How is it that the brain - a three-pound mass of mostly fat and protein - can generate cognition and experience? It's a question that has puzzled philosophers for centuries. With recent advances in mathematics, computer science, and neuroscience, the endeavor to understand the neural underpinning of experience has finally moved to the domain of empirical research. As part of that endeavor, I utilize insights from graph theory, information theory, and nonlinear dynamics to better understand large-scale neural information flow, and how that relates to different brain states.

I also care deeply about science communication. I maintain a websiteTwitter account, and Instagram account devoted to communicating science. 

I am a National Science Foundation Graduate Research Fellow. 


Toker, D., Sommer, F., and D'Esposito, M. The Chaos Decision Tree Algorithm: A Fully Automated Tool for the Experimental Study of Chaotic Dynamics. arXiv. 2019.

Toker, D., Sommer, F.  Information Integration In Large Brain Networks. PLoS Computational Biology. 2019.

Lositsky, O., Chen, J., Toker, D., Honey, C.J., Shvartsman, M., Poppenk, J.L., Hasson, U. and Norman, K.A., 2016. Neural pattern change during encoding of a narrative predicts retrospective duration estimates. eLife5, p.e16070.

Toker D, Sommer F. Moving Past the Minimum Information Partition: How To Quickly and Accurately Calculate Integrated Information. arXiv preprint arXiv:1605.01096. 2016 May 3.

Bishop SJ, Aguirre GK, Nunez-Elizalde AO, Toker D. Seeing the world through non rose-colored glasses: anxiety and the amygdala response to blended expressions. Frontiers in human neuroscience. 2015;9.