## Frontmatter | | | | --- | --- | | Authors | [[Umut Güçlü]], [[Jordy Thielen]], [[Michael Hanke]], [[Marcel van Gerven]] | | Date | 2016/12 | | Source | [[Conference on Neural Information Processing Systems]] | | URL | http://papers.nips.cc/paper/by-source-2016-1108 | | Citation | Güçlü, U., Thielen, J., Hanke, M., & van Gerven, M. (2016). [[Brains on beats]]. In _Conference on Neural Information Processing Systems_. [[URL](http://papers.nips.cc/paper/by-source-2016-1108)]. #Conference | ## Abstract 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. ## PDF ![[Brains on beats.pdf]]