Data Science for Neuroimaging

An Introduction

Ariel Rokem, Tal Yarkoni

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Hardback

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English

Princeton University Press
20 March 2024

Data analysis: general; Physiological & neuro-psychology, biopsychology; Biomedical engineering; Biology, life sciences; Neurosciences

Data science methods and tools - including programming, data management, visualisation and machine learning - and their application to neuroimaging research.

As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage and analyse datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, 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 explains such elements of data science as programming, data management, visualisation and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions.

By: Ariel Rokem, Tal Yarkoni
Imprint: Princeton University Press
Country of Publication: United States
Dimensions: Height: 254mm, Width: 178mm,
ISBN: 9780691222738
ISBN 10: 0691222738
Pages: 392
Publication Date: 20 March 2024
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Ariel Rokem is research associate professor at the University of Washington Department of Psychology and Data Science Fellow at the University of Washington eScience Institute. He is a contributor to Python open-source tools for scientific computing and directs the NIH-funded Summer Institute for Neuroimaging and Data Science. Tal Yarkoni is a data scientist and research professor in the Department of Psychology at the University of Texas at Austin. His academic work focuses on developing new tools and methods for the analysis of psychology and neuroimaging data.

Reviews for Data Science for Neuroimaging: An Introduction

"""I would absolutely recommend this book, not just for those wanting to do neuroimagining analyses, but for anyone who wants to do any serious scientific computing using Python. The well-selected exercises ensure that both undergraduate and graduate students will find engaging and thorough learning experiences throughout this book.""---Jonathan Shock, Mathemafrica"