J
John W. Krakauer
Researcher at Johns Hopkins University
Publications - 190
Citations - 25005
John W. Krakauer is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Motor learning & Stroke. The author has an hindex of 66, co-authored 169 publications receiving 21008 citations. Previous affiliations of John W. Krakauer include Columbia University Medical Center & Johns Hopkins University School of Medicine.
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Holding the arm still through subcortical mathematical integration of cortical commands
TL;DR: It is found that the brain uses a design principle in which its holding controller is not driven by the spatial location of the target, Rather, holding is obtained via mathematical integration of moving, potentially through a subcortical structure.
Journal ArticleDOI
A theory for curing the diseases of modernity
TL;DR: The showdown between a virus and the ailments of a hyperconnected but politically fragmented modern world is attracting increasing commentary, with a recent article referring to it as a ‘complexity crisis’.
Posted ContentDOI
Finger recruitment patterns during mirror movements suggest two systems for hand recovery after stroke
Naveed Ejaz,Jing Xu,Meret Branscheidt,Meret Branscheidt,Benjamin Hertler,Heidi M. Schambra,Mario Widmer,Andreia V. Faria,Michelle D. Harran,Juan C. Cortes,Nathan Kim,Tomoko Kitago,Pablo Celnik,Andreas R. Luft,John W. Krakauer,Jörn Diedrichsen +15 more
TL;DR: It is concluded that the pattern of mirror movements across homologous and non-homologous fingers reflect the summed contributions of both cortical and subcortical systems, and the implications of the results towards hand recovery after stroke.
Journal ArticleDOI
Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data
Divya Ramamoorthy,Kristen A. Severson,Soumya Ghosh,Karen Sachs,Emily G. Baxi,Alyssa N. Coyne,Elizabeth Mosmiller,Lindsey R. Hayes,Aianna Cerezo,Omar B. Ahmad,Promit Roy,Steven R. Zeiler,John W. Krakauer,Jonathan Li,Aneesh Donde,Nhan Huynh,Miriam Adam,Brook T. Wassie,Alexander LeNail,Natasha L. Patel-Murray,Y. Sivaji Raghav,Velina Kozareva,Stanislav Tsitkov,Tobias Ehrenberger,Julia A. Kaye,Leandro Lima,Stacia K. Wyman,Edward Vertudes,Naufa F. Amirani,K. Raja,Reuben J. Thomas,Ryan G. Lim,Ricardo Miramontes,Jie Wu,Vineet Vaibhav,Andrea Matlock,Vidya Venkatraman,Ronald Holewenski,Niveda Sundararaman,Rakhi Pandey,Danica-Mae Manalo,Aaron Frank,Loren Ornelas,Lindsey Panther,Emilda Gomez,Erick Galvez,Daniel Perez,Imara Meepe,Susan Lei,L. Esparcia Pinedo.,Chunyan Liu,Ruby Moran,Dhruv Sareen,Barry Landin,Carla Agurto,Guillermo A. Cecchi,Raquel Norel,Sara K. Thrower,Sarah Luppino,Alanna Farrar,Lindsay Pothier,Hong-yan Yu,Ervin Sinani,Prasha Vigneswaran,Alexander Sherman,S. M. Farr,Berhan Mandefro,Hannah Trost,Maria G. Banuelos,V. Garcia,Michael J. Workman,R. Ho,Robert W. Baloh,Jennifer Roggenbuck,Matthew B. Harms,Carolyn Prina,Sarah Heintzman,Stephen J. Kolb,Jennifer Stocksdale,Keona Q. Wang,Todd Morgan,Daragh Heitzman,Arish Jamil,Jennifer Jockel-Balsarotti,Elizabeth Muhito Karanja,Jesse Markway,M. McCallum,Tim Miller,Ben Mifsud Joslin,Deniz Alibazoglu,Senda Ajroud-Driss,Jay Beavers,Mary Bellard,E. Bruce,Nicholas J. Maragakis,Merit Cudkowicz,James D. Berry,Terri Thompson,Steven Finkbeiner,Leslie M. Thompson,Jennifer E. Van Eyk,Clive N. Svendsen,Jeffrey D. Rothstein,Jonathan D. Glass,Christina Fournier,Christian Lunetta,David Walk,Ghazala Hayat,James Wymer,Kelly G. Gwathmey,Nicholas T. Olney,Terry Heiman-Patterson,Ximena Arcila-Londono,Kenneth Faulconer,Ervin Sanani,Alex J. Berger,Julia C Mirochnick,Todd M. Herrington,Kenney Ng,Ernest Fraenkel +119 more
TL;DR: In this article , the authors developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster.
Journal ArticleDOI
On tests of activation map dimensionality for fMRI-based studies of learning.
TL;DR: The development of the framework, a large scale simulation study, and the subsequent application to a study of motor learning in healthy adults found that the study of linear dimensionality is able to capture learning effects.