PMID- 33551782
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20210210
IS  - 1662-5188 (Print)
IS  - 1662-5188 (Electronic)
IS  - 1662-5188 (Linking)
VI  - 14
DP  - 2020
TI  - BCNNM: A Framework for in silico Neural Tissue Development Modeling.
PG  - 588224
LID - 10.3389/fncom.2020.588224 [doi]
LID - 588224
AB  - Cerebral ("brain") organoids are high-fidelity in vitro cellular models of the 
      developing brain, which makes them one of the go-to methods to study isolated 
      processes of tissue organization and its electrophysiological properties, 
      allowing to collect invaluable data for in silico modeling neurodevelopmental 
      processes. Complex computer models of biological systems supplement in vivo and 
      in vitro experimentation and allow researchers to look at things that no 
      laboratory study has access to, due to either technological or ethical 
      limitations. In this paper, we present the Biological Cellular Neural Network 
      Modeling (BCNNM) framework designed for building dynamic spatial models of neural 
      tissue organization and basic stimulus dynamics. The BCNNM uses a convenient 
      predicate description of sequences of biochemical reactions and can be used to 
      run complex models of multi-layer neural network formation from a single initial 
      stem cell. It involves processes such as proliferation of precursor cells and 
      their differentiation into mature cell types, cell migration, axon and dendritic 
      tree formation, axon pathfinding and synaptogenesis. The experiment described in 
      this article demonstrates a creation of an in silico cerebral organoid-like 
      structure, constituted of up to 1 million cells, which differentiate and 
      self-organize into an interconnected system with four layers, where the spatial 
      arrangement of layers and cells are consistent with the values of analogous 
      parameters obtained from research on living tissues. Our in silico organoid 
      contains axons and millions of synapses within and between the layers, and it 
      comprises neurons with high density of connections (more than 10). In sum, the 
      BCNNM is an easy-to-use and powerful framework for simulations of neural tissue 
      development that provides a convenient way to design a variety of tractable in 
      silico experiments.
CI  - Copyright (c) 2021 Bozhko, Galumov, Polovian, Kolchanova, Myrov, Stelmakh and 
      Schioth.
FAU - Bozhko, Dmitrii V
AU  - Bozhko DV
AD  - JetBrains Research Department, Space Office Center, Saint Petersburg, Russia.
FAU - Galumov, Georgii K
AU  - Galumov GK
AD  - JetBrains Research Department, Space Office Center, Saint Petersburg, Russia.
FAU - Polovian, Aleksandr I
AU  - Polovian AI
AD  - JetBrains Research Department, Space Office Center, Saint Petersburg, Russia.
FAU - Kolchanova, Sofiia M
AU  - Kolchanova SM
AD  - JetBrains Research Department, Space Office Center, Saint Petersburg, Russia.
AD  - Department of Biology, University of Puerto Rico at Mayaguez, Mayaguez, PR, 
      United States.
AD  - Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State 
      University, Saint Petersburg, Russia.
FAU - Myrov, Vladislav O
AU  - Myrov VO
AD  - Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 
      Helsinki, Finland.
AD  - Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, 
      Finland.
FAU - Stelmakh, Viktoriia A
AU  - Stelmakh VA
AD  - JetBrains Research Department, Space Office Center, Saint Petersburg, Russia.
AD  - Skolkovo Institute of Science and Technology, Center of Life Sciences, Moscow, 
      Russia.
FAU - Schioth, Helgi B
AU  - Schioth HB
AD  - Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, 
      Sweden.
AD  - Institute for Translational Medicine and Biotechnology, Sechenov First Moscow 
      State Medical University, Moscow, Russia.
LA  - eng
PT  - Journal Article
DEP - 20210120
PL  - Switzerland
TA  - Front Comput Neurosci
JT  - Frontiers in computational neuroscience
JID - 101477956
PMC - PMC7855713
OTO - NOTNLM
OT  - axon guidance
OT  - brain organoid
OT  - neurogenesis
OT  - neuronal connectivity
OT  - simulation
OT  - tissue development
COIS- DB, GG, AP, VS, and SK were employed by legal entities which are a part of 
      JetBrains group of companies. The remaining authors declare that the research was 
      conducted in the absence of any commercial or financial relationships that could 
      be construed as a potential conflict of interest.
EDAT- 2021/02/09 06:00
MHDA- 2021/02/09 06:01
PMCR- 2020/01/01
CRDT- 2021/02/08 05:35
PHST- 2020/07/28 00:00 [received]
PHST- 2020/12/18 00:00 [accepted]
PHST- 2021/02/08 05:35 [entrez]
PHST- 2021/02/09 06:00 [pubmed]
PHST- 2021/02/09 06:01 [medline]
PHST- 2020/01/01 00:00 [pmc-release]
AID - 10.3389/fncom.2020.588224 [doi]
PST - epublish
SO  - Front Comput Neurosci. 2021 Jan 20;14:588224. doi: 10.3389/fncom.2020.588224. 
      eCollection 2020.