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Front. Neurosci. | doi: 10.3389/fnins.2018.00957

COMPASS: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry

 Ali Yousefi1, 2*,  Angelique C. Paulk3, Ishita Basu4,  Darin D. Dougherty4, Emad N. Eskandar5, 6,  Uri T. Eden2 and  Alik S. Widge4, 7
  • 1Harvard Medical School, United States
  • 2Boston University, United States
  • 3Department of Neurology, Massachusetts General Hospital, Harvard Medical School, United States
  • 4Department of Psychiatry Harvard Medical School, United States
  • 5Massachusetts General Hospital, Harvard Medical School, United States
  • 6Albert Einstein College of Medicine, United States
  • 7University of Minnesota Twin Cities, United States

Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and few of toolboxes and analytical platforms are capable of processing these categories of signals. We developed the Computational Psychiatry Adaptive State-Space (COMPASS) toolbox, an open-source MATLAB-based software package, to be easy to use and capable of integrating signals with a variety of distributions. COMPASS has tools to process signals with continuous-valued and binary measurements or signals with incomplete - missing or censored - measurements, which makes it well suited for processing signals captured during psychophysical tasks After specifying a few parameters in a small set of user-friendly functions, COMPASS allows the user to efficiently fit a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can be tested using goodness-of-fit methods. Here, we demonstrate that COMPASS can replicate two computational behavior analyses from different groups. COMPASS replicates and, in one case, slightly improves on the original modeling results. We also demonstrate COMPASS application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.

Keywords: Computational Psychiatry, Mathematical Behavioral Analysis, computational methods, state-space modeling, Open Source Software, Cognitive neuroscience

Received: 31 Jul 2018; Accepted: 30 Nov 2018.

Edited by:

J L. Lujan, Mayo Clinic College of Medicine & Science, United States

Reviewed by:

Fidel Santamaria, University of Texas at San Antonio, United States
Suelen Lucio Boschen, Mayo Clinic, United States  

Copyright: © 2018 Yousefi, Paulk, Basu, Dougherty, Eskandar, Eden and Widge. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Ali Yousefi, Harvard Medical School, Boston, United States, ayousefi@mgh.harvard.edu