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Workflow for the Creation of 3D Stereoscopic Models of Supra- and Infratentorial Brain Venous Anatomy and their Integration in a Virtual Reality Environment
Workflow for the Creation of 3D Stereoscopic Models of Supra- and Infratentorial Brain Venous Anatomy and their Integration in a Virtual Reality Environment
The recent advance in technology allows for the photorealistic digitalization of anatomical specimens that can now be pres...
RELICT-NI: Replica Detection in Synthetic Neuroimaging—A Study on Noncontrast CT and Time-of-Flight MRA
RELICT-NI: Replica Detection in Synthetic Neuroimaging—A Study on Noncontrast CT and Time-of-Flight MRA
Synthetic neuroimaging data has the potential to augment and improve the generalizability of deep learning models. However...
3D Morphometric and Computational Modeling of the Human Fasciola Cinerea: A Hidden Gate of Memory Networks
3D Morphometric and Computational Modeling of the Human Fasciola Cinerea: A Hidden Gate of Memory Networks
The fasciola cinerea (FC) is a slender archicortical band at the posterior hippocampal tail, and its human morphology and ...
Optimizing Theta Burst Stimulation Protocols: A Computational Exploration of Novel Alpha-Beta and Alpha-Gamma Frequency Couplings
Optimizing Theta Burst Stimulation Protocols: A Computational Exploration of Novel Alpha-Beta and Alpha-Gamma Frequency Couplings
This computational study aimed to optimize the theta burst stimulation (TBS) protocols by systematically exploring the eff...
Inferences on the Watts-Strogatz Model: A Study on Brain Functional Connectivity
Inferences on the Watts-Strogatz Model: A Study on Brain Functional Connectivity
Modelling real-world networks allows investigating the structure and the dynamics of such networks, which led to significa...
: An Open-Source Python Package for the Analysis of Open Field Exploration Data
: An Open-Source Python Package for the Analysis of Open Field Exploration Data
The open field test is widely used in behavioral neuroscience, providing insights into exploration, anxiety, and the learn...
Hierarchical Storage Management in User Space for Neuroimaging Applications
Hierarchical Storage Management in User Space for Neuroimaging Applications
Neuroimaging open-data initiatives have led to increased availability of large scientific datasets. While these datasets a...
Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
Accurate classification of neuronal cell types is essential for understanding brain organization, but multimodal neuron da...
Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren’s Syndrome
Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren’s Syndrome
Central nervous system (CNS) involvement in primary Sjögren’s syndrome (pSS), although less frequent, can lead ...
Impact of Neuron Models on Spiking Neural Network Performance: A Complexity-based Classification Approach
Impact of Neuron Models on Spiking Neural Network Performance: A Complexity-based Classification Approach
This study addresses the important question of how neuron model choice and learning rules shape the classification perform...
Revealing Structural Brain-Cognition Relationships in Children: A Comparison of Morphometric Similarity and INverse Divergence Networks
Revealing Structural Brain-Cognition Relationships in Children: A Comparison of Morphometric Similarity and INverse Divergence Networks
The study of structural brain networks (SBNs) offers critical insights into brain-cognition relationships. However, a comp...
Towards Multi-Brain Decoding in Autism: A Self-Supervised Learning Approach
Towards Multi-Brain Decoding in Autism: A Self-Supervised Learning Approach
This study introduces a self-supervised learning (SSL) approach to hyperscanning electroencephalography (EEG) data, target...
Deep Learning-Based Classification of Temporal Stages of AT8-Labeled Tau Pathology After Experimental Traumatic Brain Injury
Deep Learning-Based Classification of Temporal Stages of AT8-Labeled Tau Pathology After Experimental Traumatic Brain Injury
Tauopathies are characterised by a progressive accumulation of hyperphosphorylated tau. However, early and intermediate st...
A Validated Transcriptomic NMJ Remodeling Score Reveals Synaptic Dysfunction Independent of Muscle Atrophy after Immobilization in a Microgravity Analog
A Validated Transcriptomic NMJ Remodeling Score Reveals Synaptic Dysfunction Independent of Muscle Atrophy after Immobilization in a Microgravity Analog
Muscle weakness after immobilization often exceeds that explained by loss of muscle mass alone, suggesting a role for neur...
Enhancing fMRI Decoded Neurofeedback with Co-adaptive Training: Simulation and Proof-of-principle Evidence
Enhancing fMRI Decoded Neurofeedback with Co-adaptive Training: Simulation and Proof-of-principle Evidence
A significant challenge for neurofeedback training research and related clinical applications, is participants’ diff...
Robust Containerization of the High Angular Resolution Functional Imaging (HARFI) Pipeline
Robust Containerization of the High Angular Resolution Functional Imaging (HARFI) Pipeline
Alejandra, F. V. NeuroCOVID MRI DWI and FMRI with reversal learning (OpenNeuro, 2024), https://doi.org/doi:https://doi.org...
A Complex Network-Based Approach for Detecting and Characterizing Power Neurons in Drosophila
A Complex Network-Based Approach for Detecting and Characterizing Power Neurons in Drosophila
Connectome analysis investigates the connections in the brain to understand how brain regions communicate with each other ...
WaveNet’s Precision in iEEG Classification
WaveNet’s Precision in iEEG Classification
This study introduces a WaveNet-based deep learning model designed to automate the classification of Intracranial Electroe...
Dual-Modal Deep Learning with In-Domain Training and Attention for Infant Brain Myelination Prediction
Dual-Modal Deep Learning with In-Domain Training and Attention for Infant Brain Myelination Prediction
Myelin plays a critical role in the central nervous system, and its maturation is essential for understanding brain develo...
A Comprehensive Analysis of Inflammation Regulatory Biomarkers among three Neuropsychiatric Disorders using Transcriptomic Approach
A Comprehensive Analysis of Inflammation Regulatory Biomarkers among three Neuropsychiatric Disorders using Transcriptomic Approach
Neuropsychiatric disorders (NPDs) affect more than 125 million individuals globally. Major depressive disorder (M...
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...
SeizyML: An Application for Semi-Automated Seizure Detection Using Interpretable Machine Learning Models
SeizyML: An Application for Semi-Automated Seizure Detection Using Interpretable Machine Learning Models
Despite the vast number of publications reporting seizures and the reliance of the field on accurate seizure detection, th...
Efficient, Automatic, and Reproducible Patch Clamp Data Analysis with “Auto ANT”, a User-Friendly Interface for Batch Analysis of Patch Clamp Recordings
Efficient, Automatic, and Reproducible Patch Clamp Data Analysis with “Auto ANT”, a User-Friendly Interface for Batch Analysis of Patch Clamp Recordings
Patch-clamp recordings are vital for investigating the electrical properties of excitable cells, yet the analysis of these...
Optimizing Colocalized Cell Counting Using Automated and Semiautomated Methods
Optimizing Colocalized Cell Counting Using Automated and Semiautomated Methods
Inflammation within the spinal subarachnoid space leads to arachnoid hypercellularity. Multiplex immunohistochemistry (MP-...
Estimation of Task-Related Dynamic Brain Connectivity via Data Inflation and Classification Model Explainability
Estimation of Task-Related Dynamic Brain Connectivity via Data Inflation and Classification Model Explainability
Study of brain function often involves analyzing task-related switching between intrinsic brain networks, which connect va...
Revealing the Multivariate Associations Between Autistic Traits and Principal Functional Connectome
Revealing the Multivariate Associations Between Autistic Traits and Principal Functional Connectome
Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition characterized by a spectrum of behavioral an...
Classification of Major Depressive Disorder Using Graph Attention Mechanism with Multi-Site rs-fMRI Data
Classification of Major Depressive Disorder Using Graph Attention Mechanism with Multi-Site rs-fMRI Data
Major Depressive Disorder (MDD) significantly impacts global health, impairing individual functioning and increasing socio...
Predicting Placebo Responses Using EEG and Deep Convolutional Neural Networks: Correlations with Clinical Data Across Three Independent Datasets
Predicting Placebo Responses Using EEG and Deep Convolutional Neural Networks: Correlations with Clinical Data Across Three Independent Datasets
Identifying likely placebo responders can help design more efficient clinical trials by stratifying participants, reducing...
Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T-Weighted MRI Gray Matter-White Matter Intensity Contrast
Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T-Weighted MRI Gray Matter-White Matter Intensity Contrast
In T1-weighted magnetic resonance imaging (MRI), cortical thickness (CT) and gray-white matter contrast (GWC) capture brai...
SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices
SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices
Brain slicing is a commonly used technique in brain science research. In order to study the spatial distribution of labele...
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