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Abstract
Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of “bursty” dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.
High-amplitude and network-level events detected in mouse and human brains using fMRI are supported by modular structural connectomes.
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1 Oberlin College, Neuroscience Program, Oberlin, USA (GRID:grid.261284.b) (ISNI:0000 0001 2193 5532)
2 Indiana University, Cognitive Science Program, Bloomington, USA (GRID:grid.257410.5) (ISNI:0000 0004 0413 3089); Indiana University, School of Informatics, Computing, and Engineering, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X)
3 Indiana University, Department of Psychological and Brain Sciences and Cognitive Science Program, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X)
4 The University of Oklahoma, Stephenson School of Biomedical Engineering, Norman, USA (GRID:grid.266900.b) (ISNI:0000 0004 0447 0018)
5 Indiana University, School of Informatics, Computing, and Engineering, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); Indiana University, Program in Neuroscience, Bloomington, USA (GRID:grid.257410.5) (ISNI:0000 0004 0413 3089)
6 Fondazione Bruno Kessler, Trento, Italy (GRID:grid.11469.3b) (ISNI:0000 0000 9780 0901)
7 Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Functional Neuroimaging Lab, Rovereto, Italy (GRID:grid.509937.1)
8 Indiana University, Cognitive Science Program, Bloomington, USA (GRID:grid.257410.5) (ISNI:0000 0004 0413 3089); Indiana University, Department of Psychological and Brain Sciences and Cognitive Science Program, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); Indiana University, Program in Neuroscience, Bloomington, USA (GRID:grid.257410.5) (ISNI:0000 0004 0413 3089)