Neuroinformatics: sharing, organizing and
accessing data and models
Arnd Roth
Wolfson Institute for Biomedical Research
University College London
The optogenetics revolution
Fuhrmann et al., 2015
The optogenetics revolution
Fuhrmann et al., 2015
The connectomics revolution
Helmstaedter et al., 2013
The connectomics revolution
Helmstaedter et al., 2013
Connectomics data mining
Jonas & Körding, 2015
Connectomics data mining
Jonas & Körding, 2015
Deep artificial neural networks
Mnih et al., 2015
Neuroinformatics: sharing, organizing
and accessing experimental data
Allen Institute http://alleninstitute.org
Janelia Research Campus https://www.janelia.org/
Open Connectome Project http://www.openconnectomeproject.org/
Cell Image Library http://www.cellimagelibrary.org/
Human Brain Project http://www.humanbrainproject.eu/
INCF http://www.incf.org/
Single neuron and network simulators
NEURON http://www.neuron.yale.edu/neuron/
GENESIS https://www.genesis-sim.org/
MOOSE http://moose.ncbs.res.in/
PSICS http://www.psics.org/
NEST http://www.nest-initiative.org/
Meta-simulators: simulator-
independent model description
PyNN http://neuralensemble.org/PyNN/
neuroConstruct http://www.neuroconstruct.org/
NeuroML http://www.neuroml.org/
NineML http://software.incf.org/software/nineml
12http://www.opensourcebrain.org
neuroConstruct
13http://www.opensourcebrain.org
neuroConstruct
Software tool (written in Java) developed in Angus Silver’s Laboratory of Synaptic Transmission and Information Processing
Facilitates development of 3D network models of biologically realistic cells through graphical interface
Allows anatomical positioning of cells and complex connectivity of axons/dendrites
Automatically generates scripts for running simulations in NEURON/GENESIS/MOOSE/PSICS/PyNN & more
Support for import, export & conversion of NeuroML
14http://www.opensourcebrain.org
neuroConstruct – latest developments
neuroConstruct can generate code for Parallel NEURON
- Most widespread platform for large scale detailed neuronal simulations
- Near linear speedup of simulations up to hundreds of cores
Python scripting interface
- Python becoming language of choice for neuroinformatics applications
- Gives access to all functionality “behind the GUI”
Open Source Brain
- Platform for sharing & collaboratively developing models in computational neuroscience
- Many neuroConstruct projects from multiple brain regions available
3D version of Traub et al 2005
Thalamocortical column model
Parallel simulation durations
scale approx. linearly up to 200 processors & 10,000
cells
Example using Python interface & Parallel NEURON
16http://www.opensourcebrain.org
Wider interoperability framework
Towards multiscale simulation:
from molecules to circuits
MCell http://www.mcell.org/
CellBlender http://www.mcell.org/
STEPS http://steps.sourceforge.net/
TrakEM2 http://fiji.sc/TrakEM2
TREES toolbox http://www.treestoolbox.org/
Public databases of neural models
ModelDB https://senselab.med.yale.edu/ModelDB/
NeuroMorpho.org http://neuromorpho.org/
BigNeuron http://alleninstitute.org/bigneuron
OpenSourceBrain http://www.opensourcebrain.org/
Human Brain Project http://www.humanbrainproject.eu/
19http://www.opensourcebrain.org
How to make computational neuroscience a more accepted scientific approach?
Reproducibility: easy to rerun and validate simulation result reported in a scientific paper.
Accessibility: available to theoretical and experimental neuroscientists in an understandable format
Portability: cross-simulator validation and exchange of models and components enabling reuse
Transparency: exposure of internal properties and automated validation
20http://www.opensourcebrain.org
Neuroinformatics infrastructure
NeuroMLA simulator-independent language for describing and exchanging
detailed neuronal and network models
LEMS Compact and flexible model description language that underlies
NeuroML 2
The Open Source Brain InitiativeAccessible repository of standardized models and infrastructure
for collaborative, open source model development
21
The Open Source Brain repository
22
Current model development life-cycle
23http://www.opensourcebrain.org
Current model development life-cycle
24http://www.opensourcebrain.org
OSB collaborative development scenario
OSB iterative development through critical evaluation
Validate
Experiment
Model
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http://www.opensourcebrain.org
A Whole Community Approach
• Must bring experimental and theoretical & computational neuroscience closer.
• While the latter seek minimal models, the former want hard earned experimental facts not to be ignored.
• As the functional principles of neuronal networks in the brain remain elusive, and the interactions are often highly non-linear, ignoring biological facts without thought to errors can easily result in misleading conclusions, and erroneous theories of brain function.
• Adhoc simplification is a matter of taste
Level of detail: A rift in neuroscience
1. Simplify the details– minimal model for hypothesis-driven science– Adhoc simplification– Minimal for which question?
vs2. Consider all known
– data-driven is data-ready– Hypothesis-free integration of facts– Algorithms fill in gaps from sparse data– Fewer free parameters!– Avoid wasting time hand tuning parameters for a
given model “island”
“We find that the major obstacle that hinders our understanding the brain is the fragmentation of brain research and the data it produces.
Our most urgent need is thus a concerted international effort that can integrate this data in a unified picture of the brain as a single multi-level system...”
The HBP-PS Consortium 2012:8
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