BIOSTATISTICAL RESEARCH CORE
生物统计研究核心
基本信息
- 批准号:8074012
- 负责人:
- 金额:$ 10.6万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-06-01 至 2011-05-31
- 项目状态:已结题
- 来源:
- 关键词:AlgorithmsAnalysis of VarianceAnimalsBehavioralCerealsComputersDataDependenceDetectionEnvironmentExperimental DesignsFamiliarityHeterogeneityHippocampus (Brain)Impaired cognitionInterneuronsLiteratureLocationLogistic RegressionsMapsMarkov ChainsMethodsModelingMonte Carlo MethodN-Methyl-D-Aspartate ReceptorsNeuronsOdorsProbabilityResearchResolutionSchizophreniaSignal TransductionSilverTechnologyTestingUpdateWeightWorkbasebrain cellcell assemblydensityexpectationgamma-Aminobutyric Acidreceptor functionresearch study
项目摘要
The Biostatistical Research Core (BRC) will continue to serve the six projects through applications of
classical, modern, and newly-emerging quantitative methods for experimental design and analysis of
empirical findings. In addition, the BRC will work with the Computational and Animal Behavioral Cores to
develop new computational and biostatistical technologies for the projects. The BRC will also serve to
integrate the efforts of all three cores. The major continuing challenge of the BRC is to push biostatistical
interactions with the projects beyond mere confirmation of their expectations towards the discovery of
previously undetected signals hidden in noisy data. With the Benes project and the Animal Behavioral Core,
the BRC will apply mixed-effects Poisson analyses of variance models to test the hypotheses that GABA
blockade and reduced NMDA receptor function in hippocampal CA sectors can result in aspects of cognitive
dysfunction found in schizophrenia by assessing the significance of Treatment X Environment interactions in
the novelty detection study. Computer-intense Bayesian Markov Chain Monte Carlo (MCMC) methods will
also be employed. In a combined analysis, the DISH experiments will employ similar yet weighted Poisson
models with silver grain NR2A densities as weights for the counts of GAD67-positive hippocampal
interneurons. We will also apply our existing semi-automatic algorithms for detection of Fos bodies. With the
Lisman project and the Computational Core, we will apply MCMC technology to revise prior connectivitymorphology
probability mappings based on existing literature by new data likelihoods obtained from studies
in the Benes project to yield updated posterior probability mappings. The Greene project and the Animal
Behavioral Core will benefit from our longitudinal mixed-effects logistic regression models applied to their
odor familiarity and recognition study. The BRC will serve as consultant to the Coyle, Yurgelun-Todd and
Goff projects on an as needed basis. Further biostatistical applications include tests to distinguish between
local spatial heterogeneity (different neuronal densities in different regions) and spatial dependence
(correlations between neuronal locations) and Poisson random field methods to detect features of 3D brain
cell assemblies at multiple levels of spatial resolution.
生物统计研究中心(BRC)将继续为这六个项目提供服务
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
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 }}
JOSEPH T. COYLE其他文献
Combined Use of Tricyclic Antidepressants and Neuroleptics in the Management of Terminally 111 Children: A Report on Three Cases
- DOI:
10.1016/s0002-7138(09)60569-0 - 发表时间:
1985-07-01 - 期刊:
- 影响因子:
- 作者:
MOHAMMAD MAISAMI;BARBARA H. SOHMER;JOSEPH T. COYLE - 通讯作者:
JOSEPH T. COYLE
Lesion of striatal neurons with kainic acid provides a model for Huntington's chorea
用红藻氨酸损伤纹状体神经元可提供亨廷顿舞蹈病的模型
- DOI:
10.1038/263244a0 - 发表时间:
1976-09-01 - 期刊:
- 影响因子:48.500
- 作者:
JOSEPH T. COYLE;ROBERT SCHWARCZ - 通讯作者:
ROBERT SCHWARCZ
JOSEPH T. COYLE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 }}
{{ truncateString('JOSEPH T. COYLE', 18)}}的其他基金
NMDA hypofunction and episodic memory: An animal model
NMDA 功能减退和情景记忆:动物模型
- 批准号:
8074007 - 财政年份:2010
- 资助金额:
$ 10.6万 - 项目类别:
Biomarkers of NMDA dysfunction and D-serine effects
NMDA 功能障碍和 D-丝氨酸效应的生物标志物
- 批准号:
8074011 - 财政年份:2010
- 资助金额:
$ 10.6万 - 项目类别:
Dopamine and NMDA: role in novelty detection
多巴胺和 NMDA:在新颖性检测中的作用
- 批准号:
8074006 - 财政年份:2010
- 资助金额:
$ 10.6万 - 项目类别:
Dopamine and NMDA: role in novelty detection
多巴胺和 NMDA:在新颖性检测中的作用
- 批准号:
7858385 - 财政年份:2009
- 资助金额:
$ 10.6万 - 项目类别:
相似海外基金
Generalized multivariate analysis of variance (GMANOVA) models for high dimensional data
高维数据的广义多变量方差分析 (GMANOVA) 模型
- 批准号:
402477-2011 - 财政年份:2015
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Generalized multivariate analysis of variance (GMANOVA) models for high dimensional data
高维数据的广义多变量方差分析 (GMANOVA) 模型
- 批准号:
402477-2011 - 财政年份:2014
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Solution to the Fokker Planck Kolmogorov Equation using Hoeffding's Functional Analysis of Variance Decomposition
使用 Hoeffding 方差分解泛函分析求解 Fokker Planck Kolmogorov 方程
- 批准号:
464881-2014 - 财政年份:2014
- 资助金额:
$ 10.6万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Master's
Generalized multivariate analysis of variance (GMANOVA) models for high dimensional data
高维数据的广义多变量方差分析 (GMANOVA) 模型
- 批准号:
402477-2011 - 财政年份:2013
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Generalized multivariate analysis of variance (GMANOVA) models for high dimensional data
高维数据的广义多变量方差分析 (GMANOVA) 模型
- 批准号:
402477-2011 - 财政年份:2012
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Generalized multivariate analysis of variance (GMANOVA) models for high dimensional data
高维数据的广义多变量方差分析 (GMANOVA) 模型
- 批准号:
402477-2011 - 财政年份:2011
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Investigations in Robust Analysis of Variance
稳健方差分析研究
- 批准号:
9209709 - 财政年份:1992
- 资助金额:
$ 10.6万 - 项目类别:
Continuing Grant
Inference problems in inverse gaussian distribution, analysis of variance models and super population models
逆高斯分布的推理问题、方差模型和超总体模型的分析
- 批准号:
3661-1990 - 财政年份:1992
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Inference problems in inverse gaussian distribution, analysis of variance models and super population models
逆高斯分布的推理问题、方差模型和超总体模型的分析
- 批准号:
3661-1990 - 财政年份:1991
- 资助金额:
$ 10.6万 - 项目类别:
Discovery Grants Program - Individual
Robust Analysis of Variance and Analysis of Designed Experiments
稳健方差分析和设计实验分析
- 批准号:
9001860 - 财政年份:1990
- 资助金额:
$ 10.6万 - 项目类别:
Standard Grant














{{item.name}}会员




