Cargando…
Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses
Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the aver...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4678290/ https://www.ncbi.nlm.nih.gov/pubmed/26659399 http://dx.doi.org/10.1371/journal.pone.0144796 |
_version_ | 1782405428604305408 |
---|---|
author | Bennett, Maxwell R. Farnell, Les Gibson, William G. Lagopoulos, Jim |
author_facet | Bennett, Maxwell R. Farnell, Les Gibson, William G. Lagopoulos, Jim |
author_sort | Bennett, Maxwell R. |
collection | PubMed |
description | Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular) connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular) connections. |
format | Online Article Text |
id | pubmed-4678290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-46782902015-12-31 Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses Bennett, Maxwell R. Farnell, Les Gibson, William G. Lagopoulos, Jim PLoS One Research Article Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular) connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular) connections. Public Library of Science 2015-12-14 /pmc/articles/PMC4678290/ /pubmed/26659399 http://dx.doi.org/10.1371/journal.pone.0144796 Text en © 2015 Bennett et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bennett, Maxwell R. Farnell, Les Gibson, William G. Lagopoulos, Jim Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title | Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title_full | Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title_fullStr | Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title_full_unstemmed | Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title_short | Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses |
title_sort | cortical network models of firing rates in the resting and active states predict bold responses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4678290/ https://www.ncbi.nlm.nih.gov/pubmed/26659399 http://dx.doi.org/10.1371/journal.pone.0144796 |
work_keys_str_mv | AT bennettmaxwellr corticalnetworkmodelsoffiringratesintherestingandactivestatespredictboldresponses AT farnellles corticalnetworkmodelsoffiringratesintherestingandactivestatespredictboldresponses AT gibsonwilliamg corticalnetworkmodelsoffiringratesintherestingandactivestatespredictboldresponses AT lagopoulosjim corticalnetworkmodelsoffiringratesintherestingandactivestatespredictboldresponses |