As far as I understand, the basics of neurogenesis (abstracted down to the level that makes sense to a computer scientist) is as follows:
- Neural progenitor cells differentiate into new neurons that have zero (or very few) synaptic connections, but are sensitive to the local chemistry.
- (Optional) Sometimes (such as in adult neurogenesis in the olfactory bulb) these immature neurons-to-be are produced far away from where they are needed and follow standard pathways to migrate to the correct brain region
- The immature neuron extends dendrites towards upstream neurons and starts to develop an axon
- The immature neuron extends axon towards downstream neurons, and
- The neuron matures and becomes indistinguishable from the network it joined.
I've eliminated many of the biological details, since I want to just capture the details (more info). The part that seems to be not well described, and my question, is:
- How do neurons select where to make their initial dendrite and axon connections?
- How/when does a given network notify the progenitor cells that they should differentiate?
Cecchi et al. (2001) proposed a model where the new neurons produce initial connections randomly, and then the only the ones that contribute to the function of the network end up firing frequently and surviving, and the rest die. This inspired by the observation of high death rate among immature neurons. However, there is not biological evidence to support that the initial connections are in fact random, and I hope that there has been more evidence gathered since the early work in 2001.
This question is motivated by the search for computational models with a biologically reasonable account of neurogenesis.
I am looking for some sort of abstract local explanation to my questions at-least at the rule-of-thumb level. For examples, if I was asking about plasticity of established connections (and not neurogenesis in particular), then Hebb's "neurons that fire together wire together" would be a sufficient answer, although STDP would be a better one. However, I do not need all the biological details, just the high level rule if one is known.
- Cecchi GA, Retreanu LT, Alvarez-Buylla A, Magnasco MO – “Unsupervised Learning and Adaptation in a Model of Adult Neurogenesis” Journal of Computational Neuroscience; 11:175-182; 2001 [preprint]