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Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech
To understand how the human brain represents this information, one approach is to build encoding models that predict fMRI responses to natural language using representations extracted from neural network language models (LMs).
Multi-timescale Representation Learning in LSTM Language Models
Earlier work has demonstrated that dependencies in natural language tend to decay with distance between words according to a power law.
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