Towards an Enhanced Automatic
Point-to-Point Comparison of
3D Neuron Reconstructions
Yinan Wan
Advisor: Hanchuan Peng
JUS Opening Symposium 2011/6/24
Digital Neuronal Morphologies
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[neuromorpho.org]
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Neuronal morphologies
are reconstructed
manually or automatically.
Although time-consuming
and technically
challenging, they are
extremely versatile and of
considerable scientific
utility.
An increasing number of
3D reconstructions are
being freely shared.
JUS Opening Symposium
2011/6/24
Neuron Mapping -Similarity Quantification
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We need to quantify the similarity between two
neurons/neuron sets.
Shape similarity is a widely-studied problem in the
field of pattern recognition.
Neuron source already known?
?
[neuromorpho.org; Peng et al., 2011]
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JUS Opening Symposium
2011/6/24
Difference Detection
Effects of β-catenin on
dendritic morphology
Developmental changes in spinal
motoneuron dendrites in mice
[Krichmar, 2006; Li, 2005;]
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2011/6/24
Previous Reseach: L-measure
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A software tool for
quantitative
characterization on
neuronal morphology
Based on extraction
of morphological
metrics
Statistically
comparison between
the feature
distribution two
groups of cells
[Scorcioni et al., 2008]
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JUS Opening Symposium
2011/6/24
Objects
What we are looking for is way to…
 Quantify the (dis)similarity of 3D neuron
reconstructions systematically.
 Pinpoint the loci of their differences.
 Take full advantage of the known information.
Thus, towards a final goal of neuron comparison….
Our method should base on 3D structures, rather
than morphological features.
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JUS Opening Symposium
2011/6/24
Our Current Pepline
Input Neurons
Refine Matching
Extract Neuron Nodes
Initial Matching
[by Peng & Qu, unpublished]
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JUS Opening Symposium
2011/6/24
Current Algorithm:
Refine Matching
Initial Matching
1.
2.
Geodesic distance based
neuron normalization;
3.
Compute and compare
shape context;
4.
5.
6.
2.
Refine matching is based on
the result of initial matching;
The local distance and
direction consistence of
matched pairs are maximized
in a iterative way;
arg max( Econs )
Dual direction vote for best
several candidates;
where :
Econs 
1
Edis ( Pi , Pj )  Edir ( Pi , Pj )


Pi 1 &
Pj  2
Pick the top voted
candidate as initial match;
Kill all multi-matched pairs;
[by Peng & Qu, unpublished]
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1.
Compute the Geodesic
distance between every
possible pair of point set;

Pi  Pj
1  Pi  Pj
Edis ( Pi , Pj )  

2   Pi  Pm
Pj  Pn

 mN p
n

N
pj
i

Edir ( Pi , Pj ) 
1 
1
Pi  Pj 
2
N pi

JUS Opening Symposium
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 Pm  Pi  Pj 
mN pi
2011/6/24
1
N pj


P

n

nN p j

The current algorithm is not perfect…
It did not take topology into account
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
Develop a topology-dependent comparison algorithm
It only allows comparisons between two neuron
reconstructions
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Find a way to realize multiple morphological comparison
Optimization method remains to be improved
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Try more robust optimization method
JUS Opening Symposium
2011/6/24
Method Design
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For a topology-dependent method
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Multiple Morphological Comparison
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Branch-point segmentation
Consider the multiple sequence alignment algorithm: to
compute the similarity between two groups of
morphologies.
Numerical optimization
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Gaussian embedding & PDE
JUS Opening Symposium
2011/6/24
Acknowledgement
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Hanchuan Peng
Hang Xiao and other members in Peng Lab
Questions and…
How would you judge the similarity between neurons?
We do need suggestions from neuro-biologists!
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JUS Opening Symposium
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Reference
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Duque, A. et al. Morphological characterization of electrophysiologically
identified basal forebrain neurons: cholinergic vs. neuropeptide Y-containing
neurons. Brain Struct. Funct. 1, 55–73 (2007).
Krichmar, et al. Effects of b-catenin on dendritic morphology and simulated
firing patterns in cultured hippocampal neurons. Biol. Bull. 211, 31–43 (2006).
Li, Y., et al Developmental changes in spinal motoneuron dendrites in
neonatal mice. J. Comp. Neurol. 483, 304–317 (2005).
Peng H., et al. V3D enables real-time 3D visualization and quantitative
analysis of large-scale biological image data sets. Nature Biotechnology, 28,
348-353 (2010).
Peng H. et al. BrainAligner: 3D registration atlases of Drosophila brains.
Nature Methods, 8,493-399 (2011).
Scorcioni L-Measure: a web-accessible tool for the analysis, comparison and
search of digital reconstructions of neuronal morphologies. Nature Protocols,
3, 866-876(2008).
http://neuromorpho.org
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