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Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System
Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System
Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form actio...
CADENCE — Neuroinformatics Tool for Supervised Calcium Events Detection
CADENCE — Neuroinformatics Tool for Supervised Calcium Events Detection
CADENCE is an open Python 3-written neuroinformatics tool with Qt6 graphic user interface for supervised calcium events de...
Classifying Neuronal Cell Types Based on Shared Electrophysiological Information from Humans and Mice
Classifying Neuronal Cell Types Based on Shared Electrophysiological Information from Humans and Mice
The brain is an intricate system that controls a variety of functions. It consists of a vast number of cells that exhibit ...
Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study
Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred ...
AnNoBrainer, An Automated Annotation of Mouse Brain Images using Deep Learning
AnNoBrainer, An Automated Annotation of Mouse Brain Images using Deep Learning
Annotation of multiple regions of interest across the whole mouse brain is an indispensable process for quantitative evalu...
Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models
Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models
Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigatio...
Morphology and Texture-Guided Deep Neural Network for Intracranial Aneurysm Segmentation in 3D TOF-MRA
Morphology and Texture-Guided Deep Neural Network for Intracranial Aneurysm Segmentation in 3D TOF-MRA
This study concentrates on the segmentation of intracranial aneurysms, a pivotal aspect of diagnosis and treatment plannin...
MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies
MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies
Mouse models are crucial for neuroscience research, yet discrepancies arise between macro- and meso-scales due to sample p...
Detection of Schizophrenia from EEG Signals using Selected Statistical Moments of MFC Coefficients and Ensemble Learning
Detection of Schizophrenia from EEG Signals using Selected Statistical Moments of MFC Coefficients and Ensemble Learning
Schizophrenia is a mental disorder characterized by neurophysiological dysfunctions that result in disturbances in thinkin...
Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging – A Symposium Review
Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging – A Symposium Review
Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for transl...
Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex
Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex
Subdural electrocorticography (ECoG) is a valuable technique for neuroscientific research and for emerging neurotechnologi...
Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains
Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains
Brain reconstruction, specially of the cerebral cortex, is a challenging task and even more so when it comes to highly gyr...
A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images
A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images
Characterizing the anatomical structure and connectivity between cortical regions is a critical step towards understanding...
Improved ADHD Diagnosis Using EEG Connectivity and Deep Learning through Combining Pearson Correlation Coefficient and Phase-Locking Value
Improved ADHD Diagnosis Using EEG Connectivity and Deep Learning through Combining Pearson Correlation Coefficient and Phase-Locking Value
Attention Deficit Hyperactivity Disorder (ADHD) is a widespread neurobehavioral disorder affecting children and adolescent...
Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability
Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability
Visibility graphs provide a novel approach for analysing time-series data. Graph theoretical analysis of visibility graphs...
Age Prediction Using Resting-State Functional MRI
Age Prediction Using Resting-State Functional MRI
The increasing lifespan and large individual differences in cognitive capability highlight the importance of comprehending...
InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels
InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels
Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and $$\gamma$$ -aminobutyric ...
Visual Prompting Based Incremental Learning for Semantic Segmentation of Multiplex Immuno-Flourescence Microscopy Imagery
Visual Prompting Based Incremental Learning for Semantic Segmentation of Multiplex Immuno-Flourescence Microscopy Imagery
Deep learning approaches are state-of-the-art for semantic segmentation of medical images, but unlike many deep learning a...
Decentralized Mixed Effects Modeling in COINSTAC
Decentralized Mixed Effects Modeling in COINSTAC
Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging d...
MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline
MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline
Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instr...
A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer’s Disease using MRI Images
A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer’s Disease using MRI Images
Recently, the early diagnosis of Alzheimer’s disease has gained major attention due to the growing prevalence of the...
Preserving Derivative Information while Transforming Neuronal Curves
Preserving Derivative Information while Transforming Neuronal Curves
The international neuroscience community is building the first comprehensive atlases of brain cell types to understand how...
High-Density Exploration of Activity States in a Multi-Area Brain Model
High-Density Exploration of Activity States in a Multi-Area Brain Model
To simulate whole brain dynamics with only a few equations, biophysical, mesoscopic models of local neuron populations can...
Editorial: On the Economics of Neuroscientific Data Sharing
Editorial: On the Economics of Neuroscientific Data Sharing
Abe, T., Kinsella, I., Saxena, S., Buchanan, E. K., Couto, J., Briggs, J., Kitt, S. L., Glassman, R., Zhou, J., Paninski, ...
Improving the Eligibility of Task-Based fMRI Studies for Meta-Analysis: A Review and Reporting Recommendations
Improving the Eligibility of Task-Based fMRI Studies for Meta-Analysis: A Review and Reporting Recommendations
Decisions made during the analysis or reporting of an fMRI study influence the eligibility of that study to be entered int...
Topological Data Analysis Captures Task-Driven fMRI Profiles in Individual Participants: A Classification Pipeline Based on Persistence
Topological Data Analysis Captures Task-Driven fMRI Profiles in Individual Participants: A Classification Pipeline Based on Persistence
BOLD-based fMRI is the most widely used method for studying brain function. The BOLD signal while valuable, is beset with ...
Analyzing Thalamocortical Tract-Tracing Experiments in a Common Reference Space
Analyzing Thalamocortical Tract-Tracing Experiments in a Common Reference Space
Current mesoscale connectivity atlases provide limited information about the organization of thalamocortical projections i...
Correction to: Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester
Correction to: Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which...
Editorial: Is Now the Time for Foundational Theory of Brain Connectivity?
Editorial: Is Now the Time for Foundational Theory of Brain Connectivity?
For more than a century, the neuron doctrine has provided the bedrock of neuroscience...
Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data
Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data
Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive imaging technique widely used in neuroscie...
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