Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. As neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired, this book gives an accessible foundation to the field of computational neuroimaging, suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. It is widely recognized that effective interpretation and extraction of information from complex data requires quantitative modeling. However, modeling the brain comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. This book takes a critical step towards synthesizing and integrating across different modeling approaches. Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging dataWritten by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimagingGives insights into the similarities and differences across different modeling approachesAnalyses details of outstanding research challenges in the field INDICE: Statistical modeling: Harnessing uncertainty and variation in neuroimaging dataSensory modeling: Understanding computation in sensory systems through image-computable modelsCognitive modeling: Joint models use cognitive theory to understand brain activationsNetwork modeling: The explanatory power of activity flow models of brain functionBiophysical modeling: An approach for understanding the physiological fingerprint of the BOLD fMRI signalBiophysical modeling: Multicompartment biophysical models for brain tissue microstructure imagingDynamic brain network models: How interactions in the structural connectome shape brain dynamicsNeural graph modellingMachine learning and neuroimaging: Understanding the human brain in health and diseaseDecoding models: From brain representation to machine interfacesNormative modeling for clinical neuroscience
- ISBN: 978-0-443-13480-7
- Editorial: Academic Press
- Encuadernacion: Rústica
- Páginas: 354
- Fecha Publicación: 18/06/2024
- Nº Volúmenes: 1
- Idioma: Inglés