Garvert Mona M, Dolan Raymond J, Behrens Timothy Ej
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.
Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Elife. 2017 Apr 27;6:e17086. doi: 10.7554/eLife.17086.
The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.
海马体-内嗅皮层系统编码了一幅引导空间导航的空间地图。空间导航之外的目标导向行为同样需要一种抽象形式的关系知识表征。这些信息依赖于同一神经系统，但尚不清楚支配连续地图的组织原则是否可以扩展到离散的非空间图的隐式编码。在这里，我们表明人类海马体-内嗅皮层系统可以使用一种依赖于关联强度的度量来表示物体之间的关系。在关系是非空间而非空间、离散而非连续且无法被意识察觉的情况下，我们直接从海马体-内嗅皮层功能磁共振成像适应信号重建出一种类似地图的知识结构。值得注意的是，最能预测隐式知识行为特征和血氧水平依赖适应的度量是未来状态的加权和，类似于为解释位置和网格细胞放电模式而提出的后继表征。
