Figure collage from my published work.
Scientific research. I am interested in formal mathematical analysis of two unexplained phenomena: consciousness and emergence. To understand the biological basis of consciousness, my research has focused on how the spatiotemporal scale of conscious experience emerges in the brain, issues around falsifying contemporary theories of consciousness, and using information theory to track the differences in neural activity between consciousness and unconsciousness. Another central goal of my research is to develop formal measures of emergence. Specifically, I have focused on how dimension reductions can improve causal models of Boolean networks, how macroscales can act as error-correcting codes to reduce the noise in causal relationships, as well as under what conditions of connectivity networks develop informative macroscales. Recently, I have become interested in deep learning and creating toolkits to examine the causal structure of artificial neural networks. This has also led to developing a theory of the neural purpose of dreaming, wherein the goal of dreams is to combat daily overfitting of the brain, which I also think just might be the purpose of fictions themselves.
Selected publications.
- Mattsson, S., Michaud, E. J., & Hoel, E. (2020). Examining the causal structures of deep neural networks using information theory. arXiv preprint arXiv:2010.13871.
- Hoel, E. (2020). The Overfitted Brain: Dreams evolved to assist generalization. arXiv preprint arXiv:2007.09560.
- Kleiner, J., & Hoel, E. (2020). Falsification and consciousness. arXiv preprint arXiv:2004.03541.
- Klein, B., & Hoel, E. (2020). The Emergence of Informative Higher Scales in Complex Networks. Complexity, 2020.
- Albantakis, L., Marshall, W., Hoel, E., & Tononi, G. (2019). What caused what? A quantitative account of actual causation using dynamical causal networks. Entropy, 21(5), 459.
- Wenzel, M., Han, S., Smith, E. H., Hoel, E., Greger, B., House, P. A., & Yuste, R. (2019). Reduced Repertoire of Cortical Microstates and Neuronal Ensembles in Medically Induced Loss of Consciousness. Cell systems, 8(5), 467-474.
- Hoel, E. (2017). When the map is better than the territory. Entropy, 19(5), 188.
- Hoel, E., Albantakis, L., Marshall, W., & Tononi, G. (2016). Can the macro beat the micro? Integrated information across spatiotemporal scales. Neuroscience of Consciousness, 2016(1).
- Hoel, E., Albantakis, L., Cirelli, C., & Tononi, G. (2016). Synaptic refinement during development and its effect on slow-wave activity: a computational study. Journal of neurophysiology, 115(4), 2199-2213.
- Hoel, E., Albantakis, L., & Tononi, G. (2013). Quantifying causal emergence shows that macro can beat micro. Proceedings of the National Academy of Sciences, 110(49), 19790-19795.
News media discussing my scientific work.
- Tufts Now (2021). "A New Theory for Why We Dream"
- Discover Magazine (2020). "How Artificial Neural Networks Paved the Way For A Dramatic New Theory of Dreams"
- Forbes (2018). "30 Under 30 profiles"
- WIRED (2017). "New Math Untangles the Mysterious Nature of Causality"
- Nautilus (2017). "A Theory of Consciousness Can Help Build a Theory of Everything"