, 2000) At such connections, the electrical synapse can be detec

, 2000). At such connections, the electrical synapse can be detected using hyperpolarizing current pulses. The postsynaptic response to a presynaptic AP will, however, consist of a mixture of the GABAergic synaptic current and the filtered electrically coupled AP. These can be disentangled by

applying gabazine, which blocks the GABAergic IPSC and isolates the remaining electrical component selleck chemical (Figure 1C, right). In contrast, a pure electrical response is unaffected by gabazine application (Figure 1C, left). The distribution of synaptic strengths for the electrical and chemical components of dual connections was similar to that of the overall population (Figures 1D and 1E). The overall probability of dual connections was pD = 0.12. These results show that the chemical and electrical networks within the interneuron population of the cerebellar molecular layer can overlap. We next examined how the probability of connections

between individual MLI pairs depends on the intersomatic distance, after confirming that our estimate of connection probability is not affected by the slicing process (Figure S2A). this website Over the distances tested (≤180 μm in the sagittal Δxy plane; ≤50 μm along the transverse Δz axis; Figures S2B and S2C), the probability of an electrical connection pE and chemical connection pC decreased with both increasing Δxy and Δz (Figure 2A). Along the transverse

axis, the electrical coupling appears confined to a remarkably narrow plane, with Δz ≤30 μm (Figure 2B), whereas the chemical connection is less strongly confined. These results can be explained by the somatodendritic morphology of MLIs: their dendrites are planar and follow the sagittal plane, similarly to Purkinje cell dendrites (Palay and Chan-Palay, 1974, Rakic, 1972 and Sultan and Bower, 1998), whereas their axons have a broader spatial distribution. To quantify the difference between the spatial extent of axons and dendrites, we reconstructed MLIs individually filled with biocytin and imaged their structure using high-resolution confocal microscopy GPX6 (Figure 2C). Their morphologies were centered and realigned with respect to the sagittal plane and pial surface (Supplemental Experimental Procedures; Figure 2D; n = 12 cells) and used to generate a density map in the xy and yz planes. The width of the normalized density map of dendrites and axons along the z axis was estimated as 2σ (dendrite) = 24.1 μm and 2σ (axon) = 41.3 μm, respectively (Figure 2D, right). Thus, dendrites are more segregated to the sagittal plane than axons, which, given the dendritic location of electrical synapses between MLIs (Sotelo and Llinás, 1972), explains the tighter spatial confinement of electrical coupling.

The notion is that in area CA3, synapses forming the recurrent co

The notion is that in area CA3, synapses forming the recurrent connection from other area CA3 pyramidal cells, and the perforant path input from the entorhinal cortex have their effective strengths reduced, but are rendered more labile. The ability (M) of neuromodulators to control the course of activity by regulating which of a number of gross pathways determines the activity of neurons is a common scheme. There are also other potential neuromodulatory routes for this influence: for instance, ACh helps regulate oscillations ([N], a critical dynamical effect of neuromodulators in many circumstances)

that simultaneously affect multiple sub-regions of the hippocampal formation (Buzsáki, 2002). It has been suggested that different pathways between these regions are Alectinib purchase dominant at different BMN 673 order phases of theta (Hasselmo et al., 2002),

providing a route for neuromodulatory effects. ACh is also capable of influencing shorter-term storage in working memory (Klink and Alonso, 1997; Hasselmo, 2006). The (O) effects of neuromodulators on various timescales of plasticity are among their most influential. Another obvious issue for memory is whether or not an input actually merits long term storage. One way to assess this is to consider its affective consequences, bearing in mind that they may only be evident after some time has passed. Given the evidence adduced above, it should come as no surprise to find that dopamine is implicated in the later phases of hippocampal storage (Lisman et al., 2011), although this is a rather different function from the plasticity engendered by dopaminergically coded prediction errors that we discussed above as underpinning the learning of appetitive predictions. The extended timescale over which such assessments might be relevant could result in findings such as that patterns that are only incidentally correlated with the delivery of unexpected and reward are also preferentially stored (Wittmann et al., 2005). Boosted storage can perhaps be seen as

an instance of internal, cognitive, “approach” to a stimulus based on the reward it predicts (Adcock et al., 2006), matching the internal action of storage in working memory to the externally directed engagement actions that we mentioned above. An informationally more complex case for neuromodulatory influences on plasticity comes in the context of animal conditioning experiments (Gallistel and Gibbon, 2000; Pearce and Hall, 1980), which have particularly centered on the model-free Pavlovian case. Psychological notions, such as that the associability of a stimulus varies with the degree of surprise with which it is endowed (Pearce and Hall, 1980), can be translated into computational terms as the relative learning rate of a stimulus being determined by its predictive uncertainty (Dayan et al.

4 in South African infants and 51 5 in Malawian infants) Althoug

4 in South African infants and 51.5 in Malawian infants). Although neither study was powered to compare the two dosing regimes,

further results indicated that a threedose schedule of Rotarix may have an advantage in providing long-term protection against severe RV gastroenteritis and severe all-cause gastroenteritis. It is interesting to note that in Malawi, only 17/126 (13.5%) children selleck chemicals had >20 U of RV IgA at baseline which is much lower than reported here. This study had several limitations, including the small sample size, and the lack of collection of serum samples between doses. It is possible that the timing of collection of serum samples may have coincided with waning of the antibody response to the vaccine following multiple doses, with an earlier peak response after the first or the second dose. Nonetheless, although baseline seropositivity made no difference to the rates of seroconversion, the increase in antibody levels was much greater in baseline seropositive

infants in both arms. Those with prior natural infection had a much higher initial antibody level at baseline than was induced by vaccination in unexposed children. Additionally, baseline seropositive children showed much greater absolute increases than those without prior natural infection, which could possibly be explained by higher and more robust responses being Adriamycin concentration induced by natural infection than vaccination or by as yet undiscovered biological differences between responders and non-responders. Given that high baseline seropositivity rates indicate ongoing exposure, measuring serum RV-IgA levels after a full course of vaccination may be uninformative. Studies with more frequent sampling might result in a

better understanding of the immune response to oral rotavirus vaccines, also but these studies are difficult to do because of the young age of children receiving vaccine and the need for frequent blood sampling. Overall, it is a significant concern that the seroresponses with Rotarix are much lower than reported in a previous bridging study in India [29], but the bridging study administered the vaccine at older ages (e.g., eight and 12 weeks) and without concomitant administration of OPV which has been shown to interfere with the rotavirus vaccine response. Based on the studies conducted mainly in Latin America, it appeared that rotavirus vaccines did not affect immune responses to OPV, but IgA antibody levels following rotavirus vaccination were lower when rotavirus vaccines were co-administered with OPV. Data suggested that the interference was greater after the first dose of OPV, and was overcome with subsequent rotavirus vaccine doses [29]. However, it is possible that in developing country settings, the interference may be greater than has been recognized so far, underscoring the need for further studies to understand the immune response to rotavirus vaccines and the functional consequences of response and non-response.

We used the parameter estimates generated by the individual RSFs

We used the parameter estimates generated by the individual RSFs to evaluate the relationship between supplementary feeding site selection

(i.e., the response variable), selection for landscape variables, as well as bear-year specific data (i.e., bear ID, year, and reproductive status) with linear mixed-effect regression models ( Dingemanse & Dochtermann 2013). We included ‘bear ID’ as a random factor. We used akaike information criteria differences (ΔAICc) and weights (AICcw) to select the most parsimonious model among seven candidates defined a priori ( Table 1). We considered models with ΔAICc values >4 as inconclusive ( Burnham, Anderson, & Huyvaert 2011). We validated the most parsimonious models by plotting the model residuals versus the fitted values to evaluate potential heteroskedasticity selleck compound ( Zuur, Ieno, Walker, Saveliev, & Smith 2009). We used R 2.15.0 for all statistical analyses ( R Development Core Team 2013). We obtained relocation data and behavioral estimates from 24 and 33 bears in Sweden and Slovenia, respectively (Table 2). We removed behavioral responses to roads from the Slovenian dataset in the second step, because of collinearity with settlements

(r = −0.67) ( Table 1). The most parsimonious model was the ‘null’ model for both Sweden and Slovenia (AICcw = 1). Individual bear variance explained 33% and 43% of the total variance in supplementary feeding site selection in Sweden (1.59/4.91 × 10−8) and Slovenia (1.96/4.75 × 10−7), respectively. All other candidate models were inconclusive (ΔAICc values >54.4, selleck chemical Table 1). Bears in Slovenia generally selected for supplementary feeding sites (β = 0.589 × 10−3; 95% bootstrapped

confidence limits 0.484 – 0.896 × 10−3); whereas Parvulin Swedish bears generally did not select for or against supplementary feeding sites (μ = 0.045 × 10−3; −0.013 − 0.105 × 10−3). No heteroskedasticity was apparent in the model residuals. We found that individual behavior best explained the strength and direction of selection for supplementary feeding sites (hypothesis 3), and suggest that variation in individual behavior dilutes population-wide patterns related to supplementary feeding site selection. Selection for supplementary feeding sites was not related to reproductive state, year, and selection for human facilities in both Sweden and Slovenia (Fig. 2.). This indicates that diversionary feeding has only low conflict-mitigation potential (hypothesis 1), and that supplementary feeding generally is unlikely to cause nuisance behavior (hypothesis 1) in brown bears. Our results are consistent in both countries, although bears in Slovenia generally selected for supplementary feeding sites whereas Swedish bears did not. Supplementary feeding is common in wildlife management and conservation, and has received considerable attention in the literature (Putman and Staines, 2004 and Robb et al., 2008).

, 2009, Walther et al , 2009 and MacEvoy and Epstein, 2011), but

, 2009, Walther et al., 2009 and MacEvoy and Epstein, 2011), but they are still far smaller than the likely representational capacity of the human visual system. Theoreticians have argued that the simple statistical properties of natural scenes explain selectivity to low-level features in peripheral sensory areas (Olshausen and Field, 1996 and Smith and Lewicki, 2006). Behavioral data suggest that low-level natural scene statistics also influence the perception of scene categories (Oliva and Torralba, 2001 and Torralba and Oliva, 2003). Though several qualitative theories have

been proposed that link the object statistics of natural scenes with human scene perception (Biederman, 1981 and Palmer, 1975), none have provided an objective, quantitative framework to support this link. The current study provides such a framework. Our data-driven, model-based approach shows that scene categories encoded in the human brain can be derived check details from the co-occurrence statistics of objects in natural scenes.

This further suggests that the brain exploits natural scene statistics at multiple levels of abstraction. If this is true, then natural scene statistics might be used as a principled means Smad inhibitor to develop quantitative models of representation throughout the visual hierarchy. The work reported here could be extended in several ways. For example, although the spatial distribution of objects within a scene appears to influence the representation of the scene (Biederman et al., 1982, Green and Hummel, 2006 and Kim and Biederman, 2011), the modeling framework used here isothipendyl makes no assumptions about the spatial distribution of objects within scenes. More sophisticated models that incorporate spatial statistics or other mediating factors such as attention may provide further

information about the representation of scenes and scene categories in the human brain. The experimental protocol used was approved by the UC Berkeley Committee for the Protection of Human Subjects. All fMRI data were collected at the UC Berkeley Brain Imaging Center using a 3 Tesla Siemens Tim Trio MR scanner (Siemens, Germany). For subjects S1, S3, and S4, a gradient-echo echo planar imaging sequence, combined with a custom fat saturation RF pulse, was used for functional data collection. Twenty-five axial slices covered occipital, occipitoparietal, and occipitotemporal cortex. Each slice had a 234 × 234 mm2 field of view, 2.60 mm slice thickness, and 0.39 mm slice gap (matrix size = 104 × 104; TR = 2,009.9 ms; TE = 35 ms; flip angle = 74°; voxel size = 2.25 × 2.25 × 2.99 mm3). For subject S2 only, a gradient-echo echo planar imaging sequence, combined with a custom water-specific excitation (fat-shunting) RF pulse was used for functional data collection. In this case, 31 axial slices covered the entire brain, and each slice had a 224 × 224 mm2 field of view, 3.50 mm slice thickness, and 0.

On the other hand, an increasing number of studies indicate that

On the other hand, an increasing number of studies indicate that the physio-pathological role of tumor-derived exosomes might be more in favor of immune suppression and tumor promotion. One of the earliest evidence that tumor exosomes might contribute in blunting cancer-specific T cells, at least in defined phases of their activation state, derives from studies focused on the expression by these organelles of a bioactive membrane-bound form of FasL. Apoptosis

via Fas/FasL interaction represents indeed one of the major pathways controlling T cell homeostasis click here through the selective elimination of over-reactive Fas-expressing T cells [38], [39], [40] and [41]. Several years ago, tumor cells, particularly from melanoma and colorectal carcinoma, were found to express FasL and to exploit this expression as a novel pathway of immune escape [42] and [43]. In 2002, as one of the groups investigating this phenomenon, we found that FasL was expressed in melanoma cells mostly at intracellular level and with an endosome-associated pattern, and small organelles Selleckchem BTK inhibitor resembling melanosomes, initially quoted as microvesicles, expressed bioactive FasL as well. Characterization

studies then revealed that melanoma cell supernatant contained vesicular organelles sharing with exosomes the size (50–100 nm), the expression of specific markers such as CD63 and the presence of melanosomal proteins like gp100 and MART-1 [17]. In the following years many tumor cell lines of different histologies, including pancreatic [44], oral cancer [19], head and neck cancer [45] melanoma [46], colorectal carcinoma

[18] and gastric cancer [47], have been shown to share the ability to release pro-apoptotic exosomes, carrying not only FasL but also TRAIL on their surface. Altogether these data depicted a common scenario represented by the ability of tumor-released vesicles to eliminate activated T cells by a simple ligand–receptor interaction. Noteworthy, this could also be shown with exosomes isolated from biological fluids, such as plasma, serum and ascites [18], [48] and [49], ascribing this mechanism a potential relevance in cancer patients. This finding paved the way to a series of studies aimed at investigating first the possibility that tumor exosomes, thanks to their ability of recirculating at systemic level, could exert additional deleterious effects on the immune effector cell compartment [17], [18] and [50]. The presence of FasL on tumor exosomes was also reported to mediate the down-modulation of CD3-ζ chain expression and subsequent TCR signaling impairment in patients with ovarian carcinoma [51]. Other mechanisms concerning tumor exosome-induced T cell apoptosis have been recently described for Epstein–Barr Virus (EBV)-infected nasopharyngeal carcinoma (NPC), whose exosomes eliminate EBV-specific CD4+ lymphocytes through the binding of galectin-9 to the cognate membrane receptor Tim-3, suggesting a role in the suppression of Th1 cells at both the tumor and systemic levels [52].

Finally, we discuss neuropeptide signaling systems that act upstr

Finally, we discuss neuropeptide signaling systems that act upstream of GABAARs and exert their neural

effects in part through altered GABAAR trafficking. GABAARs are members of the superfamily of heteropentameric ligand-gated ion channels that also include the nicotinic acetylcholine receptors, glycine receptors, and 5-HT3 receptors (Figure 1A) (reviewed in Unwin, 1989 and Barnard et al., 1998). The subunits of all these receptors share a common ancestral structure that includes an extracellular N-terminal domain, four transmembrane domains (TM1-4), and an extended cytoplasmic loop region between TM3 Selleckchem Compound C and TM4 that mediates interactions with trafficking and signaling factors (Figures 1B and 1C). GABAAR subunits are encoded by 19 different genes that have been grouped into eight subclasses based on sequence homology (α1-6, β1-3, γ1-3, δ, ɛ, θ, π, ρ1-3). Alternative splicing contributes to additional receptor

Talazoparib in vitro diversity. In particular, the γ2 (Whiting et al., 1990) and β2 subunits (McKinley et al., 1995) exist as short and long splice variants distinguished by the presence or absence of eight and 38 amino acids, respectively. Different subunit combinations give rise to a large number of structurally and functionally distinct GABAAR subtypes. Based on a recent conservative count, 11 structurally and functionally distinct receptor subtypes have been conclusively identified and are reasonably abundant in at least parts PDK4 of the brain. They represent combinations of 2α and 2β subunits together with a single γ2 or δ subunit. An additional 15 receptor subtypes exist with high probability and a more limited distribution (Olsen and Sieghart, 2008).

These numbers do not account for additional heterogeneity based on two different types of α or β subunits in one receptor complex (Khan et al., 1996 and Benke et al., 2004), or due to alternative splicing of subunits. GABAARs with different subunit compositions exhibit different pharmacology and channel gating properties, are differentially expressed during development and in the adult brain, accumulate at different neuronal cell surfaces, and are subject to differential regulation by extracellular cues. The subsets of GABAARs at synapses are composed of two α1, α2, or α3 subunits together with two β2 or β3 subunits and a single γ2 subunit. Compared to other GABAAR subtypes discussed below, these receptors exhibit low affinity for GABA and thus are optimized to respond selectively to relatively high concentrations of GABA released into the synaptic cleft (300 μM, Perrais and Ropert, 1999). The γ2 subunit is essential for postsynaptic clustering of GABAARs (Essrich et al., 1998). However, the γ3 subunit can substitute for the γ2 subunit and contribute to postsynaptic GABAARs in the developing postnatal brain (Baer et al., 1999).

We chose to perform these experiments at P28 because synaptogenes

We chose to perform these experiments at P28 because synaptogenesis is mostly complete at this time, and synapse loss in CSPα KOs is not yet pronounced (Chandra et al., 2005 and Fernández-Chacón et al., 2004). This time point, therefore, avoids nonspecific changes in synaptic proteins that occur once more synapses are lost in CSPα KO mice. Wild-type and VE822 CSPα KO brains were homogenized to prepare synaptosomes and further fractionated to obtain purified synaptic plasma membranes, cytosol, and synaptic

vesicles (Figure 1A). This fractionation procedure allowed us to increase our signal-to-noise ratio and delve deeper into the synaptic proteome. The synaptic plasma membrane, cytosol, and vesicle fractions of the two genotypes were subjected to DIGE and iTRAQ in a pairwise fashion. We carried out multiple, independent DIGE and iTRAQ experiments, and analyzed over 1,500 synaptic proteins in the three fractions (Table 1). By analyzing these ∼1,500 proteins, we sampled nearly the entire synaptic proteome. All protein changes CP-690550 ic50 over 40% were scored and identified by mass spectrometry. Figure 1B shows a DIGE experiment on the synaptic plasma membrane fraction of wild-type and CSPα KO brains. The gels revealed only a few protein changes between the two genotypes, supporting our hypothesis that deletion of CSPα leads initially only to the loss of its clients. Similar to the

DIGE runs, the iTRAQ experiments also showed select changes in protein levels (Figure 1C; see Figure S1 available online). The most prominent changes were, as expected,

for CSPα and for the t-SNARE SNAP-25 (Figures 1B, 1C, S1A, and S1C), the previously characterized CSPα client (Chandra et al., 2005 and Sharma et al., 2011), validating this approach to identify other CSPα clients. We considered a synaptic protein 3-mercaptopyruvate sulfurtransferase to be a potential CSPα client if its levels were changed significantly in CSPα KO samples in at least two independent proteomic experiments. Based on these stringent criteria, we identified a total of 37 proteins (Table 1). This set of candidate client proteins has striking features: (1) Most of the identified proteins are presynaptic, as opposed to postsynaptic, as would be expected for CSPα clients. The 27 proteins we identified in our proteomic screen, besides the 10 chaperones, are potential CSPα clients (Table 1). These include exocytic proteins that are components of the SNARE machinery (SNAP-25, complexin I, NSF) and endocytic proteins that regulate vesicle fission (dynamin 1, Necap 1). Cytoskeletal proteins include regulators of the actin and microtubule cytoskeleton (Crmp2, Crmp3, and BASP1) and GTP binding cytoskeletal proteins (Septin 3, 5, 6, and 7). Many of these proteins are represented in Gene Ontology shortest pathway networks emanating from CSPα that are linked by a maximum of three interactions (Figure 1D), adding further credence that they may indeed be direct CSPα clients.

, 1982 and Jones-Villeneuve et al , 1983) For example, cell aggr

, 1982 and Jones-Villeneuve et al., 1983). For example, cell aggregation together with retinoic acid (RA) treatment drives the differentiation of P19 cells toward a neural fate, even as early as 4 hr postinduction (Berg and McBurney, 1990 and Staines et al., 1996). We treated aggregated P19

cells with RA together with the SHH small-molecule agonist SHHAg1.2, a combination that can initiate MN development in cultured embryonic stem (ES) cells (Wichterle et al., 2002). We found that RA/SHHAg1.2 also induced the MN marker HB9 in aggregated P19 cells (Figures 6A and 6B). Furthermore, this treatment induced expression Protein Tyrosine Kinase inhibitor of proteoglycan NG2, which marks OLPs (Figures 6E and 6F). To study the influence of OLIG2 on neural differentiation of P19 cells, we constructed two stable P19 lines that constitutively expressed V5-tagged OLIG2WT or OLIG2S147A. Without RA/SHHAg1.2 induction, both cell lines grew and behaved like the parent P19 line. With RA/SHHAg1.2 induction, the P19-OLIG2WT line produced significantly increased numbers of HB9-positive EPZ-6438 cost cells (p < 0.001) and NG2-positive cells (p < 0.05) compared to induced P19 control cells (Figures 6C and 6G). This is in keeping with previous reports that constitutive expression of OLIG2WT can enhance the output of MNs and OL lineage cells from ES cells (Du et al., 2006 and Shin et al., 2007). Under

inducing conditions P19-OLIG2S147A cultures developed a decreased number of HB9-positive cells (p < 0.05) compared with control P19 cells (Figure 6D), demonstrating a dominant-negative effect of the S147A mutant protein over endogenous, wild-type OLIG2 (which is also present in the P19 lines). Strikingly, P19-OLIG2S147A cells induced with RA/SHHAg1.2 generated many more NG2-positive cells compared to induced P19-OLIG2WT (p < 0.001)

or parental P19 (p < 0.001) lines (Figures 6F–6J). The induced NG2-positive cells also expressed SOX10 isothipendyl (Figure 6I) and MBP (Figure S5). These data provide strong confirmation that loss of OLIG2-S147 phosphorylation directs NSCs away from an MN fate toward the OL lineage. We have shown that phosphorylation of OLIG2 on S147 is required for the early functions of OLIG2 in neuroepithelial patterning and MN specification but is subsequently dispensable for OLP specification. We have also shown that S147 is phosphorylated during MN specification in the ventral spinal cord, dephosphorylated at the onset of OLP production, and that that dephosphorylation switches the binding preference of OLIG2 away from OLIG1/2 toward NGN2. We believe that this represents a key part of the regulatory mechanism that operates through OLIG2 to switch NSC fate from MNs to OLPs during ventral spinal cord development. Other phosphorylation events might also be important for the functional regulation of OLIG2, e.g., it was recently shown that casein kinase 2 (CK2)-mediated phosphorylation is required for the oligodendrogenic activity of OLIG2 (Huillard et al., 2010).

p ) 1 hr later To assure

p.) 1 hr later. To assure see more similarity of SE intensity, we quantified behavioral and EEG seizures after infusion of KA and for 1 hr intervals after treatment with diazepam and lorazepam in both vehicle- and 1NMPP1-treated TrkBF616A mice ( Figures S3 and S4). The EEG recording electrode was placed in the left hippocampus so as not to confound histological

analyses of the hippocampus ipsilateral to the infused (right) amygdala; the extensive commissural connections between the hippocampi notwithstanding, it is possible that electrographic seizure activity localized to the right hippocampus occurred and escaped detection. Unless specified otherwise, after SE, animals underwent continuous video-EEG monitoring 24 hr/day, 7 days/week during weeks 1–2 and weeks 5–6 post-SE. Spontaneous recurrent seizures (SRSs) were identified by review of video-EEG files by two independent trained readers blinded to both genotype and treatment of mice. Behavioral seizures were classified according

to a modification of the Racine scale for mice (Borges et al., 2003). All EEG SRSs were confirmed by corresponding behavioral seizures documented by time-locked video review. Quantitative analysis of EEG energy content was performed as Birinapant cost described in Lehmkuhle et al. (2009) (Figures S3 and S4). In experiments examining effects of 1NMPP1 treatment on SE-induced spontaneous recurrent seizures, the first dose of 1NMPP1 (16.6 μg/g, i.p.) was injected immediately after giving diazepam and a second dose of 1NMPP1 (16.6 ng/g) immediately after administration

of lorazepam (Figure S1B). A third dose of 1NMPP1 (16.6 μg/g, i.p.) was injected approximately 12 hr post-SE, after which 1NMPP1 was administered daily (16.6 μg/g, i.p.) and also included in drinking water (25 μM) for the ensuing 2 weeks, at which point it was tapered and discontinued. WT mice and TrkBF616A mice injected under the same regimen with vehicle (i.p. and in drinking either water) served as controls. Animals were euthanized and decapitated. Crude membranes were prepared from hippocampi and subjected to SDS-PAGE. After transfer, western blotting was conducted as described in the Supplemental Experimental Procedures. After EEG and behavioral monitoring, KA-infused mice were examined for spontaneous activity in the open field and anxiety-like behavior in the light/dark box at 8 weeks post-SE as described in the Supplemental Experimental Procedures. PBS-infused (amygdala) WT or TrkBF616A mice treated with vehicle or 1NMPP1 were tested at 8 weeks postinfusion and served as controls. At 10 weeks post-SE, mice were anesthetized and perfused with heparinized PBS followed by 4% paraformaldehyde and brains prepared for immunofluorescent study of neurons and astrocytes as described by Mouri et al. (2008).