My areas of research interest include epilepsy, neurophysiology, the seizure network and cognitive neuroscience. I’ve always been curious about how the brain works, and it fascinates me that it is still not fully understood.
My work aims to contribute to the body of knowledge for understanding fully how the brain works. While I was in the senior year of my undergrad program, I joined a clinical lab to study patients with epilepsy, particularly those who were not cured with anti-seizure medication. The overarching purpose of my research is to understand the epilepsy network and improve seizure outcomes of patients with drug-resistant epilepsy and newly diagnosed epilepsy using translational and clinical approaches.
I use advanced mathematical and statistical analysis in my research, including functional connectivity and graph theory. My work aims to predict seizure outcomes and treatment responses. I use a state-of-art noninvasive tool called Magnetoencephalography (MEG) that records magnetic fields of electrical activity to locate their source inside the brain. For patients who undergo noninvasive presurgical evaluation, we want to find better tools that precisely detect where the seizure is coming from and understand the seizure network of individual patients to predict their surgical outcome.
I am honored to have been awarded a Postdoctoral Research Fellowship from the American Epilepsy Society (2020). I began my work with Cincinnati Children’s in 2006 as a neurodiagnostic technologist. I’m now a neuroscientist and a manager of MEG Core at Cincinnati Children’s.
AS: Medical Technology, Graduate Kyoto University College of Medical Technology, Kyoto, Japan, 1998.
BS: Health Science, major of Medical Technology, The Open University of Japan, Tokyo, Japan, 2002.
AS: Electroneurodiagnostic Technology, Kirkwood Community College, Cedar Rapids, IA, 2005.
PhD: Neuroscience, The University of Cincinnati, Cincinnati, OH, 2018.
MEG for epilepsy presurgical evaluation
Neurology
Neuroscience; neurophysiology; epilepsy; brain network.
Neurology
Correlation of NICU anthropometry in extremely preterm infants with brain development and language scores at early school age. Scientific Reports. 2023; 13:15273.
Tolerability of transcranial magnetic stimulation language mapping in children. Epilepsy Research. 2023; 194:107183.
Comparing electrical stimulation functional mapping with subdural electrodes and stereoelectroencephalography. Epilepsia. 2023; 64:1527-1540.
Clinical validation of magnetoencephalography network analysis for presurgical epilepsy evaluation. Clinical Neurophysiology. 2022; 142:199-208.
MEG pharmacology: Sedation and optimal MEG acquisition. Clinical Neurophysiology. 2022; 138:143-147.
Improving Detection of Hippocampal Epileptiform Activity Using Magnetoencephalography. Journal of Clinical Neurophysiology. 2022; 39:240-246.
Beta synchrony for expressive language lateralizes to right hemisphere in development. Scientific Reports. 2021; 11:3949.
Functional Hyperconnectivity during a Stories Listening Task in Magnetoencephalography Is Associated with Language Gains for Children Born Extremely Preterm. Brain Sciences. 2021; 11.
Delineation of epileptogenic zones with high frequency magnetic source imaging based on kurtosis and skewness. Epilepsy Research. 2021; 172:106602.
The Value of Source Localization for Clinical Magnetoencephalography: Beyond the Equivalent Current Dipole. Journal of Clinical Neurophysiology. 2020; 37:537-544.