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A Graph-Theory Based fMRI Analysis
In this study, we employed a clustering approach to analyze fMRI data from a publicly available dataset of patients with mild depression. We utilized...
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EEG and fMRI Artifact Detection Techniques: A Survey of Recent Developments
The evolution of different techniques for exploring cerebral activity and the development of signal processing and analysis methods have enabled a...
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Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI
Resting-state fMRI (rs-fMRI) functional connectivity (FC) analysis provides valuable insights into the relationships between different brain regions...
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Hybrid parcellation map** approach for the extraction of connectivity measures in autism spectrum disorder fMRI data
A complicated neurodevelopmental illness known as Autism Spectrum Disorder (ASD) impacts behavior, speech, and social interaction. For early...
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Machine learning based detection of depression from task-based fMRI using weighted-3D-DWT denoising method
Depression has become an important public health problem in recent years because the probability of a depressive episode in a person's entire life is...
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Diagnosis of Parkinson’s disease using EEG and fMRI
Parkinson’s disease (PD) is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. Parkinson’s...
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Fusing Simultaneously Acquired EEG and fMRI via Hierarchical Deep Transcoding
Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are neuroimaging modalities that offer complementary strengths and...
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Affirmative and Negative Sentence Detection in the Brain Using SVM-RFE and Rotation Forest: An fMRI Study
Studies on the brain’s response to positive and negative stimuli using non-invasive techniques such as fMRI and PET scans have been widely...
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BrainNet with Connectivity Attention for Individualized Predictions Based on Multi-Facet Connections Extracted from Resting-State fMRI Data
Resting-state functional magnetic resonance imaging (RS-fMRI) has great potential for clinical applications. This study aimed to promote the...
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Investigating the impact of standard brain atlases and connectivity measures on the accuracy of ADHD detection from fMRI data using deep learning
Inattention, hyperactivity, and impulsivity are among the symptoms of Attention Deficit Hyperactivity Syndrome (ADHD). This brain disorder cannot...
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Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation
Insufficiency of training data is a persistent issue in medical image analysis, especially for task-based functional magnetic resonance images (fMRI)...
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Neural correlates of Quran recitals: a functional magnetic resonance imaging (fMRI) analysis
Religious experience is a uniquely human phenomenon present in all modern cultures. However, although there has recently been a growing interest in...
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Classifying schizophrenic and controls from fMRI data using graph theoretic framework and community detection
Schizophrenia is a psychiatric disorder characterized by symptoms such as disorganized thinking, hallucinations, disintegration of reality...
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Latent Neural Source Recovery via Transcoding of Simultaneous EEG-fMRI
Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that combines the advantages of both modalities, offering valuable insights into the...
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FFTPSOGA: Fast Fourier Transform with particle swarm optimization and genetic algorithm approach for pattern identification of brain responses in multi subject fMRI data
Functional Magnetic Resonance Imaging (fMRI) is the popular technique where it is possible to capture neural activity in brain regions when subjected...
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Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data
The application of artificial neural networks (ANNs) to functional magnetic resonance imaging (fMRI) data has recently gained renewed attention for...
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Denoising fMRI Message on Population Graph for Multi-site Disease Prediction
In general, large-scale fMRI analysis helps to uncover functional biomarkers and diagnose neuropsychiatric disorders. However, the existence of...
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Spatial-Temporal Graph Convolutional Network for Insomnia Classification via Brain Functional Connectivity Imaging of rs-fMRI
Chronic Insomnia Disorder (CID) is a prevalent sleep disorder characterized by persistent difficulties in initiating or maintaining sleep, leading to...
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Community-Aware Transformer for Autism Prediction in fMRI Connectome
Autism spectrum disorder(ASD) is a lifelong neurodevelopmental condition that affects social communication and behavior. Investigating functional...
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Assessing the Impact of Preprocessing Pipelines on fMRI Based Autism Spectrum Disorder Classification: ABIDE II Results
Resting-state functional MRI (rs-fMRI), a tool for assessing the brain’s spontaneous activity, plays a crucial role in understanding functional...