[HTML][HTML] Relationship between prediction accuracy and feature importance reliability: An empirical and theoretical study
There is significant interest in using neuroimaging data to predict behavior. The predictive
models are often interpreted by the computation of feature importance, which quantifies the …
models are often interpreted by the computation of feature importance, which quantifies the …
[PDF][PDF] There is no fundamental trade-off between prediction accuracy and feature importance reliability
There is significant interest in using neuroimaging data to predict behavior. The predictive
models are often interpreted by the computation of feature importance, which quantifies the …
models are often interpreted by the computation of feature importance, which quantifies the …
The burden of reliability: How measurement noise limits brain-behaviour predictions
Current major efforts in human neuroimaging research aim to understand individual
differences and identify biomarkers for clinical applications. One particularly promising …
differences and identify biomarkers for clinical applications. One particularly promising …
[HTML][HTML] Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
Cognitive performance can be predicted from an individual's functional brain connectivity
with modest accuracy using machine learning approaches. As yet, however, predictive …
with modest accuracy using machine learning approaches. As yet, however, predictive …
[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 …
Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging
Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating
individual differences in various behavioral phenotypes and clinical outcomes is of growing …
individual differences in various behavioral phenotypes and clinical outcomes is of growing …
[HTML][HTML] Comparison between gradients and parcellations for functional connectivity prediction of behavior
Resting-state functional connectivity (RSFC) is widely used to predict behavioral measures.
To predict behavioral measures, representing RSFC with parcellations and gradients are the …
To predict behavioral measures, representing RSFC with parcellations and gradients are the …
Individual differences in cognitive performance are better predicted by global rather than localized BOLD activity patterns across the cortex
Despite its central role in revealing the neurobiological mechanisms of behavior,
neuroimaging research faces the challenge of producing reliable biomarkers for cognitive …
neuroimaging research faces the challenge of producing reliable biomarkers for cognitive …
Determining four confounding factors in individual cognitive traits prediction with functional connectivity: an exploratory study
Resting-state functional connectivity (RSFC) has been widely adopted for individualized trait
prediction. However, multiple confounding factors may impact the predicted brain-behavior …
prediction. However, multiple confounding factors may impact the predicted brain-behavior …
A connectivity-based psychometric prediction framework for brain–behavior relationship studies
The recent availability of population-based studies with neuroimaging and behavioral
measurements opens promising perspectives to investigate the relationships between …
measurements opens promising perspectives to investigate the relationships between …