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Understanding how large-scale functional brain networks reorganize during cognitive decline remains a central challenge in neuroimaging. While recent self-supervised models have shown promise for learning representations from resting-state…

Machine Learning · Computer Science 2026-03-03 Karanpartap Singh , Adam Turnbull , Mohammad Abbasi , Kilian Pohl , Feng Vankee Lin , Ehsan Adeli

Effective connectivity analysis in functional magnetic resonance imaging (fMRI) studies directional interactions among brain regions and experimental stimuli. Dynamic causal modeling (DCM) is a widely used method to estimate effective…

Methodology · Statistics 2026-05-15 Kaitlyn R. Fales , Hyebin Song , Nicole A. Lazar

We propose a novel method that exploits fMRI Repetition Suppression (RS-fMRI) to measure the dimensionality of the set response vectors, i.e. the dimension of the space of linear combinations of neural population activity patterns in…

Quantitative Methods · Quantitative Biology 2016-06-07 Mattia Rigotti , Stefano Fusi

Estimating brain effective connectivity (EC) from functional magnetic resonance imaging (fMRI) data can aid in comprehending the neural mechanisms underlying human behavior and cognition, providing a foundation for disease diagnosis.…

Machine Learning · Computer Science 2025-03-17 Wen Xiong , Jinduo Liu , Junzhong Ji , Fenglong Ma

Functional connections in the brain are frequently represented by weighted networks, with nodes representing locations in the brain, and edges representing the strength of connectivity between these locations. One challenge in analyzing…

Applications · Statistics 2022-09-28 Yura Kim , Daniel Kessler , Elizaveta Levina

Functional Magnetic Resonance Imaging (fMRI) is predominantly harnessed for spatially mapping activation foci along distributed pathways. However, resolving dynamic information on activation sequence remains elusive. Here, we show an…

Medical Physics · Physics 2020-02-04 Rita Gil , Francisca F. Fernandes , Noam Shemesh

In recent years, Bayesian statistics methods in neuroscience have been showing important advances. In particular, detection of brain signals for studying the complexity of the brain is an active area of research. Functional magnetic…

Methodology · Statistics 2017-06-06 Jairo Alberto Fuquene Patiño , Brenda Betancourt , João B. M. Pereira

Functional magnetic resonance imaging (fMRI) data have become increasingly available and are useful for describing functional connectivity (FC), the relatedness of neuronal activity in regions of the brain. This FC of the brain provides…

Machine Learning · Statistics 2020-10-14 Andrew DiLernia , Karina Quevedo , Jazmin Camchong , Kelvin Lim , Wei Pan , Lin Zhang

Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the relationship between the functional neural processes and anatomical…

Machine Learning · Computer Science 2021-04-20 Hongyuan You , Sikun Lin , Ambuj K. Singh

The brain is often studied from a network perspective, where functional activity is assessed using functional Magnetic Resonance Imaging (fMRI) to estimate connectivity between predefined neuronal regions. Functional connectivity can be…

Applications · Statistics 2025-07-22 Olivier Bisson , Yanis Aeschlimann , Samuel Deslauriers-Gauthier , Xavier Pennec

Functional magnetic resonance imaging (fMRI) data is characterized by its complexity and high--dimensionality, encompassing signals from various regions of interests (ROIs) that exhibit intricate correlations. Analyzing fMRI data directly…

Applications · Statistics 2024-01-18 Yeseul Jeon , Jeong-Jae Kim , SuMin Yu , Junggu Choi , Sanghoon Han

Human brain functional connectivity (FC) is often measured as the similarity of functional MRI responses across brain regions when a brain is either resting or performing a task. This paper aims to statistically analyze the dynamic nature…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Mengyu Dai , Zhengwu Zhang , Anuj Srivastava

With the wide adoption of functional magnetic resonance imaging (fMRI) by cognitive neuroscience researchers, large volumes of brain imaging data have been accumulated in recent years. Aggregating these data to derive scientific insights…

Applications · Statistics 2020-06-01 Ming Bo Cai , Michael Shvartsman , Anqi Wu , Hejia Zhang , Xia Zhu

For neurological disorders and diseases, functional and anatomical connectomes of the human brain can be used to better inform targeted interventions and treatment strategies. Functional magnetic resonance imaging (fMRI) is a non-invasive…

Methodology · Statistics 2023-07-03 Matt Ryan , Gary Glonek , Jono Tuke , Melissa Humphries

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…

Applications · Statistics 2015-01-26 Christopher J. Brignell , William J. Browne , Ian L. Dryden , Susan T. Francis

Recent advances in neuroimaging have deepened our understanding of the brain's complex functional and structural organization. Among these, functional Magnetic Resonance Imaging (fMRI) - particularly resting-state fMRI (rs-fMRI) - has…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 M. Moein Esfahani , Sepehr Salem Ghahfarokhi , Mohammed Alser , Jingyu Liu , Vince Calhoun

Contemporary accounts of ongoing thought recognise it as a heterogeneous and multidimensional construct, varying in both form and content. An emerging body of evidence demonstrates that distinct types of experience are associated with…

Functional magnetic resonance imaging (fMRI) data provides information concerning activity in the brain and in particular the interactions between brain regions. Resting state fMRI data is widely used for inferring connectivities in the…

Applications · Statistics 2019-03-04 Christina Stoehr , John A D Aston , Claudia Kirch

Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more accurate estimates of effect sizes and more reliable and…

The human brain is a complex and highly dynamic system, and our current knowledge of its functional mechanism is still very limited. Fortunately, with functional magnetic resonance imaging (fMRI), we can observe blood oxygen level-dependent…

Neurons and Cognition · Quantitative Biology 2024-12-31 Yifei Sun , Mariano Cabezas , Jiah Lee , Chenyu Wang , Wei Zhang , Fernando Calamante , Jinglei Lv
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