"HippoMaps" simplifies hippocampus research

Hippomaps Simplifies Hippocampus Research Image
Surface folding and density are matched to a given sample shape and resolution. Mapping to a standardized unfolded space enables registration and interpolation across scales and data formats, which can then be followed by averaging within a modality, comparison between modalities by spatial correlation, or comparison to anterior–posterior and subfield-related axes of hippocampal organization. Copyright: DeKraker, J. et al. HippoMaps: multiscale cartography of human hippocampal organization. https://doi.org/10.1038/s41592-025-02783-3

Despite the important role of the hippocampus in many cognitive processes of the human brain, there has so far been no unified system to record, jointly present, and analyze the structure and function of this region using different measurement methods.

For this reason, an international team of scientists has developed "HippoMaps" within the framework of the German-Canadian HIBALL project (Helmholtz International BigBrain Analytics and Learning Laboratory): a freely accessible software toolbox including an online database, specifically for deep learning-based integration of image data from various sources and resolutions, as well as for the analysis and mapping of the hippocampus. The aim is to better understand the relationships between its structure and function in both healthy and diseased brains. In a recent study published in Nature Methods, they present "HippoMaps".

The hippocampus is the region of the brain responsible for memory formation and learning processes, the transition between short-term and long-term memory, spatial orientation, and emotional processing. It has a complex multi-layered structure with different cell types and is closely interconnected with various brain regions. Damage to the hippocampus can impair memory in different ways. Early changes in the hippocampus are already detectable in dementia. However, its complicated architecture—especially its complex internal and external connections, i.e., functional neural networks—makes its research challenging.

Data Collection and Software Tool

With "HippoMaps," researchers from Canada, the USA, Switzerland, and Germany developed a software toolbox to uniformly merge data from different investigation methods and make them usable for further research. From the Jülich Institute of Neuroscience and Medicine (INM-1) came histological data and data obtained from 3D-PLI (3D Polarized Light Imaging) examinations. Other data originate from various magnetic resonance imaging studies as well as intracranial electroencephalography of patients with epilepsy. "HippoMaps" enables comparison of hippocampal features recorded by different methods—particularly to align imaging data from the living brain with data from tissue samples.

Furthermore, the relationships between hippocampal structure and function can be explored, for example by relating results from functional imaging or direct brain measurements to spatial patterns from anatomical data. "HippoMaps" also allows detection of abnormalities in patients with diseases and evaluation against known structural principles of the hippocampus. Finally, understanding of hippocampal connectivity and functionality is enhanced by more precise mapping of connections and microstructures, leading to improved knowledge of its functions.

Application Perspective

"HippoMaps" is freely accessible and developed according to the latest standards to ensure easy use and broad dissemination in basic and clinical neuroscience. Due to the special significance of the hippocampus for neuroanatomy and cognitive functions, "HippoMaps" also provides important insights for the development and validation of new brain-inspired AI systems.

Original paper: DeKraker, J., Cabalo, D.G., Royer, J. et al. HippoMaps: multiscale cartography of human hippocampal organization. Nat Methods (2025). https://doi.org/10.1038/s41592-025-02783-3

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