AIMC Topic: Connectome

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Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks.

Human brain mapping Feb 24, 2020
Electroencephalogram (EEG) microstates that represent quasi-stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dyn...
Humans Neural Networks, Computer Electroencephalography Datasets as Topic Cerebral Cortex Connectome Stress, Psychological Time Factors Magnetic Resonance Imaging Adult Male Middle Aged
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Pre-Synaptic Pool Modification (PSPM): A supervised learning procedure for recurrent spiking neural networks.

PloS one Feb 24, 2020
Learning synaptic weights of spiking neural network (SNN) models that can reproduce target spike trains from provided neural firing data is a central problem in computational neuroscience and spike-based computing. The discovery of the optimal weight...
Computer Simulation Animals Connectome Models, Neurological Nerve Net Presynaptic Terminals Action Potentials Supervised Machine Learning
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Space-independent community and hub structure of functional brain networks.

NeuroImage Feb 17, 2020
Coordinated brain activity reflects underlying cognitive processes and can be modeled as a network of inter-regional functional connections. The most costly connections in the network are long-distance correlations that, in the absence of underlying ...
Models, Theoretical Magnetic Resonance Imaging Connectome Nerve Net Humans Neural Networks, Computer
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Towards deep learning for connectome mapping: A block decomposition framework.

NeuroImage Feb 15, 2020
We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network (CNN), but can also be straightforwardly incorporated i...
Humans Connectome Diffusion Magnetic Resonance Imaging Brain Deep Learning Models, Neurological
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Optimising network modelling methods for fMRI.

NeuroImage Feb 13, 2020
A major goal of neuroimaging studies is to develop predictive models to analyze the relationship between whole brain functional connectivity patterns and behavioural traits. However, there is no single widely-accepted standard pipeline for analyzing ...
Magnetic Resonance Imaging Biological Specimen Banks Datasets as Topic Adult Deep Learning Models, Theoretical Humans Neural Networks, Computer Connectome
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Somatosensory evoked fields predict response to vagus nerve stimulation.

NeuroImage. Clinical Feb 4, 2020
There is an unmet need to develop robust predictive algorithms to preoperatively identify pediatric epilepsy patients who will respond to vagus nerve stimulation (VNS). Given the similarity in the neural circuitry between vagus and median nerve affer...
Somatosensory Cortex Afferent Pathways Vagus Nerve Stimulation Drug Resistant Epilepsy Humans Magnetoencephalography Treatment Outcome Retrospective Studies Evoked Potentials, Somatosensory Male Support Vector Machine Adolescent Median Nerve Female Child Connectome
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An improved deep network for tissue microstructure estimation with uncertainty quantification.

Medical image analysis Jan 22, 2020
Deep learning based methods have improved the estimation of tissue microstructure from diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients. These methods learn the mapping from diffusion signals in ...
Humans Deep Learning Image Enhancement White Matter Connectome Uncertainty Diffusion Magnetic Resonance Imaging
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Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer's Disease and Autism Spectrum Disorder.

NeuroImage. Clinical Jan 17, 2020
Functional modules in the human brain support its drive for specialization whereas brain hubs act as focal points for information integration. Brain hubs are brain regions that have a large number of both within and between module connections. We arg...
Nerve Net Deep Learning Adolescent Aged Child Young Adult Cerebral Cortex Adult Magnetic Resonance Imaging Connectome Humans Alzheimer Disease Autism Spectrum Disorder
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Improving the detection of autism spectrum disorder by combining structural and functional MRI information.

NeuroImage. Clinical Jan 17, 2020
Autism Spectrum Disorder (ASD) is a brain disorder that is typically characterized by deficits in social communication and interaction, as well as restrictive and repetitive behaviors and interests. During the last years, there has been an increase i...
Neuroimaging Connectome Child Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Reproducibility of Results Young Adult Adult Male Middle Aged Adolescent Autism Spectrum Disorder Brain Female Humans Machine Learning
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From Synaptic Interactions to Collective Dynamics in Random Neuronal Networks Models: Critical Role of Eigenvectors and Transient Behavior.

Neural computation Dec 13, 2019
The study of neuronal interactions is at the center of several big collaborative neuroscience projects (including the Human Connectome Project, the Blue Brain Project, and the Brainome) that attempt to obtain a detailed map of the entire brain. Under...
Nerve Net Models, Neurological Humans Neurons Neural Networks, Computer Connectome Brain
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