No differences in ChR2-YFP expression profile were observed between F2s originating from the same founder. Coronal slices (325 μm) were obtained from adult rats (3 months or older) previously injected

with virus (see Supplemental Experimental Procedures for details). In the analysis find protocol of in vitro electrophysiology, listed membrane potential refers to the initial potential measured immediately after attaining whole-cell configuration. To measure the magnitude of the hyperpolarization-activated inward Ih current, cells were held at −40mV, and a 500 ms voltage step to −120mV was applied. Ih was measured as the difference between the initial capacitative response to the voltage step (usually ∼20–40 ms after the beginning of the voltage step) and the final steady-state current the end of the 500 ms pulse; responses greater than 115 pA were classified as Ih/large. The apparent input resistance was calculated from the linear portion

of the steady-state I-V curve obtained by applying 500 ms hyperpolarizing current pulse steps. www.selleckchem.com/products/Everolimus(RAD001).html Action potential threshold was measured as the voltage at which the first-order derivative of the membrane potential (dV/dt) exhibited a sharp transition (typically > 10mV/ms). The action potential threshold was also used to set the threshold in determining spike fidelity (% of successful action potential after various light stimulation frequencies). Peak and steady-state photocurrents were measured from a 1 s light pulse in voltage-clamp mode. Series resistances were carefully monitored and recordings were not used if the series resistance changed significantly (by >20%) or reached 20 MΩ. Statistical analysis was performed with a two-tailed Student’s t test, with a level of significance set at p < 0.05. Simultaneous optical stimulation and extracellular electrical recording were performed in anesthetized rats as described previously (Gradinaru et al., 2007). See Supplemental Experimental Procedures for details. Coronal brain slices (300–400 μm) were prepared from enough adult rats previously injected with virus. A carbon-fiber glass electrode was positioned in the NAc under fluorescent guidance. Voltammetric measurements

were made every 100 ms by application of a triangular waveform (−0.4V to +1.3V, at 400V/s) to the carbon-fiber electrode versus an Ag/AgCl reference electrode. To estimate changes in DA release, background current at the electrode was subtracted from the current measured immediately following optical stimulation. Background-subtracted cyclic voltammogram showed peak oxidation and reduction currents at ∼650mV and −200mV, respectively, indicating that the signals were due to the detection of evoked DA release, and consistent with previous results. See Supplemental Experimental Procedures for additional details. Fifteen male Th::Cre rats, 300–550 g at the start of the experiment, were individually housed in a light-regulated (12 hr light/dark cycle, lights on at 07:00) colony room.

05, χ2 test), and using both the first and second sniff cycles resulted in only a small increase in accuracy (Figure 5D). Therefore, spike counts in ensembles of aPC neurons appear to be sufficient to explain both the speed and accuracy of decisions in an odor mixture discrimination task. If firing rates across ensembles of aPC neurons are used by the brain to form behavioral responses, and if sensory uncertainty reduces performance accuracy, as in the mixture trials, then we might be able to observe Ribociclib in vivo trial-by-trial correlations between decoding based on these neural representations and the animals’ choices. To test this idea, we first compared neuronal firing

rates on correct and error choices for a given stimulus, a measure

analogous to “choice probability,” a measure that has been used previously to test the role of a neural representation in behavior (Britten et al., 1996; Cury and Uchida, 2010; Parker and Newsome, 1998). We found a low average correlation between the firing rates of individual neurons and subjects’ choices (avg. choice prob. = 0.51 ± 0.011; Figures 5E and 5F). This correlation was somewhat smaller than those found in previous observations in visual cortex (0.53–0.7; Britten et al., 1996; Cohen and Newsome, 2009; Dodd et al., 2001; Uka and DeAngelis, 2004). However, if the information for choices is distributed across a large number of uncorrelated aPC neurons such that the contribution of single neurons is diluted (Cohen and Newsome, 2009), then we reasoned that the accuracy of decoding based on simultaneously recorded ensembles may be correlated on a trial-by-trial basis with behavioral Palbociclib manufacturer choices. Indeed, we found that

patterns of spike counts across aPC neurons in correct trials provided significantly higher decoding accuracy than patterns in error Rutecarpine trials (Figure 5G; p = 0.030, Wilcoxon test). In contrast, decoding using peak timing or latency did not show a significant difference between correct and error trials (Figures 5H and 5I; p > 0.05, Wilcoxon test). Therefore, spike rates in aPC not only carry substantial stimulus information, they are also correlated at an ensemble level with the behavioral choices of the animal. The above results indicate that odor information is coded by a large number of neurons in aPC. A critical feature of information coding in neuronal ensembles is the structure and magnitude of correlated fluctuations in firing, which can affect the ability of downstream neurons to decode the information. A simple example of ensemble decoding is population averaging or pooling. By this strategy, neuronal noise can, in principle, be eliminated by averaging the activity of a large number of neurons. However, if noise is not random across neurons, that is, if neural activity cofluctuates across neurons, the benefit of pooling can be significantly curtailed (Cohen and Kohn, 2011; Zohary et al., 1994).

One important complexity is that animals have a very extensive repertoire of species-specific defensive consummatory behaviors appropriate to the nature and imminence of frank threats,

at least partly realized in the sophisticated structure of areas such as the periacqueductal gray (Bolles, 1970; McNaughton and Corr, 2004; Keay and Bandler, 2001). This makes it hard to understand the interplay between such inbuilt responses, Pavlovian preparatory responses such as behavioral inhibition that are tied via prediction (whose neuromodulatory basis is debated; McNally et al., 2011) to initially neutral stimuli, and fully-fledged instrumental responses www.selleckchem.com/products/abt-199.html in the light of aversion. One long-standing and critical division is between passive and active avoidance (Konorski, 1967). Although exact definitions differ, passive avoidance involves not doing actions that lead to punishment, whereas active avoidance requires emitting specific responses to avoid deleterious outcomes. The abstinence in passive avoidance can be specific to particular, problematical, choices, or it can be general, as in behavioral inhibition or certain forms of freezing. Conversely active avoidance involves the emission of specific responses to obviate potential punishment. A key idea here is so-called two-factor

Caspase inhibitor learning (Mowrer, 1947) and safety signaling. This involves learning that circumstances which could be associated with punishment have low values, and that the change in circumstance associated with removing the threat is appetitive. It can

therefore reinforce the action concerned, just as in the previous section. To the extent that unexpected punishments are coded in the inhibition of phasic dopamine responses below baseline (Ungless et al., 2004; Cohen et al., 2012), just like non-delivery of expected reward (Schultz et al., 1997), the indirect pathway through the striatum which is tonically inhibited by dopamine via D2 receptors is well-placed to realize specific passive avoidance (Frank et al., 2004). Indeed, selectively activating second neurons in just this pathway has recently been shown to lead to place and action avoidance in spatial and operant paradigms (Kravitz et al., 2012), exactly opposite to the effect of activating neurons in the direct pathway. However, suppression of phasic dopamine activity is not the whole story for passive avoidance, since serotonergic neuromodulation has also been implicated in behavioral inhibition (Gray and McNaughton, 2003; Crockett et al., 2009, 2012), including in the face of punishment. Apparently more problematic is the fact that dopamine neurons have been reported to be phasically excited by punishments (Mirenowicz and Schultz, 1996; Bromberg-Martin et al.

Second, if the γ-Pcdhs affected a parallel pathway,

treatment with Gö6983 or PF-228 should increase branching in both control and mutant neurons without affecting the difference between them. However, we found that these inhibitors had a greater effect on mutant neurons than Transmembrane Transporters activator on control neurons (Figure 4J), with each treatment narrowing the difference in branching between the two genotypes. Finally, consistent with MARCKS being a major downstream component of signaling regulated by the γ-Pcdhs, overexpression of MARCKS brought branching in mutant and control neurons to nearly identically high levels (Figure S4L). Together, our experiments provide strong support for a model in which the γ-Pcdhs bind to FAK and inhibit its activation, as shown by Chen et al. (2009). This inhibition leads to reductions in the activities of PLC and PKC, resulting in the maintenance of actin-associated,

nonphosphorylated MARCKS at the membrane, thus promoting dendrite arborization. In the absence of the γ-Pcdhs, the activity of this FAK-PLC-PKC pathway is elevated, resulting in click here increased phosphorylation of MARCKS and the observed defects in arborization. Here, we generated mice with forebrain-restricted loss of the γ-Pcdhs and used them in experiments that identify (1) an in vivo function for these diverse adhesion molecules in regulating dendrite arborization during cortical development and (2) a PKC/MARCKS signaling pathway through which the

γ-Pcdhs exert this function. Previous analyses showed a role for the γ-Pcdhs in neuronal survival in the spinal cord (Wang et al., 2002b and Prasad et al., 2008), retina (Lefebvre et al., 2008), and hypothalamus (Su et al., 2010). Surprisingly, we found no evidence for increased apoptosis in Pcdh-γ mutant cortex. This could reflect greater genetic redundancy either in the control of cortical neuron survival and/or a differential requirement for the γ-Pcdhs in distinct neuronal types. The latter possibility is supported by previous observations: distinct spinal cord ( Prasad et al., 2008), retinal ( Lefebvre et al., 2008), and hypothalamic ( Su et al., 2010) populations exhibit increased apoptosis to different extents in the absence of γ-Pcdhs. Although it is tempting to suggest that interneurons require γ-Pcdhs, whereas “projection” neurons, such as layer V neurons, do not, this may be too simplistic: Lefebvre et al. (2008) documented significant apoptosis of Pcdh-γ mutant retinal ganglion cells, as well as of interneurons. Recently, Lin et al. (2010) identified the adaptor protein PDCD10/CCM3 as an interaction partner of the γ-Pcdh constant domain and downstream effector of the γ-Pcdhs’ regulation of neuronal survival. Though PDCD10 is ubiquitously expressed in the developing brain ( Petit et al.

Taken together, these studies are the first to report that VEGF is essential for proper axon guidance at the CNS midline in vivo. VEGF-A functions as a midline-derived chemoattractant for RGC axons in the diencephalon and functions similarly selleck products for commissural axons in the developing spinal cord. In the

visual system, Npn-1 is an obligatory receptor for VEGF attraction, while in the developing spinal cord, Flk1 is required for the VEGF-mediated attractive response. No significant expression of Flk1 or Flt1 is detected in developing RGCs (Erskine et al., 2011), and conversely, Npn-1 is not expressed by precrossing spinal commissural neurons (Ruiz de Almodovar et al., 2011). Although, Flk1 mutants have not been examined for RGC midline crossing defects, the current data suggest that RGCs and spinal commissural neurons employ distinct selleck inhibitor and independent signaling mechanisms for VEGF attraction. How does VEGF signal attraction in RGCs? Npn-1 is a type-1 transmembrane protein with a short cytoplasmic domain, and one possibility is that Npn-1 signals attraction through

its cytoplasmic domain, independent of a coreceptor(s). Alternatively, Npn-1 might form a complex with a coreceptor to form a holoreceptor complex that signals VEGF attraction. NrCAM has been shown to regulate neuropilin signaling in response to Sema3s during commissural axon guidance in the anterior commissure (Falk et al., 2005). When coupled with NrCAM’s role in promoting RGC axon midline crossing in vivo, it is possible that NrCAM is part of a Npn-1/VEGF receptor complex which promotes midline crossing. Arguing

against this possibility, however, are the distinct temporal requirements for NrCAM and Npn-1/VEGF for proper decussation of RGC axons. Defective RGC midline crossing Org 27569 in Npn-1and Vegfa120/120 mutant mice is observed as early as E14, while defects in NrCAM mutants are observed only late in visual system development, from E17.5 onward ( Williams et al., 2006). Recent evidence suggests that Flk1 functions as the signal transducing receptor component for Sema3E, providing additional evidence for shared mechanisms involving Sema3s and VEGF ( Bellon et al., 2010). These present studies do not address whether VEGF influences guidance in a Plexin-dependent manner. Npn-1 forms a complex with Plexin receptors, and Plexins are regulators of both attractive and repulsive axon guidance ( Kolodkin and Tessier-Lavigne, 2010). Genetic tools are available, and it will be interesting to examine whether Plexin mutants show guidance defects at the CNS midline related to impaired VEGF function. The identification of VEGF as a novel midline attractant released by the floor plate begs the question as to how VEGF might fit in with previously identified spinal commissural axon guidance mechanisms.

However, when tetanus toxin (TeNT), a protease that cleaves most VAMP proteins, is added to dissociated cultures, dendritic arbor development is largely unaffected even after weeks of

exposure to TeNT (Harms and Craig, 2005). Furthermore, neuronal morphology was normal in animals lacking VAMP2 or SNAP25 (Schoch et al., 2001 and Washbourne et al., 2002). These observations may be reconciled by data demonstrating that a toxin insensitive VAMP family member, Ti-VAMP/VAMP7, is involved in neurite outgrowth in differentiating PC12 cells (Burgo et al., 2009 and Martinez-Arca et al., 2001). Whether Ti-VAMP/VAMP7 plays this website a role specifically in axon or dendritic outgrowth, or whether a SNARE-independent pathway exists for neuronal development, remain

open questions. Once established, neuronal polarity and morphology are maintained for months or years in spite of rapid turnover of cell membrane lipids and proteins. Demonstrating the importance of ongoing membrane trafficking in maintaining neuronal morphology, Horton et al. (2005) blocked the secretory pathway by disrupting trafficking at the level of the Golgi apparatus in mature neurons. This manipulation triggered a dramatic simplification of the dendritic arbor and a ∼30% loss in total dendrite length after 24 hr, indicating that forward trafficking I-BET151 chemical structure through the secretory pathway to the PM is required for maintenance of dendritic morphology. Consistent with results from Drosophila sensory neurons ( Ye et al., 2007), axonal morphology of cortical and hippocampal neurons was not affected by blocking secretory trafficking ( Horton et al., 2005), indicating that ongoing membrane trafficking through the canonical secretory pathway is selective for dendritic growth and stability, perhaps due to a switch in the directionality of polarized post-Golgi traffic and exocytosis from

axons to dendrites ( de Anda et al., 2005). While the overall architecture of mature neurons is stable, dendrites from cortical neurons exhibit activity-dependent morphological plasticity, particularly during development. This is illustrated by experiments demonstrating the influence of sensory experience on cortical ocular dominance columns and whisker barrel columns. In both cases, dendrites from Dichloromethane dehalogenase layer IV stellate neurons in regions bordering sensory deprived receptive fields orient themselves away from the deprived field, demonstrating the role of ongoing dendrite remodeling in shaping neuronal connectivity in response to experience (Datwani et al., 2002 and Kossel et al., 1995). While future experiments will be necessary to determine how neuronal activity is coupled to experience-dependent changes in cellular morphology, it is likely that sensory input ultimately impinges upon factors influencing cytoskeletal rearrangement and exocytic trafficking to sculpt dendritic architecture important for circuit connectivity and sensory plasticity.

In both monkeys, baseline activity was indistinguishable learn more between attend-in and attend-distributed (paired t test, monkey 1, p = 0.95; monkey 2, p = 0.57), but significantly lower in attend-out relative to the other two attentional states (paired t test, monkey 1, p < 0.0052 for both

tests; monkey 2, p < 0.015 for both tests); baseline activity in attend-out and blank conditions was indistinguishable (paired t test, monkey 1, p = 0.29; monkey 2, p = 0.39), and this was true at the location where the distracter could appear (opposite to the cue) as well as the two other unattended locations (Figure S3). The Gaussian amplitude was independent of attentional state (paired t test, p > 0.094 for all tests). To quantify this effect, we normalized all responses by the average amplitude of the Gaussian component. The average normalized amplitude of the attentional

baseline elevation was 23% in monkey 1 and 12% in monkey 2, while the average normalized target-evoked response (additional response evoked by the target in the presence Lapatinib mw of the mask) was only 4.7% in monkey 1 and 7.1% in monkey 2. While responses under focal and distributed attention are the same on average, it is still possible that attention enhances neural sensitivity under focal attention by modulating neural noise (Cohen and Maunsell, 2009 and Mitchell et al., 2009). To examine this possibility, we computed the SD of the response amplitude across trials and the spatial correlations of the response variability (Chen et al., 2006). Neither the SDs nor the spatial correlations varied significantly with attentional state (Figure 5), suggesting that in our task, attention does not lead to significant changes in these noise properties at the population level in V1. To determine when the attentional modulations are initiated and how they evolve over time, we compared the dynamics of the baseline component in the three

attentional states (see Experimental Procedures). Our results show that the attentional modulations start to build up about 100 ms before the stimulus-evoked response (compare Figures 6A and 6D with Figures 6C and 6F) and about 200 ms after fixation point dimming. Similar results were obtained in control trials in which no visual stimulus Sclareol was presented after the cue(s) ( Figures 6B and 6E). These modulations, therefore, are stimulus independent, are preparatory in nature, and are timed to occur shortly before stimulus onset. Our results suggest that top-down mechanisms can modulate neural population responses in V1 based on stimulus relevance, but before we can conclude that the elevated baseline reflects a genuine top-down attentional signal, we have to rule out several confounding effects. First, it is possible that the observed baseline modulations are due to direct visual response to the cue.

Nymphs and adults were dissected, the salivary glands collected and immersed in a cell lysis solution for subsequent DNA extraction. DNA was extracted from cervid blood samples (300 μL) with the aid of a Wizard® Genomic DNA Purification Kit (Promega, Madison, find protocol WI, USA) employed according to the manufacturer’s instructions. In order to extract DNA from tick salivary glands, the same commercial kit was used following the manufacturer’s instructions designated for the extraction

of DNA from tissue cultures. The nPCR assay of genomic DNA involved two separate amplification reactions. The first reaction was carried out using the primers RIB-19 (5′CGGGATCCAACCTGGTTGATCCTGC3′) and RIB-20 (5′CCGAATTCCTTGTTACGACTTCTC3′) that are specific

for a 1700 bp segment of the 18S rRNA gene from RG7204 Babesia and Theileria spp. ( Zahler et al., 2000). The reaction mixture comprised 1.2 μL of dNTPs (0.2 mM), 0.15 μL of Taq polymerase (0.05 U), 1.5 μL which buffer (1×), 0.6 μL of a solution containing the mixed primers (10 μM) and sufficient sterile ultra-pure water to give a final volume of 15 μL. A 1.5 μL aliquot of the DNA template was added to the reaction mixture, and amplification was performed using an Eppendorf (São Paulo, SP, Brazil) Mastercycler® thermocycler programmed as follows: 94 °C for 5 min (initial denaturation step), 30 cycles each comprising 92 °C for 1 min (denaturation), 54 °C for 1 min (annealing) and 72 °C for 2 min (extension), and a final extension step at 72 °C for 8 min. Following amplification, reaction mixtures were maintained at 12 °C. PCR amplicons were separated by electrophoresis on 1% agarose gel (40 min, 100 V), stained with ethidium bromide and visualised under ultraviolet light. The second reaction was carried out using primers BabRumF (5′ACCTCACCAGGTCCAGACAG3′) and BabRumR (5′GTACAAAGGGCAGGGACGTA3′) that were designed to amplify a common 420 bp Babesia 18S rRNA fragment identified by aligning sequences from Babesia spp. available at GenBank (http://www.ncbi.nlm.nih.gov), Non-specific serine/threonine protein kinase namely, B. bigemina (X59607), B. odocoilei (U16369), Babesia

divergens (U07885) and B. bovis (L31922). The reaction mixture comprised 2.0 μL of dNTPs (0.2 mM), 0.25 μL of Taq polymerase (0.05 U), 2.5 μL which buffer (1×), 1.0 μL of a solution containing the mixed primers (10 μM) and sufficient sterile ultra-pure water to give a final volume of 25 μL. An aliquot (2.5 μL) of amplicon obtained in the first reaction were added to the reaction mixture and amplification was carried out under the conditions described above. Products were separated by electrophoresis and visualised as described above, and subsequently purified with the aid of QIAquick PCR Purification Kit (Qiagen Biotecnologia Brasil, São Paulo, SP, Brazil) used according to the recommendations of the manufacturer.

, 2007). Typical power levels on sample were 230 ± 80 mW (40×, 0.8 NA objective) or 170 ± 60 mW (20×, 0.5 NA objective). We usually evoked bursts of APs to ensure detecting connections. Successive neuronal targets were stimulated

every second; this rapid neuron to neuron stimulation allowed us to quickly assess the connectivity BVD-523 concentration of multiple neuronal pairs using the “switching test” (see Results). Occasionally, responses were “mixed,” composed of outward and inward currents at −40 mV. Since the purpose of our study was to detect all potential inhibitory connections, we tallied these responses as inhibitory for our analysis, because they did reveal the existence of an inhibitory connection. All maps with paired or triple recordings were acquired with a 20× objective (0.5 NA); the investigated fields represented around 600 × 800 μm, including therefore layers 2/3 and 1. Neurons were filled with biocytin (5 mg/ml; Sigma) by the patch pipette. Subsequently, slices were fixed overnight in 4% paraformaldehyde in 0.1 M phosphate buffer at 4°C. Biocytin-filled cells were visualized using the avidin-biotin-horseradish peroxidase reaction. Successfully filled and stained neurons were then reconstructed using

Neurolucida (MicroBrightField) (see details in Supplemental Experimental Procedures). Off-line analysis was conducted using Matlab or IGOR Pro with the Neuromatic v2.0 package. All results are expressed as mean ± SEM. Statistical significance was assessed using Student’s t test, Mann-Whitney, and Wilcoxon tests or one-way this website ANOVA at the significance level (p) indicated. Analysis

of electrophysiological properties of interneuron and characteristics of synaptic transmission are detailed in the Supplemental Experimental Procedures. We thank V. Nikolenko for inspiration and help, L. McGarry, Y. Shin, and J. Miller for anatomical reconstructions, M. Dar for help with mice, L. McGarry for cluster analysis and D. Rabinowitz and members of the laboratory for help and comments. Supported by the Kavli Institute for Brain Oxalosuccinic acid Science, the National Eye Institute, and the Marie Curie IOF Program. “
“A ubiquitous idea in psychology, neuroscience, and behavioral economics is that the brain contains multiple, distinct systems for decision-making (Daw et al., 2005, Kahneman, 2003, Loewenstein and O’Donoghue, 2004, Rangel et al., 2008, Redish et al., 2008 and Sloman, 1996). One long-prominent contender, the “law of effect,” states that an action followed by reinforcement is more likely to be repeated in the future (Thorndike, 1911). This habit principle is also at the heart of temporal-difference (TD) learning accounts of the dopaminergic system and its action in striatum (Barto, 1995 and Schultz et al., 1997).

Thus far, TARPs have not exhibited any subtype-dependent differences in the enhancement of mean channel conductance of GluA2-lacking AMPARs (Soto et al., 2007, Soto et al., 2009 and Suzuki et al., 2008). However, recent evidence shows that TARP subtypes can differentially modulate the mean channel conductance of heteromeric, GluA2-containing

AMPARs (Jackson et al., 2011). Even the type II TARP γ-5 enhances the mean channel conductance of both homomeric and heteromeric AMPARs (Soto et al., 2009). GluA2-lacking, calcium-permeable AMPARs are subject to SB431542 order voltage-dependent block by endogenous intracellular polyamines such as spermine and spermidine, resulting in characteristic inwardly rectifying current-voltage (I-V) relationships (McBain and Dingledine, 1993, Bochet et al., 1994, Jonas et al., 1994, Geiger et al., 1995, Kamboj et al., 1995, Koh et al.,

1995 and Bowie and Mayer, 1995). The degree of rectification of both synaptic and agonist-evoked AMPAR-mediated current is frequently used as a metric for GluA2 content (Isaac et al., 2007). TARP association dramatically diminishes the affinity of the AMPAR pore for intracellular spermine, thus enhancing charge transfer and calcium entry (Bowie and Mayer, 1995, Soto et al., 2007 and Soto et al., 2009) (Figure 3 and Table 1). TARP-dependent effects on I-V shape may account for rectification being a misleading measure of synaptic and extrasynaptic GluA2 content (Jackson and Nicoll, 2011). Moreover, recent evidence suggests that TARP association enhances the www.selleckchem.com/products/sch-900776.html efficacy of externally applied polyamine toxins such as philanthotoxins (PhTx) in a subunit-dependent and agonist-dependent manner (Jackson et al., 2011). The effects

of the type II TARPs on AMPAR gating are complex and sometimes contradictory. TARP γ-7, but not γ-5, was shown to display modest slowing of both the deactivation and desensitization kinetics of GluA1 homomers (Kato et al., 2007), although in another study neither γ-7 nor γ-5 had any effect on the desensitization Thymidine kinase kinetics of GluA4 homomers, but had differential effects on other gating parameters (Soto et al., 2009). And while γ-5 does nothing to unedited GluA subunits, Kato and coworkers showed that it can modulate the gating of edited GluA2(R)-containing, calcium-impermeable AMPARs, seeming to have a more pronounced effect on GluA2/3 heteromers than GluA1/2 heteromers, by accelerating both deactivation and desensitization. Furthermore, γ-5 association lowers the affinity of GluA2-containing AMPARs for glutamate (Kato et al., 2008). TARP γ-5, therefore, appears to be a contrarian TARP that does not participate in AMPAR trafficking but modulates AMPARs of a specific composition, in a way that is opposite to that of other TARPs. The eccentric functional behavior of γ-5 is all the more remarkable when compared with that of γ-7, with which it exhibits a high degree of sequence homology.