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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…

In order to decode the human brain, Multivariate Pattern (MVP) classification generates cognitive models by using functional Magnetic Resonance Imaging (fMRI) datasets. As a standard pipeline in the MVP analysis, brain patterns in…

Machine Learning · Statistics 2018-08-07 Muhammad Yousefnezhad , Daoqiang Zhang

Over the past decade, several studies have explored the potential of magnetic resonance fingerprinting (MRF) for the quantification of brain hemodynamics, oxygenation, and perfusion. Recent advances in simulation models and reconstruction…

Signal Processing · Electrical Eng. & Systems 2025-12-16 T. Coudert , A. Delphin , A. Barrier , E L Barbier , B. Lemasson , J M Warnking , T. Christen

Human brains exhibit highly organized multiscale neurophysiological dynamics. Understanding those dynamic changes and the neuronal networks involved is critical for understanding how the brain functions in health and disease. Functional…

Neurons and Cognition · Quantitative Biology 2024-09-09 Manuel Morante , Kristian Frølich , Naveed ur Rehman

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…

Optimization and Control · Mathematics 2017-03-31 Giulia Prando , Mattia Zorzi , Alessandra Bertoldo , Alessandro Chiuso

As a relatively new field, network neuroscience has tended to focus on aggregate behaviours of the brain averaged over many successive experiments or over long recordings in order to construct robust brain models. These models are limited…

Neurons and Cognition · Quantitative Biology 2022-05-19 James Wilsenach , Katie Warnaby , Charlotte M. Deane , Gesine Reinert

In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable. For this, neuroscientists rely on basic methods such as…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Akrem Sellami , François-Xavier Dupé , Bastien Cagna , Hachem Kadri , Stéphane Ayache , Thierry Artières , Sylvain Takerkart

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…

Methodology · Statistics 2023-06-07 Andrew S. Whiteman , Andreas J. Bartsch , Jian Kang , Timothy D. Johnson

In daily life, we encounter diverse external stimuli, such as images, sounds, and videos. As research in multimodal stimuli and neuroscience advances, fMRI-based brain decoding has become a key tool for understanding brain perception and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pengyu Liu , Guohua Dong , Dan Guo , Kun Li , Fengling Li , Xun Yang , Meng Wang , Xiaomin Ying

Neuroscience theory posits that the brain's visual system coarsely identifies broad object categories via neural activation patterns, with similar objects producing similar neural responses. Artificial neural networks also have internal…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Nathaniel Blanchard , Jeffery Kinnison , Brandon RichardWebster , Pouya Bashivan , Walter J. Scheirer

Various neuroimaging studies suffer from small sample size problem which often limit their reliability. Meta-analysis addresses this challenge by aggregating findings from different studies to identify consistent patterns of brain activity.…

Machine Learning · Computer Science 2025-11-27 Seunghun Baek , Jaejin Lee , Jaeyoon Sim , Minjae Jeong , Won Hwa Kim

Functional Magnetic Resonance Imaging~(fMRI) is widely used to study activation in the human brain. In most cases, data are commonly used to construct activation maps corresponding to a given paradigm. Results can be very variable, hence…

Applications · Statistics 2022-05-04 Ranjan Maitra

The human brain can be considered as complex networks, composed of various regions that continuously exchange their information with each other, forming the brain network graph, from which nodes and edges are extracted using resting-state…

Machine Learning · Computer Science 2025-02-19 Parnian Jalali , Mehran Safayani

The hemodynamic response (HR) in event-related functional magnetic resonance imaging is typically assumed to be stationary. While there are some approaches in the literature to model nonstationary HRs, few focus on rapid changes. In this…

Methodology · Statistics 2025-02-19 Friederike Preusse , Thorsten Dickhaus , André Brechmann

A standard approach in functional neuroimaging explores how a particular cognitive task activates a set of brain regions (one task-to-many regions mapping). Importantly though, the same neural system can be activated by inherently different…

Neurons and Cognition · Quantitative Biology 2016-03-23 Romy Lorenz , Ricardo Pio Monti , Ines R. Violante , Christoforos Anagnostopoulos , Aldo A. Faisal , Giovanni Montana , Robert Leech

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.…

Methodology · Statistics 2023-10-31 Zhengxin Wang , Daniel B. Rowe , Xinyi Li , D. Andrew Brown

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…

Applications · Statistics 2016-06-16 Stefano Castruccio , Hernando Ombao , Marc G. Genton

Segmentation of structural and diffusion MRI (sMRI/dMRI) is usually performed independently in neuroimaging pipelines. However, some brain structures (e.g., globus pallidus, thalamus and its nuclei) can be extracted more accurately by…

Computer Vision and Pattern Recognition · Computer Science 2019-03-12 Juan Eugenio Iglesias , Koen Van Leemput , Polina Golland , Anastasia Yendiki

Functional magnetic resonance imaging (fMRI) technology is popularly used in many fields for studying how the brain reacts to mental stimuli. The identification of optimal fMRI experimental designs is crucial for rendering precise…

Statistics Theory · Mathematics 2015-10-30 Ching-Shui Cheng , Ming-Hung Kao

Functional magnetic resonance imaging (fMRI) is a notoriously noisy measurement of brain activity because of the large variations between individuals, signals marred by environmental differences during collection, and spatiotemporal…