AIMC Topic: Nerve Net

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A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.

NeuroImage Nov 30, 2021
The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic resonance imaging (fMRI) has emerged as a common neuroimaging technique for s...
Connectome Nerve Net Attention Deficit Disorder with Hyperactivity Humans Neural Networks, Computer Adult Young Adult Magnetic Resonance Imaging Cerebral Cortex
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Neural correlates of word representation vectors in natural language processing models: Evidence from representational similarity analysis of event-related brain potentials.

Psychophysiology Nov 24, 2021
Natural language processing models based on machine learning (ML-NLP models) have been developed to solve practical problems, such as interpreting an Internet search query. These models are not intended to reflect human language comprehension mechani...
Humans Machine Learning Brain Semantics Nerve Net Evoked Potentials Young Adult Natural Language Processing Electroencephalography
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Echo state network models for nonlinear Granger causality.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Oct 25, 2021
While Granger causality (GC) has been often employed in network neuroscience, most GC applications are based on linear multivariate autoregressive (MVAR) models. However, real-life systems like biological networks exhibit notable nonlinear behaviour,...
Connectome Nerve Net Humans Neural Networks, Computer Brain Magnetic Resonance Imaging
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Brain functional and effective connectivity based on electroencephalography recordings: A review.

Human brain mapping Oct 20, 2021
Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional...
Machine Learning Brain Electroencephalography Humans Connectome Nerve Net
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Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics.

Human brain mapping Oct 16, 2021
Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional ...
Amyotrophic Lateral Sclerosis Connectome Nerve Net Middle Aged Deep Learning Magnetic Resonance Imaging Adult Male Brain Female Aged Humans
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MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning.

Nature communications Oct 13, 2021
Understanding the basis of brain function requires knowledge of cortical operations over wide spatial scales and the quantitative analysis of brain activity in well-defined brain regions. Matching an anatomical atlas to brain functional data requires...
Machine Learning Algorithms Animals Nerve Net Brain Mapping Male Atlases as Topic Stereotaxic Techniques Cerebral Cortex Image Processing, Computer-Assisted Mice, Transgenic Optical Imaging Mice
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Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity.

Brain structure & function Oct 11, 2021
Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely used in brain research, the full extent to which these functional measures are related to the unde...
Nerve Net Magnetic Resonance Imaging Connectome Neural Pathways Humans Brain Deep Learning
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The information theory of developmental pruning: Optimizing global network architectures using local synaptic rules.

PLoS computational biology Oct 11, 2021
During development, biological neural networks produce more synapses and neurons than needed. Many of these synapses and neurons are later removed in a process known as neural pruning. Why networks should initially be over-populated, and the processe...
Synapses Nerve Net Information Theory Computational Biology Models, Neurological Neurons Algorithms Animals Humans Neural Networks, Computer
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Effective gene expression prediction from sequence by integrating long-range interactions.

Nature methods Oct 4, 2021
How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction a...
Humans Machine Learning Epigenesis, Genetic Databases, Genetic Cell Line Animals Mice Genomics Nerve Net Genome Quantitative Trait Loci DNA Gene Expression Regulation
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A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRI.

Human brain mapping Sep 29, 2021
Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that ...
Connectome Deep Learning Humans Nerve Net Magnetic Resonance Imaging Brain Intelligence
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