Peer Herholz

Predicting functional topography of the human visual cortex from cortical anatomy at scale

This paper introduces a deep learning tool to predict functional topography of the human visual cortex from anatomy, demonstrating its utility across diverse conditions and large-scale datasets.

fMRIflows: a consortium of fully automatic univariate and multivariate fMRI processing pipelines

This paper introduces fMRIflows, a fully automatic fMRI processing pipeline that provides standardized preprocessing and both univariate and multivariate analyses.

An open MRI dataset for multiscale neuroscience

The paper shares a multimodal MRI dataset for studying multiscale brain organization, including connectomes and gradients from multiple imaging modalities.

Micapipe: a pipeline for multimodal neuroimaging and connectome analysis

Micapipe is an open pipeline for processing multimodal MRI data, generating structural and functional connectomes, geodesic distances, and microstructural profiles across multiple brain parcellations and surface spaces.

Neuroscout, a unified platform for generalizable and reproducible fMRI research

Neuroscout provides an automated platform for analyzing naturalistic fMRI data, enabling reproducible and generalizable research through machine learning and open tools.

BrainStat: A toolbox for brain-wide statistics and neuroscientific contextualization

BrainStat provides a toolbox for statistical analysis and feature association in neuroimaging data, integrating multiple modalities and templates to enhance cross-modal research.

Variability in the analysis of a single neuroimaging dataset by many teams

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.

LAB-QA2GO: A free, easy-to-use toolbox for the quality assessment of magnetic resonance imaging data

LAB-QA2GO is a virtual machine that automates MRI data quality assessment with minimal setup and technical knowledge.