[HTML][HTML] Classification and prediction of brain disorders using functional connectivity: promising but challenging
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …
data, have been employed to reflect functional integration of the brain. Alteration in brain …
Functional connectomics from resting-state fMRI
Spontaneous fluctuations in activity in different parts of the brain can be used to study
functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the …
functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the …
[HTML][HTML] Identification of autism spectrum disorder using deep learning and the ABIDE dataset
The goal of the present study was to apply deep learning algorithms to identify autism
spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the …
spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the …
Task-induced brain state manipulation improves prediction of individual traits
Recent work has begun to relate individual differences in brain functional organization to
human behaviors and cognition, but the best brain state to reveal such relationships remains …
human behaviors and cognition, but the best brain state to reveal such relationships remains …
DPABI: data processing & analysis for (resting-state) brain imaging
Brain imaging efforts are being increasingly devoted to decode the functioning of the human
brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding …
brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding …
Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity
Functional magnetic resonance imaging (fMRI) studies typically collapse data from many
subjects, but brain functional organization varies between individuals. Here we establish …
subjects, but brain functional organization varies between individuals. Here we establish …
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
Abstract Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise
to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such …
to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such …
Enhancing studies of the connectome in autism using the autism brain imaging data exchange II
The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance
the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent …
the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent …
Predicting brain-age from multimodal imaging data captures cognitive impairment
The disparity between the chronological age of an individual and their brain-age measured
based on biological information has the potential to offer clinically relevant biomarkers of …
based on biological information has the potential to offer clinically relevant biomarkers of …
Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age
RW Emerson, C Adams, T Nishino, HC Hazlett… - Science translational …, 2017 - science.org
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social
deficits and repetitive behaviors that typically emerge by 24 months of age. To develop …
deficits and repetitive behaviors that typically emerge by 24 months of age. To develop …