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Brains on Beats

We developed task-optimized deep neural networks (DNNs) that achieved state-of-the-art performance in different evaluation scenarios for automatic music tagging. These DNNs were subsequently used to probe the neural representations of music. Representational similarity analysis revealed the existence of a representational gradient across the superior temporal gyrus (STG). Anterior STG was shown to be more sensitive to low-level stimulus features encoded in shallow DNN layers whereas posterior STG was shown to be more sensitive to high-level stimulus features encoded in deep DNN layers.

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Co-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipAuthorshipWorks onAuthorshipAuthorshipAuthorshipTopic signalWBrains on Beatspreprint / 2016AUmut GüçlüResearcherAJordy ThielenResearcherAMichael HankeResearcherAMarcel A. J. Van GervenResearcherTNeurons and Cognition1536 works
PaperSignal 105 links

Brains on Beats

preprint / 2016

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