[HTML][HTML] Ten simple rules for predictive modeling of individual differences in neuroimaging
Establishing brain-behavior associations that map brain organization to phenotypic
measures and generalize to novel individuals remains a challenge in neuroimaging …
measures and generalize to novel individuals remains a challenge in neuroimaging …
Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research
Abstract The Organization for Human Brain Map** (OHBM) has been active in advocating
for the instantiation of best practices in neuroimaging data acquisition, analysis, reporting …
for the instantiation of best practices in neuroimaging data acquisition, analysis, reporting …
Machine learning algorithm validation with a limited sample size
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other
technology-based data collection methods have led to a torrent of high dimensional …
technology-based data collection methods have led to a torrent of high dimensional …
Long-term wireless streaming of neural recordings for circuit discovery and adaptive stimulation in individuals with Parkinson's disease
Neural recordings using invasive devices in humans can elucidate the circuits underlying
brain disorders, but have so far been limited to short recordings from externalized brain …
brain disorders, but have so far been limited to short recordings from externalized brain …
[HTML][HTML] Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study
How individual differences in brain network organization track behavioral variability is a
fundamental question in systems neuroscience. Recent work suggests that resting-state and …
fundamental question in systems neuroscience. Recent work suggests that resting-state and …
Cross-validation failure: Small sample sizes lead to large error bars
G Varoquaux - Neuroimage, 2018 - Elsevier
Predictive models ground many state-of-the-art developments in statistical brain image
analysis: decoding, MVPA, searchlight, or extraction of biomarkers. The principled approach …
analysis: decoding, MVPA, searchlight, or extraction of biomarkers. The principled approach …
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets
Recently, deep learning has unlocked unprecedented success in various domains,
especially using images, text, and speech. However, deep learning is only beneficial if the …
especially using images, text, and speech. However, deep learning is only beneficial if the …
Spatial topography of individual-specific cortical networks predicts human cognition, personality, and emotion
Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to
delineate individual-specific brain networks. A major question is whether individual-specific …
delineate individual-specific brain networks. A major question is whether individual-specific …
Cross-ethnicity/race generalization failure of behavioral prediction from resting-state functional connectivity
Algorithmic biases that favor majority populations pose a key challenge to the application of
machine learning for precision medicine. Here, we assessed such bias in prediction models …
machine learning for precision medicine. Here, we assessed such bias in prediction models …
Individual-specific areal-level parcellations improve functional connectivity prediction of behavior
Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of
individual-specific cortical parcellations. We have previously developed a multi-session …
individual-specific cortical parcellations. We have previously developed a multi-session …