AIMC Topic: Brain Mapping

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Finding Distributed Needles in Neural Haystacks.

The Journal of neuroscience : the official journal of the Society for Neuroscience Dec 17, 2020
The human cortex encodes information in complex networks that can be anatomically dispersed and variable in their microstructure across individuals. Using simulations with neural network models, we show that contemporary statistical methods for funct...
Magnetic Resonance Imaging Brain Mapping Multivariate Analysis Facial Recognition Humans Neural Networks, Computer Brain
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Deep learning networks reflect cytoarchitectonic features used in brain mapping.

Scientific reports Dec 16, 2020
The distribution of neurons in the cortex (cytoarchitecture) differs between cortical areas and constitutes the basis for structural maps of the human brain. Deep learning approaches provide a promising alternative to overcome throughput limitations ...
Visual Cortex Humans Deep Learning Image Processing, Computer-Assisted Brain Mapping
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DIKA-Nets: Domain-invariant knowledge-guided attention networks for brain skull stripping of early developing macaques.

NeuroImage Dec 15, 2020
As non-human primates, macaques have a close phylogenetic relationship to human beings and have been proven to be a valuable and widely used animal model in human neuroscience research. Accurate skull stripping (aka. brain extraction) of brain magnet...
Brain Animals Deep Learning Macaca Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Mapping
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Changes to information in working memory depend on distinct removal operations.

Nature communications Dec 7, 2020
Holding information in working memory is essential for cognition, but removing unwanted thoughts is equally important. Here we use multivariate pattern analyses of brain activity to demonstrate the successful manipulation and removal of information f...
Brain Female Adult Male Humans Machine Learning Brain Mapping Memory, Short-Term Neurons Neuroimaging Adolescent Cognition Magnetic Resonance Imaging Models, Neurological
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Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning.

Neuroscience letters Nov 6, 2020
This study applied machine learning regression to predict motor function after stroke based on multimodal magnetic resonance imaging. Fifty-four stroke patients, who underwent T1 weighted, diffusion tensor, and resting state functional magnetic reson...
Multimodal Imaging Stroke Retrospective Studies Female Aged Male Middle Aged Magnetic Resonance Imaging Brain Mapping Humans Machine Learning Brain
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Reliability of robotic transcranial magnetic stimulation motor mapping.

Journal of neurophysiology Nov 4, 2020
Robotic transcranial magnetic stimulation (TMS) is a noninvasive and safe tool that produces cortical motor maps using neuronavigational and neuroanatomical images. Motor maps are individualized representations of the primary motor cortex (M1) topogr...
Female Adult Sensitivity and Specificity Male Humans Transcranial Magnetic Stimulation Brain Mapping Robotics Evoked Potentials, Motor Motor Cortex
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Multi-band MR fingerprinting (MRF) ASL imaging using artificial-neural-network trained with high-fidelity experimental data.

Magnetic resonance in medicine Oct 26, 2020
PURPOSE: We aim to leverage the power of deep-learning with high-fidelity training data to improve the reliability and processing speed of hemodynamic mapping with MR fingerprinting (MRF) arterial spin labeling (ASL).
Male Hemodynamics Arteries Magnetic Resonance Imaging Brain Mapping Cerebrovascular Circulation Reproducibility of Results Humans Kinetics Spin Labels Young Adult Neural Networks, Computer Perfusion Adult Computer Simulation Data Compression Healthy Volunteers Female Moyamoya Disease Gray Matter
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BrainNET: Inference of Brain Network Topology Using Machine Learning.

Brain connectivity Oct 8, 2020
To develop a new functional magnetic resonance image (fMRI) network inference method, BrainNET, that utilizes an efficient machine learning algorithm to quantify contributions of various regions of interests (ROIs) in the brain to a specific ROI. B...
Sensitivity and Specificity Male Adolescent Algorithms Child Humans Brain Neural Pathways Image Processing, Computer-Assisted Machine Learning Computer Simulation Magnetic Resonance Imaging Attention Deficit Disorder with Hyperactivity Female Brain Mapping
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Reconstructing lost BOLD signal in individual participants using deep machine learning.

Nature communications Oct 7, 2020
Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles gov...
Cerebral Cortex Deep Learning Adolescent Deep Brain Stimulation Image Processing, Computer-Assisted Female Healthy Volunteers Young Adult Humans Magnetic Resonance Imaging Datasets as Topic Models, Neurological Adult Parkinson Disease Male Brain Mapping Oxygen
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Differential Covariance: A New Method to Estimate Functional Connectivity in fMRI.

Neural computation Sep 18, 2020
Measuring functional connectivity from fMRI recordings is important in understanding processing in cortical networks. However, because the brain's connection pattern is complex, currently used methods are prone to producing false functional connectio...
Animals Humans Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Brain Models, Neurological Brain Mapping Neural Pathways Nerve Net
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