We found that, within each targeted network, a node’s vulnerability was best predicted by greater total connectional flow through that node and by a shorter functional path to the disease-related epicenters. Extending this analysis across all regions contained in any of the five networks revealed that intrinsic functional proximity to the epicenters represents the most potent predictor of disease-related atrophy. Therefore, although both the nodal stress and transneuronal spread model predictions received support from analyses of the individual target networks, incorporating the off-target networks provided

strongest support for the notion that neurodegenerative diseases spread from region to region along connectional lines to adopt a network-based Y-27632 chemical structure spatial pattern. The most mysterious aspect of neurodegenerative disease regards how each disease selects its initial target or targets. Early selective vulnerability, though not the focus of this study, creates a starting point from which disease then spreads. Regions showing greatest atrophy at later stages

may or may not represent the sites of initial injury, and even longitudinal imaging studies that follow patients from health to disease may overlook incipient microscopic pathology within small neuronal populations selleck kinase inhibitor (Braak et al., 2011). Despite these important caveats, our findings check details converge with our previous work to suggest that the regions most atrophied in each syndrome represent disease-specific network “epicenters,” whose connectivity in health serves as a template for the spatial patterning of disease. These epicenters bear close relationships to the early clinical deficits that define each parent syndrome. In AD, the angular gyrus may serve as the key heteromodal association hub through which information flows from posterior unimodal and polymodal association cortices to modules specialized for the memory, visuospatial, language, and praxis functions lost in patients with AD. Because atrophy in AD is more closely related to tau neurofibrillary

than amyloid plaque pathology (Scheinin et al., 2009 and Whitwell et al., 2008), we suspect that our connectivity-vulnerability findings in AD largely reflect tau pathology within posterior elements of the large-scale network known as the default mode network (Greicius et al., 2003 and Greicius et al., 2004). Nonetheless, the hub-like nature of the angular gyrus may produce activity-dependent “wear and tear” or increases in amyloid production that heighten its early vulnerability to amyloid deposition (Buckner et al., 2009) and incite or compound the neurodegenerative process. Interestingly, numerous frontal regions exhibit striking resistance to AD-related neurodegeneration despite having high fibrillar amyloid-beta deposition (Jack et al.

, 2008). Although this process might involve additional structural changes, it is nonetheless reasonable to assume that the available X-ray structures are broadly LEE011 mw representative of the active state without

further information. There is currently no atomic-resolution structure of a Kv channel in the resting state. This has motivated efforts aimed at translating the results from various experiments into structural information using modeling (Jiang et al., 2003, Lainé et al., 2003, Ruta et al., 2005, Posson et al., 2005, Chanda et al., 2005, Yarov-Yarovoy et al., 2006, Campos et al., 2007, Grabe et al., 2007, Lewis et al., 2008 and Pathak et al., 2007). Despite their inherent approximate nature, such experimentally constrained structural models selleck chemicals llc can serve to provide a context for the rational interpretation and design of future experiments. They can also be used to interpret and validate future experimental structures targeting the resting state of the VSD. Information about the conformation of the VSD in the resting state has come from a wide range of experiments, including mutagenesis (Starace et al., 1997, Starace and Bezanilla, 2001, Starace and Bezanilla,

2004, Ahern and Horn, 2004, Ahern and Horn, 2005, Grabe et al., 2007, Lin et al., 2010 and Tao et al., 2010), cross-linking (Jiang et al., 2003, Lainé et al., 2003, Ruta et al., 2005 and Campos et al., 2007), fluorescence (Pathak et al., 2007), resonance-energy transfer (Cha et al., 1999, Chanda et al., 2005 and Posson et al., 2005), and inhibitory toxins (Phillips et al., 2005b). Despite the wealth of experimental information, not all measurements can be easily translated into simple structural constraints. In that regard, experimental observations involving residue-residue interactions are of interest because they provide highly specific spatial constraints for the resting conformation of Kv channels (Campos et al., Adenosine 2007, Lin et al., 2010 and Tao et al., 2010). Engineered metal bridges are particularly informative because they involve strong chemically specific interactions occurring between residues that

are within atomic proximity from one another. Furthermore, the presence of a high-affinity metal bridge indirectly implies that the interaction reliably reports the protein conformation because large distortions would be expected to cause unfavorable strain energy that would result in a low-affinity site. Here, we review the available information on the resting state of the VSD and assess how its conformation is constrained by the available experimental data. We set out to explicitly simulate several of the key interactions associated with the resting state using molecular dynamics (MD). Although MD simulations are limited by approximations, the approach enables an objective evaluation of how these interactions can contribute to restricting the conformation of the VSD.

This analysis reveals a significant 6-fold increase in the volume of glutamate receptor clusters and a corresponding 4-fold decrease in the number of separable glutamate receptor clusters per synaptic bouton. These data are consistent with the observation of nearly continuous

electron dense regions in our EM analysis ( Figures 3C and 3D). In addition, in sections where there appears to be a severe perturbation of presynaptic ultrastructure, we observe two additional phenotypes: (1) the postsynaptic SSR is less dense, consistent with the disassembly of the postsynaptic SSR as observed previously ( Figure 3D; Eaton et al., 2002 and Pielage et al., 2005), and (2) the presynaptic mitochondria are severely perturbed even though muscle mitochondria, in the same image, appear normal. Finally, in all cases, boutons with wild-type ultrastructure selleckchem were also observed within each animal, consistent with our light level observations (data not shown). Thus, our ultrastructural data are consistent with the conclusion that hts is necessary to maintain the stability of the Drosophila NMJ. We next sought to define where Hts is required for synapse stability. First, we expressed transgenically encoded RNAi under UAS control (htsRNAi) to knock down Hts protein

in either the presynaptic neuron or postsynaptic Inhibitor Library ic50 muscle. Presynaptic expression of htsRNAi significantly depletes Hts-M protein from the nervous system ( Figure 4H). When htsRNAi is expressed presynaptically, with or without coexpression of dicer2 to enhance RNAi efficiency ( Dietzl et al., 2007), we observe a significant increase in NMJ retractions compared to control (Gal4-driver lines crossed to w1118) ( Figures 4B and 4G; 36% and 28% of muscle 4 NMJs show retractions compared to 1% in control; n > 98 NMJs for all genotypes). In addition, presynaptic knockdown of Hts

shows all hallmarks of synapse retraction observed in hts mutants including loss of presynaptic antigens, persistence of postsynaptic antigens (note the confluence of glutamate receptor staining as documented above; Figure 4B, inset) and the fragmentation of the presynaptic nerve membrane ( Figure 4B; see below for additional quantification of bouton numbers). By contrast, Cathepsin O although muscle-specific expression of htsRNAi was equally efficient at eliminating Hts protein (data not shown), it did not cause an increase in synapse retractions ( Figures 4C and 4G; 2% of NMJs show retractions, n = 60). In addition, the morphology of the NMJ appears grossly normal following postsynaptic knockdown of Hts ( Figure 4C; see below for further quantification). To further address the tissue-specific function of Hts, we expressed an hts cDNA in the hts mutant background using the GAL4/UAS expression system. We used a cDNA encoding the 718 aa long isoform of Hts that contains the conserved C-terminal MARCKS domain (Hts-M).

, 2010), we wondered whether mTOR signaling is increased in POMC neurons of aging mice. If so, suppressing this

excessive mTOR signaling via rapamycin administration may reestablish the hypothalamic circuit and ameliorate age-dependent obesity. In this study, we have found that mTOR signaling is elevated in the hypothalamic POMC neurons of old mice, causing silencing of these neurons due to upregulation http://www.selleckchem.com/products/PD-98059.html of KATP channel activity accompanied with an aging-associated expression of the Kir6.2 pore-forming subunit of KATP channels. In support of the critical role of enhanced mTOR signaling in causing obesity, removal of the mTOR-negative regulator TSC1 in POMC neurons of young mice elevated KATP channel activity, leading to silencing of POMC neurons and obliteration of leptin-induced release

of the anorexic hormone α-MSH. Whereas TSC1 deletion in POMC neurons resulted in obesity of young mice, TSC1 deletion in NPY/AgRP neurons had no effect on neuronal excitability or body weight. Remarkably, infusion of the mTOR inhibitor rapamycin into the brain of aging mice caused a reduction of body weight. This intracerebral rapamycin infusion reduced food intake without altering the blood glucose level. It also suppressed KATP channel activity to increase repetitive firing of POMC neurons, and expanded the POMC neuronal projection into the paraventricular nucleus (PVN) involved in controlling food intake and body weight. Taken together with our finding that systemic rapamycin injection also reduces body weight of old mice, this study http://www.selleckchem.com/products/XL184.html raises the prospect of potential therapeutic application enough of rapamycin

to reduce midlife obesity. Studies of POMC neurons from young rodents (typically < 3 months old) have shown that these neurons fire action potentials repeatedly so as to cause α-MSH secretion; elimination of action potential firing in POMC neurons abolishes α-MSH secretion (Bunel et al., 1990). It is an open question whether POMC neurons are still active in older rodents, which tend to display obesity and increased-adiposity. Our recording of green fluorescent protein (GFP)-labeled POMC neurons from transgenic mouse hypothalamic slices revealed that POMC neurons from young (1 month old) mice were electrically active (Figures 1A and 1D). In contrast, POMC neurons from aging (>6 months old) mice, which had gained more weight (Figure S1C available online), were silent (Figures 1B and 1D). As control for the health of brain slices from aging mice, recordings from neurons without GFP labeling from 12-month-old POMC-GFP mice revealed that these neurons fired action potentials repeatedly, and some displayed rhythmic bursting characteristic of tuberoinfundibular neurons in the arcuate nucleus (Figures S1A and S1B) (Lyons et al., 2010). By surveying four different age groups of mice, we found a significant reduction of input resistance of POMC neurons from 6-, 12-, or 18-month-old mice as compared to those from 1-month-old mice (p < 0.

After NMDAR activation, BAPTA blocked changes in rectification, implicating the involvement of elevated Ca2+ and supporting a role for NMDARs in this process (n = 8; RI, 0.54 ± 0.06 to 0.57 ± 0.07; p = 0.39). Our hypothesis is that the NMDAR-induced changes in rectification we observe are due to a loss of CI-AMPARs with a possible replacement by CP-AMPARs. There are several different mechanisms by which the loss of CI-AMPARs could occur. One is check details through lateral diffusion of AMPARs from the synaptic to the extrasynaptic membrane (Borgdorff and Choquet, 2002). However, the best-characterized mechanism

of AMPAR removal is dynamin-dependent endocytosis, triggered by an NMDAR-induced rise in postsynaptic Ca2+ (Carroll et al., 2001). We tested whether the CI-AMPARs are internalized due to dynamin activity by dialyzing RGCs with 10 mM Icotinib mw dynamin-inhibitory peptide (DIP), which blocks endocytosis of AMPARs by interfering with the binding of amphiphysin with dynamin (Lüscher et al., 1999). In RGCs, DIP causes a run up of the extrasynaptic, not synaptic,

AMPAR-mediated response due to unbalanced insertion of AMPARs undergoing rapid cycling (Xia et al., 2007). To ensure that this separate effect of DIP would not confound our results, we first recorded a 10 min baseline of light responses during DIP dialysis before recording the control I-V. The light responses of all ten cells remained stable during this period (3.2% ± 1.3% change over DOK2 10 min; data not shown), indicating that synaptic AMPARs under our recording condition are stable and that DIP does not affect the initial AMPAR ratio. While the mean baseline RI was higher in DIP-loaded cells than that of the control cells (Figure 4F; RI = 0.74), this effect was not significant (p = 0.15, t test) and probably reflects the variability of RIs as seen in Figure 1D. We find that inclusion of DIP in the pipette solution consistently

blocked the induction of synaptic plasticity with NMDA. The average rectification was 0.74 ± 0.04 before and 0.73 ± 0.07 after application of NMDA (Figure 4; n = 10, p = 0.64). Although, on average, there was no change in RI, in three out of ten cells, there was an increase in response amplitude at −60mV and no change in amplitude at +40mV. This result suggests that new CP-AMPARs were inserted into the membrane, presumably through persistent exocytosis or membrane diffusion, and supports the hypothesis that NMDAR activation induces an exchange of CI-AMPARs for CP-AMPARs. Our findings suggest that direct pharmacological activation of NMDARs on ON and ON-OFF RGCs drives AMPAR plasticity, but they do not establish whether endogenous transmitter release from presynaptic ON bipolar cells can similarly drive NMDAR-dependent plasticity.

Real-time PCR analyses for C9ORF72 and GAPDH were performed using the ABI 7900 Sequence Detection System instrument and software (Applied Biosystems). Samples were amplified in quadruplicate in 10 μl volumes see more using the Power SYBR-green master mix (Applied Biosystems), and 10 pM of each forward and reverse primer (see Supplemental Experimental Procedures online for primer sequences), using Applied Biosystems standard cycling conditions for real time PCR (initial denaturation at 95°C for 10 min, followed by 40 cycles of 95°C for 15 s, 60°C for 1 min). Cells were fixed with ice-cold methanol for 2 min and

blocked with 10% FBS for 30 min at 37°C. Primary antibody (anti-C9ORF72 antibody by Santa Cruz, sc-138763, 1:30) and secondary antibody (Alexa488-conjugated anti-rabbit antibody by Invitrogen, 1:200) were diluted in 5% FBS and incubated at 37°C for 3 hr or 30 min, this website respectively. The cells were then treated with 5 μg/ml of Alexa633-conjugated wheat germ agglutinin

(Invitrogen) in PBS for 10 min at room temperature (to detect cellular membranes), followed by incubation with 2 μg/ml propidium iodide (Invitrogen) in PBS for 3 min (to stain the nuclei). The cells were imaged with a TCS SP2 confocal microscope (Leica). This work was supported in part by the Intramural Research Programs of the NIH, National Institute on Aging (Z01-AG000949-02), and NINDS. The work was also supported by the Packard Center for ALS Research at Hopkins (B.J.T.), the ALS Association (B.J.T., A.C.), Microsoft Research (B.J.T., P.J.T.), ifoxetine Ontario Research Fund (E.R.), Hersenstichting Nederland Fellowship project B08.03 and the Neuroscience Campus Amsterdam (J.S.-S.), Nuts Ohra Fonds (J.v.S.), Stichting Dioraphte (J.v.S. – Grant 09020300), the UK MND Association (H.M. – MNDA Grant 6057, J.H., R.W.O.), The Medical

Research Council UK (J.H., S.P.B.), the Wellcome Trust (J.H.), the Helsinki University Central Hospital, the Finnish Academy (P.J.T.), the Finnish Medical Society Duodecim, Kuopio University, the Italian Health Ministry (Ricerca Sanitaria Finalizzata 2007, to A.C.), Fondazione Vialli e Mauro ONLUS (A.C.), Federazione Italiana Giuoco Calcio (A.C., M.S., B.J.T.) and Compagnia di San Paolo (A.C., G.R.), the European Community’s Health Seventh Framework Programme (FP7/2007-2013) under grant agreements 259867 (A.C.) and 259867 (M.S., C.D.), Deutsche Forschungsgemeinschaft (M.S. – Grant SFB 581, TP4), the Muscular Dystrophy Association (M.B., J.W.), the Emory Woodruff Health Sciences Center (M.B., J.W.), EVO grants from Oulu University Hospital (A.M.R.) and the Finnish Medical Foundation (A.M.R.). DNA samples for this study were obtained in part from the NINDS repository at the Coriell Cell Repositories (http://www.coriell.org/), and the National Cell Repository for Alzheimer’s Disease (http://ncrad.iu.edu).

, 2011), and PL neurons show conditioning-induced increases in auditory responses (Burgos-Robles et al., 2009). Unlike the lateral amygdala, in which conditioned responses last only a few hundred milliseconds (Quirk et al., 1995), PL neurons exhibit sustained conditioned increases in rate that mirror the time course of freezing to a tone (Burgos-Robles et al., 2009). This suggests that fear responses are initiated by the amygdala, but sustained by computations occurring in PL. PL receives direct input from the basolateral amygdala

(BLA) and the ventral hippocampus (vHPC), which has been implicated in contextual gating of fear responses (Bouton, 2002). Both BLA and vHPC innervate pyramidal neurons as well as inhibitory interneurons in PL (Carr and Sesack, 1996; Gabbott et al., 2002, 2006; Hoover and Vertes, 2007; McDonald, 1991), SCH727965 order consistent with excitatory and inhibitory influences (Dégenètais et al., 2003; Floresco and Tse, 2007; McDonald,

1991; Parent et al., 2010; Sun and Laviolette, 2012; Tierney et al., 2004). It is not known, however, if and how PL integrates hippocampal and amygdala inputs in behaving rats. We addressed this by combining multichannel unit-recording in PL with local pharmacological inactivation in behaving rats subjected to auditory fear conditioning. We evaluated the effects of inactivation of BLA and vHPC on both selleck chemicals spontaneous and tone-evoked activity of PL neurons. Inactivation of BLA reduced the firing rate of pyramidal neurons and eliminated conditioned tone responses. In contrast, inactivation of vHPC reduced the firing rate of inhibitory interneurons and augmented conditioned tone responses. Consistent with vHPC gating of fear after extinction (Bouton, 2002; Hobin et al., 2006), inactivation of vHPC caused a return of fear responses

and increased PL pyramidal cell activity in rats that had been extinguished. To evaluate fear signaling in PL, we conducted our experiments in conditioned rats, which show robust tone responses in PL (Burgos-Robles et al., 2009). Rats previously subjected Interleukin-11 receptor to auditory fear conditioning were infused with the GABAA agonist muscimol into either BLA (n = 7) or vHPC (n = 7), while the activity of PL neurons was monitored through chronically implanted drives. Coronal brain drawings in Figure 1A show the reconstruction of PL unit-recording sites as well as BLA and vHPC infusion sites. We initially characterized the effects of input inactivation on spontaneous activity of PL cells, while rats that were conditioned pressed a bar for food in the conditioning chamber. Inactivation of either BLA or vHPC after conditioning yielded significant increases and decreases in firing rate of individual PL neurons (paired Student’s t test, p < 0.05). The proportions of different responses were similar for the two inputs (Figures 1B and 1C, insets).

Despite the accumulating evidence suggesting that saccade preparation and attention are not necessarily interdependent it is still

unclear how the diverse neuronal types contribute to each of these processes. Neurons with visual, visuomotor, and motor properties have been described in the FEF (Bruce and Goldberg, 1985), but how these different functional classes contribute to attentional selection is not yet fully understood. One study (Thompson et al., 2005) recorded the responses of FEF neurons with visual and saccade-related activity in an exogenous (pop-out) search task and found that only the responses of visual neurons were modulated by attention whereas the responses of movement neurons were suppressed. However, it has been argued that oculomotor mechanisms GSK1120212 cost should be engaged in endogenous rather than in exogeneous (pop-out) attention tasks (Awh et al., 2006, Klein, 1980 and Rizzolatti et al., 1994).

If so, then Selumetinib movement cells should be active when attention is voluntarily directed to a spatial location covertly, which has not yet been tested. In addition to modulating firing rates, attention also modulates synchronous activity within and across cortical areas. We have previously shown that attention increases neuronal synchronization within the FEF as well as between FEF and V4 in the gamma frequency range (Gregoriou et al., 2009a), suggesting that top-down feedback enhances visual processing at least partly through synchronization of activity. However, it is not known whether the top-down Levetiracetam attentional control of visual cortex results from oculomotor or separate attentional signals in FEF. If movement cells synchronized their activity with V4 during attention, it would strongly support premotor theories. To address

these unresolved issues, we recorded the firing rates and synchrony of FEF and V4 neurons. Our goal was to test the contribution of different classes of FEF neurons to covert attention and saccades. The results suggest that covert and overt selection are not mediated by the same neural elements and can be further dissociated by synchronous interactions. We recorded single-unit activity from FEF and area V4 of two macaque monkeys engaged in two tasks with different eye movement requirements: a covert attention task and a memory-guided saccade task (Figure 1). In the attention task, the monkeys were rewarded for detecting a color change of a target stimulus presented among distracters. The location of the target was randomized in different trials so that attention could be directed inside or outside the RF of the recorded neurons. The monkeys were rewarded for releasing a bar as soon as the target stimulus changed color, ignoring color changes of the distracters.

These results are consistent with previous experimental data: a large increase in calcium (using focal laser-induced photolysis to release caged calcium in one side of a growth cone) mediates attraction, whereas a small increase in calcium mediates repulsion (Zheng, 2000 and Hong

et al., 2000). However, when neurons were placed in a calcium-free medium, thus reducing intracellular calcium, the same release of caged calcium resulted in repulsion (Zheng, 2000 and Wen et al., 2004). When the resting calcium level is reduced in the model, either a small or large local increase in calcium in the up-gradient compartment causes a lower CaMKII:CaN ratio in that compartment compared to the down-gradient compartment, which results in repulsion (Figures 2A and 2B, line 2, and Figures 2C and 2D, point L). Thus, reducing the resting calcium level converts the response ZD1839 mouse to a large increase in calcium from attraction to repulsion, whereas the response to a small increase in calcium remains as repulsion. Increasing the baseline calcium can also affect the guidance response. MAG is a guidance cue for repulsion, and it causes a small elevation of internal calcium when binding to Nogo-66

receptors selleck screening library (Tojima et al., 2011). If the resting calcium level is increased, then MAG acts as an attractive guidance cue (Henley et al., 2004). This behavior is also reproduced in G protein-coupled receptor kinase the model (Figure 2B, line 3, and Figure 2D, point MH). Although attraction could occur in our model at very low levels of calcium, in reality growth cones are unable to turn in either direction in this case, because there

is then an insufficient calcium influx to trigger turning (Gomez and Zheng, 2006). Based on the results of previous experiments, our model therefore confirms that it is not only the magnitude of the calcium increase which is important, but also the baseline calcium. The only way for attraction to occur at biologically plausible calcium concentrations is for one compartment to be over a certain threshold, which occurs due to the bimodal nature of CaMKII (Zhabotinsky, 2000). As in LTP/LTD, the threshold for CaMKII activation acts as a switch between attraction and repulsion (Lisman et al., 2002). The model predicts that increasing the resting levels of calcium in the neuron past that of point H in Figures 2A and 2B leads to repulsion, as now a local increase in calcium in the up-gradient compartment causes a lower CaMKII:CaN ratio in that compartment (Figure 2A, line 3, Figure 2B, line 4, and Figures 2C and 2D, point H). cAMP plays a role in determining whether a neuron is attracted or repelled from a gradient, acting as a switch between attraction and repulsion in a steep gradient (Ming et al., 1997, Song et al., 1997, Song et al., 1998, Nishiyama et al., 2003, Wen et al.

005, nonparametric Mann-Whitney

test). A similar 2 hr temperature increase had no effect on control (Pdf-Gal4/+, UAS-TrpA1/+, and Pdf-Gal4 > UAS-mCD8GFP) fly lines ( Figures S2A and S2B). Similar to the role of mammalian Mef2 in activity-dependent neuronal plasticity ( Fiore et al., 2009, Flavell et al., 2006 and Flavell et al., 2008), activation of PDF cells with TrpA1 in a Mef2 RNAi knockdown strain induced defasciculation of the s-LNv dorsal termini (DI > 30%) in only ∼40% of brains, in contrast to ∼90% in wild-type brains (data not shown); the DI difference is statistically significant ( Figure 2B, p = 0.01, nonparametric Mann-Whitney test). This was not due to the extra UAS, as addition of a control UAS-mCherry element to a background fly line did not decrease axonal defasciculation in response to TrpA1 activation ( Figures S2C and S2D). The incomplete effect of the Mef2 knockdown probably reflects residual Mef2 activity and/or the Z-VAD-FMK in vivo very strong effect of TrpA1 on firing. An additional possibility is that Mef2-independent pathways also contribute to activity-induced axonal defasciculation. To gain further insight into the molecular selleck chemicals llc mechanisms that underlie Mef2 function in the circadian system, direct Mef2 target genes were identified with chromatin prepared from Drosophila adult heads. We analyzed the data with genome-wide tiling arrays (ChIP-Chip) and an antibody against isoform D of

Mef2 Ramoplanin ( Sandmann et al., 2006). The same antibody had been successfully used for identification of Mef2 targets in Drosophila embryos ( Junion et al., 2005 and Sandmann et al., 2006). We also addressed rhythmic binding of Mef2 to its genomic targets, i.e., the ChIP-Chip analysis was done on chromatin from fly heads collected at six different time points spanning the 24 hr light-dark cycle. Mef2 binds to a large number of sites in the Drosophila genome ( Table S1), and many of these were previously identified as Mef2 targets

genes in Drosophila embryos ( Sandmann et al., 2006); the overlap between the two gene lists is statistically significant (data not shown). Modified Fourier analysis ( Wijnen et al., 2005) of the six time points revealed rhythmic oscillations of Mef2 binding to a significant fraction of these loci. Maximal Mef2 binding was always in the latter half of the night and early morning, from approximately ZT17 to ZT2 ( Figure S3A). This temporal pattern of Mef2 chromatin cycling is in agreement with the gene expression data, which show an increase of Mef2 transcript levels in PDF neurons during the night ( Kula-Eversole et al., 2010; Figure 5B), as well as with the described oscillations of Mef2 protein levels in these cells, with maximal Mef2 nuclear accumulation at ZT22 ( Blanchard et al., 2010). We further validated Mef2 binding as well as cycling on several promoters by qRT-PCR analysis of three independent experimental repeats ( Figure S3B; Table S2).