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Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752631/ https://www.ncbi.nlm.nih.gov/pubmed/31572229 http://dx.doi.org/10.3389/fpsyt.2019.00611 |
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author | Towlson, Emma K. Vértes, Petra E. Müller-Sedgwick, Ulrich Ahnert, Sebastian E. |
author_facet | Towlson, Emma K. Vértes, Petra E. Müller-Sedgwick, Ulrich Ahnert, Sebastian E. |
author_sort | Towlson, Emma K. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6752631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67526312019-09-30 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. Front Psychiatry Psychiatry 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. Frontiers Media S.A. 2019-09-12 /pmc/articles/PMC6752631/ /pubmed/31572229 http://dx.doi.org/10.3389/fpsyt.2019.00611 Text en Copyright © 2019 Towlson, Vértes, Müller-Sedgwick and Ahnert http://creativecommons.org/licenses/by/4.0/ 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. |
spellingShingle | Psychiatry Towlson, Emma K. Vértes, Petra E. Müller-Sedgwick, Ulrich Ahnert, Sebastian E. Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title | Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title_full | Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title_fullStr | Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title_full_unstemmed | Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title_short | Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls |
title_sort | brain networks reveal the effects of antipsychotic drugs on schizophrenia patients and controls |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752631/ https://www.ncbi.nlm.nih.gov/pubmed/31572229 http://dx.doi.org/10.3389/fpsyt.2019.00611 |
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