An Information Theoretic Characterisation of Auditory Encoding

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Abstract
The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content. Understanding how the brain makes sense of our acoustic environment remains a major challenge. One way to describe the complexity of our acoustic environment is in terms of information entropy: acoustic signals with high entropy convey large amounts of information, whereas low entropy signifies redundancy. To investigate how the brain processes this information, we controlled the amount of entropy in the signal by using pitch sequences. Participants listened to pitch sequences with varying amounts of entropy while we measured their brain activity using functional magnetic resonance imaging (fMRI). We show that the planum temporale (PT), a region of auditory association cortex, is sensitive to the entropy in pitch sequences. In two convergent fMRI studies, activity in PT increases as the entropy in the pitch sequence increases. The results establish PT as an important “computational hub” that requires less resource to encode redundant signals than it does to encode signals with high information content.