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Unraveling Integration-Segregation Imbalances in Schizophrenia Through Topological High-Order Functional Connectivity
Unraveling Integration-Segregation Imbalances in Schizophrenia Through Topological High-Order Functional Connectivity
Background: The occurrence of brain disorders correlates with detectable dysfunctions in the specialization of brain conne...
FrAMBI: A Software Framework for Auditory Modeling Based on Bayesian Inference
FrAMBI: A Software Framework for Auditory Modeling Based on Bayesian Inference
Research in hearing science often relies on auditory models to describe listener’s behaviour and its neural underpin...
Generalized Coupled Matrix Tensor Factorization Method Based on Normalized Mutual Information for Simultaneous EEG-fMRI Data Analysis
Generalized Coupled Matrix Tensor Factorization Method Based on Normalized Mutual Information for Simultaneous EEG-fMRI Data Analysis
The complementary properties of both modalities can be exploited through the fusion of electroencephalography (EEG) and fu...
Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation
Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation
The bidirectional interactions between brain and heart through autonomic nervous system is the prime focus of neuro-cardio...
Blood Flow Velocity Analysis in Cerebral Perforating Arteries on 7T 2D Phase Contrast MRI with an Open-Source Software Tool (SELMA)
Blood Flow Velocity Analysis in Cerebral Perforating Arteries on 7T 2D Phase Contrast MRI with an Open-Source Software Tool (SELMA)
Blood flow velocity in the cerebral perforating arteries can be quantified in a two-dimensional plane with phase contrast ...
CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model
CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model
Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and adults. One of the ma...
Determination of the Time-frequency Features for Impulse Components in EEG Signals
Determination of the Time-frequency Features for Impulse Components in EEG Signals
Accurately identifying the timing and frequency characteristics of impulse components in EEG signals is essential but limi...
Complementary Strategies to Identify Differentially Expressed Genes in the Choroid Plexus of Patients with Progressive Multiple Sclerosis
Complementary Strategies to Identify Differentially Expressed Genes in the Choroid Plexus of Patients with Progressive Multiple Sclerosis
Multiple sclerosis (MS) is a neurological disease causing myelin and axon damage through inflammatory and autoimmune proce...
Classification Prediction of Hydrocephalus After Intercerebral Haemorrhage Based on Machine Learning Approach
Classification Prediction of Hydrocephalus After Intercerebral Haemorrhage Based on Machine Learning Approach
In order to construct a clinical classification prediction model for hydrocephalus after intercerebral haemorrhage(ICH) to...
Large Scale in vivo Acquisition, Segmentation and 3D Reconstruction of Cortical Vasculature using $$\mu $$ Doppler Ultrasound Imaging
Large Scale in vivo Acquisition, Segmentation and 3D Reconstruction of Cortical Vasculature using $$\mu $$ Doppler Ultrasound Imaging
The brain is composed of a dense and ramified vascular network of arteries, veins and capillaries of various sizes. One wa...
Twenty Years of Neuroinformatics: A Bibliometric Analysis
Twenty Years of Neuroinformatics: A Bibliometric Analysis
This study presents a thorough bibliometric analysis of Neuroinformatics over the past 20 years, offering insights into th...
Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study
Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study
Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in the cerebrovascular sy...
Predicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques
Predicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques
The problem at hand is the significant global health challenge posed by children’s diseases, where timely and accura...
“The Brain is…”: A Survey of the Brain’s Many Definitions
“The Brain is…”: A Survey of the Brain’s Many Definitions
A reader of the peer-reviewed neuroscience literature will often encounter expressions like the following: ‘the brai...
Computational Generation of Long-range Axonal Morphologies
Computational Generation of Long-range Axonal Morphologies
Long-range axons are fundamental to brain connectivity and functional organization, enabling communication between differe...
Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability
Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability
This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline t...
NeuroCarto: A Toolkit for Building Custom Read-out Channel Maps for High Electrode-count Neural Probes
NeuroCarto: A Toolkit for Building Custom Read-out Channel Maps for High Electrode-count Neural Probes
Neuropixels probes contain thousands of electrodes across one or more shanks and are sufficiently small to allow chronic r...
A Self-supervised Deep Learning Model for Diagonal Sulcus Detection with Limited Labeled Data
A Self-supervised Deep Learning Model for Diagonal Sulcus Detection with Limited Labeled Data
Sulci are a fundamental part of brain morphology, closely linked to brain function, cognition, and behavior. Tertiary sulc...
Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
Meningioma, the most common primary brain tumor, presents significant challenges in MRI-based diagnosis and treatment plan...
Simulation Study of Envelope Wave Electrical Nerve Stimulation Based on a Real Head Model
Simulation Study of Envelope Wave Electrical Nerve Stimulation Based on a Real Head Model
In recent years, the modulation of brain neural activity by applied electromagnetic fields has become a hot spot in neuros...
Stimulation Effects Mapping for Optimizing Coil Placement for Transcranial Magnetic Stimulation
Stimulation Effects Mapping for Optimizing Coil Placement for Transcranial Magnetic Stimulation
The position and orientation of transcranial magnetic stimulation (TMS) coil, which we collectively refer to as coil place...
Anatomic Interpretability in Neuroimage Deep Learning: Saliency Approaches for Typical Aging and Traumatic Brain Injury
Anatomic Interpretability in Neuroimage Deep Learning: Saliency Approaches for Typical Aging and Traumatic Brain Injury
The black box nature of deep neural networks (DNNs) makes researchers and clinicians hesitant to rely on their findings. S...
Interdisciplinary and Collaborative Training in Neuroscience: Insights from the Human Brain Project Education Programme
Interdisciplinary and Collaborative Training in Neuroscience: Insights from the Human Brain Project Education Programme
Neuroscience education is challenged by rapidly evolving technology and the development of interdisciplinary approaches fo...
Improved ADHD Diagnosis Using EEG Connectivity and Deep Learning through Combining Pearson Correlation Coefficient and Phase-Locking Value
Improved ADHD Diagnosis Using EEG Connectivity and Deep Learning through Combining Pearson Correlation Coefficient and Phase-Locking Value
Attention Deficit Hyperactivity Disorder (ADHD) is a widespread neurobehavioral disorder affecting children and adolescent...
A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images
A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images
Characterizing the anatomical structure and connectivity between cortical regions is a critical step towards understanding...
Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex
Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex
Subdural electrocorticography (ECoG) is a valuable technique for neuroscientific research and for emerging neurotechnologi...
Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains
Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains
Brain reconstruction, specially of the cerebral cortex, is a challenging task and even more so when it comes to highly gyr...
Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging – A Symposium Review
Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging – A Symposium Review
Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for transl...
Detection of Schizophrenia from EEG Signals using Selected Statistical Moments of MFC Coefficients and Ensemble Learning
Detection of Schizophrenia from EEG Signals using Selected Statistical Moments of MFC Coefficients and Ensemble Learning
Schizophrenia is a mental disorder characterized by neurophysiological dysfunctions that result in disturbances in thinkin...
MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies
MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies
Mouse models are crucial for neuroscience research, yet discrepancies arise between macro- and meso-scales due to sample p...
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