Mindboggle 2 interface: online visualization of extracted brain features with XTK

Journal of Inherited Metabolic DiseaseVolume 29, Issue 6 p. 764-764 ErratumFree Access X-linked creatine transporter defect: A report on two unrelated boys with a severe clinical phenotype This article corrects the following: X-linked creatine transporter defect: A report on two unrelated boys with a severe clinical phenotype I. M. Anselm, F. S. Alkuraya, G. S. Salomons, C. Jakobs, A. B. Fulton, M. Mazumdar, M. Rivkin, R. Frye, T. Young Poussaint, D. Marsden, Volume 29Issue 1Journal of Inherited Metabolic Disease pages: 214-219 First Published online: February 1, 2006 I. A. Anselm, I. A. Anselm Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorF. S. Alkuraya, F. S. Alkuraya Division of Genetics and Metabolism, Children's Hospital Boston, Harvard Medical School, 300 Longwood Ave., Boston, MA, 02115 USASearch for more papers by this authorG. S. Salomons, G. S. Salomons Department of Clinical Chemistry, Metabolic Unit, VU University Medical Center, Amsterdam, The NetherlandsSearch for more papers by this authorC. Jakobs, C. Jakobs Department of Clinical Chemistry, Metabolic Unit, VU University Medical Center, Amsterdam, The NetherlandsSearch for more papers by this authorA. B. Fulton, A. B. Fulton Department of Ophthalmology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorM. Mazumdar, M. Mazumdar Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorM. Rivkin, M. Rivkin Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorR. Frye, R. Frye Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorT. Young Poussaint, T. Young Poussaint Department of Radiology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorD. Marsden, Corresponding Author D. Marsden deborah.marsden@childrens.harvard.edu Division of Genetics and Metabolism, Children's Hospital Boston, Harvard Medical School, 300 Longwood Ave., Boston, MA, 02115 USA deborah.marsden@childrens.harvard.eduSearch for more papers by this author I. A. Anselm, I. A. Anselm Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorF. S. Alkuraya, F. S. Alkuraya Division of Genetics and Metabolism, Children's Hospital Boston, Harvard Medical School, 300 Longwood Ave., Boston, MA, 02115 USASearch for more papers by this authorG. S. Salomons, G. S. Salomons Department of Clinical Chemistry, Metabolic Unit, VU University Medical Center, Amsterdam, The NetherlandsSearch for more papers by this authorC. Jakobs, C. Jakobs Department of Clinical Chemistry, Metabolic Unit, VU University Medical Center, Amsterdam, The NetherlandsSearch for more papers by this authorA. B. Fulton, A. B. Fulton Department of Ophthalmology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorM. Mazumdar, M. Mazumdar Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorM. Rivkin, M. Rivkin Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorR. Frye, R. Frye Department of Neurology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorT. Young Poussaint, T. Young Poussaint Department of Radiology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USASearch for more papers by this authorD. Marsden, Corresponding Author D. Marsden deborah.marsden@childrens.harvard.edu Division of Genetics and Metabolism, Children's Hospital Boston, Harvard Medical School, 300 Longwood Ave., Boston, MA, 02115 USA deborah.marsden@childrens.harvard.eduSearch for more papers by this author First published: 12 October 2006 https://doi.org/10.1007/s10545-006-9997-4 The online version of the original article can be found at https://doi.org/10.1007/s10545-006-0123-4 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume29, Issue6December 2006Pages 764-764 RelatedInformation

"Connectivity Map" Comparisons of Disease and Drug Signatures May Accelerate Development of New Therapies

Event Abstract Back to Event Modeling firing-rate dynamics: From spiking to firing-rate networks Evan S. Schaffer1* and L. F. Abbott1 1 Columbia University, United States Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models have the obvious shortcoming of using a single time constant (typically a membrane or synaptic time constant) to describe all changes in rate, and they require neurons in a network to fire asynchronously. This is likely to be violated in many cases; in fact, transient synchronization of subgroups of neurons may be an important mechanism for generating rapid behavioral responses. To address this issue without losing the advantages associated with a simple firing-rate description, we have developed a form of firing-rate model based on an approximate Fokker-Planck analysis. A Fokker-Planck equation can be used to describe the distribution of membrane potentials for a population of neurons receiving noisy input. However, most methods for approximating solutions to this type of equation lead to considerably more complex equations than are practical for large networks. For example, there is no closed-form solution describing a population of Integrate-and-Fire (IAF) neurons receiving arbitrary time-varying input. A linear approximation to the response can be calculated, yielding impressively high accuracy, but it involves cumbersome equations (e.g. Brunel & Hakim, 1999; Mattia & Del Giudice, 2002; Ostojic et al., 2009). We show here that in a variant of this model, the Quadratic IAF, the fully nonlinear rate response can be approximated in a surprisingly simple form. Importantly, this approximate solution makes no assumptions about the shape, amplitude, or continuity of the input current. With an understanding of how dynamic external inputs drive firing rates for both asynchronous and synchronous populations of neurons, we study how units described in this way can be linked to describe the firing-rate dynamics of spiking networks with various patterns of synaptic connectivity. We find that the novel firing-rate model captures the time-varying firing-rates of the spiking network across a wide range of parameters. This holds equally well in parameter ranges where the asynchronous state is stable, and where highly synchronized firing occurs. Furthermore, the model also reproduces the dynamics of transient synchronization, which can be quite complicated. Finally, we show that the rich firing dynamics of a network of both excitatory and inhibitory neurons can be well approximated by a coupled E-I rate network. The simplicity of the model we have derived makes it highly amenable to use as the basis for network models. This will hopefully make tractable the study of the dynamics of large networks. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session II Citation: Schaffer ES and Abbott LF (2010). Modeling firing-rate dynamics: From spiking to firing-rate networks. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00269 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 05 Mar 2010; Published Online: 05 Mar 2010. * Correspondence: Evan S Schaffer, Columbia University, New York, United States, ess2129@columbia.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Evan S Schaffer L. F Abbott Google Evan S Schaffer L. F Abbott Google Scholar Evan S Schaffer L. F Abbott PubMed Evan S Schaffer L. F Abbott Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Back to table of contents Previous article Next article Members in the NewsFull AccessPsychiatrist's Deafness Opened Doors to Wider WorldAaron LevinAaron LevinPublished Online:7 Aug 2009https://doi.org/10.1176/pn.44.15.0022Sanjay Gulati, M.D., practices psychiatry in a silent world, a world he resisted, then grew accustomed to, then embraced. His deafness has given child psychiatrist Sanjay Gulati, M.D., a deeper insight into the worlds of his patients.Credit: Aaron LevinFor Gulati, now a child psychiatrist in Cambridge, Mass., the silence arrived on tiptoes: a move to the front row in high school; good grades in small, advanced classes in college and poor ones in large introductory ones; an unexamined preference for the quiet dinner for two rather than the boisterous party.Finally there was the failed audiogram, the diagnosis of hearing loss, the steady loss of five decibels a year."Otosclerosis is not supposed to strike this hard, or this young," he recalled in a recent interview. The disease is hereditary but, unlike his father's case, was not correctable by surgery. A hearing aid compensated enough to get through undergraduate school at the University of Virginia. In retrospect, he is amazed at how unaware he was of the vast number of adaptations to hearing loss he had made without ever recognizing them as such.He made a late decision to go to medical school."I think it says a lot about how much medicine my parents taught me that I scored the same in the MCAT on physics, my college major, and biology, which I didn't study at all!" he said.Gulati's father was a surgeon (who later retrained as a neuroradiologist) and his mother an anesthesiologist. Their families left Pakistan for India after the two countries were partitioned in 1947, and the couple eventually settled in Nottingham, England, where Sanjay was born. They sailed to the United States in the 1960s, when Gulati was 9."At that point, I was already starting to lose hearing, but I was not yet aware of it," he recalled. "My piano teacher complained that I wasn't playing pianissimo, even when I was sure that I was."His deafness, although progressive, was incremental. He adapted to hearing loss, but still felt cut off from much of the life going on around him. Before passage of the Americans With Disabilities Act, medical schools rarely accommodated the needs of the deaf or others with disabilities, he noted."I remember offering to pay for a better microphone during an observation class and being told no," he said. "As I went through med school and residency, it felt like I just barely slipped through each door as it shut behind me."His increasing deafness might have isolated him from the world, but it had the opposite effect. He became more attuned to body language and other visual cues to behavior. Watching sports prompted his own inner game, trying to intuit what move the pitcher or quarterback would make on the next play. Gulati applied the same skill later during shifts in the emergency room to judge if patients were dangerous.In medical school, he let go of an early interest in surgery—in the OR, everyone talks and everyone wears masks, precluding lip reading. Other logical choices for a doctor losing his hearing, such as pathology and radiology, seemed socially isolating. That led Gulati to his specialty."Psychiatry offered a chance to explore the subjective world, a nice mirror image to my college interest in deeply understanding the objective one," he said.Gulati graduated from Eastern Virginia Medical School in Norfolk in 1988, completed his internship there a year later, did his residency in psychiatry at Albany Medical College, and then held a child psychiatry fellowship at Cambridge Hospital. Today, he is an instructor in psychiatry at Harvard Medical School, works at the Cambridge Health Alliance and Children's Hospital Boston, and is a consultant to the American School for the Deaf in West Hartford, Conn. He has co-edited, with Neil Glickman, Ph.D., a textbook, Mental Health Care for Deaf People: A Culturally Affirmative Approach (Laurence Erlbaum Associates, 2003).Gulati did not seek out deaf patients in residency, but had his epiphany during his child psychiatry fellowship at Cambridge Hospital, recalled Terrell Clark, Ph.D., director of the Deaf and Hard of Hearing Program in the Department of Otolaryngology at Children's Hospital Boston, under whom he trained."He accompanied a child to the hospital and saw for the first time the specialty clinic here," said Clark in an interview. "He was still coping with his own hearing loss but had not yet identified with being deaf. I know of other deaf physicians and other psychiatrists with signing skills but not of another deaf psychiatrist. He's been an inspiration for others."He was not fluent in sign language when he began, but he soon became comfortable, she said. Learning to practice medicine in another language was difficult."For patients, baring your soul through a third party creates an artificial barrier," she said. "You're not sure if what you said and how you said it came across. So having a therapist with whom you can communicate is important."Gulati's personal and professional experience gives him an edge when helping patients and families understand complex information they may not want to hear, said Lauren Esposito, Ph.D., director of the Deaf and Hard of Hearing Service in the Department of Psychiatry at Cambridge Hospital, and one of Gulati's former trainees."He is good at working in a system that is not used to working with the deaf," said Esposito in an interview. "The treatment process can be anxiety-provoking for both patient and staff, especially if the staff doesn't know about deafness."When appropriate, he will share his own experience with his patients and their parents, which can inspire and validate patients, she said.Issues shared by all psychiatrists take on an added dimension for a psychiatrist who is deaf. Take the matter of transference."I have to deal with transference related to my lucky status as a late-deafened person who was able to squeak through medical school at a time when other deaf people could not," he said." Countertransferentially, I often have to deal with feelings of guilt around the same issue. I know a young man, for example, who cleans hotel rooms. It's clear to me that had he had appropriate language exposure and educational opportunity, he could have gone to college and graduate school as I did. I think one has to try to turn this anger into appropriately aimed activism. As a practicing psychiatrist, I keep my activism fairly quiet, but my current project is to seek wider recognition of the syndrome of language deprivation."Gulati has spoken out about the central role of language itself in the development of young people who are deaf. He believes that early training for those children in American Sign Language prepares neural pathways in the brain for general language development and for later acquisition of English.However, sign language doesn't always lend itself well to diagnostic language. There are currently four or five different signs in use now for autism, for example. So Gulati is working with others to agree on conventional technical terms in American Sign Language.Beyond the science, though, Gulati appreciates the fluidity and expressiveness of signing.He also appreciates the insights of deaf humor in sign language, often used to get through life's hardships, as it is for other minority groups.Deaf humor is hard to describe, he said, but often it involves acute awareness of the divide between the deaf and hearing worlds, sometimes with a touch of aggression toward the dominant (or oppressive) culture. Usually, there's some artistic or creative signing involved.He remembers one deaf woman, signing with her right hand, who momentarily forgets a word: "She slaps her right hand with her left, as if it were a malfunctioning television set."Eventually, the experience that shaped his own life would help shape that of his patients. What others might see as a handicap and a constriction, Gulati came to embrace as an opening door into a wider world."Had I not lost my hearing, I'd probably have become a competent, somewhat disconnected physicist," he concluded. "I have instead become a deeply involved and thoroughly fulfilled physician. It is difficult, in looking back over the journey so far, to see my hearing loss solely as loss or affliction. It has brought more into my life than it has taken away."▪ ISSUES NewArchived

Event Abstract Back to Event Hidden Markov models for the complex stimulus-response relationships of multi-state neurons Sean Escola1* and Liam Paninski1 1 Columbia University, United States Recent experimental results suggest that neurons are associated with multiple firing regimes, or states. We develop a general framework for estimating state-dependent neural receptive fields from paired spike-train and stimulus data assuming that neurons transition between several discrete hidden states. We modify both the discrete-time and continuous-time traditional hidden Markov model (HMM) frameworks to permit point-process observables such as spike-trains. For maximal flexibility in our model, we allow the external, time-varying stimulus and the neuron's own spike-history to drive both the spiking behavior in each state and the transitioning behavior between states. We employ an appropriately modified expectation-maximization algorithm to learn the model parameters. The expectation step is solved by the standard forward-backward algorithm for HMMs. The maximization step, though it is not analytically tractable, reduces to a simple concave optimization problem if the model is restricted slightly. We test our algorithm on two stimulated data sets and are able both to fully recover the parameters used to generate the data and to accurately recapitulate the sequence of hidden states. As a demonstration of the flexibility of our model, we apply our framework to a recently-published data set of purportedly multi-state neurons and show that we can implement a hybrid half multi-state/half histogram model which captures more of the neuronal variability than either a simple HMM or a simple histogram-based model alone Conference: Bernstein Symposium 2008, Munich, Germany, 8 Oct - 10 Oct, 2008. Presentation Type: Poster Presentation Topic: All Abstracts Citation: Escola S and Paninski L (2008). Hidden Markov models for the complex stimulus-response relationships of multi-state neurons. Front. Comput. Neurosci. Conference Abstract: Bernstein Symposium 2008. doi: 10.3389/conf.neuro.10.2008.01.043 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 13 Nov 2008; Published Online: 13 Nov 2008. * Correspondence: Sean Escola, Columbia University, New York, United States, gse3@columbia.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Sean Escola Liam Paninski Google Sean Escola Liam Paninski Google Scholar Sean Escola Liam Paninski PubMed Sean Escola Liam Paninski Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Thyroid surgery at Children's Hospital Boston: a 35-year single-institution experience

The RIVUR Voiding Cystourethrogram Pilot Study: Experience with Radiologic Reading Concordance

Harvard Work Hours, Health, and Safety Group; Division of Sleep Medicine; Department of Medicine; Brigham and Women's Hospital; Harvard Medical School; Boston, MA; Division of Sleep Medicine; Harvard Medical School; Boston, MA; Division of General Pediatrics; Department of Medicine; Children's Hospital Boston; Harvard Medical School; Boston, MA Dr. Landrigan is a paid employee of Brigham and Women's Hospital and Children's Hospital Boston, both of which employ interns, residents, physicians, and nurses. In the past 5 years, he has received support as a consultant from The District Health Boards of New Zealand; the RX Foundation; Vital Issues in Medicine, and AX Dev. He has also received monetary awards, honoraria, and travel reimbursement from multiple academic and professional organizations for delivering lectures on sleep deprivation, resident performance, and safety, and he has served as an expert witness in legal cases. For information regarding this article, E-mail: [email protected]

Over the past decade, there has been an explosion in the use of molecular tests to diagnose and manage infectious diseases. HIV is a prime example of an infectious agent whose diagnosis at least in the acute stage, susceptibility testing, and management are all dependent on molecular diagnostics. The ability to accurately diagnose a plethora of respiratory pathogens quickly, simply, and relatively inexpensively compared to traditional methods is becoming a reality. Direct sequencing and microarray analysis holds great promise for directly detecting a wide variety of organisms from clinical specimens. The question is where this testing should be done in the clinical laboratory. There are at least four models that have emerged: Molecular infectious disease testing as an arm of the clinical microbiology laboratory. Molecular infectious disease testing done in a central molecular pathology laboratory under the leadership of a clinical microbiologist. Molecular infectious disease testing done in a central molecular pathology laboratory under the leadership of an individual whose primary interest is in another area of molecular pathology. Molecular infectious disease testing sent to a reference laboratory and not done on site or within the institution's health care system. We have asked three individuals who have thought about this very complex issue to share their rationale for supporting one of these models. Frederick Nolte is the Director of Clinical Laboratories and Director of Molecular Pathology at the Medical University of South Carolina, is active in and held several positions of responsibility in AMP (Association of Molecular Pathology) and is Chair of the CLSI's Area Committee for Molecular Methods, Alex McAdam is the Director of the Infectious Diseases Diagnostic Division at Children's Hospital Boston and an editor of this journal, and his colleague, Nima Mosammaparast, is the Assistant Director of the Infectious Diseases Diagnostic Laboratory at Children's Hospital Boston.

The domain of teaching medicine involves the mastery of many complex skills that almost always need to be performed in real life situations following very high professional standards. However, this training is not always possible for various reasons such as ethics, safety and costs. Virtual reality (VR) and augmented reality (AR) have started to be widely used as alternative medical teaching practices. Our proposed AR system works online, so no installation is required on a users device; it only requires a generic colour web-cam to track a pictorial AR tag which contains a hidden QR code. These QR codes contain data, such as the ID of a three-dimensional (3D) model, and merge it with text so that it can be used as both an identity and tag pattern in the AR marker. The system can then show the corresponding computer-generated 3D anatomical models of organs; relevant text information about the subject is displayed above the AR Tag. The tag is numerically encrypted and decrypted and detectable by shape and orientation. Different from other similar techniques, our AR Tag is both a bar-code and a template marker, QR code is used to load a previously setup website, and then the detail of that QR code is used as a template to identify the border and orientation of the marker. The system is thus faster and more robust that allows users to control and navigate the 3D environment by zooming in and out and rotating left and right. It is hoped that this virtual environment will help reduce the need for real-life surgical practice, instead of increasing intuition, the direct 3D perception of the human body and other 3D medical imaging data (mimesis). This system could even be further developed to present the framework of a patient’s anatomy.

Feature extraction plays a pivotal role in pattern recognition and matching. An ideal feature should be invariant to image transformations such as translation, rotation, scaling, etc. In this work, we present a novel rotation-invariant feature, which is based on Histogram of Oriented Gradients (HOG). We compare performance of the proposed approach with the HOG feature on 2D phantom data, as well as 3D medical imaging data. We have used traditional histogram comparison measures such as Bhattacharyya distance and Normalized Correlation Coefficient (NCC) to assess efficacy of the proposed approach under effects of image rotation. In our experiments, the proposed feature performs 40%, 20%, and 28% better than the HOG feature on phantom (2D), Computed Tomography (CT-3D), and Ultrasound (US-3D) data for image matching, and landmark tracking tasks respectively.

Training and practice on synthetic anatomical bone before perform real medical operation is useful for medical student and recently become part of medical procedure. Since there are various factors to considered, the attempt to imitate anatomical bone from medical image data of patient, using technology that based on Fused Deposition Modelling (FDM) is alternatively developed. Since durability and qualities of 3D printed model depend on process parameters which referred to 3D printer setting, this study aims to investigate effect of essential 3D printer setting parameters involve with mechanical properties of 3D printed anatomical bone part, focused on infill density and layer height, and determine regression model for mechanical strength prediction from selected printing parameters by using experimental design and statistical analysis that based on Design of Experiments (DOE). 2-levelled full factorial experiment was designed, 3 factors including layer height, infill density, and print speed were taken into account. After that, selected 27 Mid-section of femur bone from 3D medical image data were fabricated from filament of Poly-lactic acid (PLA). The models were underwent a three-point bending testing to investigate mechanical properties and statistical analyse to investigate the relationship of parameters.

Firms are increasingly moving away from proprietary technology to building commercial products on top of open source software. However, it is unclear how such commercialization of open source affects contributions from the community, as well as product quality and firm performance. Web browser technology provides a unique setting to study such questions. The largest open source project is Chromium, led by Google, which serves as the core of various web browsers. Unexpectedly, Microsoft announced a drastic change in strategy in 2018 and adopted Chromium in a complete redesign of the web browser Edge. Unique data lets us compare Chromium to other open source technologies, and Chromium-based web browsers to other web browsers. We find that overall development activity increases after Microsoft adopts Chromium, predominantly because Microsoft starts to contribute to the project. We also see a modest increase in contributions from external developers. We further document an increase in scrutiny, evident from an increase in the number of individuals performing code reviews and a surge in security vulnerability reporting. We also find positive effects for Microsoft. Edge makes a giant leap in functionality, moving it on par with the market leader Chrome. With the adoption of Chromium, Microsoft fixes more bugs, accelerates release cycles, and increases the market share of Edge at the expense of other less popular Chromium browsers. We discuss a number of general implications for managers and policy. This paper was accepted by D. J. Wu, information systems. Funding: This work was supported by Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Grant 100013_197807]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02886 .

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Otolaryngology–Head & Neck Surgery HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Otolaryngology–Head & Neck Surgery journal

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