{"title":"成人神经发生的计算模型","authors":"J. Aimone, Laurenz Wiskott","doi":"10.1101/087969784.52.463","DOIUrl":null,"url":null,"abstract":"One of the most intriguing differences between adult and developmental neurogenesis is that in the adult brain, new neurons are integrating into already-developed, functioning circuits. Newborn neurons develop highly complex neuronal morphology—an impressive feat, considering that the extracellular signaling environment (thought to be important during development) is considerably different in the adult. Adult neurogenesis has been observed in most animal species, both in the normal course of life and in response to injury in many nonmammals. The fact that adult neurogenesis is essentially limited to two regions in mammalian brains suggests that the addition of new neurons to these regions (the olfactory bulb [OB] and dentate gyrus [DG]) is of particular importance. Although the function of regenerative neurogenesis is self-evident, the purpose for lifelong neurogenesis remains unclear. There are several reasons why taking a computational modeling approach has potential. One is that any effect of adding new neurons will first be manifested computationally in the network and will only then be observed behaviorally. Modeling can permit the observation of an effect that otherwise would go unseen in standard behavioral assays. This provides a framework by which new predictions can be made that can be specifically tested experimentally. Furthermore, a well-developed computational model or theory can be altered in a manner that is impractical or impossible in animal models, such as increasing the rate of neurogenesis by tenfold or studying the effects of neurogenesis in nonneurogenic areas. Finally, modeling the computational aspects of a system often helps focus future experiments,..","PeriodicalId":10493,"journal":{"name":"Cold Spring Harbor Monograph Archive","volume":"49 1","pages":"463-481"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"22 Computational Modeling of Adult Neurogenesis\",\"authors\":\"J. Aimone, Laurenz Wiskott\",\"doi\":\"10.1101/087969784.52.463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the most intriguing differences between adult and developmental neurogenesis is that in the adult brain, new neurons are integrating into already-developed, functioning circuits. Newborn neurons develop highly complex neuronal morphology—an impressive feat, considering that the extracellular signaling environment (thought to be important during development) is considerably different in the adult. Adult neurogenesis has been observed in most animal species, both in the normal course of life and in response to injury in many nonmammals. The fact that adult neurogenesis is essentially limited to two regions in mammalian brains suggests that the addition of new neurons to these regions (the olfactory bulb [OB] and dentate gyrus [DG]) is of particular importance. Although the function of regenerative neurogenesis is self-evident, the purpose for lifelong neurogenesis remains unclear. There are several reasons why taking a computational modeling approach has potential. One is that any effect of adding new neurons will first be manifested computationally in the network and will only then be observed behaviorally. Modeling can permit the observation of an effect that otherwise would go unseen in standard behavioral assays. This provides a framework by which new predictions can be made that can be specifically tested experimentally. Furthermore, a well-developed computational model or theory can be altered in a manner that is impractical or impossible in animal models, such as increasing the rate of neurogenesis by tenfold or studying the effects of neurogenesis in nonneurogenic areas. Finally, modeling the computational aspects of a system often helps focus future experiments,..\",\"PeriodicalId\":10493,\"journal\":{\"name\":\"Cold Spring Harbor Monograph Archive\",\"volume\":\"49 1\",\"pages\":\"463-481\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cold Spring Harbor Monograph Archive\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/087969784.52.463\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cold Spring Harbor Monograph Archive","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/087969784.52.463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
One of the most intriguing differences between adult and developmental neurogenesis is that in the adult brain, new neurons are integrating into already-developed, functioning circuits. Newborn neurons develop highly complex neuronal morphology—an impressive feat, considering that the extracellular signaling environment (thought to be important during development) is considerably different in the adult. Adult neurogenesis has been observed in most animal species, both in the normal course of life and in response to injury in many nonmammals. The fact that adult neurogenesis is essentially limited to two regions in mammalian brains suggests that the addition of new neurons to these regions (the olfactory bulb [OB] and dentate gyrus [DG]) is of particular importance. Although the function of regenerative neurogenesis is self-evident, the purpose for lifelong neurogenesis remains unclear. There are several reasons why taking a computational modeling approach has potential. One is that any effect of adding new neurons will first be manifested computationally in the network and will only then be observed behaviorally. Modeling can permit the observation of an effect that otherwise would go unseen in standard behavioral assays. This provides a framework by which new predictions can be made that can be specifically tested experimentally. Furthermore, a well-developed computational model or theory can be altered in a manner that is impractical or impossible in animal models, such as increasing the rate of neurogenesis by tenfold or studying the effects of neurogenesis in nonneurogenic areas. Finally, modeling the computational aspects of a system often helps focus future experiments,..