Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls - Towlson, Emma K.; Vértes, Petra E.; Müller-Sedgwick, Ulrich; Ahnert, Sebastian E. (Frontiers in Psychiatry, 2019)
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.