, 2010) In this manner, intercellular interactions among SCN neu

, 2010). In this manner, intercellular interactions among SCN neurons (i.e., coupling) determine the population-level properties that are required for the transmission of coherent output signals to downstream tissues

and adjustment to changing environmental conditions ( Meijer et al., 2010 and Meijer et al., 2012). Although it is critical for pacemaker function, the process by which SCN neurons interact remains ill-defined. Candidates for SCN coupling factors FK228 have been identified (Aton and Herzog, 2005 and Maywood et al., 2011), with vasoactive intestinal polypeptide (VIP) known to play an especially important role. Without competent VIP signaling, SCN neurons display desynchronized rhythms and a lower propensity for sustained cellular oscillations (Aton et al., 2005). However, SCN neurons also communicate through other signaling pathways that can compensate for the lack of VIP (Brown et al., 2005,

Ciarleglio et al., 2009, Maywood et al., 2006 and Maywood et al., 2011). GABA, the most abundant neurotransmitter within the SCN (Abrahamson and Moore, 2001), is also a putative coupling factor whose role remains unclear, since GABAA signaling is sufficient (Liu and Reppert, 2000) but not required for synchrony (Aton et al., 2006). One obstacle in the attempt to develop a mechanistic understanding of the role of different SCN coupling factors is the lack of analytical paradigms that are well suited for this purpose. Previous studies have relied largely on techniques that eliminate cellular interactions via physical, pharmacological, BKM120 or genetic means to determine

which forms of intercellular signaling are necessary or sufficient for period synchrony. Although this approach is informative, it typically entails compromised neural function, which can complicate interpretation of the precise role played by the Rolziracetam candidate coupling factor. Furthermore, this approach is unable to provide insight into how the intact, functional SCN network uses and integrates different coupling signals. Here, we developed a functional assay for SCN interactions that uses genetically intact animals with competent neuronal oscillatory and coupling mechanisms. Our research strategy was modeled on one previously employed to investigate coupling within an invertebrate pacemaker system (Roberts and Block, 1985), which involved shifting one of two coupled pacemakers and then tracking resynchronization between the pair over time in vitro. Although it remains difficult to shift specific SCN subpopulations in vitro, the pacemaker network can be temporally reorganized in vivo by a variety of environmental lighting conditions (de la Iglesia et al., 2004, Inagaki et al., 2007, Meijer et al., 2010 and Yan et al., 2005). Based on previous theoretical and experimental research (Inagaki et al.

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