Mathematical tools improve theory and prediction in psychiatry

A Biological Psychiatry special issue


Philadelphia, PA, August 24, 2017

Recent years have seen an explosion in the use 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, which researchers hope will help explain mechanisms behind complex psychiatric diseases and improve treatment for patients. Biological Psychiatry presents a special issue titled “Computational Psychiatry” dedicated to these exciting advancements.

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 consists of a bewildering variety of approaches and findings that, unfortunately, often do not coalesce 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. But developing this type of theoretical understanding is not something the psychiatry field has emphasized. “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. Particularly because “computational techniques are ideally suited to understand and integrate how phenomena from the subcellular to the society lead to mental illness.” In addition, the techniques provide a way to deal with the increasing amounts of data and the complexity of psychiatric illnesses.

“What I find really exciting about this special issue is that it demonstrates that this approach is already starting to bear fruit in terms of improved understanding in psychiatry,” said Dr. Maia. This is demonstrated in the studies reviewed in the special issue, which use computational models to examine brain processes, such as learning, emotion, dopamine signaling and information processing, and how processes interact in deficits underlying psychiatric disease. The special issue also addresses the potential of mathematical frameworks for diagnosis and treatment.

“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.

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Notes for editors
The special issue is "Computational Psychiatry," Biological Psychiatry, volume 82, issue 6 (September 2017), published by Elsevier.

Copies of papers included in the issue are available to credentialed journalists upon request; please contact Rhiannon Bugno at Biol.Psych@UTSouthwestern.edu or +1 214 648 0880.

About Biological Psychiatry
Biological Psychiatry is the official journal of the Society of Biological Psychiatry, whose purpose is to promote excellence in scientific research and education in fields that investigate the nature, causes, mechanisms and treatments of disorders of thought, emotion, or behavior. In accord with this mission, this peer-reviewed, rapid-publication, international journal publishes both basic and clinical contributions from all disciplines and research areas relevant to the pathophysiology and treatment of major psychiatric disorders.

The journal publishes novel results of original research which represent an important new lead or significant impact on the field, particularly those addressing genetic and environmental risk factors, neural circuitry and neurochemistry, and important new therapeutic approaches. Reviews and commentaries that focus on topics of current research and interest are also encouraged.

Biological Psychiatry is one of the most selective and highly cited journals in the field of psychiatric neuroscience. It is ranked 6th out of 142 Psychiatry titles and 10th out of 258 Neurosciences titles in the Journal Citations Reports® published by Thomson Reuters. The 2016 Impact Factor score for Biological Psychiatry is 11.412.

About Elsevier
Elsevier is a global information analytics business that helps institutions and professionals progress science, advance healthcare and improve performance for the benefit of humanity. Elsevier provides digital solutions and tools in the areas of strategic research management, R&D performance, clinical decision support, and professional education; including ScienceDirect, Scopus, SciVal, ClinicalKey and Sherpath. Elsevier publishes over 2,500 digitized journals, including The Lancet and Cell, more than 35,000 e-book titles and many iconic reference works, including Gray's Anatomy. Elsevier is part of RELX Group, a global provider of information and analytics for professionals and business customers across industries. www.elsevier.com

Media contact
Rhiannon Bugno
Editorial Office, Biological Psychiatry
+1 214 648 0880
Biol.Psych@UTSouthwestern.edu