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Accelerometer-based head impact detection in soccer - Where are we?

Health sciences Review 2024年 10卷 100141-100141页

作者： Deju, Bamlak Afzal, Hamayl Basnyat, Suhana Dali, Animesh Scott, Katelin E.J. Delancey, Rachel Chopra, Nipun Department of Computer Science DePauw University Greencastle IN 46135 United States Cell and Molecular Biology Program Duke University Durham NC 22708 United States Department of Biology DePauw University Greencastle IN 46135 United States Department of Psychiatry University of Iowa Iowa City IA 52242 United States Department of Psychology and Neuroscience DePauw University Greencastle IN 46135 United States Biomedical Sciences Graduate Program University of Virginia School of Medicine Charlottesville VA 22903 United States

AbstractTraumatic brain injury (TBI) represents a significant burden on individuals, societies, and healthcare systems as it is associated with long-term neurological and behavioral consequences. Although these effects vary according to severity, events that lead to TBI and mild TBI (mTBI), such as concussions, subconcussive impacts, and non-impact violent head movements, may also lead to similar changes. Soccer players are particularly prone to mTBI as they are exposed to head impacts in various ways during training and gameplay. A commonly-claimed TBI risk is that posed by the " heading" technique. Our examination of the literature questions the extent to which heading actually is a risk for TBI and mTBI vs other sources of head impact in soccer. Although headgear may protect against some impacts, it has not been widely adopted due to limited efficacy, practical limitations and potential changes to the heading technique. Nevertheless, accurate assessment of head impacts and other movements that may lead to TBI in soccer would be valuable to players, coaches, athletic and medical personnel. A potential method for accurately detecting head acceleration – a crucial element of most head injuries – is measurements through accelerometers. Here, we survey the different types of accelerometers and recent findings on their accuracy and feasibility among soccer players and offer suggestions for long-term research with these tools.

关键词： Soccer Brain injury Concussion Subconcussive injury Detection

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Beneficial perturbation network for designing general adaptive artificial intelligence systems

arXiv

引用

arXiv 2020年

作者： Wen, Shixian Rios, Amanda Ge, Yunhao Itti, Laurent Department of Computer Science University of Southern California Los AngelesCA90089 United States Neuroscience Graduate Program University of Southern California United States Department of psychology University of Southern California United States

The human brain is the gold standard of adaptive learning. It not only can learn and benefit from experience, but also can adapt to new situations. In contrast, deep neural networks only learn one sophisticated but fixed mapping from inputs to outputs. This limits their applicability to more dynamic situations, where the input to output mapping may change with different contexts. A salient example is continual learning - learning new independent tasks sequentially without forgetting previous tasks. Continual learning of multiple tasks in artificial neural networks using gradient descent leads to catastrophic forgetting, whereby a previously learned mapping of an old task is erased when learning new mappings for new tasks. Here, we propose a new biologically plausible type of deep neural network with extra, out-of-network, task-dependent biasing units to accommodate these dynamic situations. This allows, for the first time, a single network to learn potentially unlimited parallel input to output mappings, and to switch on the fly between them at runtime. Biasing units are programmed by leveraging beneficial perturbations (opposite to well-known adversarial perturbations) for each task. Beneficial perturbations for a given task bias the network toward that task, essentially switching the network into a different mode to process that task. This largely eliminates catastrophic interference between tasks. Our approach is memory-efficient and parameter-efficient, can accommodate many tasks, and achieves state-of-the-art performance across different tasks and domains. Copyright © 2020, The Authors. All rights reserved.

关键词： Mapping

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Rapid TAURUS for relaxation-based color magnetic particle imaging

arXiv

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arXiv 2021年

作者： Arslan, Tunç Alper Özaslan, A. Kurt, Semih Muslu, Yavuz Saritas, Emine Ulku Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Bilkent University Ankara06800 Turkey Neuroscience Program Sabuncu Brain Research Center Bilkent University Ankara06800 Turkey Department of Biomedical Engineering University of Wisconsin-Madison MadisonWI United States Department of Radiology University of Wisconsin-Madison MadisonWI United States Department of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Science for Life Laboratory Stockholm Sweden

Magnetic particle imaging (MPI) is a rapidly developing medical imaging modality that exploits the non-linear response of magnetic nanoparticles (MNPs). Color MPI widens the functionality of MPI, empowering it with the capability to distinguish different MNPs and/or MNP environments. The system function approach for color MPI relies on extensive calibrations that capture the differences in the harmonic responses of the MNPs. An alternative calibration-free x-space-based method called TAURUS estimates a map of the relaxation time constant, τ, by recovering the underlying mirror symmetry in the MPI signal. However, TAURUS requires a back and forth scanning of a given region, restricting its usage to slow trajectories with constant or piecewise constant focus fields (FFs). In this work, we propose a novel technique to increase the performance of TAURUS and enable τ map estimation for rapid and multi-dimensional trajectories. The proposed technique is based on correcting the distortions on mirror symmetry induced by time-varying FFs. We demonstrate via simulations and experiments in our in-house MPI scanner that the proposed method successfully estimates high-fidelity τ maps for rapid trajectories that provide orders of magnitude reduction in scanning time, while preserving the calibration-free property of TAURUS. Copyright © 2021, The Authors. All rights reserved.

关键词： Trajectories

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Muscle Vectors as Temporally Dense "Labels"

Muscle Vectors as Temporally Dense "Labels"

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiang Wu Juyang Weng School of Automation Nanjing University of Science and Technology Nanjing China Department of Computer Science and Engineering Michigan State University East Lansing MI USA Cognitive Science Program Michigan State University East Lansing MI USA Neuroscience Program Michigan State University East Lansing MI USA

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Consider a human who interacts with the physical world to autonomously learn in a task non-specific way through lifetime. It seems obvious that the fully autonomous learner does not have the luxury to have the mother to provide temporally dense state labels, but the context/state at every frame is beneficial (e.g., to generate attention for the next frame). How can we enable the learner to generate frame-wise contexts/states on the fly? Our past work on Developmental Network (DN-1) has shown that frame-wise state labels (e.g., stages within a phoneme) are useful to generate temporally sparse label (the type of the phoneme). However, such dense and sparse labels were handcrafted from a static data set, using human identified frame-wise equivalence. In this paper, we study a conceptually challenging problem - how to enable an autonomous learner to generate frame-wise states autonomously without human handcrafting dense labels at all. We propose that frame-wise muscle actions (e.g., producing a sound) are not only temporally dense and high-dimensional, but also natural as dense labels. However, it is unknown how a neural network can use such high-dimensional vectors as dense labels. In this work, we provide a model for this new issue and experiment with Developmental Network-2 (DN-2) for imitation of audio sequences. Our experimental results showed DN-2 can successfully emerge high-dimensional real-valued vector actions. These actions provide DN-2 with frame-wise temporal context information. This work corresponds to a key step toward our goal to enable the agent to fully autonomously generate frame-wise actions without human-provided dense labels and with only a few human-provided sparse labels.

关键词： Task analysis Turing machines Hidden Markov models Neurons Robot sensing systems Bayes methods Natural languages

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Corrigendum to "Novel model of multiple sclerosis induced by EBV-like virus generate a unique B cell population" [Journal of Neuroimmunology volume 394 (2024) 578408]

引用

Journal of neuroimmunology 2025年 404卷 578625页

作者： J L Deffenbaugh K-J Jung S P Murphy Y Liu C N Rau C Petersen-Cherubini P L Collins D Chung A E Lovett-Racke Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA. Department of Computer Science and Engineering The Ohio State University USA. Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA Neuroscience Graduate Program The Ohio State University USA. Department of Biomedical Informatics The Ohio State University Wexner Medical Center USA Pelotonia Institute for Immuno-Oncology The Ohio State University Wexner Medical Center USA. Department of Neuroscience The Ohio State University Wexner Medical Center USA. Electronic address: amylovettracke@***.

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Autonomous programming for General Purposes: Theory and Experiments

Autonomous Programming for General Purposes: Theory and Expe...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Juyang Weng Zejia Zheng Xiang Wu Juan Castro-Garcia Department of Computer Science and Engineering Michigan State University East Lansing MI USA Cognitive Science Program Michigan State University East Lansing MI USA Neuroscience Program Michigan State University East Lansing MI USA School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Since the birth of AI, symbols have been well accepted as an abstract representation for intelligent systems, even when neural networks are employed. This theoretical work shows the following new methods: (1) Symbols are probably not used by biological brains because their behaviors are not limited by symbols. (2) Autonomous programming For General Purposes (APFGP) is necessary for scaling-up AI to animal level intelligence. "Autonomous " means inside the skull (or network). (3) A Developmental Network (DN) performs APFGP by learning a super Turing machine, called Grounded, Emergent, Natural, Incremental, Skull-closed, Attentive, Motivated, and Abstractive (GENISAMA) Turing machine. (4) A DN is free of any central controller (e.g., Master Map, convolution, or error back-propagation). (5) The GENISAMA DN does APFGP without using symbols. Experiments are reported for vision guided navigation, auditory recognition, and natural language learning. This is the first conference paper on APFGP.

关键词： Task analysis Turing machines Brain modeling Artificial intelligence programming Biological neural networks

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Task-Nonspecific and Modality-Nonspecific AI 1st

Task-Nonspecific and Modality-Nonspecific AI

引用

1st International Workshop on Human Brain and Artificial Intelligence, HBAI 2019, held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019

作者： Weng, Juyang Castro-Garcia, Juan Zheng, Zejia Wu, Xiang Department of Computer Science Michigan State University East LansingMI48824 United States Cognitive Science Program Michigan State University East LansingMI48824 United States Neuroscience Program Michigan State University East LansingMI48824 United States

ISBN: (纸本)9789811513978

It is widely accepted in Artificial Intelligence (AI) that different tasks require different learning methods. The same is true for different sensory modalities. However, auto-programming for general purposes seems to require a learning engine that is task-independent and modality-independent. We provided the Developmental Network (DN) as such an engine to all contestants of the AI Machine Learning Contest 2016 for learning three well-recognized bottleneck problems in AI—vision, audition, and natural languages. For vision, the network learned abstract visual concepts and their hierarchy with invariant properties and autonomous attention. For audition, sparse and dense actions jointly serve as auditory contexts. For natural languages, the network acquires two natural languages, English and French, conjunctively in a bilingual environment (i.e., patterns of text as inputs). All the three sensory modalities used the same DN learning engine, but each had a different body (sensors and effectors). The contestants independently verified the DN’s base performance, and competed to add (hinted) autonomous attention for better performance. This seems to be the first task-independent and modality-independent learning engine, which was also verified by independent contestants. Much remains to be done in the learner-age related sophistication of learned tasks. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Audition

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Longitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study

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Journal of Adolescent Health 2025年

作者： Fields, Christopher T. Black, Carmen Calhoun, Amanda J. Rosenblatt, Matthew Rodriguez, Raimundo Aina, Joseph Thind, Jannat K. Grayson, Jalen Khalifa, Fahmi Assari, Shervin Zhou, Xin Nagata, Jason Gee, Dylan G. Program for Recovery and Community Health Department of Psychiatry Yale School of Medicine New Haven Connecticut United States Department of Radiology Magnetic Resonance Research Center Yale School of Medicine New Haven Connecticut United States Institute of Living at Hartford Healthcare Hartford Connecticut United States Department of Psychiatry Yale School of Medicine New Haven Connecticut United States Department of Psychiatry University of Connecticut Health Center Farmington Connecticut United States Department of Electrical and Computer Engineering Morgan State University Detroit MI United States Semel Institute for Neuroscience and Human Behavior University of California-Los Angeles Los Angeles California United States Department of Family Medicine Charles R Drew University of Medicine and Science Los Angeles California United States Department of Biostatistics Yale School of Medicine New Haven Connecticut United States Division of Adolescent and Young Adult Medicine Department of Pediatrics University of California San Francisco San Francisco California United States Department of Psychology Yale University New Haven Connecticut United States

Purpose: To assess longitudinal and geographic variation in perceived discrimination from ages 10–11 to 13–14 years in the Adolescent Brain Cognitive Development cohort, and to examine how these experiences are shaped by contextual factors such as neighborhood segregation and state-level racial bias. Methods: Data were drawn from the longitudinal Adolescent Brain Cognitive Development Study (release 5.1), analyzing years 1, 2, and 4, corresponding to approximate ages 10–11, 11–12, and 13–14 years. Perceived discrimination was assessed using items adapted from the Perceived Discrimination Scale. Mixed-effects logistic regression models examined how perceived discrimination varied across time, demographic factors, and contextual variables, with models weighted using American Community Survey raked propensity scores to ensure national representativeness. Results: Black, Asian American and Pacific Islander, and Other/Multiracial non-Hispanic youth showed increasing trajectories of perceived discrimination over time, while Native American and White non-Hispanic youth exhibited decreasing trends. Significant geographic variation emerged, with Black youth reporting elevated discrimination across all regions, particularly in the West and South. Youth living in areas with concentrated poor Black households and in states with high anti-Black bias reported higher discrimination. Youth with immigrant backgrounds generally reported higher levels of perceived discrimination across most racial/ethnic groups. Discussion: Perceived discrimination follows distinct developmental trajectories during early adolescence that vary significantly by race, ethnicity, geography, and structural context. These findings highlight the critical need for targeted interventions during this developmental period, particularly for Black, Asian American and Pacific Islander, and Other/Multiracial youth. Context-specific approaches to addressing racism are essential for mitigating its harmful effects on a

关键词： Adolescent health Health disparities Intergroup relations Interpersonal racism Public health Racial discrimination Racism Racism-related stress Social determinants of health

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Deciphering seasonal depression variations and interplays between weather changes, physical activity, and depression severity in real-world settings: Learnings from RADAR-MDD longitudinal mobile health study

arXiv

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arXiv 2024年

作者： Zhang, Yuezhou Folarin, Amos A. Ranjan, Yatharth Cummins, Nicholas Rashid, Zulqarnain Conde, Pauline Stewart, Callum Sun, Shaoxiong Vairavan, Srinivasan Matcham, Faith Oetzmann, Carolin Siddi, Sara Lamers, Femke Simblett, Sara Wykes, Til Mohr, David C. Haro, Josep Maria Penninx, Brenda W.J.H. Narayan, Vaibhav A. Hotopf, Matthew Dobson, Richard J.B. Pratap, Abhishek Department of Biostatistics & Health Informatics Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Institute of Health Informatics University College London London United Kingdom NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust London United Kingdom Health Data Research UK London University College London London United Kingdom NIHR Biomedical Research Centre University College London Hospitals NHS Foundation Trust London United Kingdom Department of Computer Science University of Sheffield Sheffield United Kingdom Janssen Research and Development LLC TitusvilleNJ United States Department of Psychological Medicine Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom School of Psychology University of Sussex Falmer United Kingdom Teaching Research and Innovation Unit Parc Sanitari Sant Joan de Déu Fundació Sant Joan de Déu Barcelona Spain Centro de Investigación Biomédica en Red de Salud Mental Madrid Spain Department of Psychiatry Amsterdam UMC Vrije Universiteit Amsterdam Netherlands Mental Health Program Amsterdam Public Health Research Institute Amsterdam Netherlands Department of Psychology Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom South London and Maudsley NHS Foundation Trust London United Kingdom Center for Behavioral Intervention Technologies Department of Preventive Medicine Northwestern University ChicagoIL United States Boehringer Ingelheim Pharmaceuticals Inc. RidgefieldCT United States University of Washington Seattle United States

Prior research has shown that changes in seasons and weather can have a significant impact on depression severity. However, findings are inconsistent across populations, and the interplay between weather, behavior, and depression has not been fully quantified. This study analyzed real-world data from 428 participants (a subset;68.7% of the cohort) in the RADAR-MDD longitudinal mobile health study to investigate seasonal variations in depression (measured through a remote validated assessment - PHQ-8) and examine the potential interplay between dynamic weather changes, physical activity (monitored via wearables), and depression severity. The clustering of PHQ-8 scores identified four distinct seasonal variations in depression severity: one stable trend and three varying patterns where depression peaks in different seasons. Among these patterns, participants within the stable trend had the oldest average age (p=0.002) and the lowest baseline PHQ-8 score (p=0.003). Mediation analysis assessing the indirect effect of weather on physical activity and depression showed significant differences among participants with different affective responses to weather. Specifically, the temperature and day length significantly influenced depression severity, which in turn impacted physical activity levels (p Copyright © 2024, The Authors. All rights reserved.

关键词： Radar measurement

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In vivo imaging with a flat, lensless microscope

Research Square

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Research Square 2021年

作者： Adams, Jesse K. Yan, Dong Wu, Jimin Boominathan, Vivek Gao, Sibo Rodriguez, Alex V. Carns, Jennifer Richards-Kortum, Rebecca Kemere, Caleb Veeraraghavan, Ashok Robinson, Jacob T. Applied Physics Program Rice University 6100 Main Street HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University 6100 Main Street HoustonTX77005 United States Department of Neuroscience Baylor College of Medicine One Baylor Plaza HoustonTX77030 United States Department of Bioengineering Rice University 6100 Main Street HoustonTX77005 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States

Lenless microscopes that form images using simple, compact optics, along with associated computational algorithms provide several advantages: small, inexpensive form factors, large fields of view (FOV), and the ability to refocus an image after capture. To date, however, lensless microscopy has yet to be demonstrated for in vivo biological imaging. The primary challenge with in vivo bio-imaging is these dense, low-contrast scenes cannot be accurately reconstructed with existing lensless techniques. To overcome this challenge, we designed an optical phase mask that creates a point-spread function consisting of high-contrast contours with a broad spatial frequency spectrum. Here we show that this "contour" phase mask enables in vivo imaging where previous lensless imaging technologies have failed. As a proof of concept, we demonstrate 3D imaging of a behaving invertebrate, functional calcium imaging in mouse cortex, and in vivo imaging of microvasculature in the human oral mucosa. Together these results demonstrate the ability of lensless imaging to operate in realistic biological imaging applications ranging from pre-clinical animal models to clinical biomedical imaging. Overall, this "Bio-FlatScope" is a clinically relevant imaging technique with advantages of 3D computational refocusing in a low-cost, small form factor that is useful for low-resource settings and difficult-to-reach areas of the body. © 2021, CC BY.

关键词： Microscopes

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