Katrin Amunts

This paper introduces a workflow combining 3D-PLI, immunohistochemistry, and Nissl staining to map fiber architecture and cell types in brain sections with high resolution and reduced inter-subject variability.

The paper introduces siibra, a software tool suite that integrates diverse brain data into a Multilevel Human Brain Atlas, enabling interoperable analysis and visualization.

This paper creates a 3D histological atlas of nigrosomes in the substantia nigra aligned to MNI152 space, enabling MRI analysis of these structures in Parkinson's disease.

The paper examines how structural brain features relate to functional activity across individuals and brain regions, finding distinct mechanisms for intra- and inter-individual variability in alpha power.

The paper develops a harmonized segmentation protocol for hippocampal subfields in MRI, improving cross-study comparisons and understanding of subfield structure and function.

This paper introduces ComSLI, a method to map fiber networks in histology without sample preparation, showing its application across tissues and diseases.

This paper maps global cortical organization by integrating microstructural, connectivity, and functional data with cytoarchitectural maps, revealing a sensory-fugal gradient and functional diversity across brain areas.

This paper compares cytoarchitectonic delineations of medial temporal lobe subregions by four neuroanatomists, finding higher agreement in some areas and less in others.

HippoMaps provides a toolbox and data warehouse for mapping and analyzing hippocampal data across multiple modalities and scales.

This paper introduces a surface-based hippocampal registration method that improves subfield alignment across different morphologies.

The paper identifies 35 prefrontal areas in macaques, reveals regional receptor differences, and shows functional connectivity patterns across clusters of frontal lobe areas.

This study characterizes the anatomy of the human default mode network using histology and neuroimaging, revealing its cytoarchitectural diversity and unique signal flow properties.

This paper introduces a data-driven method to infer neural mass models and parameters from brain data, showing it can recover original parameters and produce realistic dynamics in synthetic and resting-state fMRI data.

BigBrainWarp simplifies integration of BigBrain histology with neuroimaging by providing tools for registration and cytoarchitectural feature access.

The paper investigates genetic factors influencing a neurobiological substrate for psychiatric disorders and finds that a common genetic variant is associated with the substrate but not directly with disease risk.

The paper identifies a natural axis of transmitter receptor distribution in the human cerebral cortex that reflects laminar differentiation and functional organization.

The paper improves a probabilistic cytoarchitectonic atlas of auditory cortex by introducing CBA+, a method that aligns individual brains more accurately than existing methods.

The paper introduces MAGIC, a label-free fluorescence method for 3D high-resolution reconstruction of myelinated fibers in large volumes, demonstrating its application on multiple species brain samples.

The paper presents a 3D laminar atlas of the human cerebral cortex using a convolutional neural network and uses it to analyze thickness gradients in sensory and motor cortices.