Development and applications of real-time functional MRI
The aim of this research is to develop a real-time functional MRI system at Nagoya University’s Brain and Mind Research Center and investigate its potential applications in cognitive training, brain machine interface, and neuro-rehabilitation, among others. Functional magnetic resonance imaging (fMRI) has been extensively used in the neurosciences to elucidate the different functions of the human brain. Real-time functional MRI has enabled the development of novel methods to probe these functions in almost real-time.
- Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder, J. Paul Hamilton, Gary H. Glover, Epifanio Bagarinao, Catie Chang, Sean Mackey, Matthew D. Sacchet, Ian H. Gotlib, Psychiatry Research: Neuroimaging, 2016, doi: 10.1016/j.pscychresns.2016.01.016
- Real-time fMRI applied to pain management, Heather Chapin, Epifanio Bagarinao, and Sean Mackey, Neuroscience Letters 520, 174-181, 2012 doi:10.1016/j.neulet.2012.02.076
- Dynamic monitoring of brain activation under visual stimulation using fMRI – The advantage of real-time fMRI with sliding window GLM analysis, Toshiharu Nakai, Epifanio Bagarinao, Kayako Matsuo, Yuko Ohgami, and Chikako Kato, Journal of Neuroscience Methods 157, 158-167, 2006
- Real-Time Functional MRI: Development and Emerging Applications, Epifanio Bagarinao, Toshiharu Nakai, and Yoshio Tanaka, Magn Reson Med Sci 5, 157-165, 2006
- Learning to control brain activity pattern using real-time functional MRI: A feasibility study, Kakenhi Grants-In-Aid for Scientific Research C, April 1, 2014 – March 31, 2017 (Principal investigator)
Related blog posts
Functional magnetic resonance imaging (fMRI) has been known for its high spatial resolution in localizing brain activation, but determining the timing of the activation could not be readily resolved from fMRI dataset. On the other hand, electroencephalography (EEG) data has temporal resolution in the order of milliseconds, but by itself, is not able to resolve with great accuracy the location of the activation. The combined measurement and analysis of EEG and fMRI data could therefore provide both high temporal as well as high spatial resolution in examining the functions of the human brain. In this research, we used simultaneous EEG-fMRI to identify brain activation with both high temporal as well as spatial resolution.
Epileptic focus localization
Epilepsy is a neurological disorder that roughly affects 0.5 – 1% of the world’s population. About 25% of patients with epilepsy have medically uncontrollable seizures, significantly affecting the patients’ quality of life. For medically refractory epilepsy, surgical resection is a necessary approach and accurately identifying the location of epileptic focus is critical in this operation. For this, we used simultaneous EEG-fMRI to identify the location of epileptic focus.
Detection of sub-second activation dynamics
We are also investigating the feasibility of using simultaneous EEG-fMRI measurement to detect sub-second activation changes. For this, we are developing an algorithm that employed the highly dynamic spatiotemporal information of the whole scalp EEG data to generate dynamic activation maps from fMRI data with millisecond resolution.
BMRC Aging Cohort Study
This is an ongoing study of the Brain and Mind Research Center, Nagoya University. Using several imaging modalities, such as resting state fMRI, T1- and T2-weighted MR images, diffusion tensor imaging (DTI), and magnetoencephalography (MEG), the study aimed to investigate the effects of healthy aging in brain. We’ve investigated age-related changes in resting state networks using independent component analysis and graph theory, in fractional anisotrophy using DTI, and in gray matter atrophy using anatomical T1-weighted images.
- Co-Investigator, 術中情報を統合した４Dマルチレイヤーナビゲーション・手術プラットフォームの開発, KAKENHI Grant-In-Aid for Scientific Research B (FY 2015 – 2019), PI: 藤井 正純 (Masazumi Fujii)
- Co-Investigator, リアルタイム機能的MRI－脳波同時測定装置を用いた時間的空間的脳内神経回路解析, KAKENHI Grant-In-Aid for Scientific Research Challenging Exploratory Research (FY 2015 – 2017), PI: 渡辺 弘久 (Hirohisa Watanabe)
- Co-Investigator, 運動処方への初期応答による高齢者の分類法の確立, KAKENHI Grain-In-Aid for Scientific Research B (FY 2015 – 2019), PI: 中井 敏晴 (Toshiharu Nakai)
- Principal Investigator, Learning to control brain activity pattern using real-time functional MRI: A feasibility study, KAKENHI Grants-In-Aid for Scientific Research C (FY 2014 – 2016)