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Artificial intelligence role in advancement of human brain connectome studies
Artificial intelligence role in advancement of human brain connectome studies
Neurons are interactive cells that connect via ions to develop electromagnetic fields in the brain. This structure functio...
Reproducible brain PET data analysis: easier said than done
Reproducible brain PET data analysis: easier said than done
While a great deal of recent effort has focused on addressing a perceived reproducibility crisis within brain structural m...
Can micro-expressions be used as a biomarker for autism spectrum disorder?
Can micro-expressions be used as a biomarker for autism spectrum disorder?
IntroductionEarly and accurate diagnosis of autism spectrum disorder (ASD) is crucial for effective intervention, yet it r...
Research on ECG signal reconstruction based on improved weighted nuclear norm minimization and approximate message passing algorithm
Research on ECG signal reconstruction based on improved weighted nuclear norm minimization and approximate message passing algorithm
In order to improve the energy efficiency of wearable devices, it is necessary to compress and reconstruct the collected e...
Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data
Introduction In neuroscience, methods such as electroencephalography (EEG), magnetoencephalography (MEG), electrocortico...
Editorial: Reproducible analysis in neuroscience
One of the key ingredients of scientific progress is the ability to repeat, replicate and reproduce independently importan...
Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique
1 Introduction Brain tumor is the most prevalent condition in children and also the most challenging sickness to identify...
Unsupervised method for representation transfer from one brain to another
1 Introduction Acquiring information from the brain not only contributes to understanding the neurological mechanisms und...
Editorial: Improving autism spectrum disorder diagnosis using machine learning techniques
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterised by challenges in social communicati...
Harmonizing AI governance regulations and neuroinformatics: perspectives on privacy and data sharing
In the rapidly evolving field of neuroinformatics, the intersection of artificial intelligence (AI) and neuroscience prese...
Editorial: Addressing large scale computing challenges in neuroscience: current advances and future directions
1. IntroductionNeuroscience research generates vast amounts of data, requiring advanced computing resources for storage, m...
hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction
1 Introduction High-fidelity reconstruction of electroencephalography (EEG) data is of key relevance to many deep learnin...
Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks
Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks
1 Introduction Working memory (WM) is crucial for preparing and organizing goal-directed behaviors, with its functions of...
Editorial: Emerging trends in large-scale data analysis for neuroscience research
The primary aim of this research topic is to showcase recent progress in data-driven approaches for studying the brain. It...
Leveraging deep learning for robust EEG analysis in mental health monitoring
1 Introduction Monitoring mental health through electroencephalography (EEG) has become an increasingly important area of...
Deep CNN ResNet-18 based model with attention and transfer learning for Alzheimer's disease detection
1 Introduction Alzheimer's disease (AD) is a severe neurological condition. A person with AD is unable to converse, retai...
The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint
Introduction Ischemic stroke is a frequent disease and one of the main causes of disability and death in adults worldwid...
Editorial: Protecting privacy in neuroimaging analysis: balancing data sharing and privacy preservation
Neuroimaging is an indispensable tool in neuroscience and medical research, enabling precise investigations into brain str...
Editorial: Recent applications of noninvasive physiological signals and artificial intelligence
Artificial intelligence (AI) is currently transforming diverse fields (Qasmi & Fatima, 2024; Alyabroodi et al., 20...
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...
Decision trees to evaluate the risk of developing multiple sclerosis
Decision trees to evaluate the risk of developing multiple sclerosis
IntroductionMultiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The...
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