AIMC Topic: Connectome
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Nonlinear effective connectivity measure based on adaptive Neuro Fuzzy Inference System and Granger Causality.
NeuroImage
Jul 19, 2018
Exploring brain networks is an essential step towards understanding functional organization of the brain, which needs characterization of linear and nonlinear connections based on measurements like EEG or MEG. Conventional measures of connectivity ar...
Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 16, 2018
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...
A supervised learning approach for diffusion MRI quality control with minimal training data.
NeuroImage
Jun 5, 2018
Quality control (QC) is a fundamental component of any study. Diffusion MRI has unique challenges that make manual QC particularly difficult, including a greater number of artefacts than other MR modalities and a greater volume of data. The gold stan...
The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.
NeuroImage
Jun 2, 2018
Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accura...
Large Scale Image Segmentation with Structured Loss Based Deep Learning for Connectome Reconstruction.
IEEE transactions on pattern analysis and machine intelligence
May 24, 2018
We present a method combining affinity prediction with region agglomeration, which improves significantly upon the state of the art of neuron segmentation from electron microscopy (EM) in accuracy and scalability. Our method consists of a 3D U-Net, t...
Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at rest.
NeuroImage
May 4, 2018
Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whe...
A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.
eNeuro
Apr 24, 2018
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...
A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection.
International journal of neural systems
Apr 11, 2018
Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of t...
Multiple Kernel Learning Model for Relating Structural and Functional Connectivity in the Brain.
Scientific reports
Feb 19, 2018
A challenging problem in cognitive neuroscience is to relate the structural connectivity (SC) to the functional connectivity (FC) to better understand how large-scale network dynamics underlying human cognition emerges from the relatively fixed SC ar...
Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.
NeuroImage. Clinical
Jan 31, 2018
Investigation of the brain's functional connectome can improve our understanding of how an individual brain's organizational changes influence cognitive function and could result in improved individual risk stratification. Brain connectome studies in...
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