Kavli Affiliate: Jessica Cardin & Michael Higley
| Authors: Hadas Benisty, Andrew H Moberly, Sweyta Lohani, Daniel Barson, Ronald R Coifman, Gal Mishne, Jessica A Cardin and Michael J Higley
| Summary:
Abstract Experimental work across a variety of species has demonstrated that spontaneously generated behaviors are robustly coupled to variation in neural activity within the cerebral cortex (1-10). Indeed, functional magnetic resonance imaging (fMRI) data suggest that functional connectivity in cortical networks varies across distinct behavioral states, providing for the dynamic reorganization of patterned activity (5, 7, 11, 12). However, these studies generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior typically observed in awake animals. Here, we took advantage of recent developments in wide-field, mesoscopic calcium imaging (13) to monitor neural activity across the neocortex of awake mice. Applying a novel approach to quantifying rapidly time-varying functional connectivity, we developed a “graph of graphs” method to show that spontaneous behaviors are represented by fast changes in both the activity and correlational structure of cortical network activity. Both the approach and key results were generalizable to cellular-resolution data obtained via 2-photon imaging. Finally, dynamic functional connectivity of mesoscale signals revealed subnetworks that are not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insight into how behavioral information is represented across the mammalian neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks. Summary We develop a novel approach for deriving the time-varying functional connectivity of cortical networks and show this information encodes rapid fluctuations in behavioral state. Competing Interest Statement The authors have declared no competing interest.