Machine learning in resting-state fMRI analysis
Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …
Principles and open questions in functional brain network reconstruction
O Korhonen, M Zanin, D Papo - Human Brain Mapping, 2021 - Wiley Online Library
Graph theory is now becoming a standard tool in system‐level neuroscience. However,
endowing observed brain anatomy and dynamics with a complex network representation …
endowing observed brain anatomy and dynamics with a complex network representation …
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 …
Benchmarking functional connectome-based predictive models for resting-state fMRI
Functional connectomes reveal biomarkers of individual psychological or clinical traits.
However, there is great variability in the analytic pipelines typically used to derive them from …
However, there is great variability in the analytic pipelines typically used to derive them from …
Which fMRI clustering gives good brain parcellations?
Analysis and interpretation of neuroimaging data often require one to divide the brain into a
number of regions, or parcels, with homogeneous characteristics, be these regions defined …
number of regions, or parcels, with homogeneous characteristics, be these regions defined …
Functional connectome–based predictive modeling in autism
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic
resonance imaging–based studies have helped advance our understanding of its effects on …
resonance imaging–based studies have helped advance our understanding of its effects on …
Evaluation of functional MRI-based human brain parcellation: a review
Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can
significantly affect the outcome of the analysis. In recent years, several novel approaches for …
significantly affect the outcome of the analysis. In recent years, several novel approaches for …
How machine learning is shaping cognitive neuroimaging
G Varoquaux, B Thirion - GigaScience, 2014 - academic.oup.com
Functional brain images are rich and noisy data that can capture indirect signatures of
neural activity underlying cognition in a given experimental setting. Can data mining …
neural activity underlying cognition in a given experimental setting. Can data mining …
[HTML][HTML] Large-scale probabilistic functional modes from resting state fMRI
It is well established that it is possible to observe spontaneous, highly structured, fluctuations
in human brain activity from functional magnetic resonance imaging (fMRI) when the subject …
in human brain activity from functional magnetic resonance imaging (fMRI) when the subject …
Computing personalized brain functional networks from fMRI using self-supervised deep learning
A novel self-supervised deep learning (DL) method is developed to compute personalized
brain functional networks (FNs) for characterizing brain functional neuroanatomy based on …
brain functional networks (FNs) for characterizing brain functional neuroanatomy based on …