| First Author | Bernal-Casas D | Year | 2017 |
| Journal | Neuron | Volume | 93 |
| Issue | 3 | Pages | 522-532.e5 |
| PubMed ID | 28132829 | Mgi Jnum | J:249914 |
| Mgi Id | MGI:6100164 | Doi | 10.1016/j.neuron.2016.12.035 |
| Citation | Bernal-Casas D, et al. (2017) Studying Brain Circuit Function with Dynamic Causal Modeling for Optogenetic fMRI. Neuron 93(3):522-532.e5 |
| abstractText | 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. |
