The Mathematical Characterization of Brain States

How useful would it be to attain a formal, mathematical characterization of the neuro-dynamics of
individual patients affected by stroke, Parkinson’s Disease or other neuro-degenerative disorders in
a straightforward manner? Beyond the obvious clinical application, the answer to that question
depends on attaining accurate models of the brain, on how general are their predictions, and on
how adaptive to the clinical context and in particular to the single patient medical praxis. Current
tools for brain state characterization have made a remarkable progress in the past ten years, yielding
mathematical techniques, gradually amassing a huge amount of knowledge about brain structure
and dynamics during resting state and performance of specific tasks. Pending further research to
perfect them, these techniques are to emerge as promise both for a deeper, more formal
understanding of brain function, and as a reliable tool for the clinical diagnose of neuro-
degenerative disorders.

Ignasi Cos (Barcelona, 1973; MEng Electronics 1996 – Politecnico di Torino, MEng Telecomunications
1997 – Universitat Politècnica de Catalunya; PhD in Cognitive Science and Artificial Intelligence 2006
- University of Edinburgh). After PhD graduation, he went to train as a postdoctoral fellow at the
University of California, Berkeley, and at the University of Montreal, where he specialized in the
neuroscience of motor control and decision-making. He also trained in theoretical neuroscience at
the Université Pierre and Marie Curie, at the Brain and Spine Institute of Paris, and at the Universitat
Pompeu Fabra. He is currently an Assistant Professor at the Faculty of Mathematics & Informatics,
Universitat de Barcelona, and a member of the Institute of Mathematics (IMUB). His research
focuses on developing mathematical techniques to characterize the brain operation, as a whole, in
the context of how the brain controls movement.