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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Psychiatry | doi: 10.3389/fpsyt.2019.00611

Brain networks reveal the effects of antipsychotic drugs on schizophrenia patients and controls

  • 1Center for Complex Network Research, Department of Physics, Northeastern University, United States
  • 2MIT Media Lab, United States
  • 3Behavioural and Clinical Neuroscience Institute, Department of Psychology, Faculty of Biology, University of Cambridge, United Kingdom
  • 4Department of Psychology, Faculty of Biology, University of Cambridge, United Kingdom
  • 5Barnet Enfield and Haringey Mental Health Trust, United Kingdom
  • 6Sainsbury Laboratory, University of Cambridge, United Kingdom
  • 7Department of Physics, Faculty of Physics and Chemistry, University of Cambridge, United Kingdom

The study of brain networks, including derived from functional neuroimaging data, attracts broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can potentially offer new, quantitative diagnostic methods, and a framework for better understand- ing brain and mind disorders. We explore resting state fMRI data through net- work measures. We construct networks representing 15 healthy individuals and 12 schizophrenia patients (males and females), all of whom are administered three drug treatments: (i) a placebo; and two antipsychotic medications (ii) aripiprazole and; (iii) sulpiride. We compare these resting state networks to performance at an “N-back” working memory task. We demonstrate that not only is there a distinctive network architecture in the healthy brain that is disrupted in schizophrenia, but also that both networks respond to antipsychotic medication. We first reproduce the established finding that brain networks of schizophrenia patients exhibit increased efficiency and reduced clustering compared to controls. Our data then reveals that the antipsychotic medications mitigate this effect, shifting the metrics towards those observed in healthy volunteers, with a marked difference in efficacy between the two drugs. Additionally, we find that aripiprazole considerably alters the network statistics of healthy controls. Examining the “N-back” working memory task, we establish that aripiprazole also adversely affects their performance. This suggests that changes to macroscopic brain network architecture result in measurable behavioural differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioural data. The small sample size is an inherent limitation, and means a degree of caution is warranted in interpreting the findings. Our results lay the groundwork for an objective methodology with which to calculate and compare the efficacy of different treatments of mind and brain disorders.

Keywords: Schizophrenia, fMRI, Network Science, brain network, Antipscychotic

Received: 26 Apr 2019; Accepted: 31 Jul 2019.

Edited by:

Unn Kristin Haukvik, Faculty of Medicine, University of Oslo, Norway

Reviewed by:

David M. Cole, University of Zurich, Switzerland
Nina Kraguljac, University of Alabama at Birmingham, United States  

Copyright: © 2019 Towlson, Vertes, Müller and Ahnert. 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. Emma K. Towlson, Center for Complex Network Research, Department of Physics, Northeastern University, Boston, United States, ektowlson@gmail.com