Mouse fMRI with optogenetic silencing reveals neural interactions underlying resting-state fMRI

Presented During:

Monday, June 24, 2024: 5:45 PM - 7:00 PM
COEX  
Room: Grand Ballroom 104-105  

Poster No:

1534 

Submission Type:

Abstract Submission 

Authors:

Hyun Seok Moon1, Thanh Vo1,2,3, Seong-Gi Kim1,2,3

Institutions:

1Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Sungkyunkwan University, Suwon, Korea, Republic of, 3Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea, Republic of

First Author:

Hyun Seok Moon  
Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS)
Suwon, Korea, Republic of

Co-Author(s):

Thanh Vo  
Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS)|Department of Biomedical Engineering, Sungkyunkwan University, Sungkyunkwan University|Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University
Suwon, Korea, Republic of|Suwon, Korea, Republic of|Suwon, Korea, Republic of
Seong-Gi Kim  
Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS)|Department of Biomedical Engineering, Sungkyunkwan University, Sungkyunkwan University|Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University
Suwon, Korea, Republic of|Suwon, Korea, Republic of|Suwon, Korea, Republic of

Introduction:

Resting-state (RS) fMRI is a potent tool for mapping brain-wide functional connectivity (FC), yet its mechanism remains not fully understood. RS FC only partially corresponds to monosynaptic structural connectivity (SC) while exhibiting strong interhemispheric connections, implicating polysynaptic or indirect connectivity (Honey et al. 2009, Grandjean et al. 2017). However, a causal link between spontaneous neural interactions and FC has yet to be established. Optogenetic fMRI may resolve this question by mapping changes in neural activity induced by precise spatiotemporal neural manipulation (effective connectivity; EC). Notably, optogenetic activation of local excitatory neurons revealed predominantly ipsilateral connections resembling SC (Bauer et al. 2018, Kim et al. 2023). We hypothesized that this discrepancy arises because the upregulation of neural activity does not account for spontaneously occurring connectivity. To address this, we employed optogenetic silencing to assess ongoing interactions during RS. Our study investigated (de)activation patterns resulting from excitatory and inhibitory neuron-specific optogenetic EC and their relationship with SC and FC (Figure 1A).

Methods:

For optogenetic fMRI, VGAT-ChR2-EYFP and Thy1-ChR2-EYFP mice were used for specific modulation of inhibitory/excitatory neurons. We prepared a thinned-skull cranial window covering the entire dorsal cortex for cortex-wide patterned optogenetics (Kim et al. 2023). Optogenetic CBV-weighted fMRI data were acquired at 9.4T (Bruker Biospec). Resting state BOLD fMRI data were acquired at 15.2T (Bruker Biospec) in eight C57BL/6N mice. Mice were anesthetized under a continuous infusion of dexmedetomidine (0.05 mg/kg/h) with 0.3% isoflurane during experiments. All fMRI data were preprocessed and normalized to the Allen mouse brain atlas (Wang et al. 2020). Whole-brain SC dataset was obtained from a previous study (Coletta et al. 2020), which contains a full connectivity matrix among 15,314 parcels across the brain. To match the SC resolution, our RS fMRI dataset was resampled to this parcellation, and an FC matrix was generated by pairwise correlation between parcels. For ROI-level analysis, SC and FC were further computed in 86 atlas-based bilateral cortical ROIs.

Results:

Optogenetic fMRI data were acquired by stimulating 6 cortical areas (Figure 1B). Overall, FC exhibited more extensive connectivity than SC. Notably, optogenetic activation induced localized responses in structurally connected areas, while optogenetic silencing led to more widespread responses. Quantifying connectivity strengths in 86 bilateral cortical ROIs (Figure 1C), we found a stronger association between FC strengths and optogenetic silencing-induced responses, compared to optogenetic activation (Figure 2A). We further examined intra- and inter-hemispheric connections separately, since interhemispheric connectivity is a hallmark of FC (Figure 2B, C). Optogenetic silencing exhibited extensive connections to contralateral regions, implying that interhemispheric FC may arise from neural interactions via indirect structural pathways. We also found a strong linear relationship between the strength of intrahemispheric connections and their contralateral counterparts (Figure 2D), while the slope of linear regression was highest (~0.5) for FC and optogenetic silencing, followed by optogenetic activation (~0.3), and lowest for SC (~0.1) (Figure 2E).
Supporting Image: Figure1.png
Supporting Image: Figure2.png
 

Conclusions:

Our study has several important implications. First, the connectivity patterns by optogenetic silencing were highly correlated with FC, implying that FC depends more on spontaneous activity than evoked activity. Second, we revealed that cortical regions have resting-state interactions not only with contralateral homotopic regions but also with heterotopic regions, possibly via polysynaptic structural pathways. The results suggest that FC originates, at least partially, from neural interaction during RS.

Brain Stimulation:

Direct Electrical/Optogenetic Stimulation 2

Modeling and Analysis Methods:

Connectivity (eg. functional, effective, structural) 1

Keywords:

ANIMAL STUDIES
Cortex
FUNCTIONAL MRI
HIGH FIELD MR
Other - Optogenetics

1|2Indicates the priority used for review

Provide references using author date format

Honey, C.J. (2009), Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences 106, 2035-2040.
Grandjean, J. (2017), Structural basis of large-scale functional connectivity in the mouse. Journal of Neuroscience 37, 8092-8101.
Bauer, A.Q. (2018), Effective Connectivity Measured Using Optogenetically Evoked Hemodynamic Signals Exhibits Topography Distinct from Resting State Functional Connectivity in the Mouse. Cerebral Cortex 28, 370-386.
Kim, S. (2023), Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics. Neuron 111, 1732-1747.
Wang, Q. (2020), The Allen mouse brain common coordinate framework: a 3D reference atlas. Cell 181, 936-953. e920.
Coletta, L. (2020), Network structure of the mouse brain connectome with voxel resolution. Science Advances 6, eabb7187.