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Functional Magnetic Resonance Imaging (fMRI) is an imaging technique widely used to study human brain activity. fMRI signals in areas across the brain transiently synchronise and desynchronise their activity in a highly structured manner,…

Machine Learning · Computer Science 2025-08-12 Yiran Huang , Amirhossein Nouranizadeh , Christine Ahrends , Mengjia Xu

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…

Magnetic resonance imaging (MRI) is a crucial tool to identify brain abnormalities in a wide range of neurological disorders. In focal epilepsy MRI is used to identify structural cerebral abnormalities. For covert lesions, machine learning…

While functional magnetic resonance imaging (fMRI) offers valuable insights into brain activity, it is limited by high operational costs and significant infrastructural demands. In contrast, electroencephalography (EEG) provides…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Kristofer Grover Roos , Atsushi Fukuda , Quan Huu Cap

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses has limited clinical application…

The human brain is a complex, dynamic network, which is commonly studied using functional magnetic resonance imaging (fMRI) and modeled as network of Regions of interest (ROIs) for understanding various brain functions. Recent studies…

Quantitative Methods · Quantitative Biology 2024-06-26 Yifan Yang , Yutong Mao , Xufu Liu , Xiao Liu

Fast spin-echo (FSE) pulse sequences for Magnetic Resonance Imaging (MRI) offer important imaging contrast in clinically feasible scan times. T2-shuffling is widely used to resolve temporal signal dynamics in FSE acquisitions by exploiting…

Image and Video Processing · Electrical Eng. & Systems 2023-03-07 Molin Zhang , Junshen Xu , Yamin Arefeen , Elfar Adalsteinsson

This paper proposes a novel approach of integrating different neuroimaging techniques to characterize an autistic brain. Different techniques like EEG, fMRI and DTI have traditionally been used to find biomarkers for autism, but there have…

Functional MRI (fMRI) has been widely used to study activity patterns in the human brain. It infers neuronal activity from the associated hemodynamic response, which fundamentally limits its spatial and temporal specificity. In mice, the…

Neurons and Cognition · Quantitative Biology 2023-03-02 Shota Hodono , Reuben Rideaux , Timo van Kerkoerle , Martijn A. Cloos

Current AI frameworks for brain decoding and encoding, typically train and test models within the same datasets. This limits their utility for brain computer interfaces (BCI) or neurofeedback, for which it would be useful to pool…

T2 mapping in fetal brain MRI has the potential to improve characterization of the developing brain, especially at mid-field (0.55T), where T2 decay is slower. However, this is challenging as fetal MRI acquisition relies on multiple…

Real-time fMRI neurofeedback (rtfMRI-nf) with simultaneous EEG allows volitional modulation of BOLD activity of target brain regions and investigation of related electrophysiological activity. We applied this approach to study correlations…

Neurons and Cognition · Quantitative Biology 2018-01-15 Vadim Zotev , Masaya Misaki , Raquel Phillips , Chung Ki Wong , Jerzy Bodurka

The objective of this paper is to provide a temporal dynamic model for resting state functional Magnetic Resonance Imaging (fMRI) trajectory to predict future brain images based on the given sequence. To this end, we came up with the model…

Signal Processing · Electrical Eng. & Systems 2020-11-17 Zheyu Wen

A Brain Computer Interface (BCI) connects the human brain to the outside world, providing a direct communication channel. Electroencephalography (EEG) signals are commonly used in BCIs to reflect cognitive patterns related to motor function…

Machine Learning · Computer Science 2025-11-19 Abdullah Al Shiam , Md. Khademul Islam Molla , Abu Saleh Musa Miah , Md. Abdus Samad Kamal

At present, MRI scans are performed inside a fully-enclosed RF shielding room, posing stringent installation requirement and unnecessary patient discomfort. We aim to develop an electromagnetic interference (EMI) cancellation strategy for…

Signal Processing · Electrical Eng. & Systems 2023-01-06 Yujiao Zhao , Linfang Xiao , Vick Lau , Yilong Liu , Alex T. Leong , Ed X. Wu

Most of the existing wavelet image processing techniques are carried out in the form of single-scale reconstruction and multiple iterations. However, processing high-quality fMRI data presents problems such as mixed noise and excessive…

Image and Video Processing · Electrical Eng. & Systems 2024-06-26 Lingxi Xiao , Jinxin Hu , Yutian Yang , Yinqiu Feng , Zichao Li , Zexi Chen

Non-invasive methods to measure brain activity are important to understand cognitive processes in the human brain. A prominent example is functional magnetic resonance imaging (fMRI), which is a noisy measurement of a delayed signal that…

Neurons and Cognition · Quantitative Biology 2020-08-17 Hans-Christian Ruiz-Euler , Jose R. Ferreira Marques , Hilbert J. Kappen

Simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be used to non-invasively measure the spatiotemporal dynamics of the human brain. One challenge is dealing with the artifacts that…

Neurons and Cognition · Quantitative Biology 2017-07-26 Josef Faller , Linbi Hong , Jennifer Cummings , Paul Sajda

The dispute of how the human brain represents conceptual knowledge has been argued in many scientific fields. Brain imaging studies have shown that the spatial patterns of neural activation in the brain are correlated with thinking about…

Neurons and Cognition · Quantitative Biology 2018-06-15 Subba Reddy Oota , Naresh Manwani , Bapi Raju S

Purpose: To develop an accelerated Cartesian MRF implementation using a multi-shot EPI sequence for rapid simultaneous quantification of T1 and T2 parameters. Methods: The proposed Cartesian MRF method involved the acquisition of highly…

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