【Success Story Vol. 43】
Takashi Tsukiura, Professor at Kyoto University

■ Learning Experience

Tsukiura Takashi graduated from Tohoku University's Faculty of Education in 1996 and completed his PhD in Disability Science in the medical research program at Tohoku University in 2001. Between 2000 and 2001, Tsukiura worked as a research fellow (DC2) at the Japan Society for the Promotion of Science. From 2001 to 2008, he served as a researcher in the Neural Information Analysis Research Division at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan and also had the opportunity to be a visiting researcher at the Duke University Center for Cognitive Neuroscience in the United States from 2006 to 2008.
From 2008 to 2011, Tsukiura Takashi held the position of Associate Professor at the Aging Research Institute of Tohoku University. Subsequently, from 2011 to 2017, he served as an Associate Professor in the Graduate School of Human and Environmental Studies at Kyoto University, and was a professor there since 2017.

■ Main Research

■ Other Research

You are very likely to live to the age of one hundred, and a large-scale scientific research project called "Lifespan Studies" aims to revolutionize traditional views on life through the integration of research from various fields such as psychology, sociology, cultural anthropology, and anthropology that may include research on retrospective aging. This shift is changing our perception of aging over time.

Tsukiura also investigates the functionality of the brain and mind from the perspectives of experimental psychology, brain function measurement, and neuropsychology. This forms the basis of the new concept of aging and studies what kind of public services and social support are needed for individuals to continue working energetically. Through sociological research and cultural anthropology studies based on field research in different cultures, Tsukiura examines cultures with different views on aging. Ultimately, Tsukiura’s aim is to integrate this knowledge into society through lifelong learning and education.

“The project is designed to understand the human life cycle through the integration of various fields. Our goal is to share a new perspective on life in a super-aging society with society as a whole, allowing individuals of all generations to lead fulfilling lives.”

■ About fMRI

Research on the mechanisms of the brain require tests with both healthy young individuals and older individuals to understand how brain usage during memory tasks changes with age in the younger generation. Using functional magnetic resonance imaging (fMRI), Tsukiura examined how performance changes with age when performing the same tasks and whether there are differences in how the brain is used.

The imaging equipment used in fMRI studies is similar to the MRI equipment used in hospitals. However, because our research employs different imaging methods, it is referred to as functional MRI (fMRI). To draw an analogy, you can use a smartphone to take photos, but you can also shoot videos. In a hospital setting, MRI is used to pinpoint the location of diseases and make diagnoses, while functional magnetic resonance imaging captures images of how the brain functions and records tiny changes occurring in the brain every second.

When there is neural activity in specific regions of the brain, the blood flow in those areas changes. fMRI captures these changes in blood flow by detecting variations in the magnetic field. Consequently, by analyzing the images obtained through fMRI, we can gain insights into how the brain is being utilized to a certain extent.

■ How an ASUSTOR NAS Helped Him

Due to the large volume of image data, much of which is captured using fMRI, Tsukiura decided to use a Network-Attached Storage (NAS) system for storage. The university often invests in and utilizes high-reliability NAS systems because they aim to store files securely, for long-term use, and with minimal risk of failures. In recent years, with the use of technologies like machine learning, the analysis of fMRI images has become more complex. To conduct analyses as efficiently as possible, workstations were purchased and used regularly.
As mentioned earlier, when conducting network analyses between specific regions of the brain or employing machine learning for analysis, workstation systems are highly valuable because they involve substantial computational workloads. They also offer the flexibility to be customized as needed, which is quite practical in our work.

■ About Student Research Projects