Statistical Challenges in Modeling Big Brain Signals
Zhaoxia Yu, Dustin Pluta, Tong Shen, Chuansheng Chen, Gui Xue,, Hernando Ombao
TL;DR
This paper reviews the statistical challenges posed by large, complex brain signal data, discussing potential solutions and future research directions to improve inference and learning in neuroscience.
Contribution
It provides a comprehensive overview of the key statistical challenges and potential solutions for modeling big brain signals, highlighting future research avenues.
Findings
Identifies major statistical challenges in big brain data
Discusses potential solutions for complex, high-dimensional data
Highlights future research directions in the field
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.
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Taxonomy
TopicsFunctional Brain Connectivity Studies · Neural dynamics and brain function · Advanced MRI Techniques and Applications