Mathematical Tools Improve Theory, Prediction in Psychiatry

With the recent emergence of mathematical models to integrate insights emerging from studies of the brain and behavior, this approach has been used to develop new theoretical perspectives that can enrich data analysis to help explain mechanisms behind complex psychiatric diseases improved psychiatric treatment. The issue was organized by guest editors Dr. Tiago Maia of University of Lisbon, Dr. Michael Frank of Brown University, and Dr. Quentin Huys of University of Zurich and ETH Zurich.

“The state-of-the-art in research in psychiatry involves a bewildering variety of approaches and findings that often do not combine into a coherent whole,” said Dr. Maia.

But advancements in mathematical theory-based approaches are now making it possible to provide a more unified explanation with the power to predict phenomena.

“This approach has been a cornerstone of monumental achievements in theoretical physics that have had tremendous practical impact,” said Dr. Maia.

“I see theory-based computational psychiatry as a long-overdue effort to finally bring to psychiatry the same rigorous mathematical tools that have so successfully shaped fields such as physics — enriched now with the capacity for computational simulations, which vastly expand the range of problems that can be addressed mathematically.”

According to Dr. Huys, although the clinical utility of mathematical models in mental health remains to be proven, great excitement around computational psychiatry reflects the belief in its potential.

“The studies included in this issue of Biological Psychiatry showcase the utility of this formal approach and that it can enrich understanding and guide principled questions in need of further investigation, spanning a range of issues of central importance,” said Dr. Frank.

Reference: https://www.sciencedaily.com/releases/2017/08/170824094039.htm

 

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