Disentangling the developmental drivers of behavioral individuality using a clonal fish
使用克隆鱼解开行为个性的发展驱动因素
基本信息
- 批准号:2100625
- 负责人:
- 金额:$ 113万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The goal of this proposal is to understand how individuality develops and investigate the molecular and neurological mechanisms underlying individual variation. You are unique, as is everyone else. This age-old adage captures a very real biological phenomenon: across the animal kingdom, individuals exhibit distinctive patterns of behavior, similar to personality in humans. However, despite its prevalence we still have a limited understanding of how and why behavioral individuality emerges. Information integration theory predicts how animals will use information and experiences to shape their behavior over their lifetimes, but this is often difficult to test empirically, in part because the vast majority of individuals are also genetically distinct. This project exploits a naturally clonal fish, the Amazon molly, to isolate the effects of experience on behavior and pinpoint the molecular mechanisms generating these changes. An innovative tracking system will follow the behavior of individual mollies from birth throughout their entire lives providing unprecedented insight into how behavior changes in response to different cues. Understanding the molecular mechanisms generating behavioral individuality will clarify how easily such changes are triggered, and once they are, how durable they may be. By testing key predictions from information integration theory, the results of this project will improve our ability to predict an individual’s response to different cues before they have even experienced that cue. This could have major implications for our ability to predict species’ responses to climate change or the efficacy of therapeutic interventions on pathological behavior in animals and humans alike. In addition, the project includes the development of classroom-based authentic research experiences for undergraduates at UC Davis, as well as for high school students at minority-serving high schools in the Davis, CA area.If we can understand the mechanisms through which individuals use, value, and integrate the information they receive over their lives, we can better predict how and why individuals behave the way they do. The goal of this proposal is to test whether Bayesian updating provides a framework that can predict how individuals integrate maternal and personal cues to generate their unique behavioral phenotypes. This project will systematically manipulate whether individuals receive cues from their mothers and/or their own experiences to 1) test whether Bayesian updating predicts behavioral change, 2) investigate potential proximate mechanisms underlying such change by following changes in brain neural activation, gene expression, and methylation status and 3) test the potential adaptive value of these behavioral changes. The use of the genetically identical Amazon molly provides a rigorous experimental system to pinpoint experiential effects on behavior by controlling for genetic variation among individuals. If individuals are using Bayesian or Bayesian-like processes to build their behavioral phenotypes, then their behavioral development should follow predictable patterns of change based on the confidence in their prior expectations, which we can measure using our innovative tracking system, and the new information they receive about the most likely state of the environment, which we can control in an experimental setting. By combining a unifying mechanistic framework with a powerful animal model and an innovative tracking system, this work will provide deep insight into the developmental drivers of behavioral individuality.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
这项建议的目标是了解个性是如何发展的,并研究个体差异背后的分子和神经机制。你是独一无二的,其他人也是。这句古老的谚语捕捉到了一个非常真实的生物学现象:在整个动物界,个体表现出独特的行为模式,类似于人类的人格。然而,尽管行为个性很普遍,但我们对行为个性是如何以及为什么出现的理解仍然有限。信息整合理论预测动物将如何利用信息和经验来塑造它们一生的行为,但这通常很难进行经验测试,部分原因是绝大多数个体在基因上也是截然不同的。这个项目利用一种天然的克隆鱼--亚马逊Molly--来分离经验对行为的影响,并准确地定位产生这些变化的分子机制。一种创新的跟踪系统将跟踪个体鼹鼠从出生起的整个一生的行为,提供前所未有的洞察力,了解行为如何随着不同的提示而变化。理解产生行为个性的分子机制将澄清这种变化被触发的容易程度,以及一旦它们被触发,它们可能会持续多久。通过测试信息整合理论的关键预测,这个项目的结果将提高我们预测个体对不同线索的反应的能力,甚至在他们经历不同线索之前。这可能会对我们预测物种对气候变化的反应的能力或对动物和人类病理行为的治疗干预的有效性产生重大影响。此外,该项目还包括为加州大学戴维斯分校的本科生和加州戴维斯地区少数族裔服务高中的高中生开发基于课堂的真实研究体验。如果我们能够理解个人使用、重视和整合他们一生中收到的信息的机制,我们就可以更好地预测个人如何以及为什么会这样做。这项提议的目的是测试贝叶斯更新是否提供了一个框架,可以预测个体如何整合母性和个人线索来产生他们独特的行为表型。这个项目将系统地操纵个体是否从他们的母亲和/或他们自己的经历中收到线索,以1)测试贝叶斯更新是否预测行为变化,2)通过跟踪脑神经激活、基因表达和甲基化状态的变化来调查潜在的近距离机制,以及3)测试这些行为变化的潜在适应价值。使用基因相同的亚马逊Molly提供了一个严格的实验系统,通过控制个体之间的基因变异来精确定位对行为的经验影响。如果个人正在使用贝叶斯或类似贝叶斯的过程来建立他们的行为表型,那么他们的行为发展应该遵循可预测的变化模式,这是基于对他们先前预期的信心,我们可以使用我们的创新跟踪系统来衡量,以及他们收到的关于环境最可能状态的新信息,我们可以在实验环境中控制这些信息。通过将统一的机械框架与强大的动物模型和创新的跟踪系统相结合,这项工作将提供对行为个性发展驱动因素的深刻洞察。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Consistent Individual Behavioral Variation: What Do We Know and Where Are We Going?
一致的个人行为变异:我们知道什么以及我们要去哪里?
- DOI:10.1146/annurev-ecolsys-102220-011451
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Laskowski, Kate L.;Chang, Chia-Chen;Sheehy, Kirsten;Aguiñaga, Jonathan
- 通讯作者:Aguiñaga, Jonathan
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Kate Laskowski其他文献
Kate Laskowski的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
相似国自然基金
22q11.2染色体微重复影响TOP3B表达并导致腭裂发生的机制研究
- 批准号:82370906
- 批准年份:2023
- 资助金额:48.00 万元
- 项目类别:面上项目
相似海外基金
Evolutionary and developmental drivers of phenotypic variation
表型变异的进化和发育驱动因素
- 批准号:
RGPIN-2022-04370 - 财政年份:2022
- 资助金额:
$ 113万 - 项目类别:
Discovery Grants Program - Individual
Interneurons as early drivers of Huntington´s disease progression
中间神经元是亨廷顿病进展的早期驱动因素
- 批准号:
10518582 - 财政年份:2022
- 资助金额:
$ 113万 - 项目类别:
Interneurons as Early Drivers of Huntington´s Disease Progression
中间神经元是亨廷顿病进展的早期驱动因素
- 批准号:
10672973 - 财政年份:2022
- 资助金额:
$ 113万 - 项目类别:
Molecular drivers of tissue-specific morphogenetic programs
组织特异性形态发生程序的分子驱动因素
- 批准号:
10440153 - 财政年份:2022
- 资助金额:
$ 113万 - 项目类别:
Molecular drivers of tissue-specific morphogenetic programs
组织特异性形态发生程序的分子驱动因素
- 批准号:
10650730 - 财政年份:2022
- 资助金额:
$ 113万 - 项目类别:
Understanding druggable drivers of meningioma tumorigenesis
了解脑膜瘤肿瘤发生的药物驱动因素
- 批准号:
10663243 - 财政年份:2021
- 资助金额:
$ 113万 - 项目类别:
Understanding druggable drivers of meningioma tumorigenesis
了解脑膜瘤肿瘤发生的药物驱动因素
- 批准号:
10456201 - 财政年份:2021
- 资助金额:
$ 113万 - 项目类别:
Understanding druggable drivers of meningioma tumorigenesis
了解脑膜瘤肿瘤发生的药物驱动因素
- 批准号:
10275399 - 财政年份:2021
- 资助金额:
$ 113万 - 项目类别:
Identifying Functional Drivers of MYC Activation via Developmental Enhancers in Diffuse Large B-cell Lymphoma
通过发育增强剂识别弥漫性大 B 细胞淋巴瘤中 MYC 激活的功能驱动因素
- 批准号:
10412020 - 财政年份:2020
- 资助金额:
$ 113万 - 项目类别:
Identifying Functional Drivers of MYC Activation via Developmental Enhancers in Diffuse Large B-cell Lymphoma
通过发育增强剂识别弥漫性大 B 细胞淋巴瘤中 MYC 激活的功能驱动因素
- 批准号:
10207556 - 财政年份:2020
- 资助金额:
$ 113万 - 项目类别: