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Outlying observations are frequently encountered across a wide spectrum of scientific domains, posing notable challenges to the generalizability of statistical models and the reproducibility of downstream analysis. They are identified…

Methodology · Statistics 2026-03-17 Dongliang Zhang , Masoud Asgharian , Martin A. Lindquist

Neuropathic pain, affecting up to 10% of adults, remains difficult to treat due to limited therapeutic efficacy and tolerability. Although resting-state functional MRI (rs-fMRI) is a promising non-invasive measurement of brain biomarkers to…

Machine Learning · Computer Science 2025-03-04 Wenrui Fan , L. M. Riza Rizky , Jiayang Zhang , Chen Chen , Haiping Lu , Kevin Teh , Dinesh Selvarajah , Shuo Zhou

In recent years, neuroimaging has undergone a paradigm shift, moving away from the traditional brain mapping approach toward developing integrated, multivariate brain models that can predict categories of mental events. However, large…

Applications · Statistics 2022-09-19 Guoqing Wang , Abhirup Datta , Martin A. Lindquist

Task-based functional magnetic resonance imaging (task fMRI) is a non-invasive technique that allows identifying brain regions whose activity changes when individuals are asked to perform a given task. This contributes to the understanding…

Neuroimaging studies produce gigabytes of spatio-temporal data for a small number of participants and stimuli. Rarely do researchers attempt to model and examine how individual participants vary from each other -- a question that should be…

Functional magnetic resonance imaging (fMRI) is now a well-established technique for studying the brain. However, in many situations, such as when data are acquired in a resting state, it is difficult to know whether the data are truly…

Applications · Statistics 2013-01-15 John A. D. Aston , Claudia Kirch

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…

Applications · Statistics 2021-11-03 Guoqing Wang , Abhirup Datta , Martin A. Lindquist

Currently there is no validated objective measure of pain. Recent neuroimaging studies have explored the feasibility of using functional near-infrared spectroscopy (fNIRS) to measure alterations in brain function in evoked and ongoing pain.…

Machine Learning · Computer Science 2018-08-22 Daniel Lopez-Martinez , Ke Peng , Sarah C. Steele , Arielle J. Lee , David Borsook , Rosalind Picard

In recent years there has been explosive growth in the number of neuroimaging studies performed using functional Magnetic Resonance Imaging (fMRI). The field that has grown around the acquisition and analysis of fMRI data is intrinsically…

Methodology · Statistics 2009-06-22 Martin A. Lindquist

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

Currently self-report pain ratings are the gold standard in clinical pain assessment. However, the development of objective automatic measures of pain could substantially aid pain diagnosis and therapy. Recent neuroimaging studies have…

Image and Video Processing · Electrical Eng. & Systems 2019-07-31 Daniel Lopez-Martinez , Ke Peng , Arielle Lee , David Borsook , Rosalind Picard

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…

Statistics Theory · Mathematics 2008-08-08 Chunming Zhang , Tao Yu

The standard approach to the analysis of functional magnetic resonance imaging (FMRI) data applies various preprocessing steps to the original FMRI. These preprocessings lead to a general underestimation of residual variance in the…

Applications · Statistics 2018-09-20 Thomas Wilhelm Dieter Möbius

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

Pain is a multifaceted phenomenon that affects a substantial portion of the population. Reliable and consistent evaluation supports individuals experiencing pain and enables the development of effective and advanced management strategies.…

Artificial Intelligence · Computer Science 2025-09-17 Stefanos Gkikas , Ioannis Kyprakis , Manolis Tsiknakis

This research presents a novel multimodal data fusion methodology for pain behavior recognition, integrating statistical correlation analysis with human-centered insights. Our approach introduces two key innovations: 1) integrating…

Artificial Intelligence · Computer Science 2025-01-22 Xingrui Gu , Zhixuan Wang , Irisa Jin , Zekun Wu

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

Random Effects analysis has been introduced into fMRI research in order to generalize findings from the study group to the whole population. Generalizing findings is obviously harder than detecting activation in the study group since in…

Applications · Statistics 2013-09-03 Jonathan D. Rosenblatt , Matthijs Vink , Yoav Benjamini

Aggregating multi-subject functional magnetic resonance imaging (fMRI) data is indispensable for generating valid and general inferences from patterns distributed across human brains. The disparities in anatomical structures and functional…

Machine Learning · Computer Science 2019-11-20 Weida Li , Mingxia Liu , Fang Chen , Daoqiang Zhang

Assessing pain in patients unable to speak (also called non-verbal patients) is extremely complicated and often is done by clinical judgement. However, this method is not reliable since patients vital signs can fluctuate significantly due…

Machine Learning · Computer Science 2020-12-29 Raul Fernandez Rojas , Julio Romero , Jehu Lopez-Aparicio , Keng-Liang Ou
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