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Domain adaptation for EEG-based, cross-subject epileptic seizure prediction
Domain adaptation for EEG-based, cross-subject epileptic seizure prediction
The ability to predict the occurrence of an epileptic seizure is a safeguard against patient injury and health complicatio...
Retraction: NeuroSuites: an online platform for running neuroscience, statistical, and machine learning tools
Retraction: NeuroSuites: an online platform for running neuroscience, statistical, and machine learning tools
The journal retracts the 17th February 2023 article above. In light of complaints received following publication of the o...
Improving the detection of sleep slow oscillations in electroencephalographic data
Improving the detection of sleep slow oscillations in electroencephalographic data
Study objectivesWe aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate t...
Enabling uncertainty estimation in neural networks through weight perturbation for improved Alzheimer's disease classification
Enabling uncertainty estimation in neural networks through weight perturbation for improved Alzheimer's disease classification
BackgroundThe willingness to trust predictions formulated by automatic algorithms is key in a wide range of domains. Howev...
In silico analyses of the involvement of GPR55, CB1R and TRPV1: response to THC, contribution to temporal lobe epilepsy, structural modeling and updated evolution
In silico analyses of the involvement of GPR55, CB1R and TRPV1: response to THC, contribution to temporal lobe epilepsy, structural modeling and updated evolution
IntroductionThe endocannabinoid (eCB) system is named after the discovery that endogenous cannabinoids bind to the same re...
The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases
The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases
Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function....
Multiscale co-simulation design pattern for neuroscience applications
Multiscale co-simulation design pattern for neuroscience applications
Integration of information across heterogeneous sources creates added scientific value. Interoperability of data, tools an...
Empirical comparison of deep learning models for fNIRS pain decoding
Empirical comparison of deep learning models for fNIRS pain decoding
IntroductionPain assessment is extremely important in patients unable to communicate and it is often done by clinical judg...
Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch
Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch
Spiking neural network simulations are a central tool in Computational Neuroscience, Artificial Intelligence, and Neuromor...
Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder
Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder
IntroductionMental disorders are a significant concern in contemporary society, with a pressing need to identify biologica...
Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation
Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation
IntroductionPharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a...
Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet
Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet
IntroductionIn recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a foc...
Editorial: Navigating the landscape of FAIR data sharing and reuse: repositories, standards, and resources
Editorial: Navigating the landscape of FAIR data sharing and reuse: repositories, standards, and resources
In response to the expanding landscape of neuroscience data and the diverse array of formats emerging from various researc...
Intra-V1 functional networks and classification of observed stimuli
Intra-V1 functional networks and classification of observed stimuli
IntroductionPrevious studies suggest that co-fluctuations in neural activity within V1 (measured with fMRI) carry informat...
A scoping review of mathematical models covering Alzheimer's disease progression
A scoping review of mathematical models covering Alzheimer's disease progression
Alzheimer's disease is a complex, multi-factorial, and multi-parametric neurodegenerative etiology. Mathematical model...
Automated analysis and detection of epileptic seizures in video recordings using artificial intelligence
Automated analysis and detection of epileptic seizures in video recordings using artificial intelligence
IntroductionAutomated seizure detection promises to aid in the prevention of SUDEP and improve the quality of care by assi...
Epileptic seizure prediction based on EEG using pseudo-three-dimensional CNN
Epileptic seizure prediction based on EEG using pseudo-three-dimensional CNN
Epileptic seizures are characterized by their sudden and unpredictable nature, posing significant risks to a patient’s dai...
A computational model of Alzheimer's disease at the nano, micro, and macroscales
A computational model of Alzheimer's disease at the nano, micro, and macroscales
IntroductionMathematical models play a crucial role in investigating complex biological systems, enabling a comprehensive ...
Turbulent dynamics and whole-brain modeling: toward new clinical applications for traumatic brain injury
Turbulent dynamics and whole-brain modeling: toward new clinical applications for traumatic brain injury
Traumatic Brain Injury (TBI) is a prevalent disorder mostly characterized by persistent impairments in cognitive function ...
suMRak: a multi-tool solution for preclinical brain MRI data analysis
suMRak: a multi-tool solution for preclinical brain MRI data analysis
IntroductionMagnetic resonance imaging (MRI) is invaluable for understanding brain disorders, but data complexity poses a ...
Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder
Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder
BackgroundArtificial intelligence (AI) has been the subject of studies in autism spectrum disorder (ASD) and may affect it...
Few-shot EEG sleep staging based on transductive prototype optimization network
Few-shot EEG sleep staging based on transductive prototype optimization network
Electroencephalography (EEG) is a commonly used technology for monitoring brain activities and diagnosing sleep disorders....
Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus
Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus
Characterizing the connectomic and morphological diversity of thalamic neurons is key for better understanding how the tha...
Corrigendum: Learning the heterogeneous representation of brain's structure from serial SEM images using a masked autoencoder
Corrigendum: Learning the heterogeneous representation of brain's structure from serial SEM images using a masked autoencoder
\sectionThree-dimensional segmentation of neural structures in serial scanning electron microscope (SEM) images is a funda...
Tissue Oxygen Depth Explorer: an interactive database for microscopic oxygen imaging data
Tissue Oxygen Depth Explorer: an interactive database for microscopic oxygen imaging data
Over the last decade, increased efforts have been made to standardize the curation, storage, and retrieval of scholarly da...
Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub
Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub
To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being...
Prognostic estimation for acute ischemic stroke patients undergoing mechanical thrombectomy within an extended therapeutic window using an interpretable machine learning model
Prognostic estimation for acute ischemic stroke patients undergoing mechanical thrombectomy within an extended therapeutic window using an interpretable machine learning model
BackgroundMechanical thrombectomy (MT) is effective for acute ischemic stroke with large vessel occlusion (AIS-LVO) within...
Editorial: Physical neuromorphic computing and its industrial applications
Editorial: Physical neuromorphic computing and its industrial applications
The importance of handling cognitive data such as images, voices and natural languages is wide spreading not only at datac...
Editorial: Bringing together data- and knowledge-driven solutions for a better understanding and effective diagnostics of neurological disorders
Editorial: Bringing together data- and knowledge-driven solutions for a better understanding and effective diagnostics of neurological disorders
In their paper entitled 'Interpretable evaluation for the Brunnstrom recovery stage of the lower limb based on wearabl...
Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks
Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks
IntroductionAcquisition and pre-processing pipelines for diffusion-weighted imaging (DWI) volumes are resource- and time-c...
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