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- December 23, 2018.
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- Version 1 (March 2, 2018 - 09:21).
- Version 2 (June 7, 2018 - 13:20).
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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Author Information
- Emily L. Mackevicius1,†,*,
- Andrew H. Bahle1,†,
- Alex H. Williams2,
- Shijie Gu1,3,
- Natalia I. Denissenko1,
- Mark S. Goldman4,* and
- Michale S. Fee1,*
- 1McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
- 2Neurosciences Program, Stanford University, Stanford, CA, 94305
- 3School of Life Sciences and Technology, ShanghaiTech University
- 4Center for Neuroscience, Department of Neurobiology, Physiology and Behavior, Department of Ophthamology and Vision Science, UC Davis
- ↵*For correspondence
: elm{at}mit.edu (ELM); fee{at}mit.edu (MSF); msgoldman{at}ucdavis.edu (MSG)
↵† These authors contributed equally to this work
Posted December 23, 2018.
Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience
