Larissa Albantakis, PhD

Biography


Larissa Albantakis is an Associate Scientist at the Wisconsin Institute for Sleep and Consciousness, University of Wisconsin—Madison. She obtained her Diploma in Physics from Ludwig-Maximilians University in Munich in 2007, and her PhD in Computational Neuroscience from Universitat Pompeu Fabra in Barcelona in 2011 under the supervision of Gustavo Deco. She has been at the University of Wisconsin since 2012, working together with Giulio Tononi on Integrated Information Theory, and aims to develop a principled account of causation and causal autonomy. Her blog “Conscious(ness) Realist” provides publication reviews and commentaries on topics related to consciousness science and its theories.

Research Interests: Consciousness, Causation and Causal Analysis, Information, Complex System Science, (Artificial) Neural Networks, Computational Neuroscience, Cognition, Decision-making, Free Will, Artificial Life/Intelligence.

Selected Publications


Albantakis L (2021) Quantifying the Autonomy of Structurally Diverse Automata: A Comparison of Candidate Measures. Entropy, 23(11): 1415. doi: 10.3390/e23111415

Grasso* M, Albantakis* L, Lang JP, Tononi G (2021) Causal reductionism and causal structures. Nature Neuroscience, 24: 1348-1355. doi: 10.1038/s41593-021-00911-8

Albantakis L, Marshall W, Hoel E, Tononi G (2019) What Caused What? A Quantitative Account of Actual Causation Using Dynamical Causal Networks. Entropy, 21:459. doi: 10.3390/e21050459

Albantakis L, Tononi G (2019) Causal Composition: Structural Differences among Dynamically Equivalent Systems. Entropy, 2019, Vol 21, Page 989 21:989. doi: 10.3390/e21100989

Marshall W, Albantakis L, Tononi G (2018) Black-boxing and cause-effect power. PLOS Comput Biol, 14:e1006114. doi: 10.1371/journal.pcbi.1006114

Marshall W, Kim H, Walker SI, Tononi G, Albantakis L (2017) How causal analysis can reveal autonomy in models of biological systems. Philos Trans A Math Phys Eng Sci 375:20160358. doi: 10.1098/rsta.2016.0358

Hoel EP, Albantakis L, Marshall W, Tononi G (2016) Can the macro beat the micro? Integrated information across spatiotemporal scales. Neurosci Conscious, 2016. doi: 10.1093/nc/niw012

Albantakis L, Tononi G (2015) The Intrinsic Cause-Effect Power of Discrete Dynamical Systems—From Elementary Cellular Automata to Adapting Animats. Entropy, 17:5472–5502. doi: 10.3390/e17085472

Albantakis L, Hintze A, Koch C, Adami C, Tononi G (2014) Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity. PLoS Comput Biol, 10:e1003966. doi: 10.1371/journal.pcbi.1003966

Oizumi* M, Albantakis* L, Tononi G (2014) From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0. PLoS Comput Biol, 10:e1003588. doi: 10.1371/journal.pcbi.1003588

Hoel EP, Albantakis L, Tononi G (2013) Quantifying causal emergence shows that macro can beat micro. PNAS, 110:19790–19795. doi: 10.1073/pnas.1314922110