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Functional Magnetic Resonance Imaging~(fMRI) is a popular non-invasive modality to investigate activation in the human brain. The end result of most fMRI experiments is an activation map corresponding to the given paradigm. These maps can…

应用统计 · 统计学 2022-05-04 Ranjan Maitra

Functional magnetic resonance imaging (fMRI) aims to locate activated regions in human brains when specific tasks are performed. The conventional tool for analyzing fMRI data applies some variant of the linear model, which is restrictive in…

统计理论 · 数学 2008-08-08 Chunming Zhang , Tao Yu

Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can…

应用统计 · 统计学 2023-10-26 Wei-Chen Chen , Ranjan Maitra

Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different scales is one of the main challenges of contemporary neuroimaging, and it could allow…

应用统计 · 统计学 2016-06-16 Stefano Castruccio , Hernando Ombao , Marc G. Genton

Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application…

统计方法学 · 统计学 2023-06-07 Andrew S. Whiteman , Andreas J. Bartsch , Jian Kang , Timothy D. Johnson

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals.…

统计方法学 · 统计学 2023-10-31 Zhengxin Wang , Daniel B. Rowe , Xinyi Li , D. Andrew Brown

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is…

神经元与认知 · 定量生物学 2016-08-09 Nikolaus Kriegeskorte , Jörn Diedrichsen

Functional Magnetic Resonance Imaging (fMRI) is a powerful non-invasive tool for localizing and analyzing brain activity. This study focuses on one very important aspect of the functional properties of human brain, specifically the…

人工智能 · 计算机科学 2014-10-28 Harris V. Georgiou

Neuronal brain activity in response to repeated stimuli can be perceived using functional magnetic resonance imaging (fMRI). In this paper, we develop a statistical model for fMRI data that estimates both the associated haemodynamic…

应用统计 · 统计学 2015-01-26 Christopher J. Brignell , William J. Browne , Ian L. Dryden , Susan T. Francis

Brain metabolism is controlled by complex regulation mechanisms. As part of their nature many complex systems show scaling behavior in their timeseries data. Corresponding scaling exponents can sometimes be used to characterize these…

凝聚态物理 · 物理学 2007-05-23 Stefan Thurner , Christian Windischberger , Ewald Moser , Markus Barth

This thesis is dedicated to the statistical analysis of multi-sub ject fMRI data, with the purpose of identifying bain structures involved in certain cognitive or sensori-motor tasks, in a reproducible way across sub jects. To overcome…

应用统计 · 统计学 2010-05-19 Merlin Keller , Alexis Roche , Marc Lavielle

Contemporary neuroscience has embraced network science to study the complex and self-organized structure of the human brain; one of the main outstanding issues is that of inferring from measure data, chiefly functional Magnetic Resonance…

最优化与控制 · 数学 2017-03-31 Giulia Prando , Mattia Zorzi , Alessandra Bertoldo , Alessandro Chiuso

Functional MRI (fMRI) has become the most common method for investigating the human brain. However, fMRI data present some complications for statistical analysis and modeling. One recently developed approach to these data focuses on…

Functional magnetic resonance imaging (fMRI) is one of the most popular methods for studying the human brain. Task-related fMRI data processing aims to determine which brain areas are activated when a specific task is performed and is…

信号处理 · 电气工程与系统科学 2022-10-18 Paris A. Karakasis , Athanasios P. Liavas , Nicholas D. Sidiropoulos , Panagiotis G. Simos , Efrosini Papadaki

Functional magnetic resonance imaging or functional MRI (fMRI) is a non-invasive way to assess brain activity by detecting changes associated with blood flow. In this work, we propose a full Bayesian procedure to analyze fMRI data for…

Resting-state brain functional connectivity quantifies the synchrony between activity patterns of different brain regions. In functional magnetic resonance imaging (fMRI), each region comprises a set of spatially contiguous voxels at which…

统计方法学 · 统计学 2025-11-07 Ruobin Liu , Chao Zhang , Chau Tran , Sophie Achard , Wendy Meiring , Alexander Petersen

Advances in neuroimaging techniques have provided us novel insights into understanding how the human mind works. Functional magnetic resonance imaging (fMRI) is the most popular and widely used neuroimaging technique, and there is growing…

神经元与认知 · 定量生物学 2022-06-15 Jihyun Hur , Jaeyeong Yang , Hoyoung Doh , Woo-Young Ahn

Functional magnetic resonance imaging (fMRI) has provided invaluable insight into our understanding of human behavior. However, large inter-individual differences in both brain anatomy and functional localization after anatomical alignment…

应用统计 · 统计学 2021-11-03 Guoqing Wang , Abhirup Datta , Martin A. Lindquist

Task functional magnetic resonance imaging (fMRI) is a type of neuroimaging data used to identify areas of the brain that activate during specific tasks or stimuli. These data are conventionally modeled using a massive univariate approach…

统计方法学 · 统计学 2022-11-04 Daniel A. Spencer , David Bolin , Amanda F. Mejia

fMRI semantic category understanding using linguistic encoding models attempt to learn a forward mapping that relates stimuli to the corresponding brain activation. Classical encoding models use linear multi-variate methods to predict the…

机器学习 · 计算机科学 2018-12-04 Subba Reddy Oota , Adithya Avvaru , Naresh Manwani , Raju S. Bapi
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