An example of mixed selectivity in a network model trained on 20 different cognitive tasks.
Yang, G. R., Song, H. F., Newsome, W. T., & Wang, X. J. (2017). Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasksbioRxiv, 183632.

To learn more about mixed selectivity and its importance for cognition, see these papers:
Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. (2013) The importance of mixed selectivity in complex cognitive tasks. Nature, 497, 585-590, doi:10.1038/nature12160. View PDF »    

Fusi, S., Miller, E.K., and Rigotti, M. (2016) Why neurons mix: High dimensionality for higher cognition.  Current Opinion in Neurobiology. 37:66-74  doi:10.1016/j.conb.2016.01.010. View PDF »

About the Author

The Miller Lab uses experimental and theoretical approaches to study the neural basis of the high-level cognitive functions that underlie complex goal-directed behavior.