Bickle J, Worley C, Bernstein M
Department of Philosophy and Program in Neuroscience, East Carolina University, Greenville, North Carolina, 27858, USA.
Conscious Cogn. 2000 Mar;9(1):117-44. doi: 10.1006/ccog.1999.0428.
Although great progress in neuroanatomy and physiology has occurred lately, we still cannot go directly to those levels to discover the neural mechanisms of higher cognition and consciousness. But we can use neurocomputational methods based on these details to push this project forward. Here we describe vector subtraction as an operation that computes sequential paths through high-dimensional vector spaces. Vector-space interpretations of network activity patterns are a fruitful resource in recent computational neuroscience. Vector subtraction also appears to be implemented neurally in primate frontal eye field activity, which computes dimensions of saccadic eye movements. We use this apparent neural implementation as a model and construct from it a general neurocomputational account of an important type of sequential cognitive and conscious process. We defend the biological plausibility of all components of the general model and show that it yields testable anatomical and physiological predictions. We close by suggesting some interesting consequences for consciousness if our model characterizes correctly the neural mechanisms producing a common type of episode in our conscious streams.
尽管神经解剖学和生理学最近取得了巨大进展，但我们仍无法直接深入到那些层面去发现高级认知和意识的神经机制。不过，我们可以基于这些细节运用神经计算方法来推进这个项目。在此，我们将向量减法描述为一种通过高维向量空间计算序列路径的运算。网络活动模式的向量空间解释是近期计算神经科学中一个富有成果的资源。向量减法似乎也在灵长类动物额叶眼区活动中通过神经方式得以实现，该活动计算眼球扫视运动的维度。我们将这种明显的神经实现方式作为一个模型，并由此构建出一种对重要类型的序列认知和意识过程的通用神经计算解释。我们捍卫通用模型所有组成部分的生物学合理性，并表明它能产生可检验的解剖学和生理学预测。如果我们的模型正确地刻画了在我们有意识的思维流中产生一种常见类型事件的神经机制，我们将通过提出一些关于意识的有趣推论来结束本文。
