[HTML][HTML] Proportional intracranial volume correction differentially biases behavioral predictions across neuroanatomical features, sexes, and development
Individual differences in brain anatomy can be used to predict variations in cognitive ability.
Most studies to date have focused on broad population-level trends, but the extent to which …
Most studies to date have focused on broad population-level trends, but the extent to which …
Does size matter? The relationship between predictive power of single-subject morphometric networks to spatial scale and edge weight
PR Raamana, SC Strother… - Brain Structure and …, 2020 - Springer
Network-level analysis based on anatomical, pairwise similarities (eg, cortical thickness) has
been gaining increasing attention recently. However, there has not been a systematic study …
been gaining increasing attention recently. However, there has not been a systematic study …
Evidence for embracing normative modeling
In this work, we expand the normative model repository introduced in Rutherford et al.,
2022a to include normative models charting lifespan trajectories of structural surface area …
2022a to include normative models charting lifespan trajectories of structural surface area …
[HTML][HTML] The unreliable influence of multivariate noise normalization on the reliability of neural dissimilarity
Representational similarity analysis (RSA) is a key element in the multivariate pattern
analysis toolkit. The central construct of the method is the representational dissimilarity …
analysis toolkit. The central construct of the method is the representational dissimilarity …
[HTML][HTML] Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics
There is significant interest in the development and application of deep neural networks
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
[HTML][HTML] Act natural: Functional connectivity from naturalistic stimuli fMRI outperforms resting-state in predicting brain activity
The search for an 'ideal'approach to investigate the functional connections in the human
brain is an ongoing challenge for the neuroscience community. While resting-state …
brain is an ongoing challenge for the neuroscience community. While resting-state …
[PDF][PDF] Is it that simple? Linear mapping models in cognitive neuroscience
Advances in cognitive neuroscience are often accompanied by an increased complexity in
the methods we use to uncover new aspects of brain function. Recently, many studies have …
the methods we use to uncover new aspects of brain function. Recently, many studies have …
[HTML][HTML] Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis
With the wide adoption of functional magnetic resonance imaging (fMRI) by cognitive
neuroscience researchers, large volumes of brain imaging data have been accumulated in …
neuroscience researchers, large volumes of brain imaging data have been accumulated in …
Resting-state functional brain connectivity best predicts the personality dimension of openness to experience
Personality neuroscience aims to find associations between brain measures and personality
traits. Findings to date have been severely limited by a number of factors, including small …
traits. Findings to date have been severely limited by a number of factors, including small …
The utility of data-driven feature selection: Re: Chu et al. 2012
The recent Chu et al.(2012) manuscript discusses two key findings regarding feature
selection (FS):(1) data driven FS was no better than using whole brain voxel data and (2) a …
selection (FS):(1) data driven FS was no better than using whole brain voxel data and (2) a …