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- New Study Reveals How the Brain Integrates Pain Prediction and Stimuli NEW
- 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
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- 작성일 2024-12-05
- 조회수 0
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- HyungGoo Kim’s Joint Research Team Unveils Instinctive Behaviors in Living Organisms Using Artificial Intelligence
- 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
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- 작성일 2024-11-20
- 조회수 45
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- Prof. Kim Inki's Lab published in Nature communications
- Prof. Kim Inki's lab published 'Metasurface-driven full-space structured light for three-dimensional imaging' in Nature communications on October, 2022. Further details can be obtained from the following link. Kim, Gyeongtae, et al. "Metasurface-driven full-space structured light for three-dimensional imaging." Nature communications 13.1 (2022): 1-10.
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- 작성일 2022-11-21
- 조회수 1045
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- Prof. Jang-Yeon Park's Lab published in Science
- 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.
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- 작성일 2022-10-18
- 조회수 1107
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- Prof. Park Chun Gwon published in Biomaterials
- Prof. Park Chun Gwon published 'Image-guided in situ cancer vaccination with combination of multi-functional nano-adjuvant and an irreversible electroporation technique' in Biomaterials on October, 2022. Further details can be obtained from the following link. Press article : http://www.lecturernews.com/news/articleView.html?idxno=106458 Han, Jun-Hyeok, et al. "Image-guided in situ cancer vaccination with combination of multi-functional nano-adjuvant and an irreversible electroporation technique." Biomaterials 289 (2022): 121762.
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- 작성일 2022-10-13
- 조회수 964
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- Prof. Woo Choong-Wan's Lab published in Science Advances
- Prof. Woo Choong-Wan's Lab published 'When self comes to a wandering mind : Brain representations and dynamics of self-generated concepts in spontaneous thought' in Science Advances on August 31th, 2022. Further details can be obtained from the following link. Kim, Byeol, et al. "When self comes to a wandering mind: Brain representations and dynamics of self-generated concepts in spontaneous thought." Science advances 8.35 (2022): eabn8616.
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- 작성일 2022-10-13
- 조회수 1254
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- Prof. Park Jaeseok's Lab published in Medical Image Analysis
- Prof. Park Jaeseok's Lab published 'Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective' in Medical Image Analysis on November , 2022. Further details can be obtained from the following link. Lim, Eun Ji, et al. "Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective." Medical Image Analysis (2022): 102621.
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- 작성일 2022-10-13
- 조회수 1261
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- Prof. Woo Choong-Wan's Lab published in Nature Neuroscience
- Prof. Woo Choong-Wan's Lab published 'Individual variability in brain representations of pain' in Nature Neuroscience on May 30th, 2022. Further details can be obtained from the following link. Kohoutová, L., Atlas, L. Y., Büchel, C., Buhle, J. T., Geuter, S., Jepma, M., ... & Woo, C. W. (2022). Individual variability in brain representations of pain. Nature Neuroscience, 1-11.
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- 작성일 2022-06-15
- 조회수 1228
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- Prof. Shin Mikyung's Lab publishes in Advanced Functional Materials
- Prof. Shin Mikyung's Lab published 'Optically Anisotropic Topical Hemostatic Coacervate for Naked-Eye Identification of Blood Coagulation' in Advanced Functional Materials on December 19th, 2021. Further details can be obtained from the following link. Jin, S., Kim, S., Kim, D. S., Son, D., & Shin, M. Optically Anisotropic Topical Hemostatic Coacervate for Naked‐Eye Identification of Blood Coagulation. Advanced Functional Materials, 2110320.
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- 작성일 2021-12-24
- 조회수 792
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- Prof. Chun Gwon Park wins the “Young Biomedical Engineering Award”
- Professor Chun Gwon Park won the Lutronic ‘Young Biomedical Engineering Award” at the Joint Conference of the IBEC and the ICBHI held on November 10th~12th. The ‘Young Biomedical Scholar Award’ is given to one of the scholars who has excellent industry-academic cooperation and academic achievements in the field of biomedical engineering, received his/her Ph.D. within 10 years and is below the age of 40. This award is sponsored by Lutronic, Korea’s No. 1 & World’s No. 10 laser medical device company. Professor Chun Gwon Park was selected as the winner for his contribution to the development of academic achievements and societies in the field of biomedical engineering and biomaterials. The Korean Society of Medical & Biological Engineering has more than 6,000 members and is a leading biomedical engineering/medical technology society in Korea since its foundation in 1979. Congratulations!
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- 작성일 2021-11-23
- 조회수 870