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Recently, the long short-term memory neural network (LSTM) has attracted wideinterest due to its success in many tasks. LSTM architecture consists of amemory cell and three gates, which looks similar to the neuronal networks inthe brain. However, there still lacks the evidence of the cognitiveplausibility of LSTM architecture as well as its working mechanism. In thispaper, we study the cognitive plausibility of LSTM by aligning its internalarchitecture with the brain activity observed via fMRI when the subjects read astory. Experiment results show that the artificial memory vector in LSTM canaccurately predict the observed sequential brain activities, indicating thecorrelation between LSTM architecture and the cognitive process of storyreading.

Bridging LSTM Architecture and the Neural Dynamics during Reading