Gray matter networks in the mouse brain
Marco Pagani1,2, Angelo Bifone1, and Alessandro Gozzi1

1Istituto Italiano di Tecnologia, Rovereto, Italy, 2Center for Mind and Brain Sciences, Rovereto, Italy

Synopsis

Structural covariance MRI (scMRI) has highlighted robust gray matter networks encompassing known neuroanatomical systems of the human brain. The application of scMRI in the mouse can provide insights on the elusive neurobiological determinants underlying the emergence of this phenomenon. We show that the mouse brain contains robust inter-hemispheric anatomical covariance networks recapitulating anatomical features observed in humans. Our findings pave the way to the use of mouse genetics to investigate the biological underpinnings of scMRI networks and their aberration in brain disorders.

PURPOSE

The presence of correlative brain networks between regional gray matter volumes as measured across-subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI)1-2. Complementary to well-known brain mapping modalities like functional connectivity and diffusion-weighted imaging, scMRI can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states3. Despite the emerging use of scMRI to study the brain structural architecture, fundamental questions regarding the genetic and environment contribution to the development of these networks remain largely unanswered. Studies on laboratory mice amenable to genetic and experimental manipulation can complement human research on the emergence of covariance and generate novel hypothesis about the etiopathological origin of aberrant scMRI findings in human brain diseases2. To map scMRI networks, we employed high resolution structural MRI coupled with voxel-based morphometry in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J).

METHODS

High-resolution morpho-anatomical T2-weighted MR imaging of mouse brains was performed in a sample of wild-type (n=53) paraformaldehyde fixed specimens. Local gray matter volumes were mapped using VBM4. Briefly, a study-based template was created aligning high-resolution T2W images to a common reference space using affine and diffeomorphic registrations. Individual images of the two groups were then nonlinearly registered to the study-based template using diffeomorphic registration. Gray matter of spatially normalized subjects was then segmented, modulated and smoothed. Neuroanatomical volumes of a parcellated reference atlas were registered to each scan, thus avoiding operator dependent bias in the location of the seed. Networks were investigated using a seed-based approach, hierarchical agglomerative clustering and source based independent component analysis. All experiments were carried out in accordance with the Italian law governing animal welfare and protection.

RESULTS

We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices (Fig 1-2). Subcortical structures also showed highly symmetric inter-hemispheric correlations (Fig 3), with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Analogous cortical network configurations were also identified using independent component analysis (Fig 4). Hierarchical cluster analysis produced robust antero-cortical, cortico-hippocampal and subcortical-limbic clusters corresponding to previously described neuroanatomical systems (Fig 5). Interestingly, results also show a significant negative correlation between anatomical distance and covariance strength, highlighting the importance of trophic interactions between homotopic distal regions.

DISCUSSION

Our work documents the presence of covarying regional gray matter volumes in a cohort of genetically-homogeneous laboratory mice, defining macroscale correlational networks characterized by high neuroanatomical specificity. Consistent with previous findings in humans, the covariance patterns identified showed strong symmetric correlations among gray matter volumes of homologous brain regions. The use of complementary computational and mapping approaches produced consistent results, thus supporting the robustness of our findings. Importantly, the lack of anatomical covariance in antero-posterior midline regions exhibiting robust white matter connectivity supports the emerging view that scMRI only partially reflect underlying fiber connections, and, as such, scMRI should not be simply considered as a proxy for white matter connectivity.

CONCLUSION

We provide the first evidence of robust inter-hemispheric anatomical covariance networks in the laboratory mouse, thus paving the way to the investigation of genetic underpinnings of scMRI alterations described in neuropsychiatric populations. Our finding of robust homotopic networks in inbred mice suggests that population-based scMRI can emerge also in genetically homogeneous population, probably as a result of plastic and environmental stimuli.

Acknowledgements

No acknowledgement found.

References

1. Evans AC. Networks of anatomical covariance. Neuroimage. 2013;80:489-504.

2. Mechelli A, Friston KJ, Frackowiak RS, Price CJ. Structural covariance in the human cortex. J Neurosci. 2005;25:8303-10.

3. Alexander-Bloch A, Giedd JN, Bullmore E. Imaging structural co-variance between human brain regions. Nat Rev Neurosci. 2013;14:322-36.

4. Pagani M, Damiano M, Galbusera A et al. Semi-automated registration-based volumetric labelling, voxel based morphometry and cortical thickness mapping of the mouse brain. 2016; In press

Figures

ScMRI: primary cortices. Correlation maps for unilateral primary motor, somatosensory and auditory gray matter volume seeds. All the seeds exhibited the involvement of homotopic regions in the contralateral hemisphere. Additionally, both right and left auditory networks were found to encompass also the visual cortex bilaterally, and somatosensory and motor networks included foci of correlation in the cingulate cortex.

ScMRI: associative cortices. Correlation maps for associative cortex gray matter volume seeds. We found positive symmetric associations between cingulate, prefrontal, insular and retrosplenial areas, and their homotopic contralateral regions.

ScMRI: subcortical regions. Correlation maps for subcortical gray matter volume seeds. Some of the subcortical structures probed showed highly symmetric patterns of inter-hemispheric correlations, with evidence of distributed bilateral correlations in the thalamus and hypothalamus.

Source based morphometry of the cerebral cortex. Six bilateral homotopic independent components were identified with SBM, including a medial prefrontal, auditory-visual, insular, retrosplenial, motor-cingulate and somatosensory source. The anatomical distribution of these components exhibits overlap with correlative networks found using seed-based analysis.

Agglomerative hierarchal clustering of regional gray matter volume. Heatmap of the correlation between inter-subject gray matter volumes in 28 representative anatomical VOIs. VOIs have been arranged based on the results of cluster analysis. Three major clusters of structures were identified: an antero-cortical cluster (A), a cortico-hippocampal cluster (B), and a subcortical-limbic cluster (C). Cluster C, in turn, can be divided into limbic (C1) and diencefalic (C2) subclusters.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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