, 2004 and Boumans et al., 2008). Individual auditory cortical neurons appear well suited to encode vocalizations presented in a distracting background, in part because the acoustic features to which individual cortical neurons respond are more prevalent in vocalizations than in other sound classes (deCharms et al., 1998 and Woolley et al., 2005). Futhermore, in response to vocalizations, auditory cortical neurons often produce sparse and selective trains of action potentials (Gentner and Margoliash,

2003 and Hromádka et al., 2008) that are theoretically well suited to extract and click here encode individual vocalizations in complex auditory scenes (Asari et al., 2006 and Smith and Lewicki, 2006). However, electrophysiology studies have found that single neuron responses to individual vocalizations learn more are strongly influenced by background sound (Bar-Yosef et al., 2002, Keller and Hahnloser, 2009 and Narayan et al., 2007). Discovering single cortical neurons that produce background-invariant spike trains and neural mechanisms for achieving these responses would bridge

critical gaps among human and animal psychophysics, population neural activity, and single-neuron coding. Here, we identify a population of auditory neurons that encode individual vocalizations in levels of background sound that permit their behavioral recognition, and we propose and test a simple cortical circuit that transforms a background-sensitive Edoxaban neural representation into a background-invariant representation using the zebra finch (Taeniopygia guttata) as a model system. Zebra finches are highly social songbirds that, like humans, communicate using complex, learned vocalizations,

often in the presence of conspecific chatter. We first measured the abilities of zebra finches to behaviorally recognize individual vocalizations (songs) presented in a complex background, a chorus of multiple zebra finch songs. We trained eight zebra finches to recognize a set of previously unfamiliar songs using a Go/NoGo task (Gess et al., 2011; Figure 1A), and we tested their recognition abilities when songs were presented in auditory scenes composed of one target song and the chorus (Figure 1B). We randomly varied the signal-to-noise ratio (SNR) of auditory scenes across trials by changing the volume of the song (48–78 dB SPL, in steps of 5 dB) while keeping the chorus volume constant (63 dB; Figure 1B). Birds performed well on high-SNR auditory scenes immediately after transfer from songs to auditory scenes (Figure S1 available online), indicating that they recognized the training songs embedded in the scene.

Thus, SGN axons are arrayed in a high-to-low-frequency tonotopic map along the dorsoventral axis of the CN (Young and Oertel, 2004). Similar tonotopy is observed in CN neuronal responses themselves, determined both electrophysiologically (Luo et al., 2009) and by Fos induction ( Friauf, 1992; Saint Marie et al., 1999). We injected FosTRAP mice with 4-OHT during a 4 or 16 kHz continuous pure tone stimulus to TRAP CN neurons tuned to those frequencies. To increase the total number of TRAPed cells, we took advantage of TRAP’s ability to integrate IEG expression over

time by using a 4 hr pure tone stimulus during the TRAPing period. Then, 4–5 days later, we delivered a second 4 or 16 kHz stimulus for 1 hr, sacrificed the mice 1 hr SAR405838 research buy later, and processed the tissue for Fos immunostaining (Figure 5A). Thus, TRAPed cells represent neurons GSK2118436 activated by the first stimulus, and Fos protein immunopositive (Fos+) cells represent neurons activated by the second stimulus. Consistent with prior results, we found that 4 kHz stimulation during the second epoch induced Fos expression in clusters of cells in all three CN

subdivisions that were located more ventrally than the clusters that were Fos+ after 16 kHz stimulation. Similar results were observed for TRAPed cells. When the tone frequency was the same for the two stimulus epochs, the TRAPed and Fos+ populations overlapped, and the 4 kHz cluster was localized more ventrally than the 16 kHz cluster (Figure 5B, first and third columns). Within mice receiving stimuli of two different frequencies, the cells TRAPed by the 16 kHz stimulus almost were dorsal to Fos+ cells induced by the 4

kHz stimulus (Figure 5B, second column), whereas the reverse was true when the 4 kHz stimulus was TRAPed and the 16 kHz representation was revealed by Fos immunostaining (Figure 5B, last column). These qualitative impressions were confirmed by the quantification of the numbers of TRAPed and Fos+ cells in bins spanning the dorsoventral axis of the central dorsal cochlear nucleus (DCN; Figure 5C). In general, the populations of TRAPed cells were less sharply confined along the dorsoventral axis than the population of Fos+ cells. This may reflect the longer stimulus used for TRAPing (4 hr, versus 1 hr for Fos immunostaining) or some general noise in the TRAP approach. Regardless, this analysis supports the observations from individual sections that both TRAP and Fos immunostaining reveal similar tonotopic maps along the dorsoventral axis of the DCN. We also quantified the overlap between TRAPed and Fos+ cells for the different treatment groups across the entire extent of the DCN.

Spinal cords from E12.5 BIBW2992 embryos were prepared in an open book configuration. Dissected tissues were lyzed for 30 min at 4°C. Samples were analyzed by western blot, using anti-Plexin-A1

(1/1,000, AbCAM) and anti-β-actin (1/1,000, Sigma) antibodies, as described in Nawabi et al. (2010). For dot blot, the samples were spotted on a nitrocellulose membrane and probed with anti-gdnf antibody (1/500, R&D). FPs were isolated from E12.5 embryos and cultured in three-dimensional plasma clots in Neurobasal medium (GIBCO). The supernatant was collected after 48 hr. For producing regular FPcm, four isolated FPs were grown in 500 μl of medium. For production of the FPcm from the gdnf mouse line, due to the limitations of obtaining more than one homozygote per littermate, one FP was placed in 250 μl of LBH589 medium and was thus diluted by 2-fold, compared with the regular FPcm. The FPs from the different gdnf genotypes were collected from the same littermates and produced concomitantly and diluted the same way. For collapse assay, dorsal spinal cord tissues from E12.5 embryos were dissociated and cells were plated onto polylysin- and laminin-coated glass coverslips

in Neurobasal supplemented with B27, Glutamine (GIBCO), and Netrin-1 (R&D) medium. After 1 or 2 days in vitro, neurons were incubated with control or FPcm or different molecules for 1 hr at 37°C. Then Sema3B-AP was added to cultures for 30 min at 37°C. Cells were fixed in paraformaldehyde (PFA) 4% in PBS/1.5% sucrose and labeled with phalloidin-TRITC (1/500, Sigma). Collapsed growth cones were scored as in

Falk et al. (2005). Statistical comparisons were done with ANOVA-1 test, ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. about Results from three to ten independent experiments with at least 80 cones per experiment were pooled for the analysis. For coculture experiments, HEK293T cells were transfected with plasmids encoding either Sema3B-Alcaline Phosphatase fusion protein gdnf or control Alcaline Phosphatase. Cell aggregates were cocultured with dorsal spinal cord tissues cut into explants in Neurobasal medium (GIBCO) supplemented with B27 (GIBCO), glutamine (GIBCO), and Netrin-1 (R&D) medium. GDNF (400 ng; Sigma) was added twice to the culture medium. Cocultures and spinal cord explants were grown for 48 hr, fixed in 4% PFA, and stained with anti-Nf160kD antibody. As described in Falk et al. (2005), a qualitative guidance index was attributed to the cocultures to assess the degree of repulsive (negative values) or attractive (positive values) effects.

Not surprisingly, fluorescence recovery after photobleaching in a C. elegans this website model of inclusion formation by synuclein in muscle has shown a substantial immobile fraction ( van Ham et al., 2008). The results in neurons with more physiological levels of expression thus indicate that synuclein

interacts weakly with elements of the nerve terminal. Despite its weak interaction with cellular membranes, synuclein nonetheless recovers more slowly after photobleaching than GFP (Fortin et al., 2004), and the N-terminal membrane-binding domain of synuclein seems likely to mediate the interaction. The A30P mutation associated with familial PD in fact disrupts both the association of synuclein with brain membranes and the presynaptic location of synuclein in cultured neurons and accelerates the rate of recovery after photobleaching to that of GFP (Fortin et al., 2004 and Jensen et al., 1998). The A30P mutation also impairs the interaction of purified, recombinant synuclein with artificial membranes (Jo et al., 2002). Although less dramatic in vitro than in cells, the effect of the A30P mutation strongly supports a role for membrane binding

by the N terminus in presynaptic localization. How then does synuclein localize specifically to presynaptic boutons rather than other cell membranes? Acidic headgroups are found on the cytoplasmic leaflet of many intracellular membranes, but synuclein has a preference for membranes with high curvature Neratinib manufacturer (Jensen et al., 2011 and Middleton and Rhoades, 2010), and synaptic vesicles are among the smallest biological membranes described. Rolziracetam Consistent with this, synuclein disperses from presynaptic boutons with stimulation (Fortin et al., 2005), suggesting that it dissociates from the membrane upon delivery to the relatively flat plasma membrane by synaptic vesicle exocytosis. What confers the specificity of synuclein

for membranes with high curvature? Interestingly, the hydrophobic face of the N-terminal α-helix contains a series of threonines at position 3 in the repeat (Figure 1). Although this polar residue might be expected to disrupt hydrophobic interactions with the membrane, threonine is in fact less polar than serine, and the precise positioning of this residue in repeats 2–5 and 7 is highly conserved among all synuclein isoforms. It is therefore possible that threonine at these positions weakens the interaction of synuclein with membranes precisely so that it can acquire specificity for high curvature. To test this possibility, the threonines were replaced by large, nonpolar residues (leucine and phenylalanine) and the recombinant mutant protein indeed loses its specificity for both acidic membranes and small vesicles (Pranke et al., 2011). When expressed in yeast, the mutant also localizes to the plasma membrane rather than to intracellular vesicles, consistent with stronger membrane interaction interfering with the preference for high curvature.

05; Figures 1A and 1B). We also confirmed that HFS-LTD is dependent on group I (Gq-coupled) mGluRs by bath application of the group I mGluR antagonist AIDA (96% ± 12%, p < 0.05 compared to control; Figure 1C). Next, we tested potential signaling pathways downstream of Gq. The canonical target of Gq is PLCβ (Hubbard and Hepler, 2006 and Taylor et al., 1991). Surprisingly, we were unable to block HFS-LTD by including the PLC inhibitor U73122 in the intracellular recording solution (54% ± 5%; Figure 1C). This finding was unexpected because other

groups have demonstrated that eCB-mediated depression in MSNs is PLCβ-dependent (Fino et al., 2010, Hashimotodani et al., 2005, Jung et al., 2005 and Yin and Lovinger, 2006) although not in all cases (Adermark and Lovinger, 2007). Therefore, we decided to examine whether the PLCβ-independence of HFS-LTD was unique to that stimulation protocol. As an alternative to HFS-LTD, we applied a low-frequency Selleck Decitabine stimulation (LFS) induction protocol that is qualitatively similar to that used in previous studies of striatal LFS-LTD (Lerner et al., 2010 and Ronesi and Lovinger, 2005). In brief, we repeatedly paired epochs of 20 Hz stimulation with postsynaptic depolarization over several minutes (see Experimental Procedures for details) to induce LTD (56% ± 10%; Figures 1D and 1E). Similar to HFS-LTD, LFS-LTD was blocked

by AM251 and AIDA (95% ± 6% in AM251; 100% ± 8% in AIDA; both p < 0.05 compared to

control; Figures 1E and 1F), indicating a dependence on CB1 receptors and group I mGluRs, respectively. However, LFS-LTD was DAPT also blocked by intracellular U73122 (102% ± 15%; p < 0.05 compared to control; Figure 1F), indicating a role for PLCβ. Thus, both Org 27569 PLCβ-dependent and -independent forms of eCB-LTD can be elicited at excitatory synapses onto striatal indirect-pathway MSNs simply by using different stimulation frequencies and repetitions. PLCβ is an enzyme that produces the intracellular secondary messenger diacylglycerol (DAG), which can be converted to the eCB 2-arachidonylglycerol (2-AG) by the enzyme DAG lipase (DAGL). The sequential activities of PLCβ and DAGL represent a well-defined pathway for 2-AG production that could mediate LFS-LTD. To test whether DAGL is also required for LFS-LTD, we applied the LFS-LTD induction protocol in the presence of the DAGL inhibitor THL and observed that THL blocked LFS-LTD (92% ± 13%; p < 0.05 compared to control; Figure 2A). In addition to DAG, PLCβ produces another important secondary messenger, IP3, which can activate IP3 receptors located on the endoplasmic reticulum and cause release of calcium from internal stores. To test whether internal calcium stores are involved in LFS-LTD, we added thapsigargin, which depletes these stores, to our intracellular recording solution, but this manipulation did not block LFS-LTD (47% ± 7%; Figure 2B).

Burkhalter, 2006, Soc. Neurosci., abstract; M. Roth, F. Helmchen, and B. Kampa, 2010, Soc. Neurosci., abstract;

M. Garrett, J. Marshall, L. Nauhaus, and E. Callaway, 2010, Soc. Neurosci., abstract). While comparatively little is known about visual response properties in unanesthetized selleck compound mice (Andermann et al., 2010 and Niell and Stryker, 2010), cortical neurons in mice and other species may demonstrate visual responses of greater magnitude (Niell and Stryker, 2010), diversity (Qin et al., 2008), and context sensitivity (Pack et al., 2001) in the awake state. Therefore, to determine the degree of functional specialization in mouse higher visual areas, we developed a chronic two-photon imaging system for mapping responses in local volumes of cortical neurons across multiple areas in awake

Selleckchem Pomalidomide mice. We found striking differences in stimulus preferences across areas, demonstrating distinct functional specialization of different higher visual areas in the mouse. We characterized the functional properties of neurons in visual cortical areas of awake mice, using the following approach (see also Experimental Procedures). First, we implanted a 5 mm cranial window over visual cortex. Following recovery, mice were gradually habituated to head restraint (Andermann et al., 2010) while free to walk on a single-axis trackball (Experimental Procedures). We then performed widefield imaging of intrinsic autofluorescence signals to obtain retinotopic maps of multiple visual areas (Figure 1A and Figure S1 available online; Kalatsky and Stryker, 2003 and Schuett et al., 2002; cf. Wang and Burkhalter, 2007). We subsequently removed the cranial window under anesthesia and injected adeno-associated Sitaxentan virus AAV2/1-synapsin-1-GCaMP3 at a depth of 250 μm below the cortical surface to obtain

neuron-specific expression of the calcium indicator GCaMP3 ( Tian et al., 2009, Dombeck et al., 2010 and O’Connor et al., 2010) at approximately matched retinotopic locations in one or two visual cortical areas. Changes in cellular GCaMP3 fluorescence provide an estimate of visually driven increases in calcium influx associated with increases in neural firing rate ( Tian et al., 2009; Experimental Procedures). We measured population visual responses across cortical areas using widefield calcium imaging ( Figure 1), followed by a more detailed mapping of individual neurons using two-photon calcium imaging ( Figure 2, Figure 3, Figure 4 and Figure 5). Specifically, we assessed tuning of neurons across multiple stimulus dimensions, including spatial and temporal frequency, speed, orientation, and direction of motion. Tuning estimates in Figure 1, Figure 2, Figure 3, Figure 4 and Figure 5 included all trials, independent of whether the mouse was moving or stationary, as tuning was not strongly affected by locomotion (see Figures 6, S2, and S6, below).

, 2010; Palminteri et al., 2009a; Hare et al., 2008). Many anatomo-functional models of reward learning share the idea that reward prediction errors (obtained minus expected reward) are encoded in dopamine signals that reinforce corticostriatal synapses (Bar-Gad and Bergman, 2001; Frank et al., 2004; Doya, 2002). The same mechanism could account for punishment learning:

dips in dopamine release might weaken approach circuits and/or strengthen avoidance circuits. This is consistent with numerous studies showing that dopamine enhancers improve reward learning, but impair punishment learning in patients with Parkinson’s disease (Frank et al., 2004; Bódi et al., 2009; Palminteri et al., 2009b). It has been suggested that another neuromodulator, serotonin, could Ion Channel Ligand Library concentration play an opponent role: it would encode punishment prediction errors (obtained minus expected punishment) so as to reinforce the avoidance pathway (Daw et al., 2002). However, this hypothesis has been challenged by several empirical studies in monkeys and humans (McCabe et al., 2010; Palminteri et al., 2012; Miyazaki et al., 2011). Beyond neuromodulation, the existence of opponent regions, which would process punishments as the ventral Bioactive Compound Library prefrontal cortex and striatum process reward, remains controversial.

In humans, fMRI studies of reinforcement learning have yielded inconsistent results. At the cortical level, several candidates for an opponent punishment system have been MTMR9 suggested, among which the anterior insula emerged as particularly prominent. Indeed, the anterior insula was found to represent cues predicting primary punishments, such as electric shocks, fearful pictures, or bad tastes, and these punishments themselves (Büchel et al., 1998; Seymour et al., 2004; Nitschke et al., 2006). These findings have been later

extended to more abstract aversive events, such as financial loss or risk (Kuhnen and Knutson, 2005; Samanez-Larkin et al., 2008; Kim et al., 2011, 2006). However, some studies have also found insular activation linked to positive reinforcers and orbitofrontal activation linked to negative reinforcers (O’Doherty et al., 2001; Gottfried and Dolan, 2004; Kirsch et al., 2003). The functional opponency between ventral prefrontal cortex and anterior insula, in learning to predict reward versus punishment, is therefore far from established. At the striatal level, many fMRI studies have reported activations related to primary or secondary reinforcers during instrumental learning (O’Doherty et al., 2003; Galvan et al., 2005; Pessiglione et al., 2008; Daw et al., 2011). Again, some studies supported the idea that the same regions encode both reward and punishments cues or outcomes, whereas other studies argued for a functional dissociation between ventral and dorsal regions (Jensen et al., 2003; Delgado et al., 2000; O’Doherty et al., 2004; Seymour et al., 2007).

In parallel to this homeostatic process, sleep has been shown to contribute to memory consolidation. Notably, repeated reactivation of activity

patterns evoked during learning has been observed during slow-wave sleep both in rats and humans. This reactivation of memory traces (“replay”), which correlate with memory consolidation, may redistribute the neural representations of memory into cortical regions for long-term storage (Diekelmann and Born, 2010). With all these important functions, sleep is no longer considered a passive resting state, but rather an active brain state essential for neuronal plasticity. In this issue of Neuron, Yokoyama et al. (2011) report exciting data extending this concept from synapses to neural circuits, illustrating an unexpected function Gefitinib datasheet of sleep in rescaling the number of neurons in the olfactory bulb

(OB). In the OB, the first central relay of the olfactory system, adult neurogenesis provides a continuous source of new neurons that mature and integrate into the preexisting OB network to become mainly mature GABAergic granule cells. Alongside this integration is a selection GSK-3 beta phosphorylation process in which 50% of the new neurons undergo apoptosis during a specific critical window ( Yamaguchi and Mori, 2005). How this selection process is regulated is the focus of intense study. In this paper, the authors discovered that a food restriction paradigm exerts a peculiar effect on apoptosis of newborn cells. They first observed that while the degree of apoptosis is constant over time in mice through allowed unlimited access to food, the number of apoptotic neurons increases strongly after eating when food is formerly and briefly restricted (for 4 hr). Interestingly, most of the apoptotic neurons were newly formed granule cells, confirming that the newborn neuron population is in constant turnover. More puzzling was the time course of this phenomenon: apoptosis approximately doubled two hours after animals begin eating. But food was not the only factor regulating cell death. Apoptosis was

potentiated only when animals underwent a postprandial nap, and this correlated with postprandial sleep duration. When animals were selectively sleep deprived after eating, apoptosis was prevented. This phenomenon was also seen to a lesser extent in ad libitum feeding mice when the authors carefully monitored feeding and postprandial behaviors for each individual. By showing that the degree of apoptosis enhancement remains constant at different circadian times, the authors also ruled out potential circadian influences in this phenomenon. What is the importance of sensory experience to this process? The OB is a great model to test experience-dependent phenomena since the sensory inputs can be easily manipulated and this manipulation can be restricted to one region of the OB, leaving other inputs intact. The authors used two strategies to reduce olfactory activity.

Steady-state gain field responses were defined as responses to stimuli flashed at least 600 ms after the beginning of a fixation. In order to be characterized as a gain field neuron, the cell had to have steady-state gain field responses in the interval from 0 to 160 ms after the probe presentation that differed significantly at two orbital positions 20° apart (two-sample t test, p > 0.05). Additionally, the high gain field peak response had to differ from the low gain field peak response by

at least 15% of the mean of the two responses. Gain field update times were calculated by fitting a sigmoid curve to the peak visual responses of all probe delays for saccades in one gain field direction using the nlinfit Matlab Erastin datasheet function. All fits yielded an R-squared value greater than 0.7, and 85% of the fits yield an R-squared value

greater than 0.9. The gain field update time, or the time point of transition from nonveridical to veridical eye position information, was defined as the probe delay subsequent to the inflection point of the sigmoid fit. The response of cells without gain fields to the two-saccade task could not be fitted with sigmoids. Behavioral data were reoriented so that the first or the second saccade vector pointed in the horizontal, rightward direction: x’=x∗cos((360−θ)∗π180)−y∗sin((360−θ)∗π180) selleck screening library y’=x∗sin((360−θ)∗π180)+y∗cos((360−θ)∗π180) x and y represent the original saccade vector in real space, θ the angle of rotation, and x′ and y′ the reoriented saccade vector. Consequently, corresponding saccade mislocalization vectors for each trial block, defined as (mean endpoint of saccades to early probe – mean endpoint of saccades to late probe) were

also reoriented. This research was supported, in part, by grants from the Keck, Zegar, Kavli, and Dana Foundations, and the National Eye Institute (P30EY019007, unless R24EY015634, R21EY017938, R01EY014978, R01EY017039, M.E.G., PI), We are grateful to Yana Pavlova for veterinary technical help, Drs. Girma Asfaw and Moshe Shalev for veterinary care, John Caban for machining, Glen Duncan for computer and electronic assistance, and Latoya Palmer and Holly Kline for facilitating everything. B.Y.X. was supported by the Columbia MSTP grant T32GM07367-33 and the NEI training grant T32EY13933-08, and C.K. was supported by Fondation pour la Recherche Médicale and Fondation Bettencourt Schueller. We thank Dr. Ning Qian for his comments on an earlier version of this manuscript, Dr. Larry Abbott for reading a later version of the paper and for his help with the mathematical analysis, and Dr. Brian Lau for help with the statistical analyses. “
“Previous fMRI studies have suggested that some categories of objects and actions are represented in specific cortical areas. Categories that have been functionally localized include faces (Avidan et al., 2005; Clark et al., 1996; Halgren et al.

Modeling studies suggest that

STI CAL-101 clinical trial vaccination should be broadly implemented in order to have a large public health impact [15]. HCP recommendation may be especially important for STI vaccine uptake among adolescents most Libraries vulnerable to non- or under-vaccination, including those with poor access to care (i.e., often racial/ethnic minorities) [12] and [16] and cultural barriers (i.e., select religious groups) [17]. Adolescents with chronic medical conditions may also be vulnerable given misinformation about disease risk and vaccine contraindications [17] and [18]. Many identify a subspecialist as their main HCP [19], which may pose additional challenges for STI vaccination. HCP recommendations may also have a particular impact in settings that use a clinic-based delivery model compared to settings that use a school-based delivery model. However, since school absenteeism can be a challenge for school-based vaccination programs, especially in resource-poor areas [17], [20] and [21], health centers may be used to complement the school-based

vaccination programs, as demonstrated by HPV vaccination programs in countries such as Vietnam and India [20]. Despite strong evidence that recommending STI vaccination of adolescents Epacadostat has a positive impact on uptake, many HCPs fail to do so. Survey studies of physicians from Asia

and Australia have shown that only half initiate conversations about else HPV vaccination [7] and [22]. Moreover, one-quarter to one-half of HCPs across disciplines and countries report that they do not routinely recommend HPV vaccination [23] and [24]. Physicians may also believe they are recommending the vaccine more than parents are “hearing” it being recommended. A study conducted in Los Angeles County found that only 30% of parents reported that a HCP recommended HPV vaccination for their adolescent daughter [12]. For HCPs who engage in a conversation about STI vaccines with their patients, it is important to understand what they are communicating and how it influences STI vaccine uptake. Several studies have explored whether messages should emphasize universal infection risk and/or non-sexual transmission modes in order to de-stigmatize STI vaccination [25], [26], [27] and [28]. In the United States, hepatitis B vaccine messaging by HCPs and others was adapted over time to reduce STI-related stigma, and this likely contributed to a simultaneous rise in hepatitis B vaccination coverage [25]. Similarly, many HCPs have chosen to emphasize cancer prevention when discussing HPV vaccination [29], [30] and [31]. It remains unclear if this is warranted based upon adolescent and parental concerns.