Studying brain circuit function with dynamic causal modeling for optogenetic fMRI. Bernal-Casas, D., Lee, H. J., Weitz, A. J., & Lee, J. H. Neuron, 93(3):522–532.e5, February, 2017. ![Studying brain circuit function with dynamic causal modeling for optogenetic fMRI [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Defining the large-scale behavior of brain circuits with cell type specificity is a major goal of neuroscience. However, neuronal circuit diagrams typically draw upon anatomical and electrophysiological measurements acquired in isolation. Consequently, a dynamic and cell type-specific connectivity map has never been constructed from simultaneous measurements across the brain. Here, we introduce dynamic causal modeling (DCM) for optogenetic fMRI experiments – which uniquely allow cell type-specific, brain-wide functional measurements – to parameterize the causal relationships among regions of a distributed brain network with cell type specificity. Strikingly, when applied to the brain-wide basal ganglia-thalamocortical network, DCM accurately reproduced the empirically observed time series, and the strongest connections were key connections of optogenetically stimulated pathways. We predict that quantitative and cell type-specific descriptions of dynamic connectivity, as illustrated here, will empower novel systems-level understanding of neuronal circuit dynamics and facilitate the design of more effective neuromodulation therapies.
@article{bernal-casas2017,
title = {Studying brain circuit function with dynamic causal modeling for optogenetic {fMRI}},
volume = {93},
issn = {0896-6273},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5472443/},
doi = {10.1016/j.neuron.2016.12.035},
abstract = {Defining the large-scale behavior of brain circuits with cell type specificity is a major goal of neuroscience. However, neuronal circuit diagrams typically draw upon anatomical and electrophysiological measurements acquired in isolation. Consequently, a dynamic and cell type-specific connectivity map has never been constructed from simultaneous measurements across the brain. Here, we introduce dynamic causal modeling (DCM) for optogenetic fMRI experiments – which uniquely allow cell type-specific, brain-wide functional measurements – to parameterize the causal relationships among regions of a distributed brain network with cell type specificity. Strikingly, when applied to the brain-wide basal ganglia-thalamocortical network, DCM accurately reproduced the empirically observed time series, and the strongest connections were key connections of optogenetically stimulated pathways. We predict that quantitative and cell type-specific descriptions of dynamic connectivity, as illustrated here, will empower novel systems-level understanding of neuronal circuit dynamics and facilitate the design of more effective neuromodulation therapies.},
number = {3},
urldate = {2021-07-13},
journal = {Neuron},
author = {Bernal-Casas, David and Lee, Hyun Joo and Weitz, Andrew J. and Lee, Jin Hyung},
month = feb,
year = {2017},
pmid = {28132829},
pmcid = {PMC5472443},
keywords = {david, DCM, data, reward circuit},
pages = {522--532.e5},
file = {Bernal-Casas et al. - 2017 - Studying brain circuit function with dynamic causa.pdf:/Users/lcneuro/Zotero/storage/DBMQQT5Z/Bernal-Casas et al. - 2017 - Studying brain circuit function with dynamic causa.pdf:application/pdf},
}
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