期刊
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 1
卷 1, 期 -, 页码 61-85出版社
ANNUAL REVIEWS
DOI: 10.1146/annurev-statistics-022513-115611
关键词
neuroimaging; fMRI; DTI; connectivity; prediction; activation
资金
- NINDS NIH HHS [U18 NS082143] Funding Source: Medline
The increasing availability of brain imaging technologies has led to intense neuroscientific inquiry into the human brain. Studies often investigate brain function related to emotion, cognition, language, memory, and responses to numerous other external stimuli, as well as resting-state brain function. Brain imaging studies also attempt to determine the functional or structural basis for psychiatric or neurological disorders and to examine the responses of these disorders to treatment. Neuroimaging is a highly interdisciplinary field, and statistics plays a critical role in establishing rigorous methods to extract information and to quantify evidence for formal inferences. Neuroimaging data present numerous challenges for statistical analysis, including the vast amounts of data collected from each individual and the complex temporal and spatial dependencies present in the data. I briefly provide background on various types of neuroimaging data and analysis objectives that are commonly targeted in the field. I also present a survey of existing methods aimed at these objectives and identify particular areas offering opportunities for future statistical contribution.
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