Kurth-Nelson Zeb, Barnes Gareth, Sejdinovic Dino, Dolan Ray, Dayan Peter
Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.
Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.
Elife. 2015 Jan 23;4:e04919. doi: 10.7554/eLife.04919.
Electrophysiological data disclose rich dynamics in patterns of neural activity evoked by sensory objects. Retrieving objects from memory reinstates components of this activity. In humans, the temporal structure of this retrieved activity remains largely unexplored, and here we address this gap using the spatiotemporal precision of magnetoencephalography (MEG). In a sensory preconditioning paradigm, 'indirect' objects were paired with 'direct' objects to form associative links, and the latter were then paired with rewards. Using multivariate analysis methods we examined the short-time evolution of neural representations of indirect objects retrieved during reward-learning about direct objects. We found two components of the evoked representation of the indirect stimulus, 200 ms apart. The strength of retrieval of one, but not the other, representational component correlated with generalization of reward learning from direct to indirect stimuli. We suggest the temporal structure within retrieved neural representations may be key to their function.
电生理数据揭示了由感觉对象诱发的神经活动模式中的丰富动态。从记忆中检索对象会恢复这种活动的组成部分。在人类中,这种检索到的活动的时间结构在很大程度上仍未得到探索,在这里我们利用脑磁图(MEG)的时空精度来填补这一空白。在一种感觉预条件范式中,“间接”对象与“直接”对象配对以形成关联链接,然后后者与奖励配对。我们使用多变量分析方法研究了在关于直接对象的奖励学习过程中检索到的间接对象的神经表征的短期演变。我们发现间接刺激诱发表征的两个成分,相隔200毫秒。其中一个而非另一个表征成分的检索强度与奖励学习从直接刺激到间接刺激的泛化相关。我们认为检索到的神经表征中的时间结构可能是其功能的关键。