The CARMEN Neuroinformatics Server

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The CARMEN Neuroinformatics Server Paul Watson1,
Tom Jackson2, Georgios Pitsilis1, Frank Gibson1,
Jim Austin2, Martyn Fletcher2, Bojian Liang2,
Phillip Lord1 1School of Computing Science,
Newcastle University 2Department of Computer
Science, University of York
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Research Challenge
Understanding the brain is the greatest
informatics challenge

• Enormous implications for science
• medicine
• biology
• computer science

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Collecting the Evidence

• 100,000 neuroscientists are
• generating vast amounts of data
• molecular (genomic/proteomic)
• neurophysiological (time-series electrical
  measures of activity)
• anatomical (spatial)
• behavioural

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Current Problems in Neuroinformatics

• Data is
• expensive to collect but rarely shared
• proprietary and locally described
• The result
• a shortage of analysis techniques that can be
  applied across neuronal systems
• Limited interaction between research centres with
  complementary expertise

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CARMEN

• CARMEN uses e-science to tackle the problem
• CARMEN supports the archiving, sharing,
  discovery, integration and analysis of
  neuroscience data
• EPSRC e-Science Pilot Project (2006-10)
• Builds on previous e-science projects
• DAME, Gold, myGrid, BROADEN, CISBAN...

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CARMEN focuses on Neural Activity
raw voltage signal data is collected using
single or multi-electrode array recording
neurone 1
neurone 2
neurone 3
cracking the neural code
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CARMEN A Hub Spoke Structure
Hub A CAIRN repository for the storage
and analysis of neuroscience
data Spokes Neuroscience projects that produce
data and analysis services for
the hub, and use it to address key
neuroscience questions
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CARMEN Active Information Repository Node
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A Typical CARMEN Scenario

• Data Collection from a Multi-Electrode Array
• Data Visualisation and Exploration
• Spike Detection
• Spike Sorting
• Analysis
• Visualisation of Analysis Results
• Currently, this is a
• semi-manual process
• CARMEN has automated this.

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Data Exploration with the Signal Data Explorer
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Defining the Process Workflow
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Example Workflow Enactment
External
Repository
Workflow Engine
Client
INPUT Data
Spike Sorting
TAVERNA
Service
SRB FileSystem
Available Services
Security
RDBMS
Query
Reporting
Dynamically Deployed Services in Dynasoar
Registry
OUTPUT Metadata
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Dynamic service deployment
A request to s4 cannot be satisfied by an
existing deployment of the service
R
The deployed service remains in place and can be
re-used - unlike job scheduling
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Routing to an Existing Service Deployment
A request for s2 is routed to an
existing deployment of the service
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Example Graph Output
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Example Movie Output
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e-Science Challenges Discovery Interpretation

• Support for sharing vast amounts of data
• How was this data produced?
• Which workflow produced this data?
• Is there any data of this type..?
• Are there services that process this data?

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e-Science Challenge Metadata Design

• Extensible, standardised metadata for
  neuroscience
• data formats (e.g. timing, data channels)
• experimental design (e.g. stimuli or drug
  treatments)
• concurrent data (e.g. behaviour, physiological
  measures)
• experimental idiosyncrasies (e.g. artifacts)
• experimental conditions (e.g. animals,
  temperature)

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Challenge Discovery

• How to locate patterns in time-series data across
  multiple levels of abstraction

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Challenge Controlling Sharing

• Only I am allowed to see this data
• My collaborators can look at this data
• Anyone can see this data
• The funders want the data to be openly available
  after 1 year
• The Gold Projects Security infrastructure will
  be used for this

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Challenge Reproducible e-Science

• Reproducible e-Science
• curating services as well as data
• repositories of deployable services
• dynamic service deployment

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CARMEN
CARMEN is delivering an e-Science
infrastructure that can be applied across
a range of diverse and
challenging applications (not only
neuroscience) CARMEN enables cooperation and
interdisciplinary working in
ways currently not possible CARMEN will
deliver new results in neuroscience,
computer science and medicine Demos on
North East Regional e-Science Centre,
White Rose and EPSRC stalls
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CARMEN Consortium
Newcastle Colin Ingram Paul
Watson Stuart Baker
Marcus Kaiser
Phil Lord Evelyne Sernagor
Tom Smulders
Miles Whittington York Jim Austin
Tom Jackson Stirling
Leslie Smith Plymouth Roman Borisyuk
Cambridge Stephen Eglen Warwick
Jianfeng Feng Sheffield Kevin Gurney
Paul Overton Manchester
Stefano Panzeri Leicester Rodrigio Quian
Quiroga Imperial Simon Schultz St.
Andrews Anne Smith
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CARMEN Consortium
Commercial Partners
- applications in the pharmaceutical sector
- interfacing of data acquisition software
- application of database infrastructure
- commercialisation of analysis tools