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The pursuit of approaches to federate data to accelerate Alzheimer’s disease and related dementia research: GAAIN, DPUK, and ADDI
The pursuit of approaches to federate data to accelerate Alzheimer’s disease and related dementia research: GAAIN, DPUK, and ADDI
There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes th...
On temporal scale-free non-periodic stimulation and its mechanisms as an infinite improbability drive of the brain’s functional connectogram
On temporal scale-free non-periodic stimulation and its mechanisms as an infinite improbability drive of the brain’s functional connectogram
Rationalized development of electrical stimulation (ES) therapy is of paramount importance. Not only it will foster new te...
Quantifying evoked responses through information-theoretical measures
Quantifying evoked responses through information-theoretical measures
Information theory is a viable candidate to advance our understanding of how the brain processes information generated in ...
Brain subnetworks most sensitive to alterations of functional connectivity in Schizophrenia: a data-driven approach
Brain subnetworks most sensitive to alterations of functional connectivity in Schizophrenia: a data-driven approach
Functional connectivity (FC) of the brain changes in various brain disorders. Its complexity, however, makes it difficult ...
Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors
Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. H...
Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies
Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies
BackgroundSeveral observational studies have explored the relationships between multiple sclerosis (MS) and breast cancer;...
The image and data archive at the laboratory of neuro imaging
The image and data archive at the laboratory of neuro imaging
The Image and Data Archive (IDA) is a secure online resource for archiving, exploring, and sharing neuroscience data run b...
NeuroWRAP: integrating, validating, and sharing neurodata analysis workflows
NeuroWRAP: integrating, validating, and sharing neurodata analysis workflows
Multiphoton calcium imaging is one of the most powerful tools in modern neuroscience. However, multiphoton data require si...
Application of a Hermite-based measure of non-Gaussianity to normality tests and independent component analysis
Application of a Hermite-based measure of non-Gaussianity to normality tests and independent component analysis
In the analysis of neural data, measures of non-Gaussianity are generally applied in two ways: as tests of normality for v...
The role of wrist-worn technology in the management of Parkinson’s disease in daily life: A narrative review
The role of wrist-worn technology in the management of Parkinson’s disease in daily life: A narrative review
Parkinson’s disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Its slow and heterogen...
QuNex—An integrative platform for reproducible neuroimaging analytics
QuNex—An integrative platform for reproducible neuroimaging analytics
IntroductionNeuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across...
Non-stationary neural signal to image conversion framework for image-based deep learning algorithms
Non-stationary neural signal to image conversion framework for image-based deep learning algorithms
This paper presents a time-efficient preprocessing framework that converts any given 1D physiological signal recordings in...
Targeted neuroplasticity in spatiotemporally patterned invasive neuromodulation therapies for improving clinical outcomes
Targeted neuroplasticity in spatiotemporally patterned invasive neuromodulation therapies for improving clinical outcomes
IntroductionInvasive neuromodulation is routinely used to effectively treat the symptoms of movement1,2 and psychiatric3 d...
Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset
Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset
IntroductionConventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS)...
BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures
BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures
We present an innovative working mechanism (the SBC memory) and surrounding infrastructure (BitBrain) based upon a novel s...
Neural simulation pipeline: Enabling container-based simulations on-premise and in public clouds
Neural simulation pipeline: Enabling container-based simulations on-premise and in public clouds
In this study, we explore the simulation setup in computational neuroscience. We use GENESIS, a general purpose simulation...
An enhanced ant colony optimizer with Cauchy-Gaussian fusion and novel movement strategy for multi-threshold COVID-19 X-ray image segmentation
An enhanced ant colony optimizer with Cauchy-Gaussian fusion and novel movement strategy for multi-threshold COVID-19 X-ray image segmentation
The novel coronavirus pneumonia (COVID-19) is a respiratory disease of great concern in terms of its dissemination and sev...
Novel methods for elucidating modality importance in multimodal electrophysiology classifiers
Novel methods for elucidating modality importance in multimodal electrophysiology classifiers
IntroductionMultimodal classification is increasingly common in electrophysiology studies. Many studies use deep learning ...
Erratum: Advancing prediction of risk of intraoperative massive blood transfusion in liver transplantation with machine learning models. A multicenter retrospective study
Erratum: Advancing prediction of risk of intraoperative massive blood transfusion in liver transplantation with machine learning models. A multicenter retrospective study
An erratum on: Advancing Prediction of Risk of Intraoperative Massive Blood Transfusion in Liver Transplantation With Mac...
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke
ObjectiveIn this study, we investigate whether a Convolutional Neural Network (CNN) can generate informative parametric ma...
A neuroscientist’s guide to using murine brain atlases for efficient analysis and transparent reporting
A neuroscientist’s guide to using murine brain atlases for efficient analysis and transparent reporting
Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analy...
CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning
CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning
Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations...
A computational model to simulate spectral modulation and speech perception experiments of cochlear implant users
A computational model to simulate spectral modulation and speech perception experiments of cochlear implant users
Speech understanding in cochlear implant (CI) users presents large intersubject variability that may be related to differe...
Maximum likelihood-based estimation of diffusion coefficient is quick and reliable method for analyzing estradiol actions on surface receptor movements
Maximum likelihood-based estimation of diffusion coefficient is quick and reliable method for analyzing estradiol actions on surface receptor movements
The rapid effects of estradiol on membrane receptors are in the focus of the estradiol research field, however, the molecu...
An accessible and versatile deep learning-based sleep stage classifier
An accessible and versatile deep learning-based sleep stage classifier
Manual sleep scoring for research purposes and for the diagnosis of sleep disorders is labor-intensive and often varies si...
A systematic comparison of deep learning methods for EEG time series analysis
A systematic comparison of deep learning methods for EEG time series analysis
Analyzing time series data like EEG or MEG is challenging due to noisy, high-dimensional, and patient-specific signals. De...
NeuroSuites: An online platform for running neuroscience, statistical, and machine learning tools
NeuroSuites: An online platform for running neuroscience, statistical, and machine learning tools
Nowadays, an enormous amount of high dimensional data is available in the field of neuroscience. Handling these data is co...
A study on the clusterability of latent representations in image pipelines
A study on the clusterability of latent representations in image pipelines
Latent representations are a necessary component of cognitive artificial intelligence (AI) systems. Here, we investigate t...
Improving the brain image resolution of generalized q-sampling MRI revealed by a three-dimensional CNN-based method
Improving the brain image resolution of generalized q-sampling MRI revealed by a three-dimensional CNN-based method
BackgroundUnderstanding neural connections facilitates the neuroscience and cognitive behavioral research. There are many ...
Robin’s Viewer: Using deep-learning predictions to assist EEG annotation
Robin’s Viewer: Using deep-learning predictions to assist EEG annotation
Machine learning techniques such as deep learning have been increasingly used to assist EEG annotation, by automating arti...
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