AIMC Topic: Brain Mapping

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Reliability of active robotic neuro-navigated transcranial magnetic stimulation motor maps.

Experimental brain research Dec 16, 2022
Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method used to study corticomotor organization and intervention-induced plasticity. Reliability of resting maps is well established, but understudied for active maps and un...
Muscle, Skeletal Brain Mapping Robotics Reproducibility of Results Adult Evoked Potentials, Motor Motor Cortex Transcranial Magnetic Stimulation Robotic Surgical Procedures Electromyography Humans
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Goals, usefulness and abstraction in value-based choice.

Trends in cognitive sciences Nov 26, 2022
Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our valu...
Choice Behavior Reward Goals Artificial Intelligence Decision Making Brain Mapping Brain
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Deep learning-regularized, single-step quantitative susceptibility mapping quantification.

NMR in biomedicine Nov 23, 2022
The purpose of the current study was to develop deep learning-regularized, single-step quantitative susceptibility mapping (QSM) quantification, directly generating QSM from the total phase map. A deep learning-regularized, single-step QSM quantifica...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Mapping Calcinosis Brain Humans Deep Learning
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NeXtQSM-A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data.

Medical image analysis Nov 23, 2022
Deep learning based Quantitative Susceptibility Mapping (QSM) has shown great potential in recent years, obtaining similar results to established non-learning approaches. Many current deep learning approaches are not data consistent, require in vivo ...
Brain Mapping Humans Algorithms Deep Learning Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study.

Human brain mapping Nov 8, 2022
Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and w...
Humans Autism Spectrum Disorder Magnetic Resonance Imaging Brain Mapping Neural Pathways Brain Deep Learning Amygdala
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Explaining neural activity in human listeners with deep learning via natural language processing of narrative text.

Scientific reports Oct 25, 2022
Deep learning (DL) approaches may also inform the analysis of human brain activity. Here, a state-of-art DL tool for natural language processing, the Generative Pre-trained Transformer version 2 (GPT-2), is shown to generate meaningful neural encodin...
Brain Comprehension Humans Brain Mapping Deep Learning Magnetic Resonance Imaging Natural Language Processing
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Inferring Effective Connectivity Networks From fMRI Time Series With a Temporal Entropy-Score.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Inferring brain-effective connectivity networks from neuroimaging data has become a very hot topic in neuroinformatics and bioinformatics. In recent years, the search methods based on Bayesian network score have been greatly developed and become an e...
Brain Mapping Bayes Theorem Entropy Nerve Net Brain Time Factors Neural Networks, Computer Magnetic Resonance Imaging
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Domain-specific and domain-general neural network engagement during human-robot interactions.

The European journal of neuroscience Sep 27, 2022
To what extent do domain-general and domain-specific neural network engagement generalize across interactions with human and artificial agents? In this exploratory study, we analysed a publicly available functional MRI (fMRI) data set (n = 22) to pro...
Magnetic Resonance Imaging Brain Mapping Humans Robotics Comprehension Neural Networks, Computer Brain
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Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.

NeuroImage Sep 15, 2022
Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural networks (CN...
Pattern Recognition, Visual Magnetic Resonance Imaging Visual Perception Brain Mapping Brain Animals Humans Neural Networks, Computer
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BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources.

Zeitschrift fur medizinische Physik Sep 2, 2022
INTRODUCTION: Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial...
Brain Mapping Head Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Humans Brain Deep Learning
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