PMID- 18797828
OWN - NLM
STAT- MEDLINE
DCOM- 20090219
LR  - 20211020
IS  - 1559-0089 (Electronic)
IS  - 1539-2791 (Linking)
VI  - 6
IP  - 4
DP  - 2008 Winter
TI  - Non-parametric algorithmic generation of neuronal morphologies.
PG  - 257-77
LID - 10.1007/s12021-008-9026-x [doi]
AB  - Generation algorithms allow for the generation of Virtual Neurons (VNs) from a 
      small set of morphological properties. The set describes the morphological 
      properties of real neurons in terms of statistical descriptors such as the number 
      of branches and segment lengths (among others). The majority of reconstruction 
      algorithms use the observed properties to estimate the parameters of a priori 
      fixed probability distributions in order to construct statistical descriptors 
      that fit well with the observed data. In this article, we present a 
      non-parametric generation algorithm based on kernel density estimators (KDEs). 
      The new algorithm is called KDE-NEURON: and has three advantages over parametric 
      reconstruction algorithms: (1) no a priori specifications about the distributions 
      underlying the real data, (2) peculiarities in the biological data will be 
      reflected in the VNs, and (3) ability to reconstruct different cell types. We 
      experimentally generated motor neurons and granule cells, and statistically 
      validated the obtained results. Moreover, we assessed the quality of the 
      prototype data set and observed that our generated neurons are as good as the 
      prototype data in terms of the used statistical descriptors. The opportunities 
      and limitations of data-driven algorithmic reconstruction of neurons are 
      discussed.
FAU - Torben-Nielsen, Benjamin
AU  - Torben-Nielsen B
AD  - TENU, Okinawa Institute of Science and Technology, Okinawa, Japan. 
      nielsen@oist.jp
FAU - Vanderlooy, Stijn
AU  - Vanderlooy S
FAU - Postma, Eric O
AU  - Postma EO
LA  - eng
PT  - Journal Article
PT  - Validation Study
DEP - 20080917
PL  - United States
TA  - Neuroinformatics
JT  - Neuroinformatics
JID - 101142069
SB  - IM
MH  - *Algorithms
MH  - Animals
MH  - Cell Polarity/physiology
MH  - Cell Shape/*physiology
MH  - Computational Biology/*methods
MH  - Computer Simulation
MH  - Data Interpretation, Statistical
MH  - Dendrites/physiology/ultrastructure
MH  - Hippocampus/cytology/physiology
MH  - Interneurons/cytology/physiology
MH  - Models, Statistical
MH  - Motor Neurons/cytology/physiology
MH  - Neuroanatomy/*methods
MH  - Neurons/*cytology/physiology
MH  - Rats
MH  - Reproducibility of Results
MH  - *Software
MH  - Spinal Cord/cytology/physiology
EDAT- 2008/09/18 09:00
MHDA- 2009/02/20 09:00
CRDT- 2008/09/18 09:00
PHST- 2008/03/31 00:00 [received]
PHST- 2008/08/26 00:00 [accepted]
PHST- 2008/09/18 09:00 [pubmed]
PHST- 2009/02/20 09:00 [medline]
PHST- 2008/09/18 09:00 [entrez]
AID - 10.1007/s12021-008-9026-x [doi]
PST - ppublish
SO  - Neuroinformatics. 2008 Winter;6(4):257-77. doi: 10.1007/s12021-008-9026-x. Epub 
      2008 Sep 17.