Computational modeling of adult neurogenesis in the dentate gyrus.

摘要

The incorporation of new neurons into the adult brain is a form of plasticity that has only recently been appreciated in neuroscience. The localization of adult neurogenesis to the dentate gyrus (DG) area of the hippocampus is of particular interest, given the hippocampus's observed role as a structure crucial for memory formation. In the rodent, thousands of new neurons are born daily, and research into this process has revealed a complex maturation process, with newborn neurons showing unique physiological and anatomical features at different stages of development. Despite these findings regarding the biology of the neurogenesis process itself, a functional role for new neurons has remained elusive.;This dissertation will describe the design, implementation, and testing of a biologically driven computational model of the adult neurogenesis process in the DG. In this model, new neurons are incorporated into the DG circuit according to the process revealed by previous biological studies. Ultimately, this work provides evidence for three separate functions for new neurons that are both novel and experimentally testable. The first hypothesis is that immature neurons are more likely to contribute to the encoding of new memories than mature neurons. This increased activity provides a pattern integration component to the global pattern separation function of the DG. The second hypothesis is that the continuing maturation of these young neurons makes this pattern integration role temporally dependent. As such, memories encoded close in time will be associated, while memories encoded far apart in time will be separated. Third, the results suggest that continual neurogenesis results in a DG network that is a cumulative representation of events experienced throughout life.;Finally, this dissertation will discuss how neuromodulation may affect the neurogenesis process and its relationship with hippocampal function and will include a description of how modulatory neurotransmitters can be considered in the computational model, and the specific example of dopamine will show how preliminary data regarding the effects of modulators on neurogenesis can be incorporated into the modeling framework.