UW Department of Psychiatry

Grand Rounds | Dr. Larissa Albantakis
2026-03-13 12:00 - 13:15 (America/Chicago)
Hybrid Event – WisPIC 6001 Research Park Blvd, Madison WI 53719, Commons Room 1616 or Virtual
Light refreshments will be provided from 12:00-12:15pm and the presentation will run from 12:15-1:15pm.

About the Speaker:

Larissa Albantakis, PhD is a computational neuroscientist and Assistant Professor of Computational Psychiatry. Her research explores the relationship between causation, complexity, consciousness, and cognition, and their quantitative assessments in neural network models and neurophysiological data from healthy subjects and clinical patient populations. Dr. Albantakis’ research group is aimed at developing novel computational tools to analyze and model the origins, symptoms, and potential for interventions of mental disorders in a causal, mechanistic manner at the individual and group level. She is affiliated with the Center for Sleep and Consciousness at the University of Wisconsin-Madison.
Dr. Albantakis obtained her Diploma (MSc) 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 Dr. Gustavo Deco. Her PhD research focused on using large-scale, biophysically-realistic neural models and dynamical systems theory to understand the neural mechanisms underlying sensorimotor decision-making in contexts where subjects have multiple choice-alternatives and the option to “change one’s mind.”
Dr. Albantakis has been at the University of Wisconsin-Madison since 2012, where she worked together with Dr. Giulio Tononi before starting her own research group in 2022. Her work with Dr. Tononi proved essential for developing (1) the mathematical formalism of the integrated information theory (IIT) of consciousness; (2) a demonstration of the adaptive advantages of recurrent architectures and high information integration in evolving artificial organisms; (3) a body of work assessing causal relations across micro and macro spatio-temporal scales in artificial neural networks; (4) an account of the relation between causal and dynamical complexity in discrete dynamical systems; (5) a quantitative framework of actual causation (“what caused what”); and (6) a formal account of informational autonomy of an agent from its environment.
Learning objectives:
1) Describe the core biophysical principles of transcranial electrical stimulation with temporal interference (TES-TI)—including carrier vs. envelope frequencies, steerability, and the depth/focality tradeoffs relative to conventional tES and other neuromodulation modalities.
2) Identify key safety, tolerability, and feasibility considerations for TES-TI in humans (e.g., frequency-dependent tolerability, acute adverse events, and current intensity constraints), and interpret how these considerations inform trial design and monitoring in psychiatric populations.
3) Identify the interdisciplinary considerations that would need alignment before TES-TI could be responsibly tested in psychiatric populations (e.g., patient selection, endpoints meaningful to care teams, risk communication, and follow-up burden).

Related Articles:
Albantakis L and Tononi G (in press) Precision Neuromodulation in Psychiatry: Focus on Temporal Interference Stimulation. American Journal of Psychiatry.
Missey F, Acerbo E, Dickey AS, et al.: Non-invasive Temporal Interference Stimulation of the Hippocampus Suppresses Epileptic Biomarkers in Patients with Epilepsy: Biophysical Differences between Kilohertz and Amplitude Modulated Stimulation. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation 2025; 0

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