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Updated: Mar 8, 2026

Optogenetic Functional MRI

Optogenetic Functional MRI

Published on: April 19, 2016

Studying Brain Circuit Function with Dynamic Causal Modeling for Optogenetic fMRI.

David Bernal-Casas¹, Hyun Joo Lee¹, Andrew J Weitz²

¹Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA.

|January 31, 2017

Summary

This summary is machine-generated.

This study introduces a new method combining dynamic causal modeling with optogenetic fMRI to map brain circuit connectivity cell-type specifically. This approach reveals dynamic brain network connections for better understanding and neuromodulation therapies.

Keywords:

basal ganglia direct and indirect pathways dynamic causal modeling ofMRI optogenetic fMRI

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Optogenetic Functional MRI

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Published on: April 19, 2016

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Published on: October 13, 2023

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Area of Science:

Neuroscience
Systems Neuroscience
Computational Neuroscience

Background:

Understanding large-scale brain circuit behavior requires cell type-specific analysis.
Current neuronal circuit mapping relies on isolated anatomical and electrophysiological data.
A dynamic, cell-type-specific brain-wide connectivity map is currently lacking.

Purpose of the Study:

To introduce dynamic causal modeling (DCM) for optogenetic fMRI experiments.
To enable cell-type-specific, brain-wide functional measurements of neuronal networks.
To parameterize causal relationships within distributed brain networks with cell type specificity.

Main Methods:

Integration of dynamic causal modeling (DCM) with optogenetic fMRI.
Acquisition of simultaneous, cell-type-specific, brain-wide functional measurements.
Application to the brain-wide basal ganglia-thalamocortical network.

Main Results:

DCM for optogenetic fMRI accurately reproduced empirical time series data.
The strongest connections identified corresponded to optogenetically stimulated pathways.
Successful parameterization of causal relationships in a distributed brain network.

Conclusions:

Quantitative, cell-type-specific dynamic connectivity descriptions are now achievable.
This approach advances systems-level understanding of neuronal circuit dynamics.
Facilitates the design of more effective neuromodulation therapies.