimulation in mPBS was inspired by tendon tapping in a specific clinical practice called the repetitive facilitation exercise or RFE. The use of mechanical stimulation for peripheral stimulation in mPBS instead of electrical stimulation is expected to not only address tight timing issues associated with electrical stimulation, but also bridge the gap between the specific clinical practice RFE and conventional PAS. The objective of this research is to understand and characterize transient neuromodulation via mPBS. In order to accomplish the objectives the following aims were completed: 1) to verify timing repeatability of the mechanical stimulator for use in mPBS, 2) to apply statistical regression methods to estimate individual instantaneous neuromodulation ISI profiles faster than the conventional incremental method, and 3) to develop a robotic system that automatically tunes ISI and estimate enhanced motor evoked potential (MEP) profiles without human involvement to characterize the association between ISI and MEP in mPBS.