No need for a cognitive map: decentralized memory for insect navigation.
No need for a cognitive map: decentralized memory for insect navigation.
复制标题
DOI：
10.1371/journal.pcbi.1002009
复制
发表时间：
2011-03
影响因子：
4.3
通讯作者：
Wehner R
中科院分区：
文献类型：
--
作者：
Cruse H;Wehner R
对许多动物来说，长距离导航的能力是觅食的重要先决条件。例如，人们普遍认为，沙漠蚂蚁和蜜蜂，以及哺乳动物，利用路径整合来找到返回家园的路。然而，动物是否能够获得和使用所谓的认知地图，这是一个长期存在的争论。这种“地图”是觅食区域的全球空间表示，通常被认为可以让动物找到两个地点之间的捷径，尽管以前从未有人走过这种直接联系。本文采用人工神经网络的方法，开发了一种基于路径集成和各种路标引导机制（一组独立的路标定义的记忆元素）的人工记忆系统。单个记忆元素的激活取决于单独的动机网络和部分不对称的侧抑制网络。有关代理的绝对位置的信息是存在的，但是驻留在单独的内存中，只能由路径集成子系统用于控制行为，但不能与系统的其他内存元素一起用于计算目的。因此，在这个模拟中没有认知地图的神经基础。然而，由该网络控制的智能体能够完成蚂蚁和蜜蜂的各种导航任务，这些任务通常被认为依赖于认知地图。例如，在蜜蜂中观察到的类似地图的行为是分散系统中出现的一种新特性。因此，这种行为可以不参照认知地图（觅食空间的连贯表征）必须存在的假设来解释。我们假设这个网络主要存在于昆虫大脑的蘑菇体中。当沙漠蚂蚁寻找食物时，它们经常要走很远的距离，超过它们身体长度的一万倍，然后返回寻找巢穴的入口。从许多实验中我们知道，这些动物使用包括太阳在内的天窗指南针、计步器和一种称为路径整合的机制。这意味着，在行走过程中，它们会不断更新从实际位置指向巢穴的向量。此外，他们还使用地标。然而，根据对蚂蚁和蜜蜂行为的观察，一些作者认为，这些动物最终采用了一种神经系统，能够以地图的形式表示经常访问的地点（“认知地图”）。拥有一个类似地图的系统可以让动物在没有事先学会这两个位置之间的直接路径的情况下，找到两个独立学习的位置之间的捷径。由于观察到这样的捷径，认知地图被认为是存在的。在这里，我们在一项基于人工神经网络的模拟研究中表明，在实验中观察到的捷径也可能与使用完全分散架构的记忆系统（不包括明确的认知地图）有关。
In many animals the ability to navigate over long distances is an important prerequisite for foraging. For example, it is widely accepted that desert ants and honey bees, but also mammals, use path integration for finding the way back to their home site. It is however a matter of a long standing debate whether animals in addition are able to acquire and use so called cognitive maps. Such a ‘map’, a global spatial representation of the foraging area, is generally assumed to allow the animal to find shortcuts between two sites although the direct connection has never been travelled before. Using the artificial neural network approach, here we develop an artificial memory system which is based on path integration and various landmark guidance mechanisms (a bank of individual and independent landmark-defined memory elements). Activation of the individual memory elements depends on a separate motivation network and an, in part, asymmetrical lateral inhibition network. The information concerning the absolute position of the agent is present, but resides in a separate memory that can only be used by the path integration subsystem to control the behaviour, but cannot be used for computational purposes with other memory elements of the system. Thus, in this simulation there is no neural basis of a cognitive map. Nevertheless, an agent controlled by this network is able to accomplish various navigational tasks known from ants and bees and often discussed as being dependent on a cognitive map. For example, map-like behaviour as observed in honey bees arises as an emergent property from a decentralized system. This behaviour thus can be explained without referring to the assumption that a cognitive map, a coherent representation of foraging space, must exist. We hypothesize that the proposed network essentially resides in the mushroom bodies of the insect brain. When desert ants search for food, they often have to travel over long distances, more then ten thousand times their body lengths and then turn back to find the nest entrance. It is known from many experiments that these animals employ a skylight compass including the sun, a pedometer, and a mechanism called path integration. This means that during walking they continuously update the vector pointing from their actual position back to the nest site. In addition they use landmarks. However, based on observations of the behaviour of ants and honey bees several authors have argued that these animals finally employ a neural system that is able to represent frequently visited locations in the form of a map (a “cognitive map”). Having a map-like system available would allow the animal to find a shortcut between two separately learned locations without having learned this direct path between both locations beforehand. As such shortcuts have been observed, cognitive maps have been assumed to exist. Here we show in a simulation study based on artificial neural networks that shortcuts as observed in the experiments are also possible with a memory system using a completely decentralized architecture not including an explicit cognitive map.
登录
查看更多内容
影响因子：
2.4
作者：
Merkle, Tobias;Wehner, Ruediger
通讯作者：
Wehner, Ruediger
DOI：
10.1007/s00359-003-0389-z
发表时间：
2003-03-01
影响因子：
2.1
作者：
Bisch-Knaden, S;Wehner, R
通讯作者：
Wehner, R
影响因子：
1.9
作者：
Kuehn, Simone;Beyn, Wolf-Juergen;Cruse, Holk
通讯作者：
Cruse, Holk
影响因子：
1.9
作者：
Makarov, Valeri A.;Song, Yongli;Cruse, Holk
通讯作者：
Cruse, Holk
影响因子：
2
作者：
Dürr, V;Schmitz, J;Cruse, H
通讯作者：
Cruse, H