In contrast, no such events were detected in control slices ( Figure 1B; Table 1) or when the mutant CS-Cbln1, which does not bind to GluD2 ( Matsuda et al., 2010), was used. Retrospective analysis of the synaptogenic events revealed that they were associated with prior protrusive changes characterized CH5424802 in vivo as SP (57%), CP (43%), or both (36%) ( Table 1). Considering the low sampling frequency of our time-lapse imaging (1 hr intervals), active PF protrusions are most

probably associated with the majority of the synaptogenic events. We also examined the frequency of PF protrusions among the events that led to the formation of transient boutons that lasted less than 4 hr (Table 1). Such transient boutons were observed in all samples, including those treated with WT-Cbln1 or CS-Cbln1 and those that were untreated. SPs were observed PD173074 manufacturer preferentially after the addition of WT-Cbln1, and led to transient PF bouton formation (Table 1). In contrast, CPs were not observed during transient bouton formation. Taken together,

our observations suggest that Cbln1 induces the formation of SPs and CPs at the sites where the contact is formed between PFs and PC spines. Because CPs were specifically associated with stable bouton formation, CPs may play an important role in promoting maturation of developing presynaptic terminals. Synaptic vesicle (SV) accumulation is an essential step during the formation of presynaptic terminals. To clarify whether PF protrusions are formed before or after SV accumulation, we visualized PF morphology and SVs simultaneously by cotransfecting cDNAs encoding GFP and synaptophysin fused with TagRFP-T (SypRFP) (Shaner et al., 2008). Synapse formation was visualized at 1 hr intervals for 6–9 hr after the addition of recombinant WT-Cbln1 to cbln1-null slices. Consistent with our previous findings, the density of SypRFP clusters in PFs was lower in cbln1-null slices (52.7 ± 0.3/mm, n = 4 slices) when compared to wild-type slices (90.7 ± 3.4/mm, n = 4 slices, p < 0.05). By comparing the images obtained before

of and after the addition of WT-Cbln1, we extracted all the synaptogenic events that resulted in new SypRFP clusters, which were formed within 5 hr after the addition of WT-Cbln1 and lasted for 4 hr or longer. To confirm that the new SypRFP clusters were associated with the PC dendrites, we performed retrospective immunostaining for calbindin to visualize PCs ( Figures 2A and 2B). In contrast to the structural changes in PFs ( Figures 1D and 1E), accumulation of SypRFP clusters was detected much earlier ( Figures 2B and 2C). Average time from the addition of WT-Cbln1 to the initial observation of SPs and CPs were 4.6 ± 0.4 hr (n = 8) and 5.8 ± 0.7 hr (n = 6), respectively (calculated from the data in Table 1). In contrast, SypRFP clusters were initially observed 1.5 ± 0.2 hr after the addition of WT-Cbln1 (n = 13; Figures 2B and 2C).

, 2002). This suggests that an important normal function of these areas may be to tonically inhibit unwanted actions. Second,

a recent neuroimaging study showed increased pre-SMA activation when an external stop signal successfully triggered inhibition of movement (Sharp et al., 2010). Finally, and compellingly, medial frontal areas that produced movement arrest during intracranial selleck products stimulation were also identified as the source of readiness potentials during action generation (Yazawa et al., 2000). A recent model of volition identified the decision of whether to act or not as an important component of volition (Brass and Haggard, 2008). Fried et al.’s data suggest one mechanism that might be involved in this decision. Decreasing neurons might withhold actions until they become appropriate through tonic inhibition and then help to trigger voluntary actions by gradually removing this tonic inhibition.

Competitive inhibitory interaction between decreasing and increasing neurons could then provide a circuit for resolving whether to act or withhold action. A similar model has already been proposed for decisions between alternative stimulus-driven actions in lateral premotor cortex (Cisek, 2007). Libet thought that “veto decisions” could represent a form of pure mind-brain causation, with consciousness directly intervening check details to interrupt the buildup of the readiness potential. Competition between populations of medial frontal neurons may provide a simpler explanation, though for it still leaves us hunting for potential “decision” areas that may modulate the

competition. Not surprisingly, several questions remain unanswered. One is the possible contribution to volition of other cortical areas not studied here. Fried et al. highlight recent reports of an experience of urge to move following parietal stimulation (Desmurget et al., 2009). They briefly present one parietal recording from their own data set, which shows an increase in firing rate prior to W very similar to medial frontal neurons. The division of labor between medial frontal and parietal cortex in volition is a topic of current debate. Neuropsychological studies of patients with focal frontal and parietal lesions suggest that both areas are involved in volition (Haggard, 2008). It seems likely that they act as a concerted network: the pre-SMA might generate action plans, and the parietal cortex might monitor their progression to execution. However, we have little insight into the detailed operation of this network. In neurosurgical studies, the sites of stimulation and placement of recording electrodes are, of course, determined by clinical need alone. Therefore, the crucial data required to resolve the debate, such as simultaneous recordings from parietal and frontal electrodes in the same individual, may not be forthcoming. A second remaining question is the activity of these neurons in the absence of voluntary action.

To limit the duration of caspase-3 activation, the broad spectrum cell-permeable caspase inhibitor Q-VD was added to the neural medium at 10, 30, and 60 min after NMDA treatment. The proportion of PI positive neurons analyzed was comparable

to that of sham-treated controls in neurons exposed to elevated active caspase-3 for 10 min or 30 min (Figure 7B), but in those exposed to elevated active caspase-3 for 60 min, it was significantly higher (Figure 7B; Table S3). These results suggest that robust and prolonged activation of caspase-3 induces cell death. If high levels of caspase-3 activity are required to induce cell death, we would expect that actinomycin D, if made to induce only a small increase in caspase-3 activity, would not cause apoptosis. Hence, in a second approach, we treated neurons with a low dose of actinomycin D

(0.1 μM), and found that this treatment increased http://www.selleckchem.com/products/frax597.html caspase-3 activity to a level similar to the peak level induced by 30 μM NMDA (Figure 7C; Table S3). In fact, the proportion of PI-positive cells assessed 22 hr after actinomycin D treatment was similar to that of untreated controls (Figure 7D; Table S3). These results show that low-level caspase-3 activation is not adequate to provoke apoptosis. In a third approach we tested whether prolonged caspase-3 PARP inhibitors clinical trials activation at low levels induces apoptosis. To this end, we employed a repetitive stimulation method with 30 μM NMDA (see Experimental Procedures). As shown in Figure 7E, the pattern of caspase-3 activation and its peak levels of activity were comparable during the first three NMDA stimulations, and there was no significant increase in PI-positive cells (Figure 7F). However, after the fourth stimulation, caspase-3 activity reached a higher level (147 ± 7% of sham-treated controls at 30 min after the fourth stimulation; Figure 7E), but it did not reach the level

observed after application of 100 μM NMDA (178 ± 8% of control at 30 min after 100 μM NMDA treatment; Figure 7A). Nevertheless, after adding Q-VD to stop caspase-3 already activation 30 min after the fourth NMDA stimulation, the proportion of PI positive cells stained 22 hr later was significantly increased (Figure 7F; Table S3). Because the higher increase of caspase-3 activity (178 ± 8%) induced by 100 μM NMDA was not sufficient to cause cell death when lasting for just 30 min (Figures 7A and 7B), it is unlikely that the 147 ± 7% increase of caspase-3 activity for 30 min after the fourth NMDA stimulation was responsible for increased cell death; rather, this increase appears to be the result of prolonged activation of caspase-3. We conclude, therefore, that it is the lower and transient activation of caspase-3 that prevents cell death in LTD. In this study, we identify a signaling pathway for caspase-3 activation in LTD and address the intriguing question of how hippocampal neurons undergoing LTD avoid cell death despite the activation of caspase-3.

, 1995). Spine density did not differ significantly between scrambled and Cyfip1 shRNA neurons (not shown). However, Cyfip1 knockdown robustly affected spine morphology: spines with mature phenotype (i.e., “stubby” and “mushroom”) were significantly reduced in Cyfip1-silenced neurons compared to control, whereas elongated, immature-looking spines increased in

number ( Figures 5D, 5E, S5E, and S5F). Mean head width was unchanged (not shown), but mean spine length was increased as a consequence of Cyfip1 silencing; cumulative Proteases inhibitor probability plots corroborated these results ( Figure 5F). To exclude the possibility that the phenotype might be due to off-target effects, we performed a rescue experiment by cotransfecting the sh315 (against Cyfip1 3′UTR) and the Cyfip1 Fulvestrant manufacturer WT coding sequence. The construct was able to restore normal CYFIP1 levels ( Figure S5E), and

consequently proper spine distribution ( Figures 5D, 5E, and S5F) and mean spine length ( Figure 5F). Finally, we aimed at investigating the contribution of CYFIP1-eIF4E and WRC to spine formation. Therefore, we cotransfected the CYFIP1 mutants validated above with Cyfip1 sh315 to knockdown the endogenous protein ( Figure S5E), and analyzed dendritic spine morphology. All mutants failed to restore the normal spine distribution and spine length ( Figures 5D, 5F, and S5F), indicating that both CYFIP1 complexes are equally important for proper spine formation. In conclusion, CYFIP1 deficiency alters the proper functioning of two complexes modulating critical synaptic processes, i.e., protein synthesis and actin cytoskeleton remodeling, both of these ultimately leading to defects in spine morphology. To further expand the knowledge of CYFIP1 in the brain, we studied its interactome in mouse cerebral cortex through immunoprecipitation with a specific anti-CYFIP1 antibody and tandem mass spectrometry (MS). In whole cortical lysates, we identified a total of 27 CYFIP1-associated proteins, of which 74% are

RNA-binding proteins (RBPs) (Figure 6A), comprising either known (FMRP and PABP-1) (Napoli et al., 2008 and Schenck et al., 2003) or novel (ELAV-like proteins, Caprin1 and hnRNPQ/SYNCRIP) partners; these are listed in Tables S2 and S3. The association mafosfamide of some interactors (ELAVL4, PABP1, Caprin1, SYNCRIP, FMRP, eIF4E, and DCTN1) was validated by reverse immunoprecipitation (Figures 6B and S6). To investigate whether these interactions depend upon RNA, CYFIP1 was immunoprecipitated from RNase-treated cortical lysates. Whereas the binding of CYFIP1 to PABP1, DCTN1 and eIF4E was not compromised by RNA degradation, the interaction with SYNCRIP, ELAVL4, and ELAVL1 was no longer detected (Figure 6C) implying that the CYFIP1 complexes contain both protein and RNA molecules. The association of FMRP with CYFIP1 was slightly reduced by treatment with RNase, confirming previous indications that RNAs (e.g., BC1) can strengthen this interaction (Napoli et al.

In addition, each FingR was expressed in a punctate pattern that localized with the corresponding endogenous protein (Figures 4E–4H, 4M–4P, and S3). In the presence of siRNA against Gephyrin, the total Gephyrin expressed in processes per cell was reduced by 96% ± 1% (Figure 4Q; n = 10 cells) compared with scrambled siRNA, whereas the staining of GPHN.FingR-GFP was reduced by 98.1% ± 1% (n = 10 cells) under the same circumstances, a difference that

is not significant (p > 0.13, t test). Similarly, in cells Z-VAD-FMK in vivo where the amount of total PSD-95 was reduced by 96% ± 1% (Figure 4R; n = 10 cells), the amount of PSD95.FingR staining in processes was reduced by 99% ± 1% (n = 10 cells) compared with cells expressing scrambled siRNA, a difference that is not significant (p > 0.1, t test). These results are consistent with the majority of PSD95.FingR and GPHN.FingR labeling their target proteins within dissociated cortical neurons. In the CNS there are three close homologs of PSD-95 that are also found at postsynaptic selleck sites: PSD-93,

SAP-97, and SAP-102 (Brenman et al., 1998). To determine whether PSD95.FingR could distinguish between different MAGUK proteins, we independently tested whether PSD95.FingR-GFP bound to PSD-93, SAP-102, or SAP-97 in our COS cell assay. We found that PSD-93 did not colocalize with PSD95.FingR-GFP, whereas SAP-102 and SAP-97 did (Figures 5A–5C). To determine whether SAP-102 and SAP-97 interact with PSD95.FingR-GFP in a more stringent assay, we coexpressed HA-tagged versions of these proteins in cultured cortical neurons where PSD-95 expression had been knocked down with siRNA. We found that when PSD95.FingR is coexpressed with either SAP-97 or SAP-102, the coexpressed proteins colocalize (Figures 5D–5K). Thus, PSD95.FingR probably binds to heterologous SAP-97 and SAP-102 with relatively high affinity, but not to heterologous PSD-93. Additional testing will be required to determine the exact specificity of binding of PSD95.FingR-GFP with endogenous MAGUK proteins in vivo. However, even in the case where PSD95.FingR does identify other synaptic MAGUK proteins, it is still

suitable for marking synapses. In addition to testing the specificity Suplatast tosilate of binding, we asked whether expression of the FingR had a morphological effect on cells. In light of the dramatic increase in spine size and density caused by overexpression of PSD-95 (El-Husseini et al., 2000; Kanaani et al., 2002) and the large aggregates seen with overexpression of Gephyrin (Yu et al., 2007), we tested whether expression of PSD95.FingR-GFP or GPHN.FingR-GFP had an effect on the size of PSD-95 or Gephyrin puncta, respectively. We found that the amounts of total Gephyrin associated with individual puncta (stained with an anti-Gephyrin antibody) were nearly identically distributed in cells expressing GPHN.FingR-GFP (μGPHN = 18.1 ± 0.7 a.u., n = 200 puncta) versus with untransfected cells (μGPHN = 18.4 ± 0.8 a.u., n = 200, p > 0.

4 ± 0.2; Table 1). Similar results were obtained with DIV7 neurons transfected with TfR-yellow fluorescent protein (YFP) constructs (see Figures S1A and S1B available online). In contrast, mutation of two other phenylalanine residues, F9 or F13 (Figure 1A), had no effect on the somatodendritic localization of TfR-YFP (Figures S1A and S1B). We also noticed that whereas wild-type TfR-GFP or TfR-YFP displayed punctate staining in the cytoplasm

of dendrites and soma, the corresponding Y20A mutants showed diffuse staining throughout the cell, including the axon (Figures 1B and 1C; Figures S2A–S2C). The punctate structures containing wild-type TfR-YFP were identified as endosomes by colocalization with internalized antibody to GFP (which recognizes the YFP tag) (Figures S2A and S2B). The diffuse staining of the selleck chemicals R428 in vitro TfR-YFP Y20A mutant, on the other hand, corresponded to the cell surface, as demonstrated by labeling of nonpermeabilized cells at 0°C with the

same antibody to GFP (Figure S2C). This change in surface staining is consistent with the known role of Y20 as an element of the YTRF endocytic signal (Collawn et al., 1990). From these experiments, we concluded that Y20 and F23 in the TfR tail are components of a somatodendritic sorting signal that overlaps with the YTRF endocytic signal. We extended our analyses to the type I integral membrane protein, CAR, a cell adhesion molecule that is highly expressed in the developing central nervous system. CAR localizes to the basolateral surface of polarized epithelial cells (Walters et al., 1999; Diaz et al., 2009) by virtue of a cytosolic YXXØ signal, YNQV (residues ADP ribosylation factor 318–321) (Figure S3A) (Cohen et al., 2001; Carvajal-Gonzalez et al., 2012). We observed that whereas a CAR-GFP construct was restricted to the somatodendritic domain (polarity index: 8.1 ± 1.1), mutants

having an alanine substitution for Y318 or V321 appeared in the axon (polarity index: 1.1 ± 0.2 and 1.2 ± 0.2, respectively) (Figures S3B and S3C). Taken together, these experiments demonstrated that tyrosine-based signals fitting the YXXØ consensus motif mediate somatodendritic sorting of two transmembrane cargoes, TfR and CAR, in hippocampal neurons. Since the epithelial-specific μ1B subunit isoform of AP-1 mediates basolateral sorting in epithelial cells (Fölsch et al., 1999; Gan et al., 2002), we hypothesized that the ubiquitous μ1A—the only μ1 isoform that is expressed in the brain (Ohno et al., 1999)—might be responsible for sorting to the somatodendritic domain of neurons. Consistent with this notion, we recently found that μ1A binds to the cytosolic tails of TfR (Gravotta et al., 2012) and CAR (Carvajal-Gonzalez et al., 2012). Further analyses using yeast two-hybrid (Y2H) and in vitro binding assays showed that interactions with μ1A require Y20 and F23, but not F9 and F13, in the TfR cytosolic tail (Figures S1C–S1E) and Y318 and V321 in the CAR cytosolic tail (Figure S3D) (Carvajal-Gonzalez et al., 2012).

Li and colleagues have also reported that Cux1 directly represses the cell-cycle regulator p27kip1 and thereby inhibits dendrite growth through RhoA ( Li et al., 2010a). The findings from Cubelos and colleagues Alisertib purchase whereby Cux1 promotes dendritic complexity are consistent with the function of the fly homolog Cut, suggesting functional evolutionary conservation of this transcription factor. Just

as in the cerebellar cortex, studies of dendrite morphogenesis in the cerebral cortex and hippocampus have highlighted the regulation of transcription factors by neuronal activity and calcium influx (Figure 4). Prominent among these is the transcription factor cAMP-responsive element binding protein (CREB), which is modulated by a variety of extrinsic cues and regulates neuronal survival, dendrite growth, and synaptic function (Flavell and Greenberg, 2008, Lonze and Ginty, 2002 and Shaywitz and Greenberg, 1999). Neuronal activity stimulates CaMKIV-dependent phosphorylation and activation of CREB in cortical neurons and thereby induces dendrite growth and arborization (Redmond et al., 2002). In more recent studies, CaMKIγ has been found to

mediate neuronal activity-dependent phosphorylation and activation of CREB in hippocampal neurons, leading to Temozolomide increased dendritic arborization (Wayman et al., 2006). The CREB coactivator CBP also participates in neuronal activity-induced dendrite morphogenesis (Redmond et al., 2002). Another calcium-regulated transcriptional coactivator termed CREST, which also associates with CBP, is required for activity-dependent dendrite growth development in the cerebral cortex (Aizawa et al., 2004). Recent studies have identified additional CREB binding partners that act as coactivators required for CREB-dependent dendrite growth, including TORC1 (transducer of regulated CREB activity) and CRTC1 (CREB-regulated transcription co-activator), which operate downstream of activity-dependent signaling and BDNF, respectively (Finsterwald et al., 2010 and Li et al., 2009). These studies highlight

the complexity of CREB-dependent transcription. It will be important to elucidate the context and signaling mechanisms controlling the association of CREB with different coregulators and the consequences on CREB-dependent transcription. Mephenoxalone Although a role for these transcriptional regulators in dendrite development is compelling, the downstream mechanisms are incompletely understood. BDNF represents a potential relevant target of CREB and associated proteins in the control of dendrite development and branching (Cheung et al., 2007, Dijkhuizen and Ghosh, 2005a, Horch and Katz, 2002, McAllister et al., 1997 and Tao et al., 1998). The secreted signaling protein Wnt-2, which promotes dendritic arborization, is also induced by CREB downstream of neuronal activity (Wayman et al., 2006).

FM1-43FX-loaded slices were fixed using rapid microwave fixation in 6% gluteraldehyde, 2% formaldeahyde in PBS as described previously (Jensen and Harris, 1989). After fixation, the samples were transferred into 100 mM glycine in PBS (1 hr), then rinsed in 100 mM ammonium chloride (1 min) and washed in PBS. For photoconversion, the slices were incubated in an oxygen-bubbled diaminobenzidine solution (DAB, 1 mg/ml, Kem

En Tec diagnostics). The DAB solution was refreshed after 10 min and the region of interest was illuminated with intense blue light (<500 nm from a Mercury lamp) for 22–25 min. After photoconversion, the selleck compound samples were prepared for electron microscopy using an established protocol (Jensen and Harris, 1989). Briefly, the samples were placed in 1% osmium tetroxide (Agar Scientific) and 1.5% potassium

ferrocyanide (Sigma) in cacodylate buffer and, after osmication, stained en block in uranyl acetate and dehydrated for embedding in EPON resin (TAAB). Sectioned samples were laid on bare mesh or formvar-coated slot grids and sections collected between ∼5 and ∼15 μm from the photoilluminated surface (see also Figure S1) were viewed using a Hitachi-7100 transmission electron microscope. Digital images were acquired using a 2,048 × 2,048 charge-coupled device camera (Gatan). Wild-type C57/blk6 mice (24–56 days old) were anesthetized with isoflurane (5% for induction, 1.5%–2.5% for surgery, and 0%–0.5% during recording), augmented with chlorprothixene either (0.5–2 mg/kg, intraperitoneally). A 2–3 mm diameter craniotomy was opened over visual cortex. The dura mater was Talazoparib research buy left intact. A thin layer of agar (1.5%) dissolved in aCSF (150 mM NaCl, 2.5 mM KCl, 10 mM HEPES, 2 mM CaCl2, and 1 mM MgCl2; pH adjusted with NaOH to 7.3; 300 mOsm) and placed on top of the brain helped dampen movement. A homeothermic heat pad maintained body temperature within the physiological range. Water-based opthalmic ointment maintained eye health. Visual stimulus presentation was controlled by routines written in MATLAB using the Psychophysics Toolbox extensions (Brainard, 1997; Kleiner et al., 2007, Perception

36 ECVP, abstract; Pelli, 1997). Square-wave gratings (0.04 cycles/deg, 2 cycles/s) of black (2 cd/m2) and white (86 cd/m2) bars in eight different orientations were displayed on an LCD screen (ESAW 7 inch VGA TFT, set at 1,024 × 768 resolution and 60 Hz refresh rate) to map orientation selectivity. For control gray screen stimulation, the total luminance was matched to that of the grating stimulus. The screen was shrouded with a cone up to the eye of the mouse to prevent contamination of the imaging pathway with light from the visual stimulus. The visual stimulus extended from +20° to +124° in azimuth and from −10° to +42° in elevation. A custom-built two-photon microscope using galvanometer-based scan mirrors (6 mm diameter, Cambridge Technologies) with a 16× magnification and 0.

In spite of these challenges, in the last decade, EGFR inhibitor the groups of Lewis, Loew, and others have pioneered the application of SHG to living cells and to measurements

of membrane potential (Bouevitch et al., 1993, Campagnola et al., 2001, Lewis et al., 1999 and Millard et al., 2003). The strategy pursued has been the application of organic dyes, based on styryl fluorophores with distinct electrochromic properties, originally synthesized for fluorescence voltage measurements (Bouevitch et al., 1993). SHG imaging of neurons has also been performed with the membrane-trafficking dye FM4-64, enabling high-resolution measurements of voltage of somata, dendrites, and dendritic spines (Figure 4C; Dombeck et al., 2004, Dombeck et al., 2005 and Nuriya et al., 2005). As an alternative strategy to the typical chromophores, one can use trans-retinal as a SHG chromophore to measure membrane potential (Nemet et al., 2004), since it exhibits a large change in dipole

moment upon light excitation (Mathies and Stryer, 1976). Nevertheless, Dasatinib molecular weight despite advances in the rational design of chromophores for nonlinear imaging, relatively little work has gone into synthesizing chromophores specifically designed for SHG in biological samples that would maximize the SHG response while minimizing damaging alternative photoprocesses. Finally, an alternative approach to measure membrane potential relies Bay 11-7085 on intrinsic changes in the optical properties of the neurons, or axons. These approaches, which are among the earliest historically (Cohen and Keynes, 1971), are potentially very powerful because they do not need exogenous chromophores. At the same time, they can only be applied in optically very accessible preparations, such as neuronal cultures or some invertebrate preparations. Also, they generate relatively small signals and extensive averaging

is necessary. These intrinsic approaches to measure voltage have exploited different types of optical measurements, mostly in invertebrate preparations. For example, changes in light scattering, changes in optical dichroism, and changes in birefringence have been explored (Ross et al., 1977). These changes are presumably related to alteration in the refractive index or small volume changes near the membrane, in response to the rapid osmotic changes associated with ion fluxes, and have been used to monitor action potentials (Cohen and Keynes, 1971, Ross et al., 1977 and Stepnoski et al., 1991). Presumably these same intrinsic mechanisms allow for the detection of action potentials with optical coherence tomography, which uses interferometry to detect small changes in optical path length resulting from action potential activity in isolated neurons.

, 2008), in line with a recent slice study indicating only a minor

role for NMDARs in fast-spiking interneuron activity (Rotaru et al., 2011). These findings are relevant for evaluating current hypotheses on schizophrenia. An involvement of NMDARs in schizophrenia is suggested by pharmacological studies of human volunteers subjected to non-specific DAPT NMDAR antagonists, such as ketamine, and recent postmortem studies on schizophrenic patients (Gilmour et al., 2012; Krystal et al., 2003; Lahti et al., 2001; Malhotra et al., 1997). The NMDAR hypofunction theory proposes that schizophrenia is associated with a reduction of NMDAR-mediated currents at pyramidal-interneuron synapses, resulting in low activity of interneurons and disinhibition of pyramidal neurons (Homayoun and Moghaddam, 2007; Lewis and Moghaddam, 2006; Lisman et al.,

2008; Olney et al., 1999). Our data indicate that NMDAR blockade-induced hyperactivity in OFC does selleckchem not arise strictly from local mechanisms, because a blockade did not significantly affect absolute firing rates of putative pyramidal neurons. Such hyperactivity likely arises from global interactions between OFC and other areas. Our data further suggest that the reduction in neuronal cue-outcome selectivity and plasticity could contribute to impairments in OFC-dependent sensory gating and cognitive function as reported in schizophrenic patients (Krystal et al., 2003; Lisman et al., 2008). Finally, consistent with theories regarding

schizophrenia as a disorder of interareal connectivity (Lynall Tryptophan synthase et al., 2010; Stephan et al., 2009), our data show that local NMDA hypofunction causes marked changes in spike-field phase-synchronization, which may result in global dysconnectivity between brain areas (Uhlhaas et al., 2008). In line with Schoenbaum et al. (1998, 1999), who demonstrated firing-rate selectivity in OFC for stimuli predictive of positive versus negative outcome, we found that during acquisition the electrophysiological S+/S− discrimination scores were significant during the entire task sequence from odor sampling to outcome delivery, both under drug and control conditions (Figure 3). D-AP5 diminished the discriminatory power of single units only during odor sampling. Under aCSF perfusion, the discrimination score during odor sampling increased over trials, due to adaptive changes in spike patterns across both S+ and S− trials (Figure 4). NMDAR blockade hampered the trial-dependent plasticity of discrimination scores across learning during the odor phase. The reduction in discrimination scores by NMDAR blockade cannot be attributed to a difference in absolute firing rates, because these did not differ significantly between pharmacological conditions for any behavioral period (Table 1). Upon reversal, under D-AP5 perfusion, units lost their prereversal selectivity during cue sampling, while this selectivity was maintained for control units (Figure S3 and S4).