Default parameter values and ranges studied.

Many insects use memories of their visual environment to adaptively drive spatial behaviours. In ants, visual memories are fundamental for navigation, whereby foragers follow long visually guided routes to foraging sites and return to the location of their nest. Whilst we understand the basic visual pathway to the memory centres (Optic Lobes to Mushroom Bodies) involved in the storage of visual information, it is still largely unknown what type of representation of visual scenes underpins view-based navigation in ants. Several experimental studies have suggested ants use “higher-order” visual information – that is features extracted across the whole extent of a visual scene – which raises the question as to how these features might be computed. One such experimental study showed that ants can use the proportion of a shape experienced left of their visual centre to learn and recapitulate a route, a feature referred to as “fractional position of mass” (FPM). In this work, we use a simple model constrained by the known neuroanatomy and information processing properties of the Mushroom Bodies to explore whether the apparent use of the FPM could be a resulting factor of the bilateral organisation of the insect brain, all the whilst assuming a simple “retinotopic” view representation. We demonstrate that such bilaterally organised memory models can implicitly encode the FPM learned during training. We find that balancing the “quality” of the memory match across left and right hemispheres allows a trained model to retrieve the FPM defined direction, even when the model is tested with novel shapes, as demonstrated by ants. The result is shown to be largely independent of model parameter values, therefore suggesting that some aspects of higher-order processing of a visual scene may be emergent from the structure of the neural circuits, rather than computed in discrete processing modules.

诸多昆虫可借助对视觉环境的记忆，自适应地调控空间行为。在蚂蚁中，视觉记忆是导航的核心基础：觅食蚁会依托视觉引导的长距离路径往返于觅食地点与巢穴之间。尽管我们已经明确了参与视觉信息存储的视觉通路基础（从视叶（Optic Lobes）到蕈形体（Mushroom Bodies）），但目前仍不清楚支撑蚂蚁基于视觉场景导航的究竟是何种类型的视觉表征。多项实验研究表明，蚂蚁会利用“高阶”视觉信息——即从整个视觉场景范围内提取的特征——这也引出了一个问题：这类特征究竟是如何被计算生成的。其中一项实验研究证实，蚂蚁可通过其视觉中心左侧所感知的形状占比来学习并复现行进路径，这一特征被称为“分数质心位置（fractional position of mass，FPM）”。本研究依托已知的蕈形体神经解剖结构与信息处理特性构建了一款简化模型，同时假设存在简单的“视网膜拓扑”视觉表征，以此探究蚂蚁对FPM的表观使用是否源于昆虫大脑的双侧组织结构。我们证实，这类具有双侧组织结构的记忆模型可在训练过程中隐式编码所习得的FPM。我们发现，平衡左右脑半球的记忆匹配“质量”，可使训练完成的模型检索到由FPM定义的行进方向，即便该模型使用全新形状进行测试时亦是如此——这与蚂蚁的实验表现一致。研究结果显示，该模型的性能在很大程度上不受模型参数取值的影响，这表明视觉场景的部分高阶处理过程或许是神经回路结构的涌现属性，而非在离散的处理模块中完成计算。