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An octopamine-specific GRAB sensor reveals a monoamine relay circuitry that boosts aversive learning

National science Review 2024年第5期11卷 186-201页

作者： Mingyue Lv Ruyi Cai Renzimo Zhang Xiju Xia Xuelin Li Yipan Wang Huan Wang Jianzhi Zeng Yifei Xue Lanqun Mao Yulong Li State Key Laboratory of Membrane Biology School of Life SciencesPeking University State Key Laboratory of Brain and Cognitive Science Institute of Biophysics Chinese Academy of Sciences PKU-IDG/Mc Govern Institute for Brain Research Yuanpei College Peking University Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary Studies Peking University Institute of Molecular Physiology Shenzhen Bay Laboratory College of Chemistry Beijing Normal University Chinese Institute for Brain Research

Octopamine（OA）,analogous to norepinephrine in vertebrates,is an essential monoamine neurotransmitter in invertebrates that plays a significant role in various biological functions,including olfactory associative ***,the spatial and temporal dynamics of OA in vivo remain poorly understood due to limitations associated with the currently available methods used to detect *** overcome these limitations,we developed a genetically encoded GPCR activation-based（GRAB） OA sensor called *** sensor is highly selective for OA and exhibits a robust and rapid increase in fluorescence in response to extracellular *** GRABOA1.0,we monitored OA release in the Drosophila mushroom body（MB）,the fly's learning center,and found that OA is released in response to both odor and shock stimuli in an aversive learning *** OA release requires acetylcholine（ACh） released from Kenyon cells,signaling via nicotinic ACh ***,we discovered that OA amplifies aversive learning behavior by augmenting dopamine-mediated punishment signals via Octβ1R in dopaminergic neurons,leading to alterations in synaptic plasticity within the ***,our new GRABOA1.0sensor can be used to monitor OA release in real time under physiological conditions,providing valuable insights into the cellular and circuit mechanisms that underlie OA signaling.

关键词： octopamine dopamine GRAB sensor learning and memory

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Over the Quantum Rainbow: Explaining Hybrid Quantum Reinforcement Learning

Over the Quantum Rainbow: Explaining Hybrid Quantum Reinforc...

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Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Junghoon Park Jiook Cha Samuel Yen-Chi Chen Shinjae Yoo Huan-Hsin Tseng Interdisciplinary Program in Artificial Intelligence Seoul National University Department of Psychology Seoul National University Department of Brain and Cognitive Sciences Seoul National University Graduate School of Data Science Seoul National University Wells Fargo Computational Science Initiative Brookhaven National Laboratory

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

In the realm of artificial intelligence, deep rein-forcement learning (RL) agents struggle with generalizability and require substantial computational resources, unlike humans who easily adapt and generalize across tasks. To address these challenges, we introduce Quantum Rainbow, a hybrid algorithm that leverages the neural mechanisms of human decision-making and the efficiency of quantum computing. Quantum Rainbow combines variational quantum circuits with the Rainbow Deep Q-Network (DQN) model to create a novel approach in rein-forcement learning that integrates quantum principles into deep learning paradigms. We evaluate our model using behavioral experiments through the Iowa Gambling Task and 4-Armed Bandit Task. Our investigations reveal a significant relationship between the architecture of quantum circuits and the performance of quantum RL agents. Specifically, using causal discovery methods, we demonstrate the critical role of quantum entanglement in enhancing model performance. These findings not only show promising results but also pave the way for future explorations into optimizing quantum circuit architectures for reinforcement learning applications. This study underscores the potential of quantum-enhanced algorithms to achieve “quantum advantage” by addressing fundamental limitations in conventional deep RL methods.

关键词： Analytical models Quantum computing Quantum algorithm Quantum advantage Quantum entanglement Computational modeling Reinforcement learning Quantum state Integrated circuit modeling Quantum circuit

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brain MRI Synthesis from Amyloid PET/CT via Enhanced Denoising Diffusion Probabilistic Model

Brain MRI Synthesis from Amyloid PET/CT via Enhanced Denoisi...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： Y.J. Seol H.B. Yoo E.J. Yoon Y.K. Kim J.S. Lee Integrated Major in Innovative Medical Science Seoul National University Seoul Republic of Korea Seoul National University Interdisciplinary Program in Bioengineering Seoul Republic of Korea Department of Nuclear Medicine and WCU Department of Brain and Cognitive Sciences Seoul National University Seoul Republic of Korea Department of Nuclear Medicine Seoul National University-Seoul Metropolitan Government Boramae Medical Center Seoul Republic of Korea Department of Nuclear Medicine Seoul National University Seoul Republic of Korea Brightonix Imaging Inc Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In this study, we presents a novel method for generating synthetic brain MRI images from amyloid PET/CT scans using an enhanced Denoising Diffusion Probabilistic Model (DDPM) conditioned with the joint probability distribution. We explored the use of early and late-phase 18 F -Florbetaben PET scans to guide the synthesis process within our DDPM framework, verifying that early-phase scans significantly improved the quality of synthetic MRI generation compared to other deep learning models. In addition, the proposed DDPMs using early-phase PET/CT suggest promising results, particularly for enhancing the accuracy of regional gray matter volume measurements and facilitating PET partial volume corrections in settings where traditional MRI is unavailable.

关键词： Temperature measurement Temperature distribution Microwave integrated circuits Semiconductor detectors Magnetic resonance imaging Volume measurement Noise reduction

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A nigroincertal projection mediates aversion and enhances coping responses to potential threat

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FASEB Journal 2023年第12期37卷 e23322-e23322页

作者： Ho, Ping-Chen Hsiao, Fu-Yun Chiu, Shi-Hong Lee, Syun-Ruei Yau, Hau-Jie The Laboratory for Neural Circuits and Behaviors Graduate Institute of Brain and Mind Sciences National Taiwan University Taipei Taiwan School of Medicine National Taiwan University Taipei Taiwan Neurobiology and Cognitive Science Center National Taiwan University Taipei Taiwan Taiwan International Graduate Program in Interdisciplinary Neuroscience National Taiwan University and Academia Sinica Taipei Taiwan Ph.D. Program in Translational Medicine National Taiwan University and Academia Sinica Taipei Taiwan

Recent studies have shown that the non-DA neurons in the ventral tegmental area (VTA) and substantia nigra (SN) not only modulate motivational behaviors but also regulate defensive behaviors. While zona incerta (ZI) is a threat-responsive substrate and receives innervations from the ventral midbrain, the function of the ventral midbrain-to-ZI connection remains poorly defined. Here, we demonstrate that the ZI receives heterogenous innervations from the ventral midbrain. By utilizing a retrograde AAV preferentially labeling non-DA neurons in the ventral midbrain, we found that ZI-projecting non-DA cells in the ventral midbrain are activated by restraint stress. We focused on the SN and found that SN-to-ZI GABAergic input is engaged by a predatory odor. Sustained pan-neuronal SN-to-ZI activation results in aversion and enhances defensive behaviors, likely through a disinhibition mechanism to recruit downstream brain regions that regulate defensive behaviors. Collectively, our results reveal a novel role of nigroincertal projection in mediating negative valence and regulating defensive behaviors. © 2023 Federation of American Societies for Experimental Biology.

关键词： defensive behavior stress substantia nigra ventral tegmental area zona increta

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Spatiotemporal Learning of brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for cognitive and Psychiatric Applications

arXiv

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arXiv 2025年

作者： Bae, Sangyoon Kwon, Junbeom Yoo, Shinjae Cha, Jiook Interdisciplinary Program in Artificial Intelligence Seoul National University Gwanak-ro 1 Seoul Seoul08826 Korea Republic of Department of Psychology University of Texas at Austin Dean Keeton Street AustinTX78712 United States Computational Science Initiative Brookhaven National Laboratory Brookhaven Avenue Shirley New York11967 United States Department of Psychology Seoul National University Gwanak-ro 1 Seoul Seoul08826 Korea Republic of Department of Brain and Cognitive Sciences Seoul National University Gwanak-ro 1 Seoul Seoul08826 Korea Republic of

A central challenge in neuroscience is understanding how the brain’s complex nonlinear dynamics give rise to emergent properties underlying adaptive cognition and behavior across spatial and temporal scales. These dynamics exhibit scale-free and multifractal properties, shaping the adaptive reconfiguration of neural networks. However, conventional neuroimaging models remain constrained by assumptions of linearity and stationarity, limiting their capacity to fully characterize these intricate processes. Transformer-based architectures, known for capturing long-range dependencies in sequential data, naturally align with the brain’s intrinsically hierarchical and temporal organization. Here, we introduce Multi-Band brain Net (MBBN), a transformer-based deep learning framework that explicitly models frequency-specific spatiotemporal brain dynamics from fMRI by integrating scale-free network principles with frequency-resolved multi-band self-attention mechanisms. Trained on three large-scale neuroimaging cohorts (UK Biobank, ABCD, ABIDE) totaling 45,951 individuals, MBBN reveals previously undetectable frequency-dependent intrinsic network interactions, shedding new light on distinct connectivity disruptions across psychiatric conditions (ADHD, ASD, depression). This extensive validation demonstrates robust generalizability and highlights core neural principles conserved across populations and developmental stages. Specifically, MBBN achieves up to 30.59% higher predictive accuracy than state-of-the-art deep learning and conventional connectome-based methods, demonstrating the advantage of frequency-informed spatiotemporal modeling in capturing latent neural computations. Furthermore, MBBN’s attention-based interpretability reveals novel frequency-specific biomarkers for neurodevelopmental disorders, offering mechanistic insights into the hierarchical organization of brain function. By providing a principled, interpretable framework for dissecting spatiotemporal learning

关键词： brain mapping

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Self-packaged stretchable printed circuits with ligand-bound liquid metal particles in elastomer

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Nature communications 2025年第1期16卷 4944页

作者： Hyeonyeob Seo Gun-Hee Lee Jiwoo Park Dong-Yeong Kim Yeonzu Son Semin Kim Kum Seok Nam Congqi Yang Joonhee Won Jae-Young Bae Hyunjun Kim Seung-Kyun Kang Steve Park Jiheong Kang Seongjun Park Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. Departments of Cogno-Mechatronics Engineering Pusan National University Busan Republic of Korea. Departments of Optics and Mechatronics Engineering Pusan National University Busan Republic of Korea. School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea. Graduate School of Semiconductor Technology Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. Medical Research Center Seoul National University Seoul Republic of Korea. Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. Department of Materials Science and Engineering Seoul National University Seoul Republic of Korea. KAIST Institute for NanoCentury Daejeon Republic of Korea. Department of Chemistry Seoul National University Seoul Republic of Korea. jiheongkang@snu.ac.kr. Medical Research Center Seoul National University Seoul Republic of Korea. seongjunpark@snu.ac.kr. Department of Biomedical Sciences College of Medicine Seoul National University Seoul Republic of Korea. seongjunpark@snu.ac.kr. School of Transdisciplinary Innovations Seoul National University Seoul Republic of Korea. seongjunpark@snu.ac.kr. Interdisciplinary Program in Bioengineering College of Engineering Seoul National University Seoul Republic of Korea. seongjunpark@snu.ac.kr. Department of Transdisciplinary Medicine Seoul National University Hospital Seoul South Korea. seongjunpark@snu.ac.kr.

Packaging in stretchable electronics is crucial to protect components from environmental damage while preserving mechanical flexibility and providing electrical insulation. The conventional packaging process involves multiple steps that increase in complexity as the number of circuit layers multiply. In this study, we introduce a self-packaged stretchable printed circuit board enabled by the in situ phase separation of liquid metal particles (LMPs) within various polymer matrices during solution-based printing processes. The ligand-bound LMPs (LB-LMPs), engineered to inhibit oxide growth, undergo in situ sintering, prompting vertical phase separation. This synthesis strategy not only achieves high initial conductivity of the LMPs but also encapsulates them within the polymer matrix, preventing leakage and providing electrical insulation. Our method enables multi-layer circuit printing, eliminating the need for additional activation and packaging processes. Furthermore, by integrating conductive materials into packaging layers for selective electrical conductivity, vertical interconnect accesses and conductive pads can be formed, enabling large-scale, stretchable, and leakage-free multi-layer electrical circuits and bio-interfaces.

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West Side Story: Regional Inter-Troop Variation in Baboon Bark-Stripping at Gorongosa National Park, Mozambique

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American Journal of Biological Anthropology 2025年第1期187卷 e70057页

作者： Biro, Dora Muschinski, Jana Hammond, Philippa Bobe, René Bamford, Marion K. Capelli, Cristian d’Oliveira Coelho, João Farassi, Rassina Lüdecke, Tina Martinez, Felipe I. Mathe, Jacinto Silva, Maria Joana Ferreira Carvalho, Susana Department of Brain and Cognitive Sciences University of Rochester Rochester NY United States Primate Models for Behavioural Evolution Lab Institute of Human Sciences School of Anthropology and Museum Ethnography University of Oxford Oxford United Kingdom Interdisciplinary Center for Archaeology and Evolution of Human Behaviour (ICArEHB) University of Algarve Faro Portugal Department of Science Gorongosa National Park Sofala Mozambique Evolutionary Studies Institute University of the Witwatersrand Johannesburg South Africa Department of Chemistry Life Sciences and Environmental Sustainability University of Parma Parma Italy Centre for Functional Ecology (CFE) Department of Life Sciences Universidade de Coimbra Coimbra Portugal Departamento de Ciências da Vida Universidade de Coimbra Coimbra Portugal Emmy Noether Group for Hominin Meat Consumption Max Planck Institute for Chemistry Mainz Germany Escuela de Antropología Facultad de Ciencias Sociales Pontificia Universidad Católica de Chile Ciudad de México Chile CIBIO Centro de Investigação Em Biodiversidade e Recursos Genéticos InBIO Laboratório Associado Campus de Vairão Universidade do Porto Vairão Portugal BIOPOLIS Program in Genomics Biodiversity and Land Planning CIBIO Vairão Portugal One Organisms and Environment Division School of Biosciences Cardiff University Cardiff United Kingdom

Objectives: Baboons possess sophisticated physical and social cognitive abilities;hence, the lack of evidence to date of large-scale behavioral variation in these primates is puzzling. Here we studied a candidate for such variation—the stripping of bark from Acacia robusta trees for consumption of the sap and soft tissue underneath—in Gorongosa National Park, Mozambique. Materials and Methods: We surveyed an area inhabited by ~60 troops of chacma baboons, recording the availability and characteristics of the target trees, as well as the presence or absence of bark-stripping at 45 habitat plots distributed across a grid covering an area of ~300 km². Results: Camera traps confirmed the presence of baboons at all habitat plots, and we identified regional clumping in the distribution of the behavior, a pattern consistent across two consecutive years. Proportion and mean height/width of A. robusta did not predict whether bark-stripping behavior was present at a given site, nor did broader ecological variables such as habitat type and distance to the nearest water source. However, stripping sites had significantly higher numbers of A. robusta than non-stripping sites, and within a given bark-stripping site, baboons preferred to strip taller and wider trees among those available. Discussion: The prominent geographical clustering we uncovered may have been driven by opportunity (i.e., the prevalence of A. robusta at a given site), but is also consistent with a possible (non-mutually exclusive) cultural interpretation. We propose avenues for future research on Gorongosa's baboons to better quantify the relative contributions of ecology, genetics, and social learning to the prevalence of bark stripping. We also briefly consider the potential relevance of baboon bark stripping to elucidating early hominin foraging strategies. © 2025 Wiley Periodicals LLC.

关键词： a cacia bark-stripping behavioral variation chacma baboon habitat survey non-technological material traces

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Correction: Astrocytic water channel aquaporin-4 modulates brain plasticity in both mice and humans: a potential gliogenetic mechanism underlying language-associated learning

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Molecular psychiatry 2021年第12期26卷 7853页

作者： J Woo J E Kim J J Im J Lee H S Jeong S Park S- Y Jung H An S Yoon S M Lim S Lee J Ma E Y Shin Y- E Han B Kim E H Lee L Feng H Chun B- E Yoon I Kang S R Dager I K Lyoo C J Lee Center for Neural Science and Functional Connectomics Korea Institute of Science and Technology (KIST) Seoul Republic of Korea. Neuroscience Program University of Science and Technology (UST) Daejeon Republic of Korea. Department of Brain and Cognitive Sciences Scranton College Ewha Womans University Seoul Republic of Korea. Ewha Brain Institute Ewha Womans University Seoul Republic of Korea. Interdisciplinary Program in Neuroscience College of Natural Sciences Seoul National University Seoul Republic of Korea. Division of Functional Food Research Korea Food Research Institute Seongnam Republic of Korea. Department of Radiology Incheon St. Mary's Hospital College of Medicine The Catholic University of Korea Seoul Republic of Korea. KU-KIST Graduate School of Converging Science and Technology Korea University145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. Department of Radiology College of Medicine Ewha Womans University Seoul Republic of Korea. Green Cross Laboratories Yongin Republic of Korea. Department of Nanobiomedical Science Dankook University Cheonan Republic of Korea. Department of Radiology University of Washington Seattle WA USA. Department of Bioengineering University of Washington Seattle WA USA. Department of Brain and Cognitive Sciences Scranton College Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Ewha Brain Institute Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Graduate School of Pharmaceutical Sciences Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Center for Neural Science and Functional Connectomics Korea Institute of Science and Technology (KIST) Seoul Republic of Korea. cjl@kist.re.kr. Neuroscience Program University of Science and Technology (UST) Daejeon Republic of Korea. cjl@kist.re.kr. KU-KIST Graduate School of Converging Science and Technology Korea University145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. cjl@kist.re.kr.

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Effect of C. sporogenes -derived metabolites on the circadian rhythm of Period2 and Bmal1 expression

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IBRO Reports 2019年 6卷 S416-S416页

作者： Kyojin Ku Inah Park Jeongah Kim Doyeon Kim Sangwon Jang Mijung Choi Han Kyoung Choe Kyungjin Kim Daegu Gyeongbuk Institute of Science and Technology Daegu Republic of Korea Department of Brain and Cognitive Sciences Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea Interdisciplinary Program in Neuroscience College of Natural Sciences Seoul National University Seoul Republic of Korea

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Volume entropy and generalized Markov system for modelling information flow in a brain graph

arXiv

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arXiv 2018年

作者： Lee, Hyekyoung Kim, Eunkyung Kang, Hyejin Huh, Youngmin Lee, Youngjo Lim, Seonhee Lee, Dong Soo Biomedical Research Institute Seoul National University Hospital Seoul National University Department of Nuclear Medicine Seoul National University Department of Rehabilitation Medicine Seoul National University College of Medicine Seoul National University Data Science for Knowledge Creation Research Center Seoul National University Interdisciplinary Program in Cognitive Science Seoul National University Department of Statistics College of Natural Sciences Seoul National University Department of Molecular Medicine and Biopharmaceutical Sciences College of Medicine or College of Pharmacy Seoul National University Graduate School of Convergence Science and Technology Department of Mathematical Sciences Seoul National University Seoul Korea Republic of Korea Brain Research Institute Daegu Korea Republic of

Entropy is a classical measure to quantify the amount of information or complexity of a system. Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis. However, they are less widely used than traditional graph theoretic measures such as global and local efficiencies because either they are not well-defined on a graph or difficult to interpret its biological meaning. In this paper, we propose a new entropy-based graph invariant, called volume entropy. It measures the exponential growth rate of the number of paths in a graph, which is a relevant measure if information flows through the graph forever. We model the information propagation on a graph by the generalized Markov system associated to the weighted edge-transition matrix. We estimate the volume entropy using the stationary equation of the generalized Markov system. A prominent advantage of using the stationary equation is that it assigns certain distribution of weights on the edges of the brain graph, which we call the stationary distribution. The stationary distribution shows the information capacity of edges and the direction of information flow on a brain graph. The simulation results show that the volume entropy distinguishes the underlying graph topology and geometry better than the existing graph measures. In brain imaging data application, the volume entropy of brain graphs was significantly related to healthy normal aging from 20s to 60s. In addition, the stationary distribution of information propagation gives a new insight into the information flow of functional brain graph. Copyright © 2018, The Authors. All rights reserved.

关键词： Entropy

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