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A generative growth model for thalamocortical axonal branching in primary visual cortex

Kassraian-Fard, Pegah and Pfeiffer, Michael and Bauer, Roman (2020) A generative growth model for thalamocortical axonal branching in primary visual cortex. PLOS Computational Biology, 16 (2). Art. No. e1007315. ISSN 1553-7358. PMCID PMC7018004. https://resolver.caltech.edu/CaltechAUTHORS:20200214-082231949

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Abstract

Axonal morphology displays large variability and complexity, yet the canonical regularities of the cortex suggest that such wiring is based on the repeated initiation of a small set of genetically encoded rules. Extracting underlying developmental principles can hence shed light on what genetically encoded instructions must be available during cortical development. Within a generative model, we investigate growth rules for axonal branching patterns in cat area 17, originating from the lateral geniculate nucleus of the thalamus. This target area of synaptic connections is characterized by extensive ramifications and a high bouton density, characteristics thought to preserve the spatial resolution of receptive fields and to enable connections for the ocular dominance columns. We compare individual and global statistics, such as a newly introduced length-weighted asymmetry index and the global segment-length distribution, of generated and biological branching patterns as the benchmark for growth rules. We show that the proposed model surpasses the statistical accuracy of the Galton-Watson model, which is the most commonly employed model for biological growth processes. In contrast to the Galton-Watson model, our model can recreate the log-normal segment-length distribution of the experimental dataset and is considerably more accurate in recreating individual axonal morphologies. To provide a biophysical interpretation for statistical quantifications of the axonal branching patterns, the generative model is ported into the physically accurate simulation framework of Cx3D. In this 3D simulation environment we demonstrate how the proposed growth process can be formulated as an interactive process between genetic growth rules and chemical cues in the local environment.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1371/journal.pcbi.1007315DOIArticle
http://www.ncbi.nlm.nih.gov/pmc/articles/pmc7018004/PubMed CentralArticle
https://doi.org/10.1371/journal.pcbi.1007315.s001DOIS1 Text
https://doi.org/10.1371/journal.pcbi.1007315.s002DOIS1 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s003DOIS2 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s004DOIS3 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s005DOIS4 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s006DOIS5 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s007DOIS6 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s008DOIS7 Fig.
https://doi.org/10.1371/journal.pcbi.1007315.s009DOIS1 Table
https://doi.org/10.1371/journal.pcbi.1007315.s010DOIS2 Table
https://doi.org/10.1371/journal.pcbi.1007315.s011DOIS3 Table
https://doi.org/10.1371/journal.pcbi.1007315.s012DOIS4 Table
https://doi.org/10.1371/journal.pcbi.1007315.s013DOIS1 Data
https://doi.org/10.1101/288522DOIDiscussion Paper
ORCID:
AuthorORCID
Kassraian-Fard, Pegah0000-0002-6562-7918
Additional Information:© 2020 Kassraian-Fard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: June 9, 2018; Accepted: August 6, 2019; Published: February 13, 2020. The authors thank Rodney J. Douglas and Kevan A.C. Martin, John C. Anderson, Andreas Hauri, Tom Binzegger, Nuno DaCosta and Peter Jagers for valuable advice during all stages of the work. P.KF. was supported by the Swiss National Science Foundation (P2EZP3_181896). R.B. was supported by the Engineering and Physical Sciences Research Council of the United Kingdom (EP/S001433/1) and the Medical Research Council of the United Kingdom (MR/N015037/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data Availability: The software and the data in XML format are available at github.com/pegahka. For access to the original dataset from which the axonal data was extracted from, interested researchers are requested to apply to ICOS.Admin@newcastle.ac.uk. Author Contributions: Conceptualization: Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer. Data curation: Pegah Kassraian-Fard, Michael Pfeiffer. Formal analysis: Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer. Funding acquisition: Roman Bauer. Investigation: Pegah Kassraian-Fard. Methodology: Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer. Software: Pegah Kassraian-Fard. Supervision: Michael Pfeiffer, Roman Bauer. Validation: Pegah Kassraian-Fard, Michael Pfeiffer. Visualization: Pegah Kassraian-Fard, Michael Pfeiffer. Writing – original draft: Pegah Kassraian-Fard. Writing – review & editing: Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer. The authors have declared that no competing interests exist.
Funders:
Funding AgencyGrant Number
Swiss National Science Foundation (SNSF)P2EZP3_181896
Engineering and Physical Sciences Research Council (EPSRC)EP/S001433/1
Medical Research Council (UK)MR/N015037/1
Issue or Number:2
PubMed Central ID:PMC7018004
Record Number:CaltechAUTHORS:20200214-082231949
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200214-082231949
Official Citation:Kassraian-Fard P, Pfeiffer M, Bauer R (2020) A generative growth model for thalamocortical axonal branching in primary visual cortex. PLoS Comput Biol 16(2): e1007315. https://doi.org/10.1371/journal.pcbi.1007315
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101283
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Feb 2020 17:18
Last Modified:02 Apr 2020 17:12

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