Modules of spontaneous cortical activity in mouse cortex during quiet wakefulness: key nodes and shaping by neuromodulators.

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Though neural activity in the brain is highly dynamic, it shows evidence of structured activity according to large-scale brain networks, which can drive both adaptive and maladaptive behaviors. These large-scale networks have been described in many species, and reflect the integration of complex physiological principles arising from mammalian evolution. Yet, how units of neural activity that rapidly transition over time assemble into networks that are stable over tens of minutes and longer timescales in the healthy brain is unclear. This is of major importance, as these transitions must be carefully regulated or the large-scale networks, and the behavioral responses they drive, would degrade. This is my research program's driving question. This Discovery Grant will utilize the mouse as a tractable neural system to advance the research program. I, and others, have previously identified stereotyped and repeated patterns of activity within spontaneous neural activity, and these motifs of activity transition from one to another in semi-predictable sequences. The realm of possible motifs and the processes governing motif transitions is key to understanding stable large-scale networks over time and their associated repertoire of behaviours. To test this hypothesis, I will use in vivo cortical imaging and genetically encoded calcium indicators to sample epochs of spontaneous cortical activity. I then propose to use novel unsupervised learning approaches capable of describing the realm of possible activity motifs and their probabilistic relationships over time. The validity of these models will be tested using chemogenetic and optogenetic approaches, in addition to characterizing the behavioral sequelae of disrupting or driving unique sequential motif assemblies. Finally, I propose to characterize highly conserved neuromodulator systems with distributed ascending projections to cortex and their role in sculpting sequential transitions in spontaneous cortical motifs. Our approach is novel, and the Discovery Grant will provide fertile and exciting opportunities for highly qualified personnel training and development. The work proposed will dramatically increase our understanding of the physiological basis underlying large-scale brain networks, and creates a resource for probing the physiology of cortical activity dynamics.