Data Science for Neuroimaging: An Introduction

This book provides neuroimaging researchers with an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. It covers programming, data management, visualization, and machine learning and their application to neuroimaging, with guided hands-on explorations of openly available neuroimaging datasets.

Format: Paperback / softback
Length: 392 pages
Publication date: 12 December 2023
Publisher: Princeton University Press

As neuroimaging research increasingly relies on data-intensive approaches, researchers in the field must acquire the skills to handle, manage, and analyze datasets on an unprecedented scale. Moreover, the demand for reproducibility and rigorous reporting of scientific findings necessitates the adoption of higher standards of computational practice. This comprehensive book serves as a valuable introduction to data science for neuroimaging researchers, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and comprehension of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book elucidates key concepts such as programming, data management, visualization, and machine learning, while illustrating their application in the realm of neuroimaging. By the end of this book, readers will possess a broad range of data science skills that can be readily applied to their own research inquiries.

The field of neuroimaging is undergoing a transformative shift towards data-intensive discovery, necessitating researchers to acquire advanced skills in accessing, managing, and analyzing datasets at unprecedented scales. Furthermore, concerns about reproducibility and the rigorous reporting of scientific results have heightened the demand for higher standards of computational practice. This comprehensive book serves as a valuable resource for neuroimaging researchers, providing an introduction to data science and presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data.

Through guided, hands-on explorations of openly available neuroimaging datasets, the book elucidates key concepts such as programming, data management, visualization, and machine learning. It explains how these elements of data science can be applied to neuroimaging research, enabling researchers to extract valuable insights and make meaningful discoveries. The book is written entirely in the Jupyter notebook format, allowing readers to execute, modify, and re-execute the code examples as part of their learning process. This interactive approach enhances the understanding and retention of the material, making it an invaluable tool for advancing the field of neuroimaging.

In conclusion, this book offers neuroimaging researchers a comprehensive and practical guide to data science, equipping them with the skills and knowledge required to handle, manage, and analyze datasets on an unprecedented scale. By embracing data science methodologies, researchers can unlock the full potential of neuroimaging data and contribute to the advancement of our understanding of the brain and its functions.

Weight: 744g
Dimension: 178 x 254 x 23 (mm)
ISBN-13: 9780691222752