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Random Forest Segregation of Drug Responses May Define Regions of Biological Significance
The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783407/ https://www.ncbi.nlm.nih.gov/pubmed/27014046 http://dx.doi.org/10.3389/fncom.2016.00021 |
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author | Bukhari, Qasim Borsook, David Rudin, Markus Becerra, Lino |
author_facet | Bukhari, Qasim Borsook, David Rudin, Markus Becerra, Lino |
author_sort | Bukhari, Qasim |
collection | PubMed |
description | The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies. |
format | Online Article Text |
id | pubmed-4783407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47834072016-03-24 Random Forest Segregation of Drug Responses May Define Regions of Biological Significance Bukhari, Qasim Borsook, David Rudin, Markus Becerra, Lino Front Comput Neurosci Neuroscience The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies. Frontiers Media S.A. 2016-03-09 /pmc/articles/PMC4783407/ /pubmed/27014046 http://dx.doi.org/10.3389/fncom.2016.00021 Text en Copyright © 2016 Bukhari, Borsook, Rudin and Becerra. 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) or licensor 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 | Neuroscience Bukhari, Qasim Borsook, David Rudin, Markus Becerra, Lino Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title | Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title_full | Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title_fullStr | Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title_full_unstemmed | Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title_short | Random Forest Segregation of Drug Responses May Define Regions of Biological Significance |
title_sort | random forest segregation of drug responses may define regions of biological significance |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783407/ https://www.ncbi.nlm.nih.gov/pubmed/27014046 http://dx.doi.org/10.3389/fncom.2016.00021 |
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