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Accurate segmentation of neonatal brain MRI with deep learning
Accurate segmentation of neonatal brain MRI with deep learning
An important step toward delivering an accurate connectome of the human brain is robust segmentation of 3D Magnetic Resona...
A data-driven approach to clinical decision support in tinnitus retraining therapy
A data-driven approach to clinical decision support in tinnitus retraining therapy
BackgroundTinnitus, known as “ringing in the ears”, is a widespread and frequently disabling hearing disorder. No pharmaco...
Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging
Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects approximately 1% of the population an...
Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on “Frontiers in Neuroinformatics”
Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on “Frontiers in Neuroinformatics”
In the field of neuroscience, the core of the cohort study project consists of collection, analysis, and sharing of multi-...
The EBRAINS Hodgkin-Huxley Neuron Builder: An Online Resource For Building Data-Driven Neuron Models
The EBRAINS Hodgkin-Huxley Neuron Builder: An Online Resource For Building Data-Driven Neuron Models
In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and inf...
Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimot...
A domain adaptation benchmark for T1-weighted brain magnetic resonance image segmentation
A domain adaptation benchmark for T1-weighted brain magnetic resonance image segmentation
Accurate brain segmentation is critical for magnetic resonance imaging (MRI) analysis pipelines. Machine-learning-based br...
Recognition ability of untrained neural networks to symbolic numbers
Recognition ability of untrained neural networks to symbolic numbers
Although animals can learn to use abstract numbers to represent the number of items, whether untrained animals could disti...
Progressive 3D biomedical image registration network based on deep self-calibration
Progressive 3D biomedical image registration network based on deep self-calibration
Three dimensional deformable image registration (DIR) is a key enabling technique in building digital neuronal atlases of ...
Corrigendum: Mapping and validating a point neuron model on intel's neuromorphic hardware Loihi
Corrigendum: Mapping and validating a point neuron model on intel's neuromorphic hardware Loihi
The original version of this article has been updated.In the published article, there was a mistake in the Funding stateme...
Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth
Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth
The goal of this study was to identify features in mouse electrocorticogram recordings that indicate the depth of anesthes...
Interpretable evaluation for the Brunnstrom recovery stage of the lower limb based on wearable sensors
Interpretable evaluation for the Brunnstrom recovery stage of the lower limb based on wearable sensors
With the increasing number of stroke patients, there is an urgent need for an accessible, scientific, and reliable evaluat...
Brain structural alterations in young girls with Rett syndrome: A voxel-based morphometry and tract-based spatial statistics study
Brain structural alterations in young girls with Rett syndrome: A voxel-based morphometry and tract-based spatial statistics study
Rett syndrome (RTT) is a neurodevelopmental disorder caused by loss-of-function variants in the MECP2 gene, currently with...
Expected affine: A registration method for damaged section in serial sections electron microscopy
Expected affine: A registration method for damaged section in serial sections electron microscopy
Registration is essential for the volume reconstruction of biological tissues using serial section electron microscope (ss...
Decoding EEG rhythms offline and online during motor imagery for standing and sitting based on a brain-computer interface
Decoding EEG rhythms offline and online during motor imagery for standing and sitting based on a brain-computer interface
Motor imagery (MI)-based brain-computer interface (BCI) systems have shown promising advances for lower limb motor rehabil...
Explainable artificial intelligence based on feature optimization for age at onset prediction of spinocerebellar ataxia type 3
Explainable artificial intelligence based on feature optimization for age at onset prediction of spinocerebellar ataxia type 3
Existing treatments can only delay the progression of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) afte...
Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project
Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project
The stimulating peripheral activity to relieve conditions (SPARC) program is a US National Institutes of Health-funded eff...
Classification of partial seizures based on functional connectivity: A MEG study with support vector machine
Classification of partial seizures based on functional connectivity: A MEG study with support vector machine
Temporal lobe epilepsy (TLE) is a chronic neurological disorder that is divided into two subtypes, complex partial seizure...
An EEG study of human trust in autonomous vehicles based on graphic theoretical analysis
An EEG study of human trust in autonomous vehicles based on graphic theoretical analysis
With the development of autonomous vehicle technology, human-centered transport research will likely shift to the interact...
Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia
Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia
Feature selection plays a crucial role in the development of machine learning algorithms. Understanding the impact of the ...
Prediction model for suicide based on back propagation neural network and multilayer perceptron
Prediction model for suicide based on back propagation neural network and multilayer perceptron
IntroductionThe aim was to explore the neural network prediction model for suicide based on back propagation (BP) and mult...
A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis
A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis
Fractional anisotropy (FA) is a quantitative map sensitive to microstructural properties of tissues in vivo and it is exte...
A deep learning approach with subregion partition in MRI image analysis for metastatic brain tumor
A deep learning approach with subregion partition in MRI image analysis for metastatic brain tumor
PurposeTo propose a deep learning network with subregion partition for predicting metastatic origins and EGFR/HER2 status ...
A numerical population density technique for N-dimensional neuron models
A numerical population density technique for N-dimensional neuron models
Population density techniques can be used to simulate the behavior of a population of neurons which adhere to a common und...