Description
Data Science for Neuroimaging provides an accessible yet rigorous introduction to the intersection of data science and neuroimaging research. Written by leading experts Ariel Rokem and Tal Yarkoni, this book equips researchers, neuroscientists, and students with practical knowledge for analyzing brain imaging data using modern computational methods.
The text covers essential topics including data preprocessing, statistical analysis, machine learning applications, and visualization techniques specific to neuroimaging datasets. It emphasizes hands-on learning through real-world examples and datasets, making complex concepts understandable for both beginners and experienced researchers transitioning into data science.
Ideal for graduate students, postdoctoral researchers, and established scientists, this Princeton University Press publication serves as both a foundational textbook and a reference guide for contemporary neuroimaging analysis workflows.
Reviews
There are no reviews yet.