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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...
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...
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: 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...
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...
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...
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...
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...
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...
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...
Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM
where hi and hj are two data points and φ· is the feature mapping function. To make data set H away from the origin, equiv...
Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation
1 Introduction Dementia represents the most prominent reason behind the defects associated with the individual's cognitiv...
The classification of absence seizures using power-to-power cross-frequency coupling analysis with a deep learning network
1 Introduction Brain oscillations span frequencies across a range of several orders of magnitude from the Berger bands b...
Quantitative evaluation method of stroke association based on multidimensional gait parameters by using machine learning
1 Introduction Stroke has a high incidence rate, mortality, disability, and recurrence rate, ranking among the leading c...
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...
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...
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...