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Zhiqiong Wang, Zican Lin, Shuo Li, Yibo Wang, Weiying Zhong, Xinlei Wang and Junchang Xin
Alzheimer?s disease (AD) is a progressive, irreversible neurodegenerative disorder that requires early diagnosis for timely treatment. Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique for detecting brain activity. To ...
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Lia Maria Hocke, Yunjie Tong and Blaise deBonneval Frederick
Multimodal functional near-infrared spectroscopy?functional magnetic resonance imaging (fNIRS?fMRI) studies have been highly beneficial for both the fNIRS and fMRI field as, for example, they shed light on the underlying mechanism of each method. However...
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Igor D. Rodrigues, Emerson A. de Carvalho, Caio P. Santana and Guilherme S. Bastos
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized primarily by social impairments that manifest in different severity levels. In recent years, many studies have explored the use of machine learning (ML) and resting-state funct...
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Jéssica Monteiro, João Castelhano, Duarte Pignatelli, Armando Tartaro and Nicoletta Cera
Background: Several functional magnetic resonance imaging (fMRI) studies investigated the brain correlates of psychogenic erectile dysfunction (PED) and premature ejaculation (PE), representing the most common sexual dysfunctions in men. These studies al...
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Mohammed Isam Al-Hiyali, Norashikin Yahya, Ibrahima Faye, Maged S. Al-Quraishi and Abdulhakim Al-Ezzi
The study of functional connectivity (FC) of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) has gained traction for uncovering FC patterns related to autism spectrum disorder (ASD). It is believed that the neurodynamic comp...
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Jin Xie, Zhiyong Huo, Xianru Liu and Zhishun Wang
For attention deficit hyperactivity disorder (ADHD), a common neurological disease, accurate identification is the basis for treatment. In this paper, a novel end-to-end representation learning framework for ADHD classification of functional magnetic res...
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Aikaterini S. Karampasi, Antonis D. Savva, Vasileios Ch. Korfiatis, Ioannis Kakkos and George K. Matsopoulos
Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, alth...
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Faria Zarin Subah, Kaushik Deb, Pranab Kumar Dhar and Takeshi Koshiba
Autism spectrum disorder (ASD) is a complex and degenerative neuro-developmental disorder. Most of the existing methods utilize functional magnetic resonance imaging (fMRI) to detect ASD with a very limited dataset which provides high accuracy but result...
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Usman Mahmood, Zening Fu, Vince D. Calhoun and Sergey Plis
Functional connectivity (FC) studies have demonstrated the overarching value of studying the brain and its disorders through the undirected weighted graph of functional magnetic resonance imaging (fMRI) correlation matrix. However, most of the work with ...
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Fabio Scoppa, Sabina Saccomanno, Gianluca Bianco and Alessio Pirino
The aim of this study was to pinpoint the cerebral regions implicated during swallowing by comparing the brain activation areas associated with two different volitional movements: tongue protrusion and tongue elevation. Twenty-four healthy subjects (11?m...
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