Findings in Drosophila

models suggest that tau phosphorylation may cause neurotoxicity in a combinatorial fashion rather than through the modification of individual phosphorylation sites and involves the folding of tau into an abnormal conformation resembling tau conformations found in AD ( Steinhilb et al., 2007). Hyperphosphorylated tau has a tighter, more folded conformation and an increased propensity to aggregate ( Jeganathan et al., 2008), as does tau with mutations found in FTLD ( Lee et al., 2001). In C. elegans, overexpression of wild-type or mutant 4R1N tau causes axonal degeneration and an uncoordinated phenotype indicative of neuronal dysfunction ( Kraemer et al., 2003). The extent of phosphorylation was similar across mutant and wild-type tau lines, but Ibrutinib mouse more insoluble tau was found in Olaparib the former ( Kraemer et al.,

2003). Worms overexpressing mutant tau that formed aggregates had a more severe phenotype ( Kraemer et al., 2003). Although filamentous tau inclusions are a pathologic hallmark of tauopathies, experimental evidence suggests that filamentous tau may not be responsible for neuronal dysfunction. In a regulatable P301L 4R0N tau transgenic mouse (rTg4510 model), inhibiting tau production after filamentous tau inclusions formed reversed behavioral deficits in the Morris water maze, even though inclusion formation progressed (Santacruz et al., 2005). Acute tau reduction by methylene blue treatment in this model improved memory scores in correlation with the reduction of soluble tau in the brain but did not alter the number or length of tau fibrils or the amount of Sarkosyl-insoluble tau compared

to untreated transgenic mice (O’Leary et al., 2010). In other mouse lines, tet-off transgenes were regulated by the CaMKII Ketanserin promoter to express either the 4R microtubule repeat domain of human tau with a deletion of lysine 280 (termed TauRD), which is highly prone to aggregation, or TauRD with an additional two mutations (I277P/I308P) that prevent its aggregation (Mocanu et al., 2008). The proaggregation transgenic mouse, which formed hyperphosphorylated tau inclusions containing TauRD and endogenous mouse tau, developed synaptic loss (Mocanu et al., 2008), memory deficits and electrophysiological impairments (Sydow et al., 2011). In contrast, the antiaggregation transgenic mouse showed none of these abnormalities. Turning off the transgene in the proaggregation mouse reversed behavioral and electrophysiological alterations without eliminating insoluble tau aggregates, which were composed entirely of endogenous mouse tau after the transgene had been turned off for 4 months (Sydow et al., 2011). These data highlight that tau aggregation causes toxicity, possibly through the formation of tau oligomers.

In addition, some mutant terminals presented big membrane presynaptic compartments of unknown origin and organelles with an unusual shape (clover shape) compatible with arrested vesicle budding from endosomes (Figure 7F, panels e and f). Some of those structures kept similarities with those observed in dynamin mutants (Ferguson et al., 2007 and Raimondi et al., 2011) or at the sternocleidomastoid muscles in CSP-α KO mice (Fernández-Chacón et al., 2004). To complement our analysis, we analyzed a set of junctions after electrical nerve stimulation (180 s at 30 Hz) (Figures 7E and 7 F and S5). We found

that mutants and WT terminals had a similar number of vesicles, with a significant tendency to be of bigger size in the mutant (Figure S5A). The presynaptic area Bafilomycin A1 concentration and the vesicle density were similar to the values found in resting conditions for both genotypes. However, when we restricted our measurements to the effective area where vesicles reside (by removing the area occupied by mitochondria and axonal filaments) we

found a significant increase in that area in WT and mutant upon stimulation that translated into a lower vesicle density in the mutants (Figure S5A). In addition, omega shape structures were also more frequent in the mutant upon stimulation (Figure 7F). Altogether, those observations could reflect INCB018424 alterations in membrane trafficking downstream of compensatory endocytosis. We wondered if the defects detected in the recycling could be caused by instability and/or degradation of dynamin1 Urease or other endocytic proteins that would normally require CSP-α to keep them stable over the time. Several proteins involved in vesicle recycling (intersectins, dynamins, Hsc-70, RME-8, and actin) were examined by immunoblotting of protein extracts from LAL muscles. Surprisingly, and in contrast to the strong decrease in SNAP-25 levels (Figure 2), we could not detect any reduction in the levels of endocytic proteins in the mutant terminals compared

to controls (Figures 7G and S5B–S5D). Thus, the measurements of vesicle recycling with FM2-10 suggested that the internalized membrane, upon strong stimulation, fails to be properly processed in order to initiate immediately a new wave of exocytosis and thus compromised the integrity of the recycling pool. That could be due to impairment in fast biogenesis of functional vesicles. Consistent with that view, the terminals from CSP-α KO mice exhibited plasma membrane features and unusual organelles compatible with slowed-down or arrested vesicle recycling. However, no decreased levels of endocytic proteins could be detected. CSP-α is essential to prevent activity-dependent degeneration of nerve terminals.

5 mM KCl, 1 mM MgCl2, 2 mM CaCl2, 1.25 mM NaH2PO4, and 12.5 mM glucose, and were incubated at 31°C–33°C for 30 min, then allowed to recover at room temperature for an additional 30 min before recording. Internal solutions were either K based, for current clamp recordings from FS interneurons in paired experiments (130 mM KMeSO3, 10 mM NaCl, 2 mM Anti-diabetic Compound Library MgCl2, 0.16 mM CaCl2, 0.5 mM EGTA, 10 mM HEPES, 2 mM Mg-ATP, 0.3 mM Na-GTP [pH 7.25]), or Cs-based, for all voltage clamp recordings

(120 mM CsCl, 15 mM CsMeSO3, 8 mM NaCl, 0.5 mM EGTA, 10 mM HEPES, 2 mM Mg-ATP, 0.3 mM Na-GTP, and 5 mM QX-314 [pH 7.3]). All recordings were performed at 31°C–33°C in ACSF (see above). For experiments measuring mIPSCs, 1 μM TTX (Ascent) and 5 μM NBQX (Ascent) were added to the external saline. For experiments using dopamine antagonists, 5 μM SCH23390 (Tocris) and 10 μM sulpiride (Tocris) were added to the external saline. Mice were pretreated

with desipramine (25 mg/kg; Sigma) and unilaterally injected with 6-OHDA at 3–4 weeks of age. Experiments were typically performed 3–7 days after 6-OHDA injections unless otherwise noted. All changes observed in FS microcircuits at 1 week were already present at 3 days, so data from these time points were pooled. Due to previous reports of changes in http://www.selleckchem.com/products/azd9291.html contralateral striatum following unilateral 6-OHDA injections, saline-injected mice were used as controls (Schwarting and Huston, 1996). TH immunostains were performed on 30 μm

sections, resectioned from acute slices (250–300 μm thick) used for recording. Immunostains for PV and vGAT were performed on 30 μm sections prepared from fixed brains of D2-GFP mice. To quantify overall colocalization between vGAT and PV, images were imported into ImageJ, where intensity thresholds and Manders overlap coefficients were determined by JACoP (Bolte and Cordelières, 2006). Biocytin cell fills were performed on FS interneurons recorded in the striatum from 300 μm thick coronal slices. Slices were fixed 30 min to 2 hr after filling a neuron in 4% PFA overnight at 4°C. Throughout the paper, t tests for unpaired Adenosine triphosphate data were used to test for significance unless otherwise noted. The nonparametric Wilcoxon signed rank test was used when data were not normally distributed. A chi-square test with Yate’s correction was used to test for significance of FS-D1 MSN and FS-D2 MSN connectivities. Our model of feedforward inhibition in the striatum was adapted from one used by Atallah and Scanziani, 2009. Each cell was modeled as a single compartment, integrate-and-fire neuron. Spiking activity for individual cells was initiated by independent stochastic background synaptic activity (Gaussian noise with a standard deviation [SD] of 100 pA). The networks contained 20 FS interneurons, 400 D1 MSNs, and 400 D2 MSNs, matching observations that FS interneurons comprise ∼2% of all striatal neurons (Gittis et al.

The method of cumulative EPSC amplitudes (Figure 5E) revealed a significantly smaller pool size in Robo3 cKO mice (8.6 ± 3.5 nA; n = 5) as compared to control mice (25.7 ± 4.8 nA; n = 7; p = 0.012). Furthermore, there was a significant reduction of release probability during the first EPSC,

as estimated by dividing the first EPSC amplitude by the pool size estimate (Figures 5E1 and 5E2). In summary, direct pre- and postsynaptic recordings at ipsilateral calyx of Held synapses indicate a more variable Ca2+ current density, a smaller size of the fast-releasable vesicle pool (FRP), and CH5424802 mouse a significant reduction of the initial release probability in Robo3 cKO mice (Figure 5). These data show that processes of synapse maturation, RG7204 order including the acquisition of fast transmitter release properties characteristic for the calyx of Held, fail to take place in Robo3 cKO mice. The finding of functional deficits at the calyx of Held synapses in Robo3 cKO mice suggests that axon midline crossing conditions the functional maturation of commissural output synapses. Alternatively, Robo3 could have a so far unknown direct role in synapse formation and synapse maturation. In a first series of experiments, we addressed this possibility by studying the developmental expression of Robo3, to verify whether Robo3 is expressed at the time of synaptogenesis

(Figures 6A–6C). In situ hybridization showed Robo3 expression at E14 in the developing VCN, but transcript levels in the VCN were essentially absent at E18 and undetectable

at P10 (Figure 6A). Using an anti-human Robo3 antibody which stained crossing hindbrain axons at E12.5 (Figure 6B), we next attempted to localize Robo3 protein in developing calyces of Held early postnatally, at P1 and P3 (Figure 6C), and at P5 and P8 (see Figure S1 available online). Robo3 was undetectable in developing calyx of Held axons, despite occasional non-specific signals (Figure 6C, arrow); the latter persisted in Robo3 cKO mice (Figure S1). This data indicates that at the calyx of SB-3CT Held projection, Robo3 expression is developmentally downregulated before E18, similar as at other commissural projections (Marillat et al., 2004; Sabatier et al., 2004; Tamada et al., 2008). The absence of Robo3 argues against a direct role of this protein in synapse development. To address a possible direct role of Robo3 in synapse development with an independent approach, we used a conditional KO approach with an inducible Cre mouse line, the CAGGS::CreERTM mouse line ( Guo et al., 2002; Livet et al., 2007). CAGGSCreERTM/+, Robo3lox/lox mice were injected at P0 with tamoxifen (referred to as Robo3 cKOTMX-P0 mice), in order to inactivate the floxed Robo3 allele following axon midline crossing, but before calyx of Held formation and – maturation.

, 2006, Stegmüller et al., 2006 and Stegmüller et al., 2008). Expression of SnoN alone can overcome myelin-dependent growth inhibition, suggesting that SnoN drives a genetic program that promotes axon growth under different extrinsic stimuli (Stegmüller et al., 2006). Interestingly, in contrast to the opposing functions of SnoN1 Androgen Receptor signaling Antagonists and SnoN2 in the control of granule neuron migration and positioning, the two isoforms of SnoN collaborate to promote axon growth (Huynh et al., 2011 and Stegmüller et al., 2006). Although SnoN is widely considered to have transcriptional repressive

functions (Luo, 2004), including in the control of neuronal positioning (Huynh et al., 2011), SnoN functions as a transcriptional coactivator in the control of axon growth (Figure 3; Ikeuchi et al., 2009). In particular, SnoN associates with the histone acetyltrasferase p300 and thereby induces the expression of a large set of genes in neurons (Ikeuchi et al., 2009). These findings support

the concept that SnoN acts in a dual transcriptional activating or repressive manner in a cell-or target-specific manner (Pot and Bonni, 2008 and Pot et al., 2010). In promoting axon growth, the cytoskeletal scaffold protein Ccd1 represents a critical downstream target of SnoN (Ikeuchi et al., 2009). Ccd1 localizes to the actin cytoskeleton at growth cones and activates the protein kinase c-Jun kinase (JNK) (Ikeuchi et al., 2009), which has been implicated CHIR 99021 in axon growth (Oliva et al., 2006). Whereas SnoN drives axon growth by triggering the expression of regulators of the actin cytoskeleton, Id2 is thought to promote axon growth by antagonizing the function of the bHLH transcription factor E47, which induces the expression of a number of genes involved in axon repulsion including NogoR, Sema3F, and Unc5A (Lasorella et al., 2006). Thus, Id2 stimulates axon growth by modulating the response of neurons to guidance cues. Interestingly, TGFβ signaling through the mafosfamide protein Smad2 regulates the abundance of SnoN protein and consequently axon growth (Stegmüller et al., 2008), thus highlighting how intrinsic determinants integrate signals

from extrinsic cues for proper development. Although transcriptional regulators such as NFAT, SnoN, and Id2 appear to regulate axon growth in postmitotic neurons, transcription factors that primarily regulate neurogenesis may also coordinate axon growth in differentiated neurons. In studies of retinotectal projection neurons and spinal cord motor neurons, several transcription factors including Vax2, Zic2, Lim1, and Lmx1b have been reported to regulate the timely and cell-specific expression of proteins involved in axon guidance, including Ephrins A and B and their receptors (Barbieri et al., 2002, Dufour et al., 2003, Herrera et al., 2003, Kania and Jessell, 2003, Kania et al., 2000, Mui et al., 2002, Schulte et al., 1999 and Williams et al., 2003).

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 MK-1775 molecular weight 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 Tanespimycin concentration 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 Ketanserin 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.

Very small pairwise correlations that have been reported as evidence for asynchrony (e.g., Ecker et al., 2010) can in fact belie large total input correlation (Rossant et al., 2011; Schneidman et al., 2006). The origins of synchronous spiking dictate MAPK inhibitor whether synchrony represents signal or noise. Realistic stimuli have spatiotemporal structure that enables them to coactivate neurons with adjacent or overlapping receptive fields; consequently, coactivation patterns can contain information about the stimulus (Brette, 2012; Dan et al., 1998; Meister et al., 1995).

If coactivation patterns contain information, synchrony represents part of the signal. Although this does not prove that synchrony-encoded MLN2238 mouse signals are decoded, nor can synchrony be labeled noise simply because it reduces the information decodable from rate-encoded signals; indeed, it would be equally unfair to label rate-encoded signals as noise because they compromise the decoding of synchrony-encoded signals (see below). That said, the aforementioned points do not rule out stimulus-independent synchrony that is truly noise (Mastronarde, 1989). What is arguably more important is that

correlated spiking in higher brain areas has been observed to be stimulus dependent (Alonso et al., 1996; deCharms and Merzenich, 1996; Kohn and Smith, 2005; Temereanca et al., 2008), consistent with synchrony-encoded signals being successfully transmitted to the cortex. Requirement 3 is satisfied insofar as synchrony-encoded signals are decodable depending on which type of cells whatever carries the message. It has been suggested that synchrony decoding is implausible because of an “inextricable” link between output correlation and spike rate (de la Rocha et al., 2007). If synchrony transfer were to vary with spike rate, input correlation could not be unambiguously decoded from output correlation without that rate sensitivity being factored in, and indeed the synchrony-encoded information could be lost unrecoverably. However, although synchrony transfer is rate dependent among integrators (except under more extreme

stimulus conditions; Schultze-Kraft et al., 2013), the same is not true for coincidence detectors (Figure 3B) (Hong et al., 2012; Tchumatchenko et al., 2010), which argues that synchrony-encoded messages carried by coincidence detectors are decodable. Hence, pyramidal neurons with coincidence detector traits should be able to produce synchronous output that is decodable. These three requirements reflect upon the encoding, transmission, and decoding of synchrony-based signals. Encoding requires the structured coactivation of neurons. Decoding requires that synchrony-encoded signals are not conflated with other signals; in that respect, decodability depends on reliable transmission. Reliable transmission requires robust synchrony transfer. We must, therefore, understand what makes synchrony transfer robust.

This observation could be due to a difference in the fusion

Metformin concentration mechanism for TMR- versus lipid-anchored syntaxin-1A, so that the distance of the SNARE motif to the membrane anchor is functionally irrelevant for the latter. Alternatively, this finding could be due to a different optimal distance of the SNARE motif from the membrane anchor for TMR- and lipid-anchored syntaxin-1. To differentiate between these two possibilities and to test whether lipid-anchored and wild-type syntaxin-1A act by similar mechanisms, we examined the effect of further amino acid insertions between the SNARE motif and the lipid anchor in syntaxin-1A. In these experiments, we tested insertions of additional 3, 7, or 14 residues

on top of the seven-residue insertion characterized above (referred to as Syntaxin-1AΔTMR+10i, Syntaxin-1AΔTMR+14i, and Syntaxin-1AΔTMR+21i, respectively; Figure S4A). We found that all insertion mutants of lipid-anchored syntaxin-1A rescued the impairment of spontaneous release in syntaxin-deficient neurons (Figures 3A and 3B). Unexpectedly, the longer insertions seemed to even increase mIPSCs, suggesting that they may “unclamp” spontaneous release. Sunitinib manufacturer We detected no consistent change in the amplitudes and kinetics of spontaneous many release under any condition (Figure S4B). When we examined action-potential-evoked release, however, we observed that similar to TMR-anchored syntaxin-1A, insertion of an additional three amino acids in

lipid-anchored synaxin-1A on top of the seven-residue insertion (which by itself improved evoked release; Figure 2) blocked evoked release (Figure 3C). This phenotype was associated with a large increase in the desynchronization of release as measured via the variability of rise times (Figure 3D). Moreover, the additional insertions into lipid-anchored syntaxin-1A also blocked the ability of syntaxin-1A to rescue fusion induced by stimulus trains in syntaxin-deficient neurons (Figure 3E). Thus, lipid-anchored syntaxin-1A essential behaves like wild-type syntaxin-1A, with the same selective requirement for a precise distance between the SNARE motif and the membrane anchor for evoked but not for spontaneous release, except that the optimal distance of the SNARE motif from the membrane anchor appears to be slightly longer. Most studies demonstrating an essential role for a SNARE TMR in fusion were performed with synaptobrevin-2.

, 2009 and Tothova et al., 2007). Treating FoxO-deficient mice with the antioxidant N-acetyl-L-cysteine partially rescues these stem cell defects. FoxO3 appears to be the most important FoxO for stem cell function, because deletion of FoxO3 alone also depletes CNS stem cells and HSCs ( Miyamoto et al., 2007, Renault

et al., 2009 and Yalcin et al., 2008). In contrast to HSCs, FoxO-deficient restricted myeloid progenitors do not exhibit increased ROS levels ( Tothova et al., 2007). This suggests that stem cells depend more upon FoxO transcription factors than certain downstream progenitors. Prdm16 is another transcription factor that promotes stem cell maintenance in multiple tissues, at least partly by regulating oxidative stress (Figure 3). Prdm16 is a zinc finger protein that was originally identified as part of a chromosomal translocation in some human acute myeloid leukemias (Morishita, 2007). Consistent with this, overexpression Vemurafenib concentration Selleckchem PD332991 of the Prdm16 proto-oncogene can immortalize myeloid cells (Nishikata et al., 2003); however, the physiological role of Prdm16 is to regulate stem cell function in multiple tissues. Prdm16 is necessary for the development of brown fat cells (Seale et al., 2008), as well as for the maintenance of stem

cell activity in the nervous and hematopoietic systems (Chuikov et al., 2010). The depletion of neural stem cells is at least partially due to increased oxidative stress, because the depletion can be partially rescued by treatment with N-acetyl-L-cysteine. Prdm16 appears to regulate mitochondrial function and to prevent the accumulation of ROS, though the mechanisms by which this occurs remain unknown. The polycomb protein Bmi-1 promotes stem cell maintenance by negatively regulating p16Ink4a and p19Arf expression

( Bruggeman et al., 2005, Jacobs et al., 1999, Molofsky et al., 2005 and Oguro et al., 2006) and likely by regulating mitochondrial function and oxidative stress as well ( Figure 3) ( Liu et al., 2009). Cells from Bmi1-deficient mice have reduced mitochondrial oxygen consumption, reduced mitochondrial oxidative capacity, reduced ATP levels, and elevated ROS levels that appear to cause DNA damage ( Liu et al., 2009). Treating Bmi1-deficient mice with N-acetyl-L-cysteine partially rescues the depletion of thymocytes, though it has not yet been tested whether this second also rescues stem cell function. The observation that Bmi-1 regulates tumor suppressor expression and mitochondrial function suggests that key self-renewal mechanisms integrate energy metabolism with cell-cycle control in a manner analogous to PI-3kinase pathway regulation by Pten, AMPK, and Lkb1. Although elevated ROS levels are toxic to stem cells, physiological levels of ROS are required for certain stem cell functions. Consistent with the role of Akt in negatively regulating FoxO function (Salih and Brunet, 2008), deletion of Akt1 and Akt2 decreases ROS levels and attenuates the proliferation and differentiation of HSCs ( Juntilla et al.

We found that the disparity index and disparity ratio were identical between control and GAD67+/GFP mice throughout postnatal development and in adulthood (Figure 3F). Taken together, these results indicate that initial CF synapse formation, functional differentiation and maturation of CF synapses, and elimination of surplus CFs until P9 are normal, whereas CF synapse Regorafenib elimination after P10 is specifically impaired, in GAD67+/GFP mice. The late phase of CF synapse elimination after P12 is known to require mGluR1 and its downstream signaling (Ichise

et al., 2000, Kano et al., 1995, Kano et al., 1997, Kano et al., 1998 and Offermanns et al., 1997), which is driven by neural activity along MF-GC-PF pathway involving NMDA receptors at MF-GC synapses (Kakizawa et al., 2000). GluD2 (or glutamate receptor δ2) and CaV2.1, a pore forming component of P/Q-type voltage-dependent Ca2+ LY294002 chemical structure channel (VDCC), are also known to be crucial for CF synapse elimination (Hashimoto et al., 2001, Hashimoto et al., 2011, Ichikawa et al., 2002 and Miyazaki et al., 2004). We therefore examined the expressions of these molecules by immunohistochemistry and found that they

were expressed normally in GAD67+/GFP cerebellum (Figures S3A–S3R). Furthermore, we confirmed that synaptically evoked mGluR1 signaling in PCs (Figure S3S), NMDA receptor-mediated EPSC at MF-GC synapse (Figure S3T), and contribution of P/Q-type VDCC to depolarization-induced Ca2+ transients in PCs (Figure S3U) were normal in GAD67+/GFP cerebellum. Therefore, the impaired CF synapse elimination in GAD67+/GFP mice is not likely to result from altered mGluR1 signaling, reduced GluD2 expression, altered CaV2.1 function or reduced NMDAR-mediated GC activation. Since GAD67 expression is reduced throughout the brain of the GAD67+/GFP mice, it Fossariinae is possible that the impaired CF synapse elimination might result from reduction of GAD in brain regions other than the cerebellum. Therefore, we examined whether chronic local application of the GAD inhibitor 3-MP

into the cerebellum of control mice causes impairment of CF synapse elimination. First, we checked whether 3-MP application affects GABAergic synaptic transmission in cerebellar slices. We recorded mIPSCs from PCs in cerebellar slices from control mice (P10–P13) that had been pre-incubated in ACSF with or without 0.1 mM 3-MP ((+) 3-MP and (−) 3-MP) for 3–5 hr at room temperature (Figures 4A–4C). The mean amplitude of mIPSCs was significantly smaller in PCs from (+) 3-MP slices than those from (−) 3-MP slices ((+) 3-MP: 54 ± 1.0 pA, n = 7; (−) 3-MP: 130 ± 17.4 pA, n = 6, p < 0.001) (Figures 4A and 4B). The mean frequency was identical between the two groups ((+) 3-MP: 4.1 ± 1.0 Hz, n = 7; (−) 3-MP: 6.0 ± 1.0 Hz, n = 6, p = 0.181) (Figure 4C). These results demonstrate that the 3-5 hr of 3-MP treatment significantly attenuated GABAergic transmission in PCs.