Richard Cameron Craddock

Moving Beyond Processing and Analysis-Related Variation in Neuroscience

The paper evaluates the impact of different preprocessing pipelines on functional MRI reproducibility and shows moderate inter-pipeline agreement, affecting brainwide association study consistency.

A low-resource reliable pipeline to democratize multi-modal connectome estimation and analysis

This paper introduces a low-resource pipeline for estimating connectomes from MRI data, demonstrating its reliability across diverse datasets without manual intervention.

Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide

This study finds that smaller spared subcortical nuclei are linked to worse sensorimotor outcomes after stroke, varying by time since stroke and type of impairment.

Eliminating accidental deviations to minimize generalization error and maximize replicability: applications in connectomics and genomics

This paper introduces a new statistic called discriminability to improve replicability by distinguishing accidental from systematic deviations in data, showing its effectiveness in both simulated and real datasets.

Is it Time to Switch Your T1W Sequence? Assessing the Impact of Prospective Motion Correction on the Reliability and Quality of Structural Imaging

This study compares two MRI sequences, MPRAGE and MPRAGE+PMC, finding that MPRAGE+PMC offers higher intra-sequence reliability but lower quality control metrics compared to MPRAGE.

U-Net Model for Brain Extraction: Trained on Humans for Transfer to Non-human Primates

The paper develops a transfer-learning U-Net model for brain extraction in non-human primates using human data, achieving better performance than traditional methods and popular MRI packages.

Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis

This study uses machine learning to analyze 608 participants and identifies two factors improving neurofeedback performance: pre-training no-feedback runs and training patients over healthy participants.

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

This study investigates whether pre-training brain activity can predict success in real-time fMRI neurofeedback learning across 24 studies and 401 participants, finding a weak correlation but no consistent predictors.

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging

The paper predicts future cognitive decline using non-brain and multimodal brain imaging data in healthy and pathological aging, finding that non-brain data and structural MRI improve predictions.

How does group differences in motion scrubbing affect false positives in functional connectivity studies?

The paper shows that group differences in motion scrubbing can inflate false positives in functional connectivity studies due to differences in temporal auto correlation modeling.

Evaluating fMRI-Based Estimation of Eye Gaze during Naturalistic Viewing

This paper validates a method to estimate eye gaze from fMRI during naturalistic viewing and identifies head motion as a key factor affecting its accuracy.

Relative Concentration of Brain Iron (rcFe) Derived from Standard Functional MRI.

The paper introduces a method to estimate relative brain iron concentrations using functional MRI, showing good correspondence with formal iron imaging and providing insights into brain iron and cognition across the lifespan.

Assessment of the impact of shared data on the scientific literature

The paper assesses the impact of shared data on scientific literature using a brain imaging case study, showing increased publication rates and broader scientific collaboration.

A High-Throughput Pipeline Identifies Robust Connectomes But Troublesome Variability

The paper develops a pipeline to estimate connectomes from neuroimaging data, showing high consistency within individuals but significant variability across studies and sites.

Delineating the macroscale areal organization of the macaque cortex in vivo

This study establishes data and scanning conditions for reproducible, stable, and internally valid areal parcellations in non-human primates using fMRI.

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations

The paper introduces ATLAS, a dataset of 304 T1-weighted MRIs with manual lesion segmentations to improve lesion segmentation algorithm accuracy.

Data-driven Assessment of Structural Image Quality

The paper develops an automated method to assess structural brain image quality using Euler number and validates its effectiveness in identifying low-quality images and its relationship with cortical thickness and age-related associations.

An open resource for transdiagnostic research in pediatric mental health and learning disorders

The paper introduces the Healthy Brain Network (HBN) biobank, a large-scale multimodal dataset for pediatric mental health and learning disorders research, with initial data release.

Individual differences in functional connectivity during naturalistic viewing conditions

This paper compares functional connectivity variability during movies and rest, finding movies enhance individual differences detection.

Clinically Useful Brain Imaging for Neuropsychiatry: How Can We Get There?

This paper discusses the potential of brain imaging in neuropsychiatry, highlighting advances that could lead to objective imaging-based markers for clinical use.

BIDS Apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

This paper introduces BIDS Apps, a framework for creating portable neuroimaging analysis tools compatible with BIDS data, improving reproducibility and ease of use.

The Healthy Brain Network Serial Scanning Initiative: A resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions.

The paper provides a resource to evaluate test-retest reliability of functional connectivity across different scan conditions and sessions in a healthy brain network.

Predicting brain-age from multimodal imaging data captures cognitive impairment

This study predicts brain-age from multimodal imaging data and finds it captures cognitive impairment with robustness to motion and generalizability across datasets.

The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository.

The paper describes a repository of fMRI data assessing inter-individual differences in default mode network activity and reports technical validation of the dataset.

Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI

The paper optimizes implementations of voxel-wise degree centrality and local functional connectivity density in AFNI for faster brain connectivity analysis.

The Preprocessed Connectomes Project Repository of Manually Corrected Skull-stripped T1-weighted Anatomical MRI Data.

The paper provides manually corrected skull-stripped T1-weighted MRI data for 125 scans, serving as a reference for improving preprocessing and evaluating skull-stripping algorithms.

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

This paper reviews the scientific potential of real-time fMRI neurofeedback as a therapeutic tool for brain disorders and outlines strategies to optimize its development and application.