Biomedical Engineering | Sungkunykwan University

본문 바로가기
주메뉴 바로가기
서브메뉴 바로가기

Inspiring Future, Grand Challenge

Read More

Read More

Read More

Read More

Notice

Department News

Professor Taehyung Kim's Research Team Selected for NRF Individual Basic Research Program
2025-03-12
Professor Taehyung Kim's Research Team Selected for NRF Individual Basic Research Program - Professor Tae-Hyung Kim has been selected for the Mid-Career Researcher Support Program (Type 1 - Global Cooperation) with his research on the development of a 3D nanomaterial-based multi-layer platform technology, receiving approximately ₩300 million per year for five years. - Dr. Kyeong-Mo Koo, a research fellow, has been awarded the Sejong Science Fellowship (Domestic Track) for his research on the development of a platform technology for cellular rejuvenation monitoring, receiving approximately ₩130 million per year for five years. ▲(From left) Professor Tae-Hyung Kim, Dr. Kyeong-Mo Koo ◇ Professor Tae-Hyung Kim and Dr. Kyeong-Mo Koo Selected for NRF Mid-Career Researcher Support Program and Sejong Science Fellowship The research team of Professor Tae-Hyung Kim has been selected for the NRF Mid-Career Researcher Support Program (Type 1 - Global Cooperation Project) under the NRF Individual Basic Research Program. Additionally, Dr. Kyeong-Mo Koo, a research fellow from the same lab, has been chosen for the Sejong Science Fellowship (Domestic Track). ◇ Professor Tae-Hyung Kim Selected for the NRF Mid-Career Researcher Support Program – Development of a 3D Nanomaterial-Based Multi-Layer Platform for Trilineage Formation The Mid-Career Researcher Support Program is designed to enhance the fundamental research capabilities of mid-career researchers and foster them into leading scientists by supporting their innovative research endeavors. Professor Kim’s research focuses on ‘Development of a three-dimensional nanomaterial multi-layer platform for high-efficiency autonomous generation of trilineage structures in vitro’. His project aims to control the differentiation of induced pluripotent stem cells (iPSCs) autonomously, facilitating the automatic formation and interaction of the three germ layers in a 3D environment. Expressing his gratitude, Professor Kim stated, “I am honored to be conducting this project among many outstanding researchers. I would like to extend my sincere appreciation to Sungkyunkwan University and the Industry-Academia Cooperation Foundation for their tremendous support during the proposal preparation process.” ▲[Figure 1] Development of a three-dimensional nanomaterial multi-layer platform for high-efficiency autonomous generation of trilineage structures in vitro ▲[Figure 2] Development of a Label-Free and Non-Destructive Multiplexing Electrochemical Platform for Mitochondrial Function Evaluation in Cellular Rejuvenation Monitoring

Turning Curiosity into Enlightenment: Science Talk Content "Between the Question Mark and Exclamation Mark"
2024-12-23
Episode 1 of "Between the Question Mark and Exclamation Mark" Hosts: Beom-Jun Kim, Dae-Han Lee Guests: Choong-Wan Woo, Won-Mok Shim → Watch Episode 1Source: Sungkyunkwan University (SKKU)

New Study Reveals How the Brain Integrates Pain Prediction and Stimuli
2024-12-05
New Study Reveals How the Brain Integrates Pain Prediction and Stimuli - Uncovering the neural mechanisms of pain processing using functional Magnetic Resonance Imaging (fMRI) - A study led by Associate Director WOO Choong-Wan of the Center for Neuroscience Imaging Research (CNIR) within the Institute for Basic Science (IBS), along with Michael YOO Seng Bum, Assistant Professor of Biomedical Engineering at Sungkyunkwan University, has uncovered new insights into how the brain processes and integrates pain information. Their research goes beyond identifying brain areas that respond to pain, revealing the mechanisms behind the brain's integration of pain-related information. Using functional magnetic resonance imaging (fMRI), they formalized how the brain combines pain expectations with the actual intensity of painful stimuli. Pain is a complex experience influenced not just by the intensity of a painful stimulus but also by the individual’s expectations. For instance, the pain one expects to feel can alter the perception of the actual pain experienced. While previous research has mapped out which brain regions handle these separate factors that contribute to our pain experience, this new study tackles the question of how these different factors come together to create a unified sensation of pain. KIM Jungwoo, the first author of the study, stated, “It’s not just about knowing which parts of the brain are important; ultimately, understanding how pain arises is key to figuring out how to eliminate unnecessary pain.” The researchers used fMRI to observe brain activity in participants exposed to varying levels of pain stimuli, while also manipulating their expectations about the level of pain they would feel. To fully understand how pain is processed in the brain, they separated the process into two stages: preservation (how the brain maintains information about pain expectations and stimulus intensity) and integration (how these elements combine to form a cohesive pain experience). They examined these processes across different levels of the brain’s cortical hierarchy*, expecting lower-level brain networks to preserve information without integrating it, and higher-level networks to preserve and integrate both. * Cortical Hierarchy: The brain processes information in a stepwise manner, with lower-level networks (like the sensory and motor networks) handling basic sensory input, and higher-level networks (such as the limbic system and default mode network) integrating more complex information. This study used this framework to understand how the brain processes and integrates pain information at different levels. Contrary to the researchers’ initial hypothesis, the results showed that all networks, regardless of level, preserved both types of information—pain expectations and stimulus intensity. However, only higher-level networks were able to integrate this information by simply adding the preserved expectation and stimulus information together. This suggests that while the entire brain stores pain information, only specific areas are responsible for integrating different pain-related signals into the experience of pain. This study represents a significant collaboration between two fields of neuroscience. Dr. Yoo, an expert in decision-making and electrophysiology, and Dr. Woo, a pain researcher specializing in fMRI, combined their expertise to explore how pain information is processed across the whole brain. Their innovative approach sheds light on the brain’s mechanisms for processing pain, providing valuable insights that could lead to new approaches to treating chronic pain. Michael YOO Seng Bum, the co-lead author said “It was a meaningful collaborative study that combined the strengths of each principal investigator to advance beyond merely reporting the activation of specific regions, allowing us to investigate principles of how information is integrated across the brain.” WOO Choong-Wan, another co-lead author, described the research as “an innovative study using geometric information encoded in brain activation patterns to reveal the integration mechanism of distinct types of pain information,” adding that “this discovery would not have been possible without a collaboration.” Figure 1. Hypothesis on the preservation and integration of pain information The left figure represents a three-dimensional space formed by fMRI voxels (volumetric activity unit captured by fMRI) within a network. The green two-dimensional plane (expectation subspace) represents the subspace preserving information about pain expectations, while the orange two-dimensional plane (stimulus subspace) represents the subspace preserving information about the stimulus intensity. The temporal activities of a network were projected onto these subspaces, and based on this information, the study examined whether each network preserved or integrated the two types of pain information. The initial hypothesis proposed that in lower-level networks (blue box), only one type of pain information would be well-preserved, leading to poor reconstruction of participants’ pain reports (indicating a lack of integration). In contrast, higher-level networks (red box) were hypothesized to preserve and integrate both types of pain information. Figure 2. Subspace patterns and comparison of reconstructed vs. actual pain reports Results are shown for the visual network (lower-level network) and the limbic system (higher-level network). The first row displays results from the visual network, while the second row shows results from the limbic system. From left to right, the columns represent brain patterns over time in the expectation subspace, brain patterns over time in the stimulus subspace, and a comparison between reconstructed pain ratings and actual pain ratings. The subspaces shown in the first and second columns preserved information related to each pain expectation and stimulus intensity. In the third column, the visual network primarily reconstructs differences in pain expectations, distinguished by different colors (red, gray, blue). In contrast, the limbic system successfully reconstructs both pain expectations and stimulus intensity information. Notes for editors - References Jungwoo Kim, Suhwan Gim, Seng Bum Michael Yoo, Choong-Wan Woo, A Computational Mechanism of Cue-Stimulus Integration for Pain in the Brain / Science Advances (2024) - Media Contact For further information or to request media assistance, please contact Choong-Wan Woo at the Center for Neuroscience Imaging Research, Institute for Basic Science (IBS) or Seng Bum Michael Yoo (CNIR) or William I. Suh at the IBS Public Relations Team (willisuh@ibs.re.kr). - About the Institute for Basic Science (IBS) IBS was founded in 2011 by the government of the Republic of Korea with the sole purpose of driving forward the development of basic science in South Korea. IBS has 7 research institutes and 31 research centers as of June 2024. There are eight physics, three mathematics, five chemistry, seven life science, two earth science, and six interdisciplinary research centers. Source : IBS Research News Link

HyungGoo Kim’s Joint Research Team Unveils Instinctive Behaviors in Living Organisms Using Artificial Intelligence
2024-11-15
Professor HyungGoo Kim's Team from the Global Biomedical Engineering Department Uncovers Principles of Instinctive Behaviors Using Artificial Intelligence Revealing the Mechanisms of "Hunger" and "Appetite" in Hypothalamic Neurons with AI-Based Models Researchers led by Professor HyungGoo Kim from Sungkyunkwan University’s Global Biomedical Engineering Department (co-first author: master’s student Jong Won Yun) and Professor Hyung Jin Choi from Seoul National University (co-first authors: Ph.D. student Kyu Sik Kim, Dr. Young Hee Lee, and Ph.D. candidate Yu-Been Kim) have presented a novel method for understanding instinctive psychological states in humans through the application of artificial intelligence (AI). Despite advancements in neuroscience enabling the observation of diverse animal behaviors, the connection between neural signals and instinctive psychological states remains insufficiently understood. Although prior studies have associated specific hypothalamic neurons with instinctive behaviors, the precise roles and mechanisms of these neurons were unclear. This collaborative research provides the first quantitative analysis of hypothalamic neural functions using AI, thereby clarifying the relationship between instinctive psychological states and behaviors. The team combined a novel homeostatic theory with AI-based neural models to reveal that Agouti-related peptide (AgRP) neurons in the hypothalamus represent "hunger," while leptin receptor (LH LepR) neurons represent "appetite." Experimental observations of hypothalamic neural activity patterns were meticulously analyzed, experimentally demonstrating how hunger and appetite are encoded through the activity patterns of specific neural populations. Professor Kim utilized a computational modeling approach, initially developed to distinguish the roles of dopamine, to devise a methodology for differentiating neural activations. This method successfully expressed Professor Choi’s novel homeostatic theory in mathematical terms. Fusing Traditional Homeostatic Theories with Cutting-Edge Neuroscientific Discoveries Professor Kim stated, “This study is the first to quantitatively analyze the activities of complex neural circuits by integrating AI with neuroscience. It marks a pivotal step toward numerically understanding instinctive behaviors in living organisms. Particularly, our elucidation of how hypothalamic neural activity regulates basic instincts like hunger and appetite holds significant implications.” Professor Choi added, “Neural responses observed in the hypothalamus during studies on feeding behavior were difficult to explain using existing theories. AgRP neurons were activated to promote feeding but decreased their activity upon food presentation. Conversely, LH LepR neurons not only promoted feeding upon activation but also increased activity when food was provided. To understand these paradoxical findings, we employed AI models, which led to the establishment of a new homeostatic theory.” Modeling Process Utilizing Artificial Intelligence The study provides crucial insights into how the brain regulates survival-essential behaviors such as feeding. It is anticipated to pave the way for new strategies in treating eating disorders, obesity, and appetite-related conditions. By integrating AI into neuroscience, the research opens possibilities for quantifying and understanding human instinctive behaviors, offering a versatile approach to investigating other instinctive behaviors and psychological states. Key Experimental Results The study includes computer modeling to demonstrate how neural activity correlates with specific psychological elements. (Gray line: neural signals; red line: optimal hunger model; green line: optimal appetite model; blue and orange lines: control models). The joint research by Professor Hyunggoo Kim and Professor Hyung Jin Choi was published in Science Advances on November 6. Paper Title: A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons Journal: Science Advances DOI: https://doi.org/10.1126/sciadv.ado1820

2024년 청소년 과학대장정(첨단 바이오) GBME학과 참여
2024-08-13
과학기술정보통신부와 한국과학창의재단이 주최한 2024년 청소년 과학대장정에 글로벌바이오메디컬공학과가 참여하였습니다. 중학생 34명과 함께 한 이야기를 성균웹진에서 소개하여 링크 첨부합니다. 성균웹진 | 커버스토리 | 커버스토리 (skku.edu) 유튜브 링크(https://youtube.com/shorts/kParm7nkyuc?si=nWMcWfNSFdpmJ7Hf)

2024 Freshman Orientation
2024-05-20
After the entrance ceremony on February 27th, the “2024 Freshman Orientation” was held at Pine Resort in Yongin for 3 days. Named 'Orientation of SKKU Institute for Convergence', a newly established orientation was conducted with the Department of Energy unlike previous years. A total of 124 students from both departments participated in the orientation and enjoyed their time.

prev next

Research Story

New Study Reveals How the Brain Integrates Pain Prediction and Stimuli
2024-12-05
New Study Reveals How the Brain Integrates Pain Prediction and Stimuli - Uncovering the neural mechanisms of pain processing using functional Magnetic Resonance Imaging (fMRI) - A study led by Associate Director WOO Choong-Wan of the Center for Neuroscience Imaging Research (CNIR) within the Institute for Basic Science (IBS), along with Michael YOO Seng Bum, Assistant Professor of Biomedical Engineering at Sungkyunkwan University, has uncovered new insights into how the brain processes and integrates pain information. Their research goes beyond identifying brain areas that respond to pain, revealing the mechanisms behind the brain's integration of pain-related information. Using functional magnetic resonance imaging (fMRI), they formalized how the brain combines pain expectations with the actual intensity of painful stimuli. Pain is a complex experience influenced not just by the intensity of a painful stimulus but also by the individual’s expectations. For instance, the pain one expects to feel can alter the perception of the actual pain experienced. While previous research has mapped out which brain regions handle these separate factors that contribute to our pain experience, this new study tackles the question of how these different factors come together to create a unified sensation of pain. KIM Jungwoo, the first author of the study, stated, “It’s not just about knowing which parts of the brain are important; ultimately, understanding how pain arises is key to figuring out how to eliminate unnecessary pain.” The researchers used fMRI to observe brain activity in participants exposed to varying levels of pain stimuli, while also manipulating their expectations about the level of pain they would feel. To fully understand how pain is processed in the brain, they separated the process into two stages: preservation (how the brain maintains information about pain expectations and stimulus intensity) and integration (how these elements combine to form a cohesive pain experience). They examined these processes across different levels of the brain’s cortical hierarchy*, expecting lower-level brain networks to preserve information without integrating it, and higher-level networks to preserve and integrate both. * Cortical Hierarchy: The brain processes information in a stepwise manner, with lower-level networks (like the sensory and motor networks) handling basic sensory input, and higher-level networks (such as the limbic system and default mode network) integrating more complex information. This study used this framework to understand how the brain processes and integrates pain information at different levels. Contrary to the researchers’ initial hypothesis, the results showed that all networks, regardless of level, preserved both types of information—pain expectations and stimulus intensity. However, only higher-level networks were able to integrate this information by simply adding the preserved expectation and stimulus information together. This suggests that while the entire brain stores pain information, only specific areas are responsible for integrating different pain-related signals into the experience of pain. This study represents a significant collaboration between two fields of neuroscience. Dr. Yoo, an expert in decision-making and electrophysiology, and Dr. Woo, a pain researcher specializing in fMRI, combined their expertise to explore how pain information is processed across the whole brain. Their innovative approach sheds light on the brain’s mechanisms for processing pain, providing valuable insights that could lead to new approaches to treating chronic pain. Michael YOO Seng Bum, the co-lead author said “It was a meaningful collaborative study that combined the strengths of each principal investigator to advance beyond merely reporting the activation of specific regions, allowing us to investigate principles of how information is integrated across the brain.” WOO Choong-Wan, another co-lead author, described the research as “an innovative study using geometric information encoded in brain activation patterns to reveal the integration mechanism of distinct types of pain information,” adding that “this discovery would not have been possible without a collaboration.” Figure 1. Hypothesis on the preservation and integration of pain information The left figure represents a three-dimensional space formed by fMRI voxels (volumetric activity unit captured by fMRI) within a network. The green two-dimensional plane (expectation subspace) represents the subspace preserving information about pain expectations, while the orange two-dimensional plane (stimulus subspace) represents the subspace preserving information about the stimulus intensity. The temporal activities of a network were projected onto these subspaces, and based on this information, the study examined whether each network preserved or integrated the two types of pain information. The initial hypothesis proposed that in lower-level networks (blue box), only one type of pain information would be well-preserved, leading to poor reconstruction of participants’ pain reports (indicating a lack of integration). In contrast, higher-level networks (red box) were hypothesized to preserve and integrate both types of pain information. Figure 2. Subspace patterns and comparison of reconstructed vs. actual pain reports Results are shown for the visual network (lower-level network) and the limbic system (higher-level network). The first row displays results from the visual network, while the second row shows results from the limbic system. From left to right, the columns represent brain patterns over time in the expectation subspace, brain patterns over time in the stimulus subspace, and a comparison between reconstructed pain ratings and actual pain ratings. The subspaces shown in the first and second columns preserved information related to each pain expectation and stimulus intensity. In the third column, the visual network primarily reconstructs differences in pain expectations, distinguished by different colors (red, gray, blue). In contrast, the limbic system successfully reconstructs both pain expectations and stimulus intensity information. Notes for editors - References Jungwoo Kim, Suhwan Gim, Seng Bum Michael Yoo, Choong-Wan Woo, A Computational Mechanism of Cue-Stimulus Integration for Pain in the Brain / Science Advances (2024) - Media Contact For further information or to request media assistance, please contact Choong-Wan Woo at the Center for Neuroscience Imaging Research, Institute for Basic Science (IBS) or Seng Bum Michael Yoo (CNIR) or William I. Suh at the IBS Public Relations Team (willisuh@ibs.re.kr). - About the Institute for Basic Science (IBS) IBS was founded in 2011 by the government of the Republic of Korea with the sole purpose of driving forward the development of basic science in South Korea. IBS has 7 research institutes and 31 research centers as of June 2024. There are eight physics, three mathematics, five chemistry, seven life science, two earth science, and six interdisciplinary research centers. Source : IBS Research News Link

HyungGoo Kim’s Joint Research Team Unveils Instinctive Behaviors in Living Organisms Using Artificial Intelligence
2024-11-15
Professor HyungGoo Kim's Team from the Global Biomedical Engineering Department Uncovers Principles of Instinctive Behaviors Using Artificial Intelligence Revealing the Mechanisms of "Hunger" and "Appetite" in Hypothalamic Neurons with AI-Based Models Researchers led by Professor HyungGoo Kim from Sungkyunkwan University’s Global Biomedical Engineering Department (co-first author: master’s student Jong Won Yun) and Professor Hyung Jin Choi from Seoul National University (co-first authors: Ph.D. student Kyu Sik Kim, Dr. Young Hee Lee, and Ph.D. candidate Yu-Been Kim) have presented a novel method for understanding instinctive psychological states in humans through the application of artificial intelligence (AI). Despite advancements in neuroscience enabling the observation of diverse animal behaviors, the connection between neural signals and instinctive psychological states remains insufficiently understood. Although prior studies have associated specific hypothalamic neurons with instinctive behaviors, the precise roles and mechanisms of these neurons were unclear. This collaborative research provides the first quantitative analysis of hypothalamic neural functions using AI, thereby clarifying the relationship between instinctive psychological states and behaviors. The team combined a novel homeostatic theory with AI-based neural models to reveal that Agouti-related peptide (AgRP) neurons in the hypothalamus represent "hunger," while leptin receptor (LH LepR) neurons represent "appetite." Experimental observations of hypothalamic neural activity patterns were meticulously analyzed, experimentally demonstrating how hunger and appetite are encoded through the activity patterns of specific neural populations. Professor Kim utilized a computational modeling approach, initially developed to distinguish the roles of dopamine, to devise a methodology for differentiating neural activations. This method successfully expressed Professor Choi’s novel homeostatic theory in mathematical terms. Fusing Traditional Homeostatic Theories with Cutting-Edge Neuroscientific Discoveries Professor Kim stated, “This study is the first to quantitatively analyze the activities of complex neural circuits by integrating AI with neuroscience. It marks a pivotal step toward numerically understanding instinctive behaviors in living organisms. Particularly, our elucidation of how hypothalamic neural activity regulates basic instincts like hunger and appetite holds significant implications.” Professor Choi added, “Neural responses observed in the hypothalamus during studies on feeding behavior were difficult to explain using existing theories. AgRP neurons were activated to promote feeding but decreased their activity upon food presentation. Conversely, LH LepR neurons not only promoted feeding upon activation but also increased activity when food was provided. To understand these paradoxical findings, we employed AI models, which led to the establishment of a new homeostatic theory.” Modeling Process Utilizing Artificial Intelligence The study provides crucial insights into how the brain regulates survival-essential behaviors such as feeding. It is anticipated to pave the way for new strategies in treating eating disorders, obesity, and appetite-related conditions. By integrating AI into neuroscience, the research opens possibilities for quantifying and understanding human instinctive behaviors, offering a versatile approach to investigating other instinctive behaviors and psychological states. Key Experimental Results The study includes computer modeling to demonstrate how neural activity correlates with specific psychological elements. (Gray line: neural signals; red line: optimal hunger model; green line: optimal appetite model; blue and orange lines: control models). The joint research by Professor Hyunggoo Kim and Professor Hyung Jin Choi was published in Science Advances on November 6. Paper Title: A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons Journal: Science Advances DOI: https://doi.org/10.1126/sciadv.ado1820

How Brain Changes as We Age: Thalamocortical Connectivity and the Formation of Functional Networks
2024-08-05
In our daily lives, our brains seamlessly process streams of visual information from the world around us while simultaneously understanding the causal structure of events. These essential cognitive functions, known as external sensory processing and internal world modeling, are critical for navigating complex environments. Our brain achieves this through large-scale functional systems responsible for these processes. Recently, an international collaboration of scientists led by the Institute for Basic Science (IBS) has explored the role of thalamocortical connectivity during the development of brain networks. One longstanding question in neuroscience is how the brain's large-scale functional networks form during development. This study investigated the changes in connectivity between the thalamus and cerebral cortex from infancy to adulthood and how these changes influence the formation of the brain's functional networks. For the first time, researchers have revealed that thalamocortical connectivity is crucial for the emergence and specialization of the brain's functional networks, particularly those processing external and internal information. Traditionally seen as a relay station for sensory information, the thalamus also influences higher cognitive functions. Sensory connections between the thalamus and cortex become established quickly at an early age, while higher-order cognitive connections develop later at maturity. However, the exact mechanisms and timeline of these developments have remained unclear. This study began to address these challenges by employing advanced neuroimaging techniques, transcriptomic analyses, and computational models on cross-sectional and longitudinal datasets, to map the development of thalamocortical connectivity across different age groups. This study revealed that during infancy, thalamocortical connectivity reflects early sensorimotor network differentiation and gene expression patterns related to brain development. As children grow, this connectivity shifts to establish connections with the salience network, differentiating external and internal functional cortical systems. Simulations confirmed thalamic connectivity's role in developing key features of the mature brain, such as functional segregation and the sensory-association axis. "Our study for the first time provides a detailed map of how thalamocortical connectivity contributes to the large-scale functional organization in the human brain from infancy through young adulthood," said lead author PARK Shinwon. "By integrating advanced neuroimaging techniques, gene expression analysis, and computational modeling, we were able to systematically track and analyze the changes in brain connectivity across different developmental stages. This comprehensive approach has allowed us to uncover the pivotal role of the thalamus in the emergence and specialization of brain networks." Unlike earlier studies that focused on regional properties of individual thalamic nuclei, this research provides a comprehensive view of the global integration of the thalamus into cortical networks. These findings offer potential implications for understanding and studying clinical conditions characterized by compromised internal and external processing, such as autism, schizophrenia, and other neurodevelopmental conditions. The corresponding author, HONG Seok Jun, a principal investigator at the IBS Center for Neuroscience Imaging Research stated, "Understanding how thalamocortical connectivity evolves and influences brain function provides a crucial foundation for identifying the mechanisms underlying neurodevelopmental conditions. This research opens up new possibilities for early diagnosis and targeted interventions, which could significantly improve outcomes for individuals with neurodevelopmental conditions." In the future, the researchers plan to investigate how thalamocortical connectivity changes in children with autism and how these changes correlate with clinical symptoms and cognitive functions. They also plan to expand their research focus to include other subcortical structures such as the striatum and cerebellum. This broader approach in systems neuroscience will help us gain a more comprehensive understanding of how various brain regions interact and develop. Figure 1. Thalamic connectopic maps (CMAP) and neocortical projection maps (NEOMAP) demonstrate the developmental changes in brain connectivity. Panel (a) shows CMAP 1 & 2 and NEOMAP 1 & 2 for infants (29–44 weeks), illustrating early differentiation of sensorimotor networks. Panel (b) displays these maps for children and young adults (8–22 years), highlighting the establishment of connections with the salience network and the differentiation between externally and internally oriented systems. Network profiles, sorted based on the Yeo-Krienan 7 Network Atlas, are depicted in box plots indicating the median and interquartile range (IQR). Panel (c) presents a schematic of the external-to-internal axis division derived from the NEOMAPs of childhood and young adulthood, showing the crucial role of the salience network.

IBS Neuroscience Imaging Research Center Director, Seong Gi Kim, Awarded ISMRM Gold Medal
2024-05-08
IBS Neuroscience Imaging Research Center Director, Seong Gi Kim, Awarded ISMRM Gold Medal - First Asian recipient in the field of magnetic resonance imaging (MRI)… Medal presentation on May 6 IBS Neuroscience Imaging Research Center Director, Seong Gi Kim (Chair Professor of Biomedical Engineering), has been awarded the prestigious Gold Medal at the International Society for Magnetic Resonance in Medicine (ISMRM), the world's leading academic conference in the MRI field. He is the first Asian scientist to receive this honor. The ISMRM Gold Medal recognizes significant contributions to the field of magnetic resonance each year and is awarded to the top 2-4 researchers. Professor Kim is one of the first scientists to apply functional magnetic resonance imaging (fMRI) techniques* to humans since 1992. After holding a professorship at the University of Pittsburgh under Professor Paul Lauterbur, a recipient of the 2003 Nobel Prize in Physiology or Medicine for his contributions to the invention of MRI, Kim returned to Korea to contribute to the advancement of neuroscience. He joined IBS in 2013. At this year's annual meeting, his contributions to understanding the basic physiological basis of fMRI signals through human and animal studies were recognized. *Functional magnetic resonance imaging measures changes in oxygen saturation due to brain activation. Professor Kim's research focuses on elucidating the correlation between phenomena occurring in brain cells and the signals captured by MRI. His notable achievements include developing new MRI methods to measure brain blood flow and volume, clarifying the relationship between brain cell activity and changes in blood flow and volume, elucidating the correlation between fMRI signals, and understanding the causality of information processing between activated brain areas. The Gold Medal was awarded to a total of three recipients: Professor Seong Gi Kim of Sungkyunkwan University, Professor Leon Axel of New York University (a medical scientist), and Professor Yi Wang of Cornell University (a physicist). In the field of medical science, Professor Kaori Togashi of Kyoto University in Japan received the award in 2020, while in the field of MR science, Director Seong Gi Kim is the first Asian recipient. Among the past recipients of the ISMRM Gold Medal, Richard Ernst, a Nobel laureate in Chemistry in 1991, and Paul Lauterbur and Peter Mansfield, Nobel laureates in Physiology or Medicine in 2003, are notable. Director Kim said, "IBS Neuroscience Imaging Research Center possesses the world's highest-quality high-field MRI facilities for both humans (7 Tesla) and animals (15.2 Tesla)." He added, "Establishing the IBS-Sungkyunkwan University N Center, the top MRI research facility, in Korea and receiving this award are significant achievements." He also stated, "It is even more honorable to achieve such results through basic research rather than through the development of new imaging technologies or clinical research in the field of MRI." *Tesla (T): Unit of magnetic field strength, with 1 Tesla being approximately 20,000 times the strength of Earth's magnetic field. ISMRM has 8,000 professional members from 58 countries, and its annual conference is the largest event attended by researchers, clinicians, government agencies, academia, and industry leaders. The award ceremony took place on May 6 in Singapore. 2024 Gold Medal Award Winners - ISMRM

Prof. Kim Seong-Gi's lab published on Neuron
2024-04-12
Prof. Seong-Gi Kim published 'Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics' in Neuron on June, 2023. Further details can be obtained from the following link. Kim, Seonghoon, et al. "Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics." Neuron 111.11 (2023): 1732-1747.

Prof. Jang-Yeon Park's Lab published in Science
2022-10-18
Prof. Jang-Yeon Park published 'In vivo direct imaging of neuronal activity at high temporospatial resolution' in Science on October, 2022. Further details can be obtained from the following link. Toi, Phan Tan, et al. "In vivo direct imaging of neuronal activity at high temporospatial resolution." Science 378.6616 (2022): 160-168.

prev next

SKKU Movie

SKKU Announcement

News
Notice
Research

Link