Neuronal
regeneration in the adult brain, which is restricted compared to that
in the embryonic brain, is a long-standing topic in neuroscience and
medical research. Based on studies in mammals, a small number of newly
generated immature neurons (neuroblasts) migrate toward damaged sites
and contribute to functional recovery. During migration, neuroblasts
form chain-like collectives and modify the morphology of glial cells
(astrocytes), which are the main components of the surrounding
environment. However, it remains unclear how neuroblasts form
collectives and how efficient migration is achieved through collective
formation in a pool of astrocytes. The main difficulty lies in tracking
individual neuroblasts within the collective, both in vitro and in vivo,
over a period. To address this impasse, we built a mathematical model
of the neuroblast-astrocyte system to assess its long-term performance
in silico. Our simulations showed that individual neuroblasts gathered
into chain-like collectives through occasional contact, astrocyte
confinement, and moderate adhesion between the neuroblasts. The forward
movement of neuroblasts in an astrocyte-dense environment was
accelerated if we assumed a simple interaction: the higher the number of
neuroblasts near an astrocyte, the stronger the shrinkage of astrocytic
protrusions. Furthermore, temporal changes in neuroblast behavior, as
indicated by our observation of living neuroblasts in culture, reinforce
the advantages of simulated collectives. A collective of neuroblasts
with constant behavior sometimes repeated non-migratory movements,
whereas those with inconstant behavior were easily untangled, resulting
in a rapid migration. These results highlight the potential for
neuroblast collectivity and inconstancy in enhancing neuronal
regeneration in the adult brain.
