, 1998). It became clear that the numbers of GPCRs outnumbered the number of known neuromodulators selleck inhibitor (later the completion of the human genome revealed the full extent of the GPCR diversity). The conclusion of this recognition was (and still is) that many orphan GPCRs must be activated by undiscovered neuromodulators, since inactive GPCRs would have been evolutionarily discarded. The corollary of this conclusion was that orphan receptors may be used as baits to identify novel neuromodulators (Civelli et al., 2001). The approach used to isolate novel neuromodulators consists of expressing an orphan GPCR in heterologous cells and test these against brain tissue extracts. Receptor

reactivity is monitored by quantifying

changes in second messenger levels. The extract displaying reactivity is fractionated and its purification is pursued to homogeneity. The first orphan GPCR used in this approach was ORL-1, an orphan GPCR sequentially related to the opioid receptors (Henderson and McKnight, 1997). Its activation was monitored by monitoring intracellular decreases in cAMP levels. Its neuromodulator was extracted from brain tissues PD0332991 purchase and shown to be a neuropeptide, named orphanin FQ or nociceptin (OFQ/N) (Meunier et al., 1995; Reinscheid et al., 1995). This neuropeptide shares sequence similarities to the opioid peptides but also precise differences that render it inactive at opioid receptors (Reinscheid et al., 1998). This strategy has since been used to discover the following neuropeptides (Figure 5): the two orexins (Oxs) (Sakurai et al., 1998), also identified STK38 through an RNA subtraction approach as hypocretins (Hcrts) (de Lecea et al., 1998); prolactin-releasing peptide (PrRP) (Hinuma et al., 1998); apelin (Tatemoto et al., 1998); ghrelin (Kojima et al., 1999); kisspeptin/metastin (Ohtaki

et al., 2001); the two prokineticins (Lin et al., 2002; Masuda et al., 2002); neuropeptide B and neuropeptide W (NPB/W) (Brezillon et al., 2003; Fujii et al., 2002; Shimomura et al., 2002; Tanaka et al., 2003); neuropeptide S (NPS) (Sato et al., 2002; Xu et al., 2004); neuromedin S (Mori et al., 2005); and finally relaxin-3 (Liu et al., 2003). Each of these neuropeptides has been the subject of intense research, which has helped better understand a number of physiological processes. I will not cover all the advances that they have brought to neuroscience here, but in the next section, I review, as examples, three of the brain-directed responses for which our understanding has been drastically impacted by orphan GPCR research. Studies on one orphan GPCR system, the orexin/hypocretin (Oxs/Hcrts) system, has had a great impact on our understanding sleep/wakefulness states. Soon after the discovery of the Oxs/Hcrts it was shown that mice devoid of Oxs/Hcrts exhibit a pronounced narcoleptic behavior (Chemelli et al., 1999).

Recent developments in brain imaging have enabled the emphasis to shift toward population LGK-974 research buy encoding. However, these studies

have focused almost exclusively on postsynaptic processing of sensory input. Very little is known on a population basis of the functional input delivered by sensory neurons to a given CNS target. The exception to this rule is the olfactory bulb, where defining the response properties of many glomeruli simultaneously at the sensory input level has provided direct insight into spatiotemporal coding of odorant stimuli (Friedrich and Korsching, 1997; Soucy et al., 2009). Here we provide the first systematic description of the form, organization, and dimensionality of the population of visual inputs to the brain using the optic tectum of larval zebrafish as a model. At 6 days postfertilization, zebrafish larvae are translucent and exhibit a repertoire of complex visually guided behaviors, making them an excellent model system for imaging studies of visuomotor transformations (Portugues and Engert, 2009). At this stage Selleck cancer metabolism inhibitor of development, the larval brain is also small in terms of physical size and number of neurons, allowing activity patterns across a substantial fraction of neurons in the brain to be imaged in a single field of view using optical approaches (Niell and Smith, 2005; Sumbre et al., 2008). The optic tectum, which is used to guide behaviors such as prey capture

and predator and obstacle avoidance (Gahtan et al., 2005), has four distinct retinorecipient laminae, and as a rule, the axon of a single retinal ganglion cell (RGC) is restricted to a single lamina (Xiao and Baier, 2007). To examine the nature of the visual input to the tectum, we fused the genetically encoded calcium sensor GCaMP3 to the synaptic vesicle protein synaptophysin (Tian et al.,

2009) and generated a stable transgenic line of zebrafish that expresses the resulting probe (SyGCaMP3) specifically in RGCs. This allows us to record visually evoked calcium transients in presynaptic terminals of RGC axons in the intact zebrafish brain. The same strategy has been adopted previously using a synaptophysin-GCaMP2 fusion to study population activity of bipolar cells in the zebrafish retina (Dreosti et al., 2009; Odermatt et al., 2012). Furthermore, we developed Terminal deoxynucleotidyl transferase an unbiased voxel-wise analysis strategy that permits functional characterization of the retinal input independent of RGC axon or tectal neuropil morphology and at a spatial scale below that of a presynaptic bouton. This not only allows visual selectivity to be determined on a voxel-by-voxel basis, but also describes visual input to the tectum on a population basis. We have used these techniques to characterize responses to drifting bars. We have identified three subtypes of direction-selective input and two subtypes of orientation-selective inputs.

Infection rates of 80%–95% of the neuron population were obtained for all three rAAVs ( Figures S3A and S3B). QRT-PCR and immunoblot analysis revealed that rAAV-shVEGFD, but not rAAV-shSCR or rAAV-emptymC, reduced VEGFD mRNA levels and blocked VEGFD protein expression ( Figure 4B selleck chemicals and Figure S3C). Expression of VEGFC was not affected by rAAV-shVEGFD or by the two control rAAVs ( Figure 4B). It has been reported that expression of certain shRNAs can have an effect on neuronal morphology because of the induction of an interferon response ( Alvarez et al., 2006). However, by using an interferon-responsive reporter gene system we found no

evidence for an interferon response induced by rAAV-shVEGFD ( Figure S3D). In addition, we observed no increase in cell death in hippocampal neurons infected with rAAV-shVEGFD ( Figure S3E). Morphological analyses revealed that compared to hippocampal neurons transfected with pAAV-shSCR or pAAV-emptymC, neurons transfected with pAAV-shVEGFD showed a less complex dendritic arbor and a reduction in total dendritic length ( Figures 4C–4E). In contrast, RNAi-mediated knockdown of VEGFD did not change spine density (number of spines/20 μm: 7.1 ± 0.36, pAAV-emptymC; 6.17 ± 0.56, pAAV-shSCR; 6.52 ±

0.51, pAAV-shVEGFD). Similar results were obtained with different shRNA sequences directed against VEGFD ( Figure S3F and Supplemental Experimental Procedures). The effect of pAAV-shVEGFD transfection on the dendritic tree could be

reversed by treatment with rVEGFD. In contrast, rVEGFD did not affect dendrite length or BGB324 nmr complexity of hippocampal neurons transfected with pAAV-shSCR and pAAV-emptymC ( Figures 4C–4E). These results identify a role for VEGFD in the regulation of dendritic architecture and further support the above-mentioned concept (see Figure 3) that dendrite arborization and spine morphogenesis are controlled by distinct nuclear calcium/CaMKIV-regulated processes. The observation that the dendrite structure is altered in shVEGFD-expressing neurons even if the surrounding untransfected cells have a normal VEGFD expression level suggests a possible autocrine mechanism of action of VEGFD. To investigate this further, we transfected hippocampal neurons with pAAV-VEGFD-HA or with a plasmid nearly containing an expression cassette for HA-tagged VEGFD resistant to shVEGFD (pAAV-resiVEGFD-HA) together with pAAV-shVEGFD in order to overexpress VEGFD in the same neurons expressing shVEGFD. Expression of resiVEGFD-HA rescued the reduction of dendrite length and complexity caused by expression of shVEGFD ( Figures 4F–4H), indicating that VEGFD acts in an autocrine manner. This conclusion is further supported by an experiment in which hippocampal neurons were first infected with rAAV-VEGFD and subsequently transfected with pAAV-shVEGFD.

Surprisingly, many synapses in the central nervous system can sustain synaptic activity upon high-frequency stimulation (Kopp-Scheinpflug et al., 2008, Kraushaar and Jonas, 2000, Lorteije et al., 2009 and Rancz et al., 2007). In order to maintain the fidelity

of synaptic transmission, synaptic vesicles (SVs) are required to undergo fast recycling to prevent depletion of the SV pool (Fernández-Alfonso EPZ-6438 mouse and Ryan, 2004 and Sudhof, 2004). Recently it has been reported that interfering with the function of endocytic proteins causes a fast, stimulation-frequency-dependent depression of SV exocytosis (Hosoi et al., 2009 and Kawasaki et al., 2000). As obvious explanation for such findings, the lack of release-ready SVs may be invoked due to absence of recycled SVs. However, some of these inhibitory effects developed so rapidly that they cannot be explained by the lack of release-ready SVs, since the reservoir of SVs should well be able to maintain release for longer periods. In this study we investigated vesicle exocytosis in cultured rat hippocampal neurons using synaptopHluorin (Miesenböck et al., 1998 and Sankaranarayanan

et al., 2000) in the presence of Folimycin, a potent and specific inhibitor of vesicular reacidification, that does not affect exo-endocytosis Selleck Panobinostat (Zhou et al., 2000). We demonstrate that upon mild stimulation no reuse of SVs occurs within 40 s and that recruitment of pre-existing PD184352 (CI-1040) SVs is fast enough to meet the needs of a high release rate. However, under the influence of the specific endocytosis inhibitor Dynasore (Macia et al., 2006) or the inhibitor of clathrin-mediated endocytosis Pitstop 2 (von Kleist et al., 2011) we observed a clear stimulation-frequency-dependent release depression. This probably reflects interference of these inhibitors with the process of rapid clearance of exocytosed SV components from the synaptic release sites. This notion was corroborated by the observation of acute vesicular protein accumulation around the release site using

dual-color STED nanoscopy. To reliably measure the level of synaptic release depression, we quantified the amount of exocytosis upon different stimulation strengths using synaptopHluorin (spH) in cultured hippocampal neurons (Miesenböck et al., 1998 and Sankaranarayanan et al., 2000). At presynaptic terminals expressing spH, exocytosis of SVs evoked by electric field stimulation (via action potentials, APs) led to dequenching of spH molecules in neutral extracellular buffer, resulting in an instantaneous fluorescence increase (Figure 1A). Under such experimental conditions, the fluorescence change is proportional to the amount of spH exocytosed. The absolute amplitude of the signal can differ, however, from cell to cell due to inhomogeneous expression of the probe and variation in release probability.

bailii NCYC 1766 in YEPD corrected to pH 4.0. Resistant of sub-populations were selected of single colonies growing in 8 mM benzoic acid or in 350 mM acetic acid at 14 days, and re-inoculated. The rates of growth Z. bailii (NCYC 1766) in increasing FK228 price concentrations of weak-acid preservatives was monitored in the 96-well microtitre plates by the time required for the yeast colonies to reach 0.5–1 mm in size. In the absence of preservatives, this required only 2–3 days incubation. At higher concentrations of preservatives, the incubation

time required increased up to 12–14 days. As previously described in Section 2.4, single colonies of Z. bailii (NCYC 1766) growing in 6 mM sorbic acid, 8 mM benzoic acid or 350 mM acetic acid after 14 days, were mixed in the microtitre well and accurately counted

by haemocytometer. Each was then serially diluted in YEPD containing the same weak acid concentration to 104 cells/ml. Each was then cross-inoculated into all combinations of weak acids, at 15–30 cells/ml into 20 ml aliquots of YEPD containing sorbic acid (0–8 mM), HDAC cancer benzoic acid 0–8 mM and acetic acid 0–450 mM. These were then dispensed into microtitre plates at 200 μl/well (maximum 3–6 colonies/well). Plates were sealed, lidded, double-bagged to prevent evaporation, and incubated at 25 °C for 14 days. The method used for determination of cellular internal pH by flow cytometry was a modification of the method described in Stratford et al. (2009). Exponentially-growing yeast cells were obtained from shake flasks at OD next 1.65–2.2 (measured OD 0.15–0.2 following an 11-fold dilution in water). Z. bailii (NCYC 1766) and S. cerevisiae (BY4741) were cultured in 40 mls YEPD pH 4.0 in 100 ml conical flasks shaken for 12–16 h at 130 rpm and

25 °C. Sub-populations in 6 mM sorbic acid, 8 mM benzoic acid and 350 mM acetic acid in microtitre plates were inoculated into 40mls of the same media and shaken for 5 days (OD 0.15 × 11). Control samples were tested in microtitre plates at 0, 6 mM sorbic acid, 8 mM benzoic acid or 350 mM acetic acid to confirm that these populations were ~ 100% resistant to preservatives. CFDASE (carboxyfluoresceindiacetate succimidyl ester) was added to yeast in the growth media at 10 μg/ml final concentration and cells were incubated at 25 °C for 30 min for uptake of the CFDASE. Uncharged CFDASE, colourless and non-fluorescent, passes into the cell where it is cleaved intracellularly by esterases. The fluorescent succimidyl ester binds to proteins, ensuring retention of the dye within the cell. The internal pH of populations of individual fluorescent cells was determined from the linear ratio of the 575 nm (largely pH-independent) and 525 nm (pH-dependent) emission signals. Calibration was carried out using cells of defined intracellular pH, permeated using 2 mM 2, 4-dinitrophenol in 0.

, 2006 and Raichle et al., Selleck Ibrutinib 2001). Until the study of spontaneous BOLD activity, however, the association

of regions within a functional system was to some extent dependent upon sets of task paradigms. Task-based approaches left functional systems open to an interpretation that rather than being a fundamentally related group of brain regions within a brain-wide context, a functional system thus defined might be just a transient and task-specific association of brain regions. The subgraphs presented herein were derived in task-free data using methods with no prior information about node identity. There is substantial agreement between aspects of paradigm-driven functional system definition in neuroimaging, and paradigm-free subgraphs derived in task-free activity. Even if one were to object that the areal network included functional

assumptions via meta-analytic localizers, the modified voxelwise analysis, which returned very similar results, made no such assumptions. In a brain-wide context, several functional systems are distinguished from each other by spontaneous activity. This task-free definition of brain functional organization can inform perspectives on cognitive function. For example, dorsal selleck chemicals llc and lateral frontal cortex appears to be apportioned among a variety of distributed subgraphs, many of which correspond to functional systems with known characteristics (Figure 2). This organization does not appear consistent with accounts of cognition that posit rostro-caudal gradients or hierarchies across frontal cortex (Badre and D’Esposito, 2009 and O’Reilly, 2010). In a related manner, the finding no of similar graph properties (relatively dense internal relationships and relatively few external relationships) in visual, SSM, and default mode systems may inform the degree to which the default mode system is seen as a processing type of system versus a control type of system. Such a finding need not contradict the description of posterior members of the default mode

system as cortical hubs (Buckner et al., 2009), but it may alter the understanding of what it means to be a hub. Recent investigations into the structure of functional brain organization using a variety of methods (Erhardt et al., 2010 and Yeo et al., 2011) have found some similar (but not identical) sets of resting state networks as the subgraphs reported here. We consider convergence across methods to be a key indicator of the validity of findings. We find the graph theoretic framework to be especially useful, because it is capable of describing the overall graph (no such measures are presented in this article, but small-world measures are an example), portions of the system (e.g., subgraphs), or individual nodes of the system (e.g., local efficiency) within a common framework. Our findings have substantial implications for past and future graph-based analyses.

Further, NMDA receptors play a crucial role in the modification of neural connectivity during or following experiences. NMDA antagonists attenuate experience-driven reorganization of the body map in S1 of awake animals (Jablonska

et al., 1999) and retard value-related changes of neural firing in orbitofrontal cortex of behaving animals (van Wingerden et al., 2012). These data suggest that neural reactivation causes formation of long-term memories via NMDA-dependent changes in synaptic strength. The pattern reactivation phenomena we describe GS-1101 mw here is also dependent on NMDA receptors and is therefore consistent with the mechanisms of memory consolidation in the awake state. Previous studies have suggested that “reverberating” patterns are similar to spontaneous patterns that precede specific sensory experience. This phenomenon is termed “preplay” and was elegantly shown in hippocampal cortex by Dragoi and Tonegawa (2011). Similarly, in Euston et al. (2007) in Figure 1, the pretask spiking patterns in medial prefrontal cortex have obvious similarity

to patterns during the task and patterns replayed after the task. The data presented here are consistent with these results and suggest that repeated stimulation induces only gradual changes to existing spiking patterns (note that, in Figures 2D and 6A–6E, similarity of evoked patterns to preceding spontaneous activity is consistently above 0). MDV3100 mouse For that, the relationship between stimulus-evoked (or reverberating) sequences to prior patterns occurring spontaneously is a very important question. We have previously shown that

stereotypical patterns of population activity are associated mostly with the beginning of UP states (Luczak and Barthó, 2012 and Luczak et al., 2007) and that stimulus-evoked patterns have strikingly similar temporal structure to such spontaneous patterns (Luczak et al., 2009). Furthermore, even in desynchronized brain states, population activity is composed of bursts of population activity with similar temporal structure to Adenylyl cyclase patterns during UP states in synchronized states (Luczak et al., 2013). Similar sequential patterns with stereotyped spatiotemporal dynamics have been also observed in vitro (Mao et al., 2001, Cossart et al., 2003, Ikegaya et al., 2004 and MacLean et al., 2005), suggesting that network UP states could be circuit attractors. Together, these in vitro and in vivo studies suggest that connectivity patterns at the local level impose significant constraints on activity propagation (Luczak and Maclean, 2012), thus leading to formation of similar sequential population patterns both spontaneously and during stimulation (although different stimuli produce slightly different variations of that sequential pattern; Luczak et al., 2013).

The large-amplitude depolarizing bumps that occurred at low frequencies in the

complex cell had roughly comparable counterparts in the simple IBET762 cell, but the match between the two waveforms was much less precise than in the complex cell pairs (for example, Figure 1). Overall, the spontaneous activity of two cells had a low correlation (0.4; Figure 7C, left and middle column, black trace), smaller than almost all of the complex cell pairs (Figure 4A). Most of this correlation was due to activity below 20 Hz, since high-pass filtering with a cutoff of 20 Hz removed much of the correlation (Figure 7C, right column, black trace). This result is also reflected in the coherence spectrum for spontaneous activity (Figure 7F, black trace), which shows significant coherence only at frequencies below 20 Hz. We can now ask how Vm synchrony responds to the presentation Apoptosis inhibitor of optimal visual stimulation. During optimal stimulation, spiking activity is largely confined to the column containing these cells. It might be, then, that the cells’ Vm becomes much more correlated. This is not the case, however. Membrane potential responses to preferred (0°) stimulation are shown in Figure 7B (second row). By the definition of simple and complex cells, the temporal patterns of visually evoked

responses in the two cells were very different, the simple cell showing strong modulation of both Vm and spike rate at the stimulus frequency (2 Hz), in contrast to the complex cell which gave an unmodulated response. As in the complex cell pairs, optimal stimulation caused a decrease in the amplitude and width of the

correlation (Figure 7C, first row, left; note that the stimulus component of the evoked response was removed before cross-correlation was calculated). The overall reduction might correspond to a strong decrease in the correlation of the low-frequency components and a weak increase in the correlation of the high-frequency components (Figure 7C, first Astemizole row, right). During visual stimulation, high-frequency components of the complex cell only had a weak correlation with those in the simple cell and the coherence was about one-third of those seen in complex-complex pairs (Figure 7F, compare the coherence value of 0.18 at 20–40 Hz with the coherence of previous complex cell pairs in similar frequency range). Visual stimulation increased the high-frequency Vm power in the simple cell without a distinctive peak in either the Vm power spectrum (Figure 7D, cyan) or the spectrum of relative power change (Figure 7E, top), in contrast to the complex cell. Nonpreferred stimulation (e.g., 270°; Figure 7B, third row) also narrowed the width of the correlation but left the amplitude nearly unchanged (Figure 7C, second row). Two more simple-complex pairs are shown in the Figure S6 (pairs 11 and 12).

A possible source is narrow-field amacrine cells (Masland, 2001 and Chen et al., 2010). The iso-latency MDV3100 cost curves were not affected by the inhibitory mechanism that underlies the gain control; iso-latency curves always depicted the standard threshold-quadratic nonlinearity. This can simply be explained by a temporal delay of inhibition, resulting from involvement of an additional synaptic stage as compared to the direct excitation from bipolar cells (Werblin and Dowling, 1969, Roska et al., 2006 and Cafaro and Rieke, 2010). Note that the inhibition may act as a

direct input into the ganglion cells or indirectly by suppressing or modulating the bipolar cell output; the functional characterizations of the present study do not distinguish between these circuit features. The inhibition makes strong local stimuli that involve only a subset of available bipolar cells OSI-744 cost less effective, or in other words, it creates a particular sensitivity for spatially homogeneous stimulation when the activity load is shared between all available bipolar cells with weaker individual activation. The characteristic notch in the iso-rate curves of homogeneity detectors can thus be explained completely by local sensitivity changes without the need to evoke a direct interaction between the subregions of the receptive field. Interestingly, an example for the required strongly nonlinear activation of inhibition

has recently been found in paired recordings of certain amacrine cells and their presynaptic bipolar cells (Jarsky et al., 2011). The disproportionally stronger activation of inhibition for stronger stimulation also explains why the iso-rate curve

shapes differ for different target spike counts. The effect of inhibition becomes stronger with stronger stimulation, and consequently the notch in the iso-rate curves becomes more pronounced with larger target spike counts (Figure 3E and 7E). The striking differences between different ganglion cells in the nonlinearities of signal integration raise the question of the associated visual functions. To illustrate the effects of the observed Adenosine receptive field nonlinearities, let us therefore consider a simple visual stimulus, which contains a large dim object as well as a group of several small objects at high contrast (Figure 8A). When viewed through linear receptive fields, both the large dim object and the area with the small high-contrast objects appear equally prominent (Figure 8C). Receptive fields that integrate their subunits with a threshold-quadratic nonlinearity, however, emphasize the high-contrast region (Figure 8D), whereas nonlinear integration in the fashion of homogeneity detectors facilitates the detection of the large dim object while being insensitive to high-contrast clutter (Figure 8E). This suggests that homogeneity detectors contribute particularly to the detection of large objects.

We emphasize that we recorded from only Bcl-2 inhibitor small numbers of IL units, and we used behavioral measures that only indirectly accessed underlying performance strategies; other features of IL activity that track behavior trial-to-trial, directly or through its interactions with other regions, may have been covertly present. It is nonetheless striking that a strong correlation did hold between the dominant

IL ensemble activity pattern and habitual features of behavior measured at the level of sessions, which were at particular levels of learning and behavioral plasticity. Notably, the times at which the task-bracketing activity pattern was observed in IL cortex were nearly identical to the times at which optogenetic IL perturbation (of all layers) could disrupt the maze habits: during overtraining, as shown here, as well as after overtraining and after postdevaluation training when a second habit had become established GSK1210151A research buy (Smith et al., 2012). These times, in turn, were highly correlated with the periods in which the numbers of deliberative head

movements declined. Together, these results suggest that the task-bracketing pattern in the IL cortex could reflect the training-related development of a potent and active IL influence over the sculpting of habits as well as an influence over their execution. The lack of trial-level correlation with behavior suggests a contribution to habits at the level of states that bias behavior toward outcome insensitivity (or low deliberation). This view might help

account, for example, for the fact that the ILs bracketing pattern remained on PP day 1, when we had previously reported that IL perturbation does not affect behavior (Smith et al., 2012); the pattern, although present, was joined by marked increases in spiking variability and magnitude reflecting perhaps a mixed habit/nonhabit state. If the IL cortex were to have such a state-level influence, how would it interact with the DLS to promote habits, given that direct connections between them have not been detected? Potential indirect connectivity could include fiber projections via the ventral striatum or the amygdala and the substantia nigra or through by way of projections to other cortical areas and then to the DLS (Hurley et al., 1991). However, as favored here, the IL cortex and the DLS might work partly in parallel, promoting habits through distinct circuit mechanisms, with the IL cortex providing, by way of its many limbic connections, routes by which it could disrupt flexibility and mnemonic processes or invigorate learned behavior. An unexpected finding of this study is that the task-bracketing pattern that did form in the IL cortex was evident only in the superficial layers. Superficial cortical layers are especially important for transcortical processing, and deeper layers for cortical projections to subcortical regions including the striatum (Anderson et al.