Krzysztof J. Gorgolewski

TemplateFlow provides a FAIR framework for sharing and managing multi-scale, multi-species brain models to improve reproducibility in neuroimaging.

The paper introduces PET-BIDS, an extension of the BIDS standard for PET data, and provides curated datasets and tools for its use.

OpenNeuro is an open archive for sharing brain imaging data following FAIR principles, hosting over 600 datasets from 20,000 participants across species and modalities, with over 150 publications citing its data.

This paper introduces fMRIPrep, a tool for preprocessing task-based fMRI data, and demonstrates its integration into a workflow for statistical analysis.

The paper shows that different analysis workflows by 70 teams on the same fMRI dataset led to varied results, but meta-analysis found consensus in activated regions.

The paper introduces a dataset linking brain functional architecture to cognitive states and personality traits through multimodal MRI and phenotypic assessments.

fMRIPrep, a BIDS-driven, self-adapting fMRI preprocessing pipeline, earned above-acceptable expert quality ratings on 50 of 54 OpenfMRI datasets and introduced less smoothing than FSL feat.

This study compares spaced versus massed reward learning in humans, finding that spaced learning leads to better long-term memory of value associations.

MEG-BIDS extends the BIDS standard to organize MEG data, enabling efficient storage, sharing, and integration with MRI data.

The paper introduces MRIQC Web-API, a resource for training automatic quality classifiers by crowdsourcing image quality metrics and expert ratings from MRI scans.

MRIQC is a tool for predicting MRI image quality that generalizes across sites with 76% accuracy but struggles with site-specific artifacts.

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

This paper introduces NIDM-Results, a standardized format for sharing neuroimaging statistical results, enabling reproducibility and meta-analysis.

The paper develops a tool to link neurogenetic and neuroimaging data by analyzing spatial gene expression patterns and psychological topics, identifying known and novel gene/cognition associations.