SUBJECT: Ph.D. Dissertation Defense
BY: Euisun Kim
TIME: Thursday, December 5, 2019, 12:00 p.m.
PLACE: MRDC Building, 4211
TITLE: Robotic Induction of Neuromodulation via Paired Brain Stimulation with Mechanical Stimulation
COMMITTEE: Dr. Jun Ueda, Chair (ME)
Dr. YongTae (Tony) Kim (ME)
Dr. Frank Hammond (ME)
Dr. Minoru Shinohara (APPH)
Dr. Dobromir Rahnev (PSYC)


Recent studies indicate that neural plasticity may contribute to functional recovery after a stroke and long-term potentiation (LTP) has been regarded as a contributor to motor learning because it strengthens excitatory synapses. Paired associative stimulation (PAS) is an intervention that repeatedly applies transcranial magnetic stimulation (TMS) with conditioned peripheral stimulation. In conventional PAS, electrical stimulation is used as peripheral stimulation. It is known that only at the appropriate inter-stimulus interval (ISI) between them, LTP is induced in the human motor cortex. To effectively induce LTP, PAS must be repeatedly applied with an appropriate ISI. Despite promising features of PAS, tight time synchronization constraint in PAS and large variability in effective ISI among individuals still remain problems. In this study, the combination of TMS and mechanical stimulation is used for paired brain stimulation with mechanical stimulation similar to PAS. This paired brain stimulation with mechanical stimulation (mPBS) was inspired by a specific clinical practice called repetitive facilitation exercise or RFE. Using mechanical stimulation in PBS instead of the electrical stimulation is expected to not only address tight timing issues associated with the electrical stimulation but also bridge the gap between the specific clinical practice RFE and conventional PAS. The objective of this research is to characterize and understand mPBS. In order for that this research focuses on the development of a mechanical stimulation platform that enables the mPBS intervention to induce neural facilitation in more repeatable ways; characterization of the ISI profile in the mPBS for each individual; and development of automated ISI tuning system for mPBS.