, 2005, 2006; Doi et al., 2011). VIP and, to a lesser extent, vasopressin and gastrin releasing peptide have been shown to mediate rhythm stability in and synchrony among circadian cells (Maywood et al., 2011). In contrast, we have found GABA to destabilize and desynchronize circadian cells. Synchronization and desynchronization are thus both

active processes that can be differentially modulated. It is interesting to speculate that developmental and seasonal changes may alter the balance between fast neurotransmission and slower neuropeptide signaling to adjust the timing among SCN neurons. It is possible that GABA plays an important role within this setting to actively drive networks of oscillators to new phase relationships. Additionally, recent work suggests that a hierarchy

of neuropeptidergic signals may differentially promote or sustain rhythmicity and synchrony among SCN cells (Maywood et al., 2011). In light of our results, we must place GABAA Sunitinib mouse signaling within this hierarchy and classify potential synchronizing agents by their ability to overcome the destabilizing effects of GABA. Our data suggest that VIP may be the only agent capable of overcoming this destabilizing effect since it is only after VIP signaling is eliminated that the desynchronizing effects this website of GABA are unmasked. Given that VIP signaling diminishes during aging (Cayetanot et al., 2005), increasingly unopposed GABAergic signaling may weaken SCN neuronal synchrony and contribute Cytidine deaminase to sleep/wake cycle fragmentation in the elderly. See a detailed description in the Supplemental Experimental Procedures. All animal procedures complied with National Institutes of Health (NIH) guidelines and were approved by the Washington University Animal Care and Use Committee. Spike trains from SCN neurons were recorded using MEAs and the Z score and strength of each interaction was measured. We graphed functional connections with GUESS software and analyzed network architecture with NodeXL software. We developed an empirical method to discriminate correlated activity that derived from real versus coincidental neuronal interactions. We reasoned

that correlations between spike trains recorded from neurons in physically distinct culture dishes do not signify connectivity. Using this logic, we iteratively cross-correlated spike trains from all neurons across 10 cultures (samples) over 1 hr to determine the distribution of Z scores associated with inherently false across-sample correlations. Using the full distribution of false across-sample correlations, we determined Z score magnitude thresholds that corresponded with likelihoods of discovering false-positive across-array correlations. To determine if connection strength systematically changed with time of day, we fit the strength versus time data with linear and cosine functions and estimated the resultant p value using the F test. PER2::LUC expression from SCN explants was measured using photomultiplier tubes or a CCD camera.