The prediction of brain activity from connectivity: advances and applications
M Bernstein-Eliav, I Tavor - The Neuroscientist, 2024 - journals.sagepub.com
The human brain is composed of multiple, discrete, functionally specialized regions that are
interconnected to form large-scale distributed networks. Using advanced brain-imaging …
interconnected to form large-scale distributed networks. Using advanced brain-imaging …
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
We propose a geometric deep-learning-based framework, TractGeoNet, for performing
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …
[HTML][HTML] MRI economics: Balancing sample size and scan duration in brain wide association studies
A pervasive dilemma in neuroimaging is whether to prioritize sample size or scan duration
given fixed resources. Here, we systematically investigate this trade-off in the context of …
given fixed resources. Here, we systematically investigate this trade-off in the context of …
Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD …
Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect
linear associations between two data matrices by computing latent variables (LVs) having …
linear associations between two data matrices by computing latent variables (LVs) having …
Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes
A Omidvarnia, L Sasse, DI Larabi, F Raimondo… - Communications …, 2024 - nature.com
In this study, we aimed to compare imaging-based features of brain function, measured by
resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total …
resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total …
TractoSCR: a novel supervised contrastive regression framework for prediction of neurocognitive measures using multi-site harmonized diffusion MRI tractography
Neuroimaging-based prediction of neurocognitive measures is valuable for studying how
the brain's structure relates to cognitive function. However, the accuracy of prediction using …
the brain's structure relates to cognitive function. However, the accuracy of prediction using …
[HTML][HTML] Voxel-wise multivariate analysis of brain-psychosocial associations in adolescents reveals six latent dimensions of cognition and psychopathology
Background Adolescence heralds the onset of much psychopathology, which may be
conceptualized as an emergence of altered covariation between symptoms and brain …
conceptualized as an emergence of altered covariation between symptoms and brain …
Benchmarking methods for mapping functional connectivity in the brain
The networked architecture of the brain promotes synchrony among neuronal populations
and the emergence of coherent dynamics. These communication patterns can be …
and the emergence of coherent dynamics. These communication patterns can be …
[HTML][HTML] Translating phenotypic prediction models from big to small anatomical MRI data using meta-matching
Individualized phenotypic prediction based on structural MRI is an important goal in
neuroscience. Prediction performance increases with larger samples, but small-scale …
neuroscience. Prediction performance increases with larger samples, but small-scale …
[HTML][HTML] Predicting depression risk in early adolescence via multimodal brain imaging
Depression is an incapacitating psychiatric disorder with increased risk through
adolescence. Among other factors, children with family history of depression have …
adolescence. Among other factors, children with family history of depression have …