Reverse-engineering? System whose mechanisms are obscured

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Baldwin Strickland
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2 Outline Motivation The Whole Brain Catalog INCF Digital Atlasing Infrastructure API Use case of multi-scale data integration: Ghosh et al Open object models for neuroscience Contributions

3 Reverse-engineering? System whose mechanisms are obscured

4 What is reverse-engineering? Individual components and an explanation of how they fit together System whose mechanisms are obscured

5 What is reverse-engineering? Provide a framework of parts ready to be snapped together

6 Putting the parts back together

7 A multi-scale data problem Whole brain data (20 um microscopic MRI) Mosiac LM images (1 GB+) Conventional LM images Scale Individual cell morphologies EM volumes & reconstructions Solved molecular structures

8 A multi-scale synthesis problem

9 A multi-scale synthesis problem From: Solari, S., A unified anatomical theory and computational model of cognitive information processing in the mammalian brain and the introduction of DNA reco codes, Ph.D Dissertation, Engineering Sciences, UCSD, 2009

cognitive information processing in the mammalian brain and

10 A multi-scale synthesis problem Shepherd GM, The Synaptic Organization of the Brain, 4 th Edition, 2004.

11 Confocal image stacks Masako Terada, Eric Bushong, Fred Gage, Mark Ellisman Amira

12 A multi-scale synthesis problem

13 The Whole Brain Catalog Drew Berry Maya

14 Allen mouse atlas brain regions

15 Allen mouse atlas brain regions

16 Opening the Mouse Brain Regions 1. Took binary geometry files from Allen Brain Explorer 2. Received contribution of C code from Allen Institute that read the binary format 3. Rewrote C code in Java 4. Converted brain regions into.obj files 5. Could import.obj files into other Open Source tools

Received contribution of C code from Allen Institute that read the binary

18 3D Atlas Surfaces: HW Dong, Allen Institute for Brain Science Dentate Gyrus Network: Aimone et al, Neuron 2009, Gage Lab CA3 Neuron: Carnevale NT et al., J. Neurosci, 1997 CA3 dendritic branch & granule cell axon terminals: Scott Wilke & Anirvan Ghosh (unpublished) Data sharing across scales

19 Whole Brain Catalog integrated with image registration workflow

20 Whole Brain Catalog integrated with image registration workflow Images served by MapServer (Geospatial image server) Client-server system allows for distributed access Very large size images (multi GB) can be viewed Preserves atlas coordinates

server) Client-server system allows for distributed access

21 Integration of a Neuron Simulation Animation

22 Network simulations can be incorporated Maex, R and De Schutter, E. Synchronization of Golgi and Granule Cell Firing in a Detailed Network Model of the Cerebellar Granule Cell Layer J Neurophysiol, Nov 1998; 80: NeuroLex id in next NeuroML 2.0!

23 Aimone et al 2009, Gage lab simulation

24 Technologies Maven2 Restlet HyperJAXB3 JMonkeyEngine Vaadin

25 Whole Brain Catalog Client Architecture overview Wbc-client-interface Wbc-core Wbc-tangible Wbc-view-3d Wbc-io Wbc-io Wbc-client Wbc-view Wbc-listeners The internet Wbc-server

26 Modular design allows two different client views to operate on a shared codebase Wbcview-3d Wbc-io Wbc-client-interface Wbc-view (Swing & Webstart) Wbc-io Wbccore Wbctangible Wbc-client View OR Wbc-listeners Jme-Vaadin-Applet Wbc-web-view (Vaadin) Wbcview-3d Wbc-io

27 User positions orange probe tool within the 3D environment on the pattern of expression of interest CCDB Protein Expression image within the Whole Brain Catalog Right clicking probe brings up Allen Gene Expression search in web browser

28 INCF Digital Atlasing Infrastructure: Purpose To develop scientific and technical foundations and development principles and prototypes for a distributed system of neuroscience resources that can be published, shared and integrated based on spatial characteristics of their content.

29 INCF Digital Atlasing Infrastructure

30 INCF Digital Atlasing Infrastructure: Vs. Allen API DAI: General, standards-based (OGC/WPS) web services to access spatial neuroscience across heterogeneous sources such as Allen Brain Atlas (ABA) Edinburgh Mouse Atlas Project (EMAP) University of California, San Diego, Cell- Centered Database (UCSD CCDB) Waxholm (WHS) Allen API: The means by which the DAI ABA hub accesses ABA data

31 An XML format for.sva Schema: /trunk/src/main/resources/sparsevaluevolume.xsd <SparseValueVolume> <Comment>... free-form metadata...</comment> <MaxDimension x="40" y="2" z="1"/> <SparseVolumeData> <Datum x="39" y="2" z="1" value=" e-06"/> <Datum x="40" y="2" z="1" value=" e-06"/>... </SparseVolumeData> </SparseValueVolume>

32 Rendering XML-based.SVA

33 Multi-scale data integration use case

34 Manipulating content

35 Interaction with multiple data sets simultaneously

36 Multiple neurons

37 Convert traced neuron into machine processable structure for analysis

38 Behind the scenes we are converting Neurolucida -> MorphML -> JUNG forest representation

39 Using reference brain, we bring different cells into near alignment

40 End point distance analysis

41 End point distance analysis

42 End point distance analysis

43 Open Object Models for Neuroinformatics NeuroML Network model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

44 Open Object Models for Neuroinformatics NeuroML Network model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

45 Open Object Models for Neuroinformatics NeuroML Network model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

46 Open Object Models for Neuroinformatics NeuroML Network model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

47 Multi-modal data overlap within a common atlas space (Waxholm) NineML / NeuroML model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

48 Tangibles NineML / NeuroML model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

49 Data Wrappers NineML / NeuroML model Polygonal mesh segmentations Image Stacks Volumetric data sets (NIFTI, CFF) CARMEN NDTF Electrophys time series

50 A common data wrapper envelope description allows different kinds of content to be mapped into the same space Tangible Data Wrapper Data Content

51 Precise naming should occur optionally at both the data wrapper level and at the tangible level Names / metadata about the context of the use of the data Names / metadata about the data files themselves Tangible Data Wrapper Data Content

52 Building a Python layer on top of Whole Brain Catalog Python scripts Java to Python glue Java libraries Wbc-io Python layer Jython layer Wbccore Wbc-clientinterface Wbctangible Wbc-client Volume Server Cellular Knowledge Base Servers NIF / NeuroLex The internet Cell Centered Database Simulation Server Main Server 2D Image Server

53 Hook different systems together via the python layer PyNN Python layer WBC Python layer DAI Python layer simulation visualization & interaction atlasing

54 Contributions Described a motivation for integrating data of the nervous system into digital forms Described building an open source google earth for the brain framework on top of Allen Institute data and APIs Described work of the INCF to create a common API across multiple sources Gave an example use case of data integration Described ongoing work to build common python APIs on top of existing open source libraries

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