Approaches to embryonic neurodevelopment: from neural cell to neural tube formation through mathematical models

Author:

Rafati Ali H12ORCID,Joca Sâmia123,Vontell Regina T4,Wegener Gregers12,Ardalan Maryam125

Affiliation:

1. Translational Neuropsychiatry Unit , Department of Clinical Medicine, , Palle Juul-Jensens Boulevard 11, 8200 Aarhus N , Denmark

2. Aarhus University , Department of Clinical Medicine, , Palle Juul-Jensens Boulevard 11, 8200 Aarhus N , Denmark

3. Department of Biomedicine - Forskning og uddannelse, Vest, Aarhus University , Vest Ole Worms Allé 4 Bygning 1160, lokale 229, 8000 Aarhus C , Denmark

4. Department of Neurology, University of Miami Miller School of Medicine , Brain Endowment Bank, 1951 NW 7th Avenue, Suite 240 Miami, FL 33136 , USA

5. Institute of Neuroscience and Physiology, Department of Physiology, Sahlgrenska Academy, University of Gothenburg , Medicinaregatan 11, 40530, Gothenburg , Sweden

Abstract

Abstract The development of the human central nervous system initiates in the early embryonic period until long after delivery. It has been shown that several neurological and neuropsychiatric diseases originate from prenatal incidents. Mathematical models offer a direct way to understand neurodevelopmental processes better. Mathematical modelling of neurodevelopment during the embryonic period is challenging in terms of how to ‘Approach’, how to initiate modelling and how to propose the appropriate equations that fit the underlying dynamics of neurodevelopment during the embryonic period while including the variety of elements that are built-in naturally during the process of neurodevelopment. It is imperative to answer where and how to start modelling; in other words, what is the appropriate ‘Approach’? Therefore, one objective of this study was to tackle the mathematical issue broadly from different aspects and approaches. The approaches were divided into three embryonic categories: cell division, neural tube growth and neural plate growth. We concluded that the neural plate growth approach provides a suitable platform for simulation of brain formation/neurodevelopment compared to cell division and neural tube growth. We devised a novel equation and designed algorithms that include geometrical and topological algorithms that could fit most of the necessary elements of the neurodevelopmental process during the embryonic period. Hence, the proposed equations and defined mathematical structure would be a platform to generate an artificial neural network that autonomously grows and develops.

Funder

Swedish Research Council

Lundbeck Foundation

Publisher

Oxford University Press (OUP)

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