In addition, we were able to integrate the functional and expression data and predict a function for one Gr ( Figure 9). While our data support the hypothesis that Gr59c encodes a bitter receptor for BER, DEN, and LOB, Gr59c is not sufficient for responses to these compounds in sugar neurons. It is also apparently not necessary, in the sense that physiological responses to these tastants

were observed in S-a sensilla that do not express the Gr59c driver. These observations suggest that there is another receptor for BER, DEN, and LOB that may recognize a different moiety of these tastants, providing multiple means of detecting some of the most behaviorally aversive bitter tastants in the panel. We note that 38 of the Gr-GAL4 drivers, slightly more than half, showed expression in the labellum. The other selleck chemicals llc Selleckchem Ku 0059436 Grs are probably expressed in other chemosensory neurons of the adult and larva ( Dunipace et al., 2001, Jones et al., 2007, Kwon et al., 2007,

Scott et al., 2001 and Thorne and Amrein, 2008) (unpublished data, A.D., J.Y.K., L.A.W., F. Ling, and J.R.C.). Of the 38 labellar Gr-GAL4 drivers, 33 are expressed in bitter neurons, and only a few in sugar neurons. It seems probable that a high fraction of Grs are devoted to bitter perception because of the number and structural complexity of bitter compounds ( Schoonhoven et al., 2005 and Schwab, 2003). Sugars are simpler and more similar in structure. In order to detect the wide diversity of noxious bitter substances that an animal may encounter, a larger and more versatile repertoire of receptors is likely needed. We note that

in mice and rats, 36 bitter receptors have been identified ( Wu et al., 2005), but few sugar receptors ( Montmayeur et al., 2001 and Nelson et al., 2001). Among the Grs mapped to bitter neurons, five map to all bitter neurons: Gr32a, Gr33a, Gr39a.a, Gr66a, and Gr89a. Some or all of these “core bitter Grs” may function as coreceptors, perhaps forming multimers with other Grs. These core Grs might play a role analogous to Or83b, an Or that is MTMR9 broadly expressed in olfactory receptor neurons and that functions in the transport of other Ors and as a channel, rather than conferring odor specificity per se (Benton et al., 2006, Sato et al., 2008 and Wicher et al., 2008). If so, the core Grs may be useful in deorphanizing other Grs in heterologous expression systems. We note that in mammals, T1R3 functions as a common coreceptor with either T1R1 or T1R2 to mediate gustatory responses to amino acids or sugars, respectively (Zhao et al., 2003). We note finally that the receptor-to-neuron map defines intriguing developmental problems.

, 2008) FGFR3, which is expressed in a gradient with highest lev

, 2008). FGFR3, which is expressed in a gradient with highest levels in selleck compound the posterior-lateral cortex, has been proposed to control the growth of this part of the cortex by regulating

cell-cycle length and duration of the neurogenic phase, based on analysis of mice expressing a constitutively active version of the receptor (Thomson et al., 2009). Although FGF10 is uniformly expressed throughout the anterior-posterior axis of the cerebral cortex, loss of Fgf10 results in excess cell proliferation only in the anterior cortex, suggesting that other factors with a similar neurogenic activity operate posteriorly (Sahara and O’Leary, 2009). FGF2 has been reported to be expressed across the whole cortical progenitor zone (also known as ventricular zone or VZ) of the cortex, as well as being released by afferent thalamic axons (Dehay et al., 2001), and in contrast

to other FGFs it is required throughout the cortex for progenitor divisions during early neurogenesis and the subsequent generation of appropriate numbers of projection neurons (Raballo et al., 2000). Analysis of the adult subventricular zone in mice that are constitutively null mutant for FGF2 or have been infused with the factor suggests that FGF2 might promote progenitor proliferation all the way to adult neurogenesis (Wagner et al., 1999 and Zheng et al., 2004). Expression of mutated versions of FGFR1 in adult neural stem cell cultures has implicated the MAPK/Erk pathway in the maintenance of adult stem cell proliferation and the PLCγ/Ca2+ pathway in inhibition of astroglial differentiation and maintenance of the neuronal and oligodendroglial differentiation potential of neural stem cells (Ma et al., 2009). However, definitive evidence of a role of FGF2 in adult neurogenesis (e.g., by adult-brain-specific deletion of the gene) is still lacking, as

the null mutation might act only indirectly during embryonic development, by reducing the number of founder cells for adult neural stem cells. FGF2 is also a potent mitogenic factor for telencephalic progenitors in vitro Resveratrol (Maric et al., 2007), and adding high concentrations of both FGF2 and epidermal growth factor (EGF) has become standard procedure to expand neural stem cells in floating “neurosphere” or adherent cultures (Conti et al., 2005, Palmer et al., 1995 and Vescovi et al., 1993). In primary cultures of rodent embryonic telencephalon, FGF2 induces responsiveness of neural progenitors to EGF, which might account in part for the synergistic activities of the two factors (Ciccolini and Svendsen, 1998 and Lillien and Raphael, 2000). FGF2 promotes the proliferation of neural progenitors in these cultures by shortening the G1 phase of the cell cycle and by inhibiting the generation of postmitotic neurons, via upregulation of cyclin D2 and downregulation of the cyclin-dependent kinase inhibitor p27/kip1 (Lukaszewicz et al., 2002, Maric et al.

The same analysis was conducted on the output side of the ventral

The same analysis was conducted on the output side of the ventral pathway (Figure 5B). The activation patterns were measured at the third time tick of speaking/naming (see Supplemental Experimental Procedures). Again there was a gradual shift in the type of similarity structure encoded across the

successive layers (vATL to the insula-motor output layer: left to right in Figure 5B), becoming increasingly sensitive to phonological similarity and less so to semantic similarity. While the pattern of behavioral dissociations varies according to the location of brain damage, the qualitative nature of impairments can also change. For example, recent voxel-symptom lesion mapping studies have demonstrated significant variation in the rate of semantic speaking/naming errors according to the location of stroke-related damage, peaking in the aSTG (Schwartz et al., 2009). The rate of semantic errors produced by the model was compared after various levels of damage to each of its internal layers (to permit a fair comparison, the level of damage for each was titrated to equate overall speaking/naming accuracy, and lesioning was repeated ten times with different random seeds to avoid idiosyncratic results [Figure 6A]; see Supplemental CB-839 mouse Experimental Procedures for further methodological details). Figure 6B (bottom) shows

the rate of semantic errors as a function of the location and degree of damage. A 4 (place of damage) × 4 (severity level) ANOVA revealed a significant interaction (F(9, 81) = 19.27, p < 0.001). Increasing damage in ADAMTS5 aSTG significantly augmented the rate of errors (F(3, 27) = 33.26, p < 0.001). This pattern, albeit less pronounced, was also found for mSTG (F(3, 27) = 40.773, p < 0.001), but not for iSMG or opercularis-triangularis (Fs < 1). In parallel to the patient data, these simulations revealed that the rate of semantic errors was most pronounced after aSTG simulated damage (aSTG versus mSTG: F(1, 9) = 10.82, p = 0.009). Importantly, like the original patient study, these simulation

analysis outcomes remained, even after the comprehension accuracy was controlled (ANCOVA). To explain their results, Schwartz et al. (2009) proposed that aSTG mediates lexical access for speech production. This raises a conundrum, however, in that the same region is associated with both verbal and nonverbal auditory comprehension in patient, rTMS, and functional neuroimaging literature (Patterson et al., 2007, Pobric et al., 2007, Scott et al., 2000 and Visser and Lambon Ralph, 2011). Using the regression-based method (see above), we probed the functioning of the aSTG layer of the model across tasks (comparing the aSTG-associated β values [highlighted with a light-gray box] in Figure 5A [comprehension] versus Figure 5B [speaking/naming]). Given the structure of the model and the lesion simulations summarized above, it is clear that the region is critical both in auditory comprehension and speaking/naming.

e., trained versus untrained intervals) changed between pre- and posttraining. We tested for learning-related effects irrespective of ΔT (i.e., averaging ΔT1 and ΔT2 trials), but we also

assessed learning effects separately for the two of ΔTs (see Table 2). For these whole-brain analyses, the statistical threshold was set to p < 0.05 FWE cluster-level corrected for multiple comparisons across the entire brain volume (cluster size estimated at a voxel level threshold p-unc = 0.001). Next, we tested whether any change of brain activity in the posttraining phase, i.e., after learning had occurred, correlated with behavioral measures of learning on a subject-by-subject basis. We used a simple regression model to assess the correlation between subject-specific BTK inhibitor price learning indexes (LI) measured

during fMRI and the corresponding BOLD effect. Specifically, we considered LI for the “200 ms & ΔT2” condition, and brain activity CP-690550 cost associated with the “200–400 ms” difference, again considering trials with ΔT2 as the comparison interval. Indeed, note that only for ΔT2 trials the LI was expected to identify learning at the behavioral level (cf. Results, about learning indexes). Corrected p values were assigned considering areas showing learning-related effects in the main ANOVA as the volume of interest (Worsley et al., 1996). Finally, we addressed the issue of whether any individual pre-existing functional difference could predict the level of training-related behavioral changes. For this purpose a regression model tested for correlation between activity associated with “200–400 ms” difference measured

in pretraining, with subject-specific learning indexes. Again we considered LI for the “200 ms & ΔT2” condition and the BOLD response DNA ligase for “200–400 ms” difference in ΔT2 condition. It is worth emphasizing here that for this analysis behavioral and imaging data were obtained in different phases of the experiment (i.e., behavior from the posttraining session, while imaging from the pretraining session). Statistical threshold was set to p < 0.05 FWE cluster-level corrected for multiple comparisons at the whole brain level (cluster size estimated at a voxel level threshold p-unc = 0.001). Voxel-Based Morphometry (VBM) (Ashburner and Friston, 2000) is an automated procedure that permits voxel-wise analysis of gray-matter volume in SPM8. An integrated approach (unified segmentation Ashburner and Friston, 2005) was used to process T1-images, including bias correction, image registration to the Montreal Neurological Institute (MNI) template and tissue classification into gray-matter, white-matter, and cerebrospinal fluid. DARTEL was used to improve intersubject registration (Ashburner, 2007) followed by scaling with the Jacobian determinants derived in the registration step (i.e., “modulation”).

In spite of their self-renewal properties, human ES and iPS cells

In spite of their self-renewal properties, human ES and iPS cells can still be difficult to genetically manipulate. Various

Ruxolitinib mouse techniques for stem cell genetic modification have been reported, and these can result in random (i.e., transgenic) or targeted integration of the DNA construct (reviewed in Giudice and Trounson, 2008). Transgenic approaches include the use of plasmid transfection (Di Giorgio et al., 2008, Lakshmipathy et al., 2004 and Siemen et al., 2005), lentiviral transduction (Ben-Dor et al., 2006 and Xia et al., 2007), transposases (Lacoste et al., 2009 and Wilber et al., 2007), and bacterial artificial chromosomes (BAC) (Placantonakis et al., 2009) as DNA delivery systems. Each of these strategies is in principal useful for the generation of both reporter systems and transgenic cell lines that either overexpress or suppress a given gene of interest. For instance, our group used plasmid transfection to generate a stable transgenic hES cell line that reports via GFP expression on spinal motor neuron differentiation (Di Giorgio et al., 2008).

Placantonakis and colleagues used BAC transgenesis of different reporter constructs to generate hES cell reporter lines that upon neural differentiation can report for neural stem cell, neuroblast, or motor neuron lineages (Placantonakis et al., 2009). In another study, Lacoste and colleagues selleck inhibitor engineered the piggyBac transposable

system to deliver cocktails of doxycycline-inducible gain and loss-of-function transgenes Rebamipide into hES cells to efficiently direct their differentiation into neural rosettes (Lacoste et al., 2009). Some of the limitations associated with transgenic approaches include the possibility of insertional mutagenesis, transgene silencing or ectopic expression of the transgene due to position effects, and lack of faithful expression of a reporter transgene due to absence of regulatory elements in the promoter fragment driving its expression (Giudice and Trounson, 2008). Unlike in mouse embryonic stem cells, where gene targeting by homologous recombination is routine, human pluripotent stem cells have proven to be more recalcitrant to this form of genetic modification. Thus far, only a few studies have reported the successful targeted genetic modification of human ES cell lines using conventional approaches (Costa et al., 2007, Davis et al., 2008, Di Domenico et al., 2008, Irion et al., 2007, Urbach et al., 2004 and Zwaka and Thomson, 2003). Recently, advances in the design of zinc finger nucleases (ZFNs) have shown promise for human ES and iPS cell-targeting experiments. Specific loci have now been disrupted, corrected, and modified to express reporter genes by means of a ZFN-mediated gene targeting (DeKelver et al., 2010, Hockemeyer et al., 2009, Lombardo et al., 2007 and Zou et al., 2009).

0-eYFP mice Venturing into the conditioned chamber triggered an

0-eYFP mice. Venturing into the conditioned chamber triggered an amber laser, which led to an aversion of the light-paired chamber already during the conditioning sessions (pretest day THcre/eNpHR3.0-eYFP 49.6% ± 4.5% versus conditioning day 2 THcre/eNpHR3.0-eYFP 29.0% ± 4.2%; conditioning day 2 THcre/eYFP 46.3% ± 5.8% versus conditioning day 2 THcre/eNpHR3.0 29.0% ± 4.2%; Figure 4G). On the test day, with the amber laser no longer active, THcre/eNpHR3.0-eYFP mice retained an aversion for the light paired-chamber (pretest day

THcre/eNpHR3.0-eYFP 2.6 ± 70.1 s versus test day THcre/eNpHR3.0-eYFP −276.4 ± 81.5 s; test day THcre/eYFP 36.3 ± 109.1 s versus test day THcre/eNpHR3.0-eYFP 276.4 ± 81.5 s; Figure 4H). Interestingly, the CPA score was almost identical to the one observed with GADcre+/ChR2-eYFP mice. The control mice groups for both conditions were indifferent to all manipulations throughout the Selleckchem HIF inhibitor duration of the experiment (Figures 4 and S4). Importantly, the blue and amber light stimulations did not have an impact on the overall locomotor activity, as the total distance traveled was similar in all groups (Figures S4D and S4G). Here, we show that optogenetic activation of VTA GABA neurons inhibits RG7204 molecular weight DA neurons of the VTA. We then provide evidence that VTA GABA neurons also inhibit DA neurons in response to a brief footshock via GABAA transmission. Finally, we observe

that activation of VTA GABA neuron or direct inhibition of DA neurons is sufficient to elicit a strong place aversion. These findings are in line with the companion paper in this issue of Neuron ( van Zessen et al., 2012). The inhibitory

synaptic networks that control DA neuron’s activity are increasingly well described. GABA neurons of the VTA receive inhibitory afferents from medium spiny neurons of the nucleus accumbens (Xia et al., 2011). If a footshock leads to a decrease in MSN activity, this could cause the disinhibition of VTA GABA neurons and eventually inhibition of DA neurons. This however seems unlikely as a tail pinch causes, on the contrary, an excitation of striatal units and would have an effect with a longer Non-specific serine/threonine protein kinase latency (Williams and Millar, 1990). Alternatively, an increased excitatory drive may be responsible for the enhanced GABA neuron activity. In rats, the lateral habenula sends excitatory inputs onto GABA neurons clustered in the tail of the VTA termed RMTg nucleus (Ji and Shepard, 2007). These neurons have been demonstrated to impinge on VTA-DA neurons (Jhou et al., 2009b and Kaufling et al., 2009). Functionally, when the RMTg is surgically lesioned, the response to aversive stimuli is attenuated, which suggests a convergence of aversive inputs onto the RMTg (Jhou et al., 2009a). The GABA neurons recorded and stimulated in the present study are located throughout the VTA, albeit with a somewhat higher density toward dorsal and caudal parts of the VTA.

To test this, we wanted to see if we could recapitulate the normal directed behavior using our Lam1 bead assays. Kif5c560-YFP-expressing RGCs were cultured in the vicinity of Lam1-coated polystyrene beads (Figure 7A, Movie S13). Consistent with our model, when a Stage 2 neurite contacted a Lam1 bead, this induced the translocation

of the Kif5c560-YFP signal to the contact BI 2536 solubility dmso point, demonstrating that Laminin contact catalyzes this specific accumulation. Interestingly, when two or more neurites contacted Lam1, Kif5c560-YFP accumulated in specifically these contacting neurites, but often only in one neurite at a time, and oscillated between these (but rarely other) neurites (Figure 7B, Movie S14). RGCs were also cultured along borders of poly-L-lysine and Lam1 by plating on coverslips with islands of Lam1 within a homogenous poly-L-lysine coating. Similar to when RGCs contacted multiple

Lam1 beads, an RGC polarizing along a Lam1 border demonstrated a clear bias in Kif5c560-YFP accumulations, where the signal oscillated between different Lam1-contacting neurites before stabilizing in one, which extended to form the axon (Figure 7C, Movie S15). Having established that this was the case in vitro, we moved to the in vivo assay. Lam1 beads were implanted into mosaic embryos created by C59 wnt cost transplantation of blastomeres from ath5:GAP-RFP, Kif5c560-YFP RNA-injected embryos into Lamα1 morphant host embryos ( Figures 7D and 7E, Movie S16). As described above, RGCs in the Lam1-deficient environment exhibit oscillatory Kif5c560-YFP accumulations. However, when one of the neurites contacted the Lam1-coated bead, Kifc560-YFP accumulated specifically at the contact point. The YFP signal accumulation was stable, with only very transient and weak signal visible within the basal process, and the Lam1 contacting process did not retract. Subsequently this

neurite transformed into the axon and extended away from the bead. Therefore, contact with Lam1 caused the cessation of the Kif5c560-YFP oscillations within Stage 2 RGCs in vivo, and recapitulated the normal behavior of RGCs Montelukast Sodium when they come in contact with the basal surface of the WT retina, where Lam1 contact results in specific and stable Kif5c560-YFP accumulation preceding axon extension. Imaging experiments in the vertebrate retina have demonstrated that bipolar cell polarization occurs through the directed sprouting of axons and dendrites from basal and apical processes, respectively (Morgan et al., 2006). Similarly, RGC polarization occurs through directed sprouting of axons from the most basal point of the cell. In contrast to behavior in cultured neurons, no multipolar Stage 2 behavior is seen prior to RGC axon extension in vivo.

Consistent with this prediction, responses in rmPFC,


Consistent with this prediction, responses in rmPFC,

ACCg, and precuneus/PCC at the time of decisions were positively correlated with behavioral estimates about agents’ expertise. The model also predicts a simulation-based revision of expertise beliefs, just after subjects observe the agent’s choice. In line with this prediction, responses in rTPJ, dmPFC, rSTS/rMTG, and premotor cortex tracked unsigned simulation-based aPEs at that time. Finally, the sequential model predicts an evidence-based revision to subjects’ expertise estimates when they witness the final feedback. Accordingly, we found that responses in lateral precuneus and rdlPFC at this time increased with unsigned evidence-based aPEs. Together, these findings show localized Roxadustat neural activity for all of the key elements of the computational model. The network found to encode expertise buy Gemcitabine estimates during decisions has previously been implicated in component processes of social cognition. rmPFC has consistently been recruited in mentalizing tasks and has been suggested to play a top-down role in biasing information to be construed as socially relevant (Frith and

Frith, 2012). Cross-species research has also suggested that ACCg plays a role in the attentional weighting of socially relevant information (Baumgartner et al., 2008, Behrens et al., 2008, Chang et al., 2013 and Rudebeck et al., 2006), whereas activity in both the ACCg and posterior cingulate gyrus, which was also found to reflect expertise estimates, has been linked to agent-specific responses during the trust game (Tomlin oxyclozanide et al., 2006). Here, we extend these findings by showing that these regions also play

a role in representing another agent’s expertise when this information must be used to guide decision making. Furthermore, we show that intersubject variance in the fit of the sequential model explains variance in the neural fluctuations associated with tracking expertise in these same regions, and also in dmPFC. Another set of brain regions, which includes rTPJ, dmPFC, and rSTS/rMTG, encoded simulation-based aPEs, when observing the agent’s choice. In order to compute simulation-based aPEs in our task, the subject must simulate his or her own prediction and then compare this with both the agent’s prediction and the agent’s estimated expertise level. The behavioral finding that learning depends on one’s own asset predictions and the neural identification of simulation-based aPEs complement recent demonstrations that simulation or modeling plays a central role in predicting others’ behavior (Nicolle et al., 2012 and Suzuki et al., 2012). Activity in components of this network has repeatedly been reported during mentalizing (Frith and Frith, 2012 and Saxe, 2006).

In the CSP-α KO, dynasore also induced a reduction in ΣQC in comp

In the CSP-α KO, dynasore also induced a reduction in ΣQC in comparison to control conditions (59,135 ± 7,207 in control and 39,961 ± 5,525 in dynasore) (Figure 6I). We interpreted that under such stimulation conditions, 139.1 ± 5.2% of the vesicles in WT junctions were reused by a dynasore-sensitive mechanism (Maeno-Hikichi et al., 2011), in contrast to only 46.0 ± 7.4% of vesicles recycled in mutant synapses (Figure 6J). A recent study at the frog NMJ (Douthitt et al., 2011) has reported that dynasore treatment increases ABT-263 solubility dmso release probability at low (1 Hz) but not at high (50 Hz) stimulation frequency, so we cannot rule

out that the fluorescence increase in dynasore attributed to endocytosis inhibition might have, in the worst of the cases, a minor component due to increased exocytosis. We have evaluated the increase in cumulative quantal content (QC) in dynasore compared to control conditions to find that such a ratio is the same for WT and mutant junctions (Figure S4G). In any case, we do not consider that such an effect of dynasore on neurotransmitter release interferes significantly with its major blocking effect of endocytosis that we have used in our study. In summary,

in the absence of CSP-α, dynasore-sensitive recycling of synaptic vesicles was impaired and that could contribute to the strong synaptic depression under repetitive stimulation at the terminals from CSP-α KO mice. We analyzed the uptake and release of the stiryl dye FM2-10 at the NMJ in CSP-α KO learn more mice that were not spH transgenic. We depolarized motor nerve terminals (600 s at 30 Hz) in the presence of FM2-10 to label the entire recycling pool (Perissinotti et al., 2008), washed out the noninternalized dye and induced dye release (600 s at 30 Hz). The WT junctions loaded the dye efficiently and, upon stimulation, underwent almost total destaining (Figures 7A, arrowheads, and 7B) as expected for normal synaptic vesicle endo- and exocytosis. The mutant terminals internalized the dye very much efficiently too (Figure 7A, arrows). However, upon stimulation, the dye released from the mutant terminals

was dramatically low (Figure 7B). FM2-10 loading at mutant terminals was even higher than at the controls (Figure 7C) (51%, p = 0.04 Student’s t test). Nevertheless, in mutant nerve terminals stimulated to release, most of the dye (66.9 ± 2.7% of the total loaded) became trapped inside, whereas in the control terminals the residual dye was very little (19.9 ± 4.4%, p < 0.001, Student’s t test) (Figure 7D). To go deeper in our study, we carried out ultrastructural analysis of synaptic terminals with electron microscopy. In general, mutant junctions fixed in resting conditions presented normal postsynaptic foldings and similar nerve terminal size and vesicle density to WT terminals (Figure 7E, panels a–c, and S5A).

, 1993a, 1993b,

, 1993a, 1993b, KU 57788 1993c). They are phase locked to population neuronal activity measured by electroencephalogram (EEG) and represent a characteristic feature of non-REM sleep (Wang, 2010). Slow oscillatory activity is associated with Up-Down state transitions in cortical neurons, consisting of hyperpolarized Down

states and intermittent depolarized Up states, as indicated by experiments performed both in vivo (Doi et al., 2007) and in vitro (Shu et al., 2003). These brain state transitions play a major role in memory consolidation (Landsness et al., 2009; Rolls et al., 2011; Steriade and Timofeev, 2003) and may also control, at least in cortical slices, gamma activity (Compte et al., 2008). During non-REM sleep as well as during many forms of anesthesia, Caspase inhibitor slow oscillations occur spontaneously (Haider et al., 2006), but they can also be evoked by brief sensory stimulation (Gao et al., 2009; Sakata and Harris, 2009), similar to activity patterns in early postnatal development such as spindle bursts (Hanganu et al., 2006; Khazipov et al., 2004). Furthermore, recent experimental evidence indicates that slow-wave-like activity is present both during periods of quiet wakefulness as well as in local neuronal clusters in nonanesthetized rodents (Poulet and Petersen, 2008; Vyazovskiy et al., 2011). Up to now, slow oscillatory activity has been monitored on population level mostly by electrophysiological

methods, such as electric local field potential (LFP) recordings (Steriade, 2006). However, it is becoming

increasingly clear that LFP might integrate neuronal activity through volume conductance over many millimeters (Kajikawa and Schroeder, 2011; Lindén et al., 2011), thus not allowing for unambiguous comparisons of spatial dynamics of slow-wave activity at different locations. Previous studies show that fluorometric Ca2+ recordings of neural activity, which monitor predominantly action potential firing (Kerr et al., 2005; Stosiek et al., 2003), represent a second useful method of recording slow-wave-associated Ca2+ transients (Rochefort et al., 2009). Such Ca2+ waves can be detected in vivo in the mammalian neocortex both during development (Adelsberger et al., 2005) and in the adult (Kerr et al., 2005). In development, these waves occur spontaneously in resting pups and may mirror functional organization of cortical circuits. In the adult, these waves may be associated with electrically recorded slow waves (Grienberger et al., 2012; Rochefort et al., 2009). Yet, the relation between Ca2+ waves and slow electrical waves on a global level remains unclear. Ca2+ waves in subcortical structures such as the thalamus have not been identified up to now. There is evidence that both spontaneous as well as sensory-evoked slow oscillatory activity may represent traveling waves, recruiting large areas of the cortex (Ferezou et al., 2007; Massimini et al., 2004; Xu et al., 2007).