Statistical Challenges in Modeling Big Brain Signals

Handle URI:
http://hdl.handle.net/10754/626551
Title:
Statistical Challenges in Modeling Big Brain Signals
Authors:
Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando
Abstract:
Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.
KAUST Department:
Biostatistics Group, King Abdullah University of Science and Technology, Saudi
Publisher:
arXiv
Issue Date:
1-Nov-2017
ARXIV:
arXiv:1711.00432
Type:
Preprint
Additional Links:
http://arxiv.org/abs/1711.00432v1; http://arxiv.org/pdf/1711.00432v1
Appears in Collections:
Other/General Submission

Full metadata record

DC FieldValue Language
dc.contributor.authorYu, Zhaoxiaen
dc.contributor.authorPluta, Dustinen
dc.contributor.authorShen, Tongen
dc.contributor.authorChen, Chuanshengen
dc.contributor.authorXue, Guien
dc.contributor.authorOmbao, Hernandoen
dc.date.accessioned2017-12-28T07:32:16Z-
dc.date.available2017-12-28T07:32:16Z-
dc.date.issued2017-11-01en
dc.identifier.urihttp://hdl.handle.net/10754/626551-
dc.description.abstractBrain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.en
dc.publisherarXiven
dc.relation.urlhttp://arxiv.org/abs/1711.00432v1en
dc.relation.urlhttp://arxiv.org/pdf/1711.00432v1en
dc.rightsArchived with thanks to arXiven
dc.titleStatistical Challenges in Modeling Big Brain Signalsen
dc.typePreprinten
dc.contributor.departmentBiostatistics Group, King Abdullah University of Science and Technology, Saudien
dc.eprint.versionPre-printen
dc.contributor.institutionDepartment of Statistics, University of California, Irvine, USAen
dc.contributor.institutionDepartment of Psychology and Social Behavior, University of California, Irvine, USAen
dc.contributor.institutionState Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, PR Chinaen
dc.identifier.arxividarXiv:1711.00432en
kaust.authorOmbao, Hernandoen
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