Mental imagery has long been of interest to the cognitive and neurosciences, but how it manifests itself in the mind and brain still remains unresolved. In pursuit of this, we built a spiking neural model that can perform mental rotation and mental map scanning using strategies informed by the psychology and neuroscience literature. Results: When performing mental map scanning, reaction times (RTs) for our model closely match behavioural studies (approx. 50 ms/cm), and replicate the cognitive penetrability of the task. When performing mental rotation, our model’s RTs once again closely match behavioural studies (model: 55–65°/s; studies: 60°/s), and performed the task using the same task strategy (whole unit rotation of simple and familiar objects through intermediary points). Overall, our model suggests: (1) vector-based approaches to neuro-cognitive modelling are well equipped to re-produce behavioural findings, and (2) the cognitive (in)penetrability of imagery tasks may depend on whether or not the task makes use of (non)symbolic processing.

中文翻译：

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空间和视觉心理意象的尖峰神经网络模型


心理意象长期以来一直受到认知和神经科学的关注，但它如何在思想和大脑中表现出来仍然悬而未决。为了实现这一目标，我们建立了一个尖峰神经模型，可以使用心理学和神经科学文献所提供的策略来执行心理旋转和心理地图扫描。结果：在执行心理地图扫描时，我们模型的反应时间 (RT) 与行为研究非常匹配（约 50 毫秒/厘米），并且复制了任务的认知渗透性。当执行心理旋转时，我们模型的 RT 再次与行为研究紧密匹配（模型：55-65°/s；研究：60°/s），并使用相同的任务策略（简单和熟悉的物体的整个单元旋转）来执行任务通过中介点）。总体而言，我们的模型表明：（1）基于向量的神经认知建模方法能够很好地重现行为发现，（2）图像任务的认知（内）渗透性可能取决于该任务是否使使用（非）符号处理。