neutube 1.0: a New Design for Efficient Neuron Reconstruction Software Based on the SWC Format123

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1 Research Article: Methods/New Tools Novel Tools and Methods neutube 1.0: a New Design for Efficient Neuron Reconstruction Software Based on the SWC Format123 neutube: Efficient Neuron Reconstruction Software Linqing Feng 1,*, Ting Zhao 2,* and Jinhyun Kim 1,3 1 Center for Functional Connectomics, Korea Institute of Science and Technology (KIST), Seoul, , Korea 2 Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, 20147, United States 3 Neuroscience Program, University of Science and Technology, Daejeon, , Korea DOI: /ENEURO Received: 30 October 2014 Revised: 23 December 2014 Accepted: 23 December 2014 Published: 2 January 2015 Author Contributions: L.F., T.Z., and J.K. designed research; L.F. and T.Z. performed research; L.F. and T.Z. analyzed data; L.F., T.Z., and J.K. wrote the paper. Funding: KIST Institutional Program Project No. 2E24210 Funding: WCI Program NRF Grant Number: WCI Funding: Howard Hughes Medical Institute Conflict of Interest: Authors report no conflict of interest. This work was supported by the KIST Institutional Program (Project No. 2E24210) and WCI Program (NRF Grant Number: WCI ). Ting Zhao is supported by Howard Hughes Medical Institute. Correspondence should be addressed to: Dr. Ting Zhao, Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, United States (zhaot@janelia.hhmi.org).) and Dr. Jinhyun Kim, Center for Functional Connectomics, Korea Institute of Science and Technology (KIST), 39-1 Hawolgokdong, Seoul, , Korea (kimj@kist.re.kr).) Cite as: eneuro 2015; /ENEURO Alerts: Sign up at eneuro.sfn.org to receive customized alerts when the fully formatted version of this article is published. Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreading process. This article is distributed under the terms of the Creative Commons Attribution License ( creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. Copyright 2015 Society for Neuroscience

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3 Manuscript Title Page 1. Manuscript Title (50 word maximum) 2. Abbreviated Title (50 character maximum) 3. List all Author Names and Affiliations in order as they would appear in the published article 4. Author Contributions: Each author must be identified with at least one of the following: Designed research, Performed research, Contributed unpublished reagents/ analytic tools, Analyzed data, Wrote the paper. Correspondence should be addressed to (include address) 6. Number of Figures: 6

4 7. Number of Tables: 1 8. Number of Multimedia: 0 9. Number of words for Abstract: Number of words for SignificanceStatement: Number of words for Introduction: Number of words for Discussion: Acknowledgements 14. Conflict of InterestA. No (State Authors report no conflict of interest ) B. Yes (Please explain) 15. Funding sources

5 Abstract Significance Statement

6 1. Introduction

7 2. Materials and Methods 2.1 The SWC framework i.e.

8 2.1.1 Abstract Definition of The SWC Model i.e SWC Operation

9 parentchild sibling geometrical operation structural operation

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11 2.1.3 User Interaction

12 2.1.4 Create SWC Nodes from Image Signal

13 2.2. Software Implementation Architecture D Visualization

14 D Visualization Image Analysis

15 2.2.5 Neuron Structure Manipulation Interpolate Set branch point

16 Reset branch point Connect multiple nodes Remove turn Resolve crossover

17 2.2.6 Implementation

18 3. Results

19 T d

20 T d T d T d Software Undo/Redo 2D 3D 3D Image 2D Neuron 3D Visualization Editing Editing Interaction Visualization neutube 1.0 Neuromantic Neurostudio 4. Application Example

21 5. Discussion

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23 References

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25 Legends Tables Figures

26 Figure 4 Examples of high-level operations of neutube 1.0. To illustrate the operation, we visualize the nodes of a neuron in different colors according to the topology: blue for root nodes, green for branch nodes, yellow for leaf nodes and red for other nodes. Selected nodes are highlighted by a yellow bounding box. For the corresponding operation as named in each row, the figure on the left (A), (C), (E), (G), (I) or (K) shows the selected nodes to operate and the one on the right (B), (D), (F), (H), (J) or (L) shows the result of operation.

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