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Front Psychiatry. 2019 Sep 12;10:611. doi: 10.3389/fpsyt.2019.00611. eCollection 2019.

Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.

Author information

1
Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA, United States.
2
Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States.
3
Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.
4
Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
5
Barnet Enfield Haringey Mental Health NHS Trust, Springwell Centre, Barnet Hospital, London, United Kingdom.
6
Theory of Condensed Matter Group, Department of Physics, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.
7
Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.

Abstract

The study of brain networks, including those derived from functional neuroimaging data, attracts a 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 understanding brain and mind disorders. We explore resting state functional Magnetic Resonance Imaging (fMRI) data through network 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 a 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 with controls. Our data then reveal that the antipsychotic medications mitigate this effect, shifting the metrics toward 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 behavioral differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioral 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:

antipscychotic medication; brain network; fMRI; network science; schizophrenia

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