1. Atlas Interoperablity I & II: progress to date, requirements gathering Session I: 8:30 – 10am Session II: 10:15 – 12pm

2. Panel discussion What is atlas interoperability in your domain? What are interoperability challenges and priorities? How can tools and approaches from other testbeds be re-used? What additional questions would you like to formulate once data and services from other testbeds become available? What immediate steps would lead towards BIRN mashups? Now that we have MBAT, Slicer, Query Atlas, DTI & LDDMM – what is next?

3. What is an atlas Multiple meanings of atlases: –as query framework –as analysis framework –as spatial/semantic data registration framework –as dataset on which the framework is built Human: atlas is a set of priors and less as a canonical atlas Mouse: atlas as a canonical digital map and a common framework for different data types

4. What is Interoperability atlas1atlas2 client registry, middleware data MBAT ABA SA NT Commons Tal/Fox Devel Other… MRI FMRI Nissl MBATABASANTCommonsTal/Fox Devel Other… X X X X X X X X

5. Human and Rodent Atlasing: what is in common, what is different Significant overlap in needs and functionality: Handling large images, using specialized grid tools Creating, registering, managing and querying 3D reconstructions Use of shared vocabularies/ontologies Image and 3D annotation

6. Human and Rodent Atlasing: what is in common, what is different Differences: Data types: focus on 3D vs a mixture of 2D and 3D –Also: Histopathology, Time series (anatomical and physiological), Behavior/Clinical, Connectivity (wiring/microwiring) Upload and registration: Regular process of image acquisition and registration, vs multiple acquisition methods, metadata conventions and resolutions, multi- scale --> multiple atlas tools Regulatory: de-identification Analytically-driven vs data registration/fetching-driven Canonical atlases vs individual atlases Different coordinate systems and location exchange needs

7. How to build the bridges Ontologies: –Neuronames, UMLS, BIRNLex, BONFIRE… –Ontology alignments (a high priority action item) –Standard ontology formats and shared ontology tools (BIRNLex) Spatial framework: –Absolute coordinates: Stereotaxic, Talairach –Coordinate translation services (?? - works within species) –Other types of location description (relative, ontology-based, expression-based) Standard formats and APIs: –To access spatial data (common image formats and label hierarchies) –To query registries (metadata, ontologies (OWL/RDF), spatial, cross- walks), XCEDE –To exchange viewpoint and state across atlases –To perform analysis: Engage automatic segmentation tools (cells and tissues) and morphometric analysis tools (incl. cell counting and volumetric analysis) –To allow conceptual interoperability (across concepts used in different species)

8. The use case The big questions: Do the observed relationships hold across species (development phases, etc.)? What is the spatial pattern of relationships? Use case: studying APOE-4 and co-located genes distribution in human and mouse –FMRI study of 40 individuals looked at variation on APOE-4 (AD factor), found strong positive correlation between functional brain activation in memory tasks with the presence of APOE-4in hippocampus –There are other areas (control regions) where the extent of activation was not related to the gene variation (e.g. occipital cortex) –Query mouse atlases (ABA’s NeuroBlast, GeneNetwork) to find distribution of APOE-4 and co-located genes in both the target and the control areas (considering there is an ontology bridge between the atlases); compare co-located gene sets in data types that MBAT can access. –Also: how to select control areas that are good controls (i.e. activation unrelated to the gene) and can be found in both species