Cooke Matthew B, O'Leary Timothy P, Harris Phelan, Ma Ricky, Brown Richard E, Snyder Jason S
Department of Psychology, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada.
Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancovuer, British Columbia, V6T 1Z3, Canada.
F1000Res. 2019 Aug 28;8:1521. doi: 10.12688/f1000research.20352.2. eCollection 2019.
Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.
空间导航是一种普遍行为,会因目标、经验和可用的感官刺激而有所不同。空间导航任务经常用于研究动物和人类的学习、记忆及目标导向行为。一种测试空间记忆的常用范式是莫里斯水迷宫,在该实验中,实验对象要学习隐藏平台的位置,这个平台能让它们从水池中逃脱。研究人员通常将学习表现为逃脱潜伏期的函数,不过这几乎无法揭示潜在的导航策略。最近,一些研究开始对水迷宫搜索策略进行分类,以阐明不同脑区精确的空间和记忆功能,并确定在疾病模型中空间记忆的哪些方面受到了破坏。然而,尽管它们很有用,但由于缺乏自动化分析软件,策略分析尚未得到广泛应用。为满足这一需求,我们开发了Pathfinder,这是一款用于分析空间导航行为的开源应用程序。在一个具有代表性的数据集中,我们展示了Pathfinder能够有效地刻画雄性和雌性小鼠学习标准空间水迷宫时高度特定的空间搜索策略的发展情况。Pathfinder可以读取来自商业和免费软件包的数据文件,针对水迷宫范式中的搜索策略分类进行了优化,并且只要有带时间戳的xy坐标,它还可用于分析其他物种在二维导航以及其他任务中的情况。Pathfinder使用简单,可以自动确定水池和平台的几何形状,生成热图,分析相对于多个目标位置的导航情况,并且可以进行更新以适应空间行为分析的未来发展。鉴于这些特性,Pathfinder可能是研究导航策略如何受环境调节、依赖特定神经回路以及如何因病理学改变的有用工具。