Note that a forward prediction generates a sensory expectation, or in the terminology of the attentional literature, a selective attentional gain applied to the expected sensory features (and/or suppression of irrelevant features). Thus, forward predictions generated via motor commands can function as a top-down attentional modulation of sensory systems. Such attentional modulation may be important for sensory feedback control because it

sharpens the perceptual acuity of the sensory system to the relevant range of expected inputs (see below). This “attentional” mechanism might then be easily co-opted for motor-directed modulation of the perception of others’ speech, which Bortezomib cell line would be especially useful

under noisy listening conditions, thus explaining the motor speech-induced effects of perception as summarized above. On the face of it, there seems to be a tension between error correction and selective attention. One the one hand, selective attention increases perceptual detectability to attended features and decreases detectability to unattended features. On the other hand, for error correction the system needs to be able to detect deviations from the expected (attended) pattern. However, these two computational effects are not OSI-906 supplier mutually exclusive. Suppose selective attention in this context both increases the gain of the response in networks tuned to the attended units and sharpens the tuning selectivity for the relevant features (Figure 5). The increased Rutecarpine gain will result in facilitation of detection of the presence of expected (attended) features, whereas the sharpened tuning curve may make deviations from the expectation more salient.

The idea that attention can modulate gain is well established (Boynton, 2005, McAdams and Maunsell, 1999, Moran and Desimone, 1985, Reynolds et al., 1999, Reynolds and Heeger, 2009, Treue and Martínez Trujillo, 1999 and Treue and Maunsell, 1999). Whether attention can sharpen the tuning properties of neurons is less well established although limited evidence exists (Murray and Wojciulik, 2004 and Spitzer et al., 1988). An alternative approach to explaining how selective attention could both enhance detection of deviation from an expected target and enhance detection of the presence of the expected target comes from recent work on the nature of the gain modulation induced by selective attention. The traditional view is that attention to a given feature increases the gain of neurons that are selective for that feature, and this model works well for detecting the presence of a stimulus or for making coarse discriminations.

Z.H. contributed to the study design, coordinated

the study, conducted the analyses, and was lead author. W.V. contributed to the study design, and all sections of this paper. All authors have read and approved the final manuscript. All authors declare that they have no conflicts of interest. We are grateful to our colleagues Wietze Gjaltema, Michiel Maas and Peter Janssen who helped us to transform the camper in a mobile lab and to drive safely with it. We thank Carel Peeters, Karin Monshouwer and Quinten Raaijmakers for their advice on the Navitoclax in vitro statistical analyses. We thank the bachelor and master students for helping with collection of the dataset. We are indebted to the principal and staff of the schools, the Trimbos Institute, all the participants and the confederates for their participation. “
“Persistent substance use during adolescence has been associated with various adverse outcomes, including an increased risk of developing substance use disorders and delinquent behaviors (Chabrol and Saint-Martin, 2009, Swift et al., 2008 and Toumbourou et al., 2003).

Research on the determinants of persistent substance use in this developmental PLX4032 purchase phase can improve our understanding of liability to substance use disorders. Twin studies have established that genetic influences contribute to the etiology of substance abuse and dependence (Agrawal and Lynskey, 2008). These studies have reported heritability estimates that range from 50 to 70% for alcohol abuse/dependence and from

34 to 78% for cannabis dependence. While genetic influences have generally been found to be strongest for these heavier stages of substance use (Agrawal and Lynskey, 2006), the role of genetic factors on initiation, use, and non-diagnostic problem use of substances has also been established (McGue et al., 2000 and Rhee et al., 2003). For the latter, the influence of shared environmental factors is relatively stronger. Findings from MTMR9 twin studies assessing multiple stages of substance involvement suggest, at least partly, common genetic and environmental risk factors for substance use and misuse among adolescents and adults (Agrawal et al., 2005, Fowler et al., 2007 and Kendler et al., 1999). The genetic influences estimated in twin studies represent the composite variance explained by multiple genes. Two of the candidate genes implicated in substance use disorders are the dopamine D2 receptor gene (DRD2) and the dopamine D4 receptor gene (DRD4) (Agrawal and Lynskey, 2009 and Kotler et al., 1997). Individuals carrying the A1 allele of the TaqIA polymorphism, close to DRD2 (rs1800497), have a reduced number of D2 dopamine receptors in brain structures linked to reinforcement, particularly in the striatum (Jonsson et al., 1999, Pohjalainen et al., 1998 and Thompson et al.

All 6 of the miRNAs are located on human chromosome 14, and 4 of these 6 (miR-376a, miR-654-3P, miR-543, miR-229-5P) are found within the same 10 kb region of the chromosome. Three of the 6 miRNAs (miR-299-3P, miR-134, miR-369-3P) are up-regulated in human and murine embryonic stem cells [53], [54] and [55], suggesting a role in cellular dedifferentiation. Dedifferentiation has been found to be the

first step in the repair of renal epithelium that occurs in vivo after acute kidney injury and in renal cells in primary culture [56] and [57]. As the expression of the 6 miRNAs increases to their maximum levels after 170–180 passages of VERO cells in concert with the expression of their tumorigenic phenotype, we speculate that changes in miRNA expression up to and during these tumor-forming passage levels occurs as a component this website of the VERO cell dedifferentiation processes involved in the expression of the tumorigenic phenotype. Studies are underway to identify the molecular pathways that might be altered by the over-expression of these signature miRNAs in our VERO cell model. In conclusion, with the goal of learning more about tumorigenesis Dasatinib clinical trial and reducing the use of animals for characterizing

the neoplastic phenotype, we have demonstrated that profiling miRNA expression predicts the tumorigenic potential of VERO cells as it evolves during cell culture. Our observations point to a potential link between miRNA profiles expressed in tumorigenic VERO cells and tumor formation in vivo, thereby indicating that miRNA profiling offers promise as a surrogate for expression of VERO cell tumorigenic phenotype. Having a molecular assay for the evaluation of the ability of immortalized cell substrates to form tumors in vivo would provide a quick and relatively inexpensive the method for detecting the expression of the VERO cell tumorigenic phenotype. The identification of appropriate biomarkers could expedite the review of vaccines manufactured

in new immortalized mammalian cells. While the relevance of the identified miRNA biomarkers was shown here for the 10–87 VERO cells that are being used as cell substrates for licensed products, such biomarkers could be useful for the development of new cell lines from the original VERO cell line or for the development of
s of African green monkey cells for vaccine manufacture; furthermore, they may help reduce animal testing. The findings and conclusions in this article have not been formally disseminated by the Food and Drug Administration and should not be construed to represent any Agency determination or policy. We thank members of our laboratories for advice and discussions. We also extend our thanks to Drs. Steve Feinstone, Robin Levis, and Carol Weiss for helpful discussions and/or comments on the manuscript.

Similarly, loss of FMRP increased ARC basal expression

( Figure 3C). Furthermore, ARC synthesis triggered by BDNF was much lower in Fmr1 KO neurons compared with wild-type (WT); inhibition of Rac1 activation before BDNF stimulation blocked ARC synthesis in WT as well as the residual synthesis in Fmr1 KO neurons, whereas no effect was observed in Cyfip1-silenced neurons ( Figure 3C). Fmr1 KO neurons silenced for Cyfip1 phenocopied CYFIP1-deficient neurons, further confirming that FMRP and CYFIP1 act in the same pathway ( Figure 3C). We also investigated ARC levels in mice where CYFIP1 expression was genetically reduced. Because click here Cyfip1 KO animals are embryonic-lethal (our observation and Bozdagi et al., 2012), we used heterozygous animals where CYFIP1 levels are reduced by 40% ( Figure 3D). We examined ARC expression in both total brain cortex and cortical synaptoneurosomes and found that Cyfip1+/− mice have elevated ARC levels at synapses ( Figure 3D). These data support the hypothesis that FMRP and CYFIP1 regulate protein synthesis downstream of Rac1 learn more activation. Activated Rac1 reshapes the CYFIP1-eIF4E complex through a conformational change, so that when translation inhibition is lifted, more CYFIP1 becomes

available for the WRC. Our results suggest that CYFIP1 complexes have a specific function in synaptic protein synthesis and actin polymerization. As proof of principle, we aimed at uncoupling the two complexes and studying their contribution to protein translation and actin polymerization. For this purpose, we designed specific CYFIP1 mutants impairing the interactions with either eIF4E or NCKAP1. To reduce the CYFIP1-eIF4E interaction, we used a mutant replacing Lys743 with a Glu (mutant E), which has been shown Rutecarpine to reduce the interaction with eIF4E (Napoli et al., 2008). To interfere with the CYFIP1-NCKAP1 complex, we studied the large surface of interaction between the two proteins (Chen et al., 2010), and found two hydrophobic patches on CYFIP1 that fit to corresponding sites on NCKAP1

(Figure S5B). The second patch shows a higher complementarity to NCKAP1, in particular in a stretch of eight consecutive hydrophobic amino acids (Ala1003–Ile1010), which was predicted as an essential binding site for NCKAP1. We therefore designed two mutants: mutant Δ, lacking the C-terminal domain that harbors the hydrophobic patch (aa 922–1251), and mutant H, in which the eight hydrophobic residues were replaced by glycines. WT and mutant proteins tagged with the yellow fluorescent protein (EYFP) were expressed in HEK293T cells (Figure S5C) and displayed correct cytoplasmic localization (data not shown). To promote the incorporation of the exogenous proteins into functional complexes, we silenced the endogenous Cyfip1 with siRNAs directed against its 3′UTR ( Figures 4A and S5D).

Critically, the Memory × Region interaction was also significant (left: F(1,29) = 39.20, p < 0.001; right: F(1,29) = 36.6, p < 0.001), indicating that the effect of Memory significantly differed across regions. We then analyzed each region separately. Of course, there was a significant main effect of Memory in IPL (left: F(1,29) = 47.88, p < 0.001; right: F(1,29) = 34.97, p < 0.001). The main effect of Memory in IPS was not significant (left: F(1,29) = .98, p = .33; right: F(1,29) = 2.56, p = 0.12). The Region × Attention × Memory interaction was not significant

(both hemispheres: F ≤ 1). These analyses indicate that the dissociation between the IPS and the IPL does not depend on the threshold employed in the whole-brain analysis. The interaction between visual attention and episodic retrieval is poorly selleck chemicals llc understood. Given that the neural systems mediating attention and episodic memory appear to be anatomically segregated, and perhaps even in competition, it is unclear which neural systems are engaged Selleckchem DAPT when visual attention is recruited during episodic retrieval.

We investigated the recruitment of visual attention by episodic retrieval during the suppression of gist-based false recognition. When two similar candidate targets were presented next to each other, participants had to systematically compare the two items and attend to the details that distinguished them in order to decide whether one of the items was old (Attention-High conditions). This process was associated with increased activity in regions previously associated with top-down visual attention ( Kastner and Ungerleider, 2000; Corbetta and Tryptophan synthase Shulman, 2002), including the IPS ( Figure 2). These results suggest

that systems for top-down visual attention, although not typically associated with episodic retrieval, can play an important role when retrieval of specific visual details is required. Although activity in the IPS was associated with the attempt to retrieve perceptual detail, it was not associated with successful retrieval of perceptual detail. In contrast, activity in the IPL, and other regions likely overlapping with the default network, was associated with the successful retrieval of perceptual detail from memory ( Figure 4). Thus, the IPS and the IPL make dissociable contributions to the retrieval of perceptual detail. Below, we discuss the implications of these findings for models of the role of the parietal cortex in episodic retrieval and visual attention. When two candidate targets were presented adjacent to one another (Attention-High conditions), participants had to systematically compare the two candidate targets and attend to the details that distinguished them in order to decide which item was old.

30, Schneeberger) and

driven by pneumatic linear actuators (6604k11, McMaster Carr). A custom implantable titanium headplate was designed to mate with the kinematic clamp. Low-force, miniature snap action switches (D42L-R1XL, Cherry) mounted on the clamp were used to detect when the anterior edge of the headplate reached the rear end of the heaplate slot. When the headplate was in this location, actuation of the kinematic clamp would drive the piston-mounted ball bearings toward the conical depression and the V groove. ZD1839 clinical trial Interaction between the piston-mounted ball bearings and the conical depression and the V groove constrained 5 of 6 of the degrees of freedom of the headplate. The sixth degree, pitch, was constrained by interactions between the top plane of the headplate and the flat surface of the ceiling of the headplate slot. In some cases, we found it necessary to more firmly constrain pitch as some animals were able to produce sufficient torque on their headplate to create pitch movements, which contributed to brain motion. In these cases, we mounted miniature Teflon-tipped brass arms to the pistons that contacted the underside of the anterior portion of the headplate and clamped the headplate more firmly to the ceiling of the headplate slot. Delivery of air pressure (0–90 PSI) to the pneumatic linear actuators was controlled either by a manual regulator combined with two solenoid valves (T9-65-900, Toohey) or using

a voltage-controlled regulator (ITV1050-31N2S4, SMC). The kinematic clamp was installed along one wall of the modified rat BKM120 operant conditioning chamber (Island Motion), which also contained two additional reward pokes on the left and right side. Position of the center poke was controlled either by a custom manual translation stage or using a motorized linear stage (ET-50-21, Newmark Systems). A behavioral control system, Bcontrol (see below), controlled the timing of fluid reward and auditory and

visual cues. A schematic diagram of the overall system architecture is shown in Figure S1. The operant conditioning chamber was mounted on an air table that also housed a movable objective microscope (Sutter Instruments). The microscope was positioned so tuclazepam that the vertically oriented objective was centered over the headport clamp. Two objectives were used for TPM: a 40×, 0.8 NA, water immersion (LUMPLFN40XW, Olympus) and a 40×, 0.6 NA with a correction collar (LUCPLFLN40X, Olympus). A Ti:Sapphire laser was used as an illumination source (Chameleon Ultra II, Coherent) for 920 nm light. A delrin collar was designed to mount on the barrel of the water-immersion objective and position two stainless steel tubes, one for fluid delivery and one for fluid removal. Upon activation of the clamp at the beginning of each insertion event, 75 μl of immersion fluid was delivered to the gap between the implanted optical window and the face of the imaging objective. Inflow was produced by a gravity-fed system.

702, mean novel AUC = 0.729 p = 0.004; late epoch, mean familiar AUC = 0.698,

mean novel AUC = 0.778, p < 0.001), with one monkey showing much stronger and reliable differences than the other. Visual experience, therefore, did not prevent neurons in ITC from contributing reliably to the encoding of both familiar and novel stimuli. Given that putative inhibitory cells had lower sparseness than putative selleck inhibitor excitatory cells but were better able to discriminate between any two arbitrarily chosen images, we wondered whether there was a relationship between sparseness and mean pairwise AUC values. In Figures 7C and 7D, we have plotted individual cells’ sparseness and mean pairwise AUC values for the early and late epochs (putative inhibitory units are indicated by open symbols). For both familiar (Figures 7C and 7D, black points and lines) and novel (green points and lines) stimuli, we observed a strong linear correlation between the two metrics. The correlation held even when we restricted the analysis to just the putative excitatory cells (Figures 7C and 7D, filled circles). This suggests that Selleck Torin 1 an increase in sparseness precluded a neuron from discriminating stimuli at the lower end of its firing rate distribution.

Because visual experience led to a considerable increase in sparseness, we conclude that individual ITC neurons contributed to the encoding of a smaller number of familiar compared to novel stimuli. Here, we asked whether visual long-term experience’s effects on single-neuron responses in ITC vary with cell type. We first showed that the best stimulus from the crotamiton familiar set drove putative excitatory cells much more robustly than the best stimulus from

the novel set. This effect was reversed for putative inhibitory cells. We further showed that, on average, both putative excitatory and putative inhibitory neurons responded with a smaller response to a randomly chosen familiar compared to novel stimulus, but this difference was much larger in the putative inhibitory population. We then went on to show that experience increased sparseness in putative excitatory neurons and, to a lesser degree, in putative inhibitory neurons. For the putative excitatory neurons, the experience-dependent increase in sparseness could be well accounted for by an increased firing rate to the top familiar stimulus. Finally, we demonstrated that the experience-dependent modifications have a minimal impact on the ability of ITC neurons to discriminate between the stimuli in the novel set. In Figure 8, we provide a schematic summarizing the observed firing rate changes in both classes of neurons.

, 2005).

Olfactory sensory neurons (OSNs) that express the same type of odorant receptor converge onto either one or a few specific glomeruli in the selleck chemicals olfactory bulb (OB), and individual odorants elicit specific spatial patterns of glomerular activity (Buck and Axel, 1991; Mombaerts et al., 1996; Mori and Sakano, 2011). Glomeruli in the OB form anatomically and functionally discrete network units that are similar to the multineuronal “barrels” and “columns” that are found in the cerebral cortex (Shepherd et al., 2004). Within each glomerulus, odor information is transferred to the various principal and local neurons that compose the glomerular module. Both types of neurons typically have only one primary dendrite that projects to a single glomerulus and receive excitatory inputs exclusively from a single type of odorant KPT-330 price receptor. Therefore, based on the anatomical structures, all neurons in the same olfactory glomerular module would be expected to have homogenous profiles of odorant selectivity. However, these

principal neurons also receive GABAergic inhibitory and other modulatory inputs from intrabulbar and/or centrifugal projections. Thus, one important question that remains to be answered is whether neurons within a single glomerular module respond to odor inputs in a homogeneous fashion. A recent study that performed dendritic recordings of projection neurons associated with a genetically identified glomerulus (using I7-M71 transgenic mice) demonstrated that the neurons comprising

the associated module have similar yet slightly different odorant response profiles (Tan et al., 2010). Furthermore, simultaneous recordings of projection neurons that are associated with the same glomerulus show similar odorant selectivities but different temporal activity patterns (Dhawale et al., 2010). However, it remains unclear whether these similarities and differences in responses are associated with neuronal cell types, dendritic arborization patterns, or horizontal/vertical cell soma locations. To further understand these potential mechanisms, it is necessary to identify the anatomical and functional architecture of the glomerular modules and compare individual neuronal activities Org 27569 within the context of the neuronal circuits. In the current study, we addressed these questions by visualizing the anatomical configuration of a single glomerular module in the mouse OB with calcium indicator dye labeling and in vivo two-photon imaging methods. Surprisingly, the anatomical distribution ranges of the neurons comprising the module were wider than the glomerulus, suggesting that distinct modules heavily overlap with each other. Furthermore, OSN presynaptic inputs to the glomerulus and individual postsynaptic neuronal excitatory responses were remarkably similar among cells located in the superficial bulb layer but not among those located in deeper layers.

Explant assays have shown that the spinal cord floor plate is strongly chemoattractive and growth promoting for commissural axons (Tessier-Lavigne et al., 1988 and Serafini et al., 1996). There, axons loose responsiveness to midline attractants only upon crossing, and instead become sensitive to repellents such as SLITs that drive them out off the midline territory (Shirasaki et al., 1998 and Sabatier et al., 2004). In contrast, explanted chiasm tissue inhibits axon growth (Wang et al., 1995 and Wang et al., 1996), and growth cones therefore slow down as they

approach this region (Godement et al., 1994 and Mason and Wang, 1997). Furthermore, there is no evidence to date that RGC axons acquire responsiveness to repellents as they encounter the midline territory; for example, they are sensitive to inhibitory SLIT signaling selleck inhibitor both before and after crossing (Thompson et al.,

2006a and Thompson et al., 2006b). Despite these differences, most RGC axons eventually cross to form the contralateral projection, suggesting that growth-promoting factors exist to help them cross. We found that in vitro, in the absence of inhibitory chiasm-derived cues, VEGF164 is a powerful growth promoter and chemoattractant for RGC axons. In vivo, VEGF164 also promotes axon crossing, but is not essential for the crossing of all RGCs, presumably because it acts redundantly with other attractive cues to ensure that RGCs overcome the selleck compound inhibitory chiasm environment. In support of this idea, presumptive ipsilateral RGC axons project contralaterally in the absence of ephrin B2 signaling (Williams et al., 2003), even though they do not normally express NRP1. An essential role for VEGF164 in balancing inhibitory signals at the chiasm midline would also explain why growth cones do not stall at the midline. Thus, inhibitory cues

are essential to prevent the trapping of NRP1-expressing RGC axons at the VEGF164-expressing Dichloromethane dehalogenase midline and help drive advancing axons into the optic tracts. Additionally, crossed axons may lose sensitivity to VEGF164, because they downregulate an unidentified NRP1 coreceptor or because they upregulate a receptor that increases sensitivity to inhibitory signals after crossing. Identifying further guidance pathways and generating compound mouse mutants will help decide between these possibilities. We have identified an attractive and growth-promoting midline signal that overcomes the repulsive environment of the chiasm midline to promote commissural axon growth. This attractive factor is the NRP1-binding VEGF164 isoform of the classical vascular growth factor VEGF-A. While there are many examples of axon guidance signals playing a prominent role in the developing vasculature, physiological evidence for an involvement of angiogenic factors in axon pathfinding was previously lacking. Our findings provide in vivo evidence that VEGF-A is essential for axon pathfinding.

, 2002, Schrouff et al., 2011 and Veselis et al., 2004) ( Figure 9). Consistent with these views, Velly et al. (2007) found that during induction of anesthesia by sevofurane and propofol in human patients with Parkinson disease, cortical EEG complexity decreased dramatically at the precise time where consciousness was lost, while for several minutes there was little change in subcortical signals, and eventually a slow decline ( Figure 9). These data suggest that in humans, the early stage of anesthesia correlates with cortical disruption, and that the effects on the thalamus are indirectly driven

by cortical feedback ( Alkire et al., 2008). Indeed, in the course of anesthesia induction, there is a decrease in EEG AC220 nmr coherence in the 20 to 80 Hz frequency range between right and left frontal cortices and between frontal and occipital territories ( John and Prichep, R428 clinical trial 2005). Quantitative analysis of EEG under propofol induction further indicates a reduction of mean information integration, as measured

by Tononi’s Phi measure, around the γ-band (40 Hz) and a breakdown of the spatiotemporal organization of this particular band ( Lee et al., 2009b). In agreement with experiments carried out with rats ( Imas et al., 2005 and Imas et al., 2006), quantitative EEG analysis in humans under propofol anesthesia induction noted a decrease of directed feedback connectivity with loss of consciousness and a return with responsiveness to verbal command ( Lee et al., 2009a). Also, during anesthesia induced by the benzodiazepine midazolam, an externally induced transcranial pulse evoked reliable initial activity monitored by ERPs in humans, but the subsequent late phase of propagation to distributed areas was abolished ( Ferrarelli et al., Ketanserin 2010). These observations are consistent with the postulated role of top-down frontal-posterior amplification in

conscious access (see also Supèr et al., 2001). Coma and vegetative state. The clinical distinctions between coma, vegetative state ( Laureys, 2005), and minimal consciousness ( Giacino, 2005) remain poorly defined, and even fully conscious but paralyzed patients with locked-in syndrome can remain undetected. It is therefore of interest to see whether objective neural measures and GNW theory can help discriminate them. In coma and vegetative state, as with general anesthesia, global metabolic activity typically decreases to ∼50% of normal levels ( Laureys, 2005). This decrease is not homogeneous, however, but particularly pronounced in GNW areas including lateral and mesial prefrontal and inferior parietal cortices ( Figure 9). Spontaneous recovery from VS is accompanied by a functional restoration of this broad frontoparietal network ( Laureys et al.