Hybridizing behavioral models: a possible solution to some problems in neurophenotyping research?
Hybridizing behavioral models: a possible solution to some problems in neurophenotyping research?
复制标题
混合行为模型：神经表型研究中某些问题的可能解决方案？
DOI：
10.1016/j.pnpbp.2007.12.010
复制
发表时间：
2008
影响因子：
5.6
通讯作者：
Sufka,Kenneth
中科院分区：
文献类型：
--
作者：
Kalueff,AllanV;LaPorte,JustinL;Murphy,DennisL;Sufka,Kenneth
使用单域测试进行神经表型研究是实现更高数据密度和探索不同行为域的常见策略。然而，这一方法也伴随着一些方法上的挑战，在此简要讨论。作为一种替代方案，本文主张更广泛地使用广泛的“混合”协议，并行评估多个域，或逻辑/逻辑上联合收割机的实验范式，在某种程度上，不成比例地最大化每个实验操作的测试表型的数量。本文给出了这种方法的几个例子，证明了减少实验时间、成本和主题要求的潜力。这种“混合”模型提供了标准单域测试所缺乏的行为分析，通过对复杂表型特征进行更彻底和更广泛的研究，能够对神经精神疾病进行创新建模。
The use of batteries of single-domain tests for neurophenotyping research is a common strategy to achieve higher data density and explore different behavioral domains. This approach, however, is accompanied by several methodological challenges, briefly discussed here. As an alternative, this paper advocates the wider use of extensive “hybrid” protocols that assess multiple domains in parallel, or logically/logistically combine experimental paradigms, in a way that disproportionately maximizes the number of tested phenotypes per experimental manipulation. Several examples of this approach are given in this paper, demonstrating the potential to reduce time, cost and subject requirements for the experiments. Offering behavioral analyses that are lacking in the standard single-domain tests, such “hybrid” models enable innovative modeling of neuropsychiatric disorders by more thorough and broader investigation of complex phenotypical characteristics.