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The Blood-Oxygen-Level-Dependent (BOLD) signal of resting-state fMRI (rs-fMRI) records the temporal dynamics of intrinsic functional networks in the brain. However, existing deep learning methods applied to rs-fMRI either neglect the…

Machine Learning · Computer Science 2021-06-30 Soham Gadgil , Qingyu Zhao , Adolf Pfefferbaum , Edith V. Sullivan , Ehsan Adeli , Kilian M. Pohl

Brain-mapping techniques have proven to be vital in understanding the molecular, cellular, and functional mechanisms of the brain. Normal anatomical imaging can provide structural information on certain abnormalities in the brain. However…

Emerging Technologies · Computer Science 2013-01-03 Nivedita Daimiwal , M. Sundhararajan , Revati Shriram

Functional magnetic resonance imaging (fMRI) is widely used in clinical applications to highlight brain areas involved in specific cognitive processes. Brain impairments, such as tumors, suppress the fMRI activation of the anatomical areas…

Neurons and Cognition · Quantitative Biology 2019-06-20 Qiongge Li , Gino Del Ferraro , Luca Pasquini , Kyung K. Peck , Hernan A. Makse , Andrei I. Holodny

Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared to gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long…

fMRI semantic category understanding using linguistic encoding models attempts to learn a forward mapping that relates stimuli to the corresponding brain activation. State-of-the-art encoding models use a single global model (linear or…

Machine Learning · Computer Science 2020-06-02 Subba Reddy Oota , Naresh Manwani , Raju S. Bapi

We present the Mixture-of-Tunable-Experts (MoTE), a method that extends the Mixture-of-Experts architecture of Large Language Models (LLMs). Without additional training, MoTE enables meaningful and focused behavior changes in LLMs…

Artificial Intelligence · Computer Science 2025-02-21 Robert Dahlke , Henrik Klagges , Dan Zecha , Benjamin Merkel , Sven Rohr , Fabian Klemm

Functional magnetic resonance imaging (fMRI) enables noninvasive investigation of brain function, while short clinical scan durations, arising from human and non-human factors, usually lead to reduced data quality and limited statistical…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yunlong Gao , Jinbo Yang , Li Xiao , Haiye Huo , Yang Ji , Hao Wang , Aiying Zhang , Yu-Ping Wang

To understand Working of Human Brain measurements related to the brain function are required. These measurements should be possibly non-invasive. Brain should be disturbed as less as possible during the measurement. Integration of various…

Emerging Technologies · Computer Science 2015-06-16 Revati Shriram , M. Sundhararajan , Nivedita Daimiwal

Early clinical assessment of Alzheimer's disease relies on behavior scores that measure a subject's language, memory, and cognitive skills. On the medical imaging side, functional magnetic resonance imaging has provided invaluable insights…

Signal Processing · Electrical Eng. & Systems 2026-04-14 Javier Salazar Cavazos , Maximillian Egan , Krisanne Litinas , Benjamin Hampstead , Scott Peltier

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

We analyze functional magnetic resonance imaging (fMRI) data from the Human Connectome Project (HCP) to match brain activities during a range of cognitive tasks. Our findings demonstrate that even basic linear machine learning models can…

Neurons and Cognition · Quantitative Biology 2025-10-08 Valeriya Kirova , Dzerassa Kadieva , Daniil Vlasenko , Isak B. Blank , Fedor Ratnikov

Obtaining high quality images of the spinal cord with MRI is difficult, partly due to the fact that the spinal cord is surrounded by a number of structures that have differing magnetic susceptibility. This causes inhomogeneities in the…

Image and Video Processing · Electrical Eng. & Systems 2022-12-09 E. Alonso-Ortiz , D. Papp , A. D'Astous , J. Cohen-Adad

Twenty cases of different brain pathology have been studied via MRI using an open resistive magnet with magnetic field strength of 0.2 Tesla. The relative signal intensity with respect to the repetition time (TR) at fixed echo time (TE)…

Medical Physics · Physics 2009-12-05 Indra Dev Sahu , Sheshkant Aryal , Shanta Lal Shrestha , Ram Kumar Ghimire

Objective: Fast neural Electrical Impedance Tomography (EIT) is a method which permits imaging of neuronal activity in nerves by measuring the associated impedance changes (dZ). Due to the small magnitudes of dZ signals, EIT parameters…

Medical Physics · Physics 2019-10-17 Ilya Tarotin , Kirill Aristovich , David Holder

Resting-state functional MRI (rs-fMRI) is a rich imaging modality that captures spontaneous brain activity patterns, revealing clues about the connectomic organization of the human brain. While many rs-fMRI studies have focused on static…

Machine Learning · Computer Science 2019-08-20 Meenakshi Khosla , Keith Jamison , Amy Kuceyeski , Mert R. Sabuncu

EEG-correlated fMRI analysis is widely used to detect regional blood oxygen level dependent fluctuations that are significantly synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone.…

Signal Processing · Electrical Eng. & Systems 2020-05-04 Simon Van Eyndhoven , Patrick Dupont , Simon Tousseyn , Nico Vervliet , Wim Van Paesschen , Sabine Van Huffel , Borbála Hunyadi

In functional MRI (fMRI), effective connectivity analysis aims at inferring the causal influences that brain regions exert on one another. A common method for this type of analysis is structural equation modeling (SEM). We here propose a…

Quantitative Methods · Quantitative Biology 2024-09-10 G. Marrelec , A. Giron

Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in brain and is widely used for brain disorder analysis.Previous studies propose to extract fMRI representations through diverse…

Quantitative Methods · Quantitative Biology 2023-06-27 Qianqian Wang , Wei Wang , Yuqi Fang , P. -T. Yap , Hongtu Zhu , Hong-Jun Li , Lishan Qiao , Mingxia Liu

Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for anomaly screening. For this ultrasound (US) is employed. While expert sonographers are adept at reading US images, MR…

Computer Vision and Pattern Recognition · Computer Science 2019-09-19 Jianbo Jiao , Ana I. L. Namburete , Aris T. Papageorghiou , J. Alison Noble

Background: Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) due to the high rate of progression from MCI to AD. Sensitive neural biomarkers may provide a tool for an accurate MCI diagnosis,…

Neurons and Cognition · Quantitative Biology 2022-11-02 Adi Wijaya , Noor Akhmad Setiawan , Asma Hayati Ahmad , Rahimah Zakaria , Zahiruddin Othman