Strikingly, our approach requires only a single transcription fac

Strikingly, our approach requires only a single transcription factor and generates large FK228 nmr amounts of human iN cells with robust synapse formation capabilities. Moreover, we demonstrate that the resulting iN cells can be used for analysis of human neuronal short-term plasticity, large-scale Ca2+-imaging, or analysis of loss-of-function states mimicking a human genetic disorder. Thus, the approach we describe may

be generally useful not only to explore the cellular phenotype associated with neuropsychiatric disorders, but also for drug screening endeavors and for mechanistic studies. Following our initial observation that the combined expression of Brn2, Ascl1, and MytL1 induces functional neurons from human ESCs (Pang et al., 2011), we examined whether forced expression of a series of single transcription factors in ESCs and iPSCs might initiate iN cell differentiation. SAHA HDAC supplier As in previous studies (Vierbuchen et al., 2010; Pang et al., 2011), we used lentiviral delivery for constitutive expression of rtTA

(Urlinger et al., 2000) and tetracycline-inducible expression of exogenous proteins driven by a tetO promoter. Surprisingly, we found that overexpressing either neurogenin-2 (Ngn2) or NeuroD1 alone rapidly converted ESCs and iPSCs into neuronal cells (Figure 1 and Figure S1, available online). Since this conversion was based on forced expression Sodium butyrate of a lineage-specific transcription factor and appears to be a direct lineage conversion similar

to lineage conversion between somatic cells, we refer to the resulting neurons as iN cells as previously (Vierbuchen et al., 2010; Pang et al., 2011). Because the effects of NeuroD1 and Ngn2 were similar, we decided to focus only on one factor and chose Ngn2. To selectively culture only cells expressing the transcription factor, we coexpressed a puromycin resistance gene with Ngn2 (allowing us to select for cells expressing Ngn2), and we additionally coexpressed EGFP (allowing us to identify lentivirally transduced cells). In the standard protocol (Figure 1A), ESCs or iPSCs were plated on day −2, the cells were infected with lentiviruses on day −1, and Ngn2 expression was induced with doxycyclin on day 0. A 24 hr puromycin selection period was started on day 1, and mouse glia (primarily astrocytes) were added on day 2 to enhance synapse formation (Figure 1B; Vierbuchen et al., 2010). Strikingly, forced Ngn2 expression converted ESCs and iPSCs into neuron-like cells in less than 1 week and produced an apparently mature neuronal morphology in less than 2 weeks (Figures 1C and 1D). This is faster than any currently available method for generating neurons from human ESCs or iPSCs (Table 1).

Furthermore, knockdown of TRIP8b in vivo

resulted in an i

Furthermore, knockdown of TRIP8b in vivo

resulted in an increased immunoreactivity for HCN1 channels in the CA1 soma and proximal dendrites that represents a redistribution of HCN1 to intracellular compartments. Additionally, coexpression of EGFP-HCN1 with TRIP8b siRNA revealed a selective loss of channel fluorescence in SLM. All together, these results indicate that, in addition to being important for HCN1 expression on the plasma membrane, TRIP8b may 3-MA cell line also be important for the targeting of HCN1 to distal dendrites. However, the loss of HCN1 in distal dendrites might not reflect a specific role of TRIP8b in dendritic targeting but may be secondary to the general loss of HCN1 surface expression upon TRIP8b knockdown. Moreover, because the TRIP8b siRNA reduced but did not eliminate TRIP8b protein, it is unclear whether the residual targeting of HCN1 to the distal dendrites results from an effect of residual TRIP8b or represents the action of some other targeting protein that interacts with HCN1. To address these questions, we adopted a third, complementary approach, discussed next. To overcome the limitations of the siRNA approach, we expressed an EGFP-tagged BMN 673 datasheet HCN1 truncation mutant (EGFP-HCN1ΔSNL) that lacks the HCN1 C-terminal SNL tripeptide required for high affinity binding of HCN1 to TRIP8b (Santoro et al., 2004, Santoro et al., 2011 and Lewis

et al., 2009). We observed a dramatic loss of dendritic targeting when we expressed EGFP-HCN1ΔSNL in the background of HCN1 KO mice (Figures 4A and 4B). Unlike wild-type HCN1, the mutant channel was expressed uniformly at high levels throughout CA1, as evident in the relatively constant EGFP-HCN1ΔSNL to DsRed2 fluorescence ratio along the somatodendritic axis. A comparison with the distribution of full-length HCN1 revealed second not only a loss of expression of the mutant channel in the distal dendrites but also an increase in expression in proximal dendrites (Figures 4C and 4D; EGF-HCN1: N = 4 mice, 8 injection sites;

EGFP-HCN1ΔSNL: N = 5 mice, 10 injection sites). As TRIP8b is the major protein that interacts with the HCN C terminus in the brain (Santoro et al., 2004, Santoro et al., 2009 and Zolles et al., 2009), these results strongly implicate TRIP8b as a key element necessary for the efficient targeting of HCN1 channels to distal portions of CA1 pyramidal neuron apical dendrites. Because of the limitations of fluorescence imaging, we used an electrophysiological approach to measure EGFP-HCN1ΔSNL channel levels in the surface membrane in HCN1 KO mice. The resting potential of neurons expressing EGFP-HCN1ΔSNL (−69.2 ± 1.2; n = 13) was identical to that of neurons expressing EGFP-HCN1 (−69.1 ± 1.1 mV; n = 15), and both were ∼14 mV more positive than the resting potential of control neurons from the HCN1 knockout mice expressing EGFP (−82.7 ± 1.5 mV; n = 15; p < 0.

It is usual for muscle (Masala et al , 2003), brain and lung (Hur

It is usual for muscle (Masala et al., 2003), brain and lung (Hurtado et al., 2001) tissue to be recommended for diagnosis, although a number of studies have demonstrated the potential of placental tissue (Owen et al., 1998a, Owen et al., 1998b, Hurtado et al., 2001, Masala et al., 2003 and Pereira-Bueno et al., 2004). In this study, 100% of the placentas

from the 5/35 animals testing positive using nested PCR also tested positive when the histopathological examination was used, owing to the presence of cysts. Various studies agree that fetal and placental tissues are the best to use for the PCR technique. Spalding et al. (2002) tested the PCR technique on samples of human blood and placenta selleck and Masala et al. (2003) on sheep fetuses and placentas, in order to diagnose congenital toxoplasmosis. These authors reported that the placental tissue is an excellent material for congenital toxoplasmosis diagnosis, in contrast to fetal serology,

which may detect maternal antibodies arising from the intake of colostrum, resulting in false positives. In another study, Owen et al. (1998b) also confirmed that a larger number of parasites were found in the placentas. Macroscopic examination enabled the state of conservation of the fetus to be classified and 71.45% of them were judged MK-1775 order to be autolyzed. This figure is close to that reported by Engeland et al. (1998), who examined miscarriages in goats in Norway and reported that 65% of them were autolyzed. However, the autolysis found in most of the animals examined for this study may

be due to the delay in collecting the fetuses and dispatching them to the laboratory, as well as poor conservation. This is one limitation of using a histopathological examination for diagnosis and suggests that this technique should be used as a complementary method for diagnosis of congenital toxoplasmosis. Vertical transmission of T. gondii in sheep is still not fully understood and the PCR technique is highly useful for studies of this nature Casein kinase 1 ( Williams et al., 2005 and Hide et al., 2009). The present study has provided evidence of the involvement of T. gondii in the aborted fetuses and placentas of naturally infected sheep in Brazil. No similar data have been described previously in the national literature. None. This study was financed by the Brazilian National Science Foundation (CNPq), grant number 472459/2008-2. “
“Toxoplasma gondii can cause mortality in several species of marine mammals, including sea otters ( Dubey et al., 2003 and Dubey, 2010). Freshwater runoff has been suggested as a risk factor for T. gondii infection in California sea otters ( Miller et al., 2002). It has been suggested that enough T. gondii oocysts to infect marine life can be excreted by felids on land and subsequently washed in to the sea to infect marine life ( Dabritz et al., 2007). T.

, 2002, Peters et al , 2002, Stucky et al , 1998, Suzuki et al ,

, 2002, Peters et al., 2002, Stucky et al., 1998, Suzuki et al., 2012 and Woo et al., 2012). A major current selleckchem challenge is defining the physiological properties of the neurons that form these two neurochemically distinct circumferential ending types. Therefore, each mouse hair follicle type receives a unique and

invariant combination of physiologically and morphologically distinct sensory neurons subtypes, making each hair follicle a distinctive mechanosensory end organ. However, these units do not function by themselves; they represent a cohort of exquisitely organized clusters containing one centrally located guard hair, about 20 surrounding awl/auchene hairs and about 80 interspersed zigzag hairs (Li et al., 2011) (Figure 3E). These clusters are organized in reiterative and partially overlapping patterns blanketing the mouse skin, highlighting a level

PD0325901 of complexity and sensitivity in hairy skin previously thought to only exist in glabrous skin. Nociceptors are uniquely tuned to stimuli that cause damage or threaten to cause damage and are found in both glabrous and hairy skin. Nociceptive neurons have been historically categorized by their stimulus response properties and more recently by their molecular profiles (Lallemend and Ernfors, 2012). High-threshold mechanoreceptors (HTMRs) are a broad category of mechanonociceptive sensory neurons that are optimally excited by noxious mechanical stimuli. HTMRs include Aδ and C free nerve endings that innervate the epidermis both in glabrous and hairy skin (Figure 1). Aδ-HTMRs, also known as A fiber mechanonociceptors (AM fibers), are

thought to mediate fast mechanical pain and can be further divided into fibers that respond to either noxious heat or cold stimuli. On the other hand, C-HTMRs respond solely to mechanical but not thermal stimuli (Bessou and Perl, 1969 and Cain et al., 2001). Nociceptors can be further categorized into two major neurochemical groups based on because neuropeptide expression. Those that contain neuropeptides, like substance P or CGRP, are referred as peptidergic nociceptors, whereas those that do not express neuropeptides are termed nonpeptidergic nociceptors and most exhibit binding to isolectin-B4 (Perry and Lawson, 1998 and Ribeiro-da-Silva et al., 1989). Their peripheral innervation patterns are segregated into unique patterns, with peptidergic neurons innervating basal regions of epidermis, while nonpeptidergic neurons innervate a more superficial epidermal region (Figures 1A and 1B). Differences in their peripheral distributions would suggest that peptidergic and nonpeptidergic C fibers differ in function. Indeed, pharmacological ablation of a population of nonpeptidergic neurons results in selective loss of sensitivity to noxious mechanical stimuli (Cavanaugh et al., 2009 and Zylka et al., 2005). Likewise, central terminal ablation of peptidergic neurons results in selective deficits in heat nociception (Cavanaugh et al., 2009).

Surprisingly, we observed neurons that encode an axis of motion m

Surprisingly, we observed neurons that encode an axis of motion matching the opposing preferences of DS neurons in the same dLGN region. We see two main possibilities for how this overlap in selectivity arises—either ASLGNs integrate opposing

direction-selective retinal ganglion cell-type inputs to form a new response class or ASLGNs receive direct input from an undiscovered axis-selective retinal ganglion cell type and relay that information. The latter hypothesis is most consistent with the view of the dLGN as a simple relay from retina to cortex. Interestingly, selleck screening library if this pathway exists, it may suggest further specificity of RGC projections based on motion axis preference, for example, if vertical axis cells are found in deeper dLGN. However, while axis-selective retinal ganglion cells have been found in the rabbit’s visual streak, they are nearly absent in the rabbit’s peripheral retina (Oyster, 1968) and have Small molecule library cost not been described previously in the rodent retina, which has no visual streak. Moreover, while the persistent view has been that the dLGN only relays retinal information and does not generate novel feature selectivity, the

current results present overlapping and opposing information channels in a single dLGN region, and thus the potential for direct integration of retinal pathways, for example, as evaluated by our random wiring model. Interestingly, one previous study suggested potential for rare mixing of RGC-type inputs in dLGN to yield intermediate tuning properties of X and Y cells in the cat (Mastronarde, 1992), suggesting that similar mechanisms may be involved in other species and cell types. However, the present results indicate that dLGN may integrate retinal

information to form a novel feature selectivity. Regardless of whether axis selectivity first arises in retina or dLGN, the importance of this pathway may be further pronounced if axis-selective inputs influence orientation selectivity in some neurons in the cortex. Integration of opposing direction preferences Levetiracetam by ASLGNs either could result from selective connectivity between DSRGCs and ASLGNs, for example, favored by developmental mechanisms, or could occur by chance if connections are nonspecific between retina and thalamus, given that incoming axonal arbors of opposing DSRGC types probably overlap spatially within superficial dLGN, as predicted by our results. Future studies are necessary to determine how axis selectivity develops in dLGN. In order to test whether our results are consistent with the generation of ASLGNs by chance integration of DSRGC afferents with opposing direction preferences, we generated a simple model based on random retinogeniculate wiring. In this model, dLGN neurons receive one to three driving retinal inputs (Chen and Regehr, 2000) randomly distributed according to the fraction of DS inputs from the retina.

Given this duplication of object representations along the ventra

Given this duplication of object representations along the ventral and lateral surface, the different response properties discovered for lateral and ventral category-selective

regions in general may also apply to Big-PHC, Small-OTS, and Small-LO. Object-responsive Obeticholic Acid molecular weight cortex anterior to early visual areas was originally thought to be nonretinotopic; however, there are now many well-documented retinotopic maps extending along dorsal and ventral streams (e.g., for reviews, see Wandell et al., 2007 and Silver and Kastner, 2009). Comparing object responses with retinotopic organization in this cortex may prove to be valuable for understanding the consistent spatial arrangement of category-selective regions (e.g., Levy et al., 2001, Malach et al., 2002, Hasson et al., 2002, Hasson et al., 2003 and Sayres and Grill-Spector, 2008), as well as the big/small object regions. Here we discuss how the big and small object responses relate to the retinotopic biases in occipitotemporal cortex. TGF-beta inhibitor The medial ventral surface has peripheral field biases while the lateral temporal surface has central

field biases, which extend directly from early visual areas V1-V4 (Levy et al., 2001, Malach et al., 2002 and Hasson et al., 2003; but see Brewer et al., 2005 and Arcaro et al., 2009, which suggest that there are separate foveal representations in these regions). Face- and scene-selective areas are found in cortex with foveal and peripheral biases, respectively (e.g., Levy et al., 2001 and Hasson et al., 2002). Similarly, given the positions of the big/small object regions relative to the scene/face regions, there is a striking convergence between big and small object information and the eccentricity biases of high-level object areas. For example, Figure 6 illustrates that Big-PHC region is near to peripheral early visual cortex, while the Small-OTS and Small-LO preferences are closer

to foveal early visual cortex, and both organizations are mirrored along the lateral surface. This convergence raises the possibility that big/small preferences may derive the in part from eccentricity biases. In their eccentricity-bias proposal of the organization of object representation, Malach and colleagues proposed a processing-based organization of cortex, positing that areas with foveal or peripheral biases carry out fine-detailed or integrative processing, respectively. On this account, any object will be represented along this cortex based on its processing-resolution needs (e.g., Malach et al., 2002). This account has met with some criticisms, however, as the concept of processing-resolution was not clearly operationalized (see also Tyler et al., 2005). For example, it is not obvious that faces require fine-detail processing and not integrative processing.

If Kr is acting in the control of NB fate as in the Hb/Kr/Pdm/Cas

If Kr is acting in the control of NB fate as in the Hb/Kr/Pdm/Cas cascade, Kr mutant NB clones should simply skip the Kr-dependent VA7l fate, resulting in the loss

of a single progeny neuron. In other words, VA7l-lacking Kr mutant NB clones should not carry any ectopic VA2 neurons, as observed in mutant www.selleckchem.com/products/bmn-673.html GMC clones. In support of this scenario, we confirmed that Kr mutant NB clones contain one lone VA2 adPN through visualizing specific adPN types using a sparse GAL4 driver ( Pfeiffer et al., 2008) ( Figure 4A). This is very different from the chinmo mutant NB clones in which loss of Chinmo-dependent adPNs was accompanied by an equivalent increase in the cell count of the next Chinmo-independent adPN type, leaving the lineage length unchanged VX-770 cell line ( Figure 4B). These observations indicate that Kr governs temporal fate transitions in the NB, whereas Chinmo acts in the offspring to refine neuronal temporal identity. We next examined how ectopic Chinmo or Kr might affect adPN development to assess their role as master genes for specifying temporal fate. Such gain-of-function experiments provide clues of their endogenous expression pattern, which is challenging to visualize in real time. In chinmo mutant NB

clones generated in first-instar larvae, expression of transgenic chinmo during neurogenesis effectively restored all the missing glomerular targets ( Figures S3C and S3D). Analogous induction also fully rescued chinmo mutant GMC clones ( Figure S3B). No gain-of-function

phenotype was observed, as ectopic Chinmo failed to elicit any late-to-early Adenylyl cyclase temporal fate changes in wild-type clones, even among those that normally acquire the D fate, the default fate for all the neurons born within the second Chinmo-required window ( Figures S3E and S3F). Use of various chinmo transgenes, including those expressed uniformly due to lack of the endogenous 5′ UTR, yielded identical outcomes ( Zhu et al., 2006). These results suggest that Chinmo promotes neuron diversity through collaborating with other temporal factors governed by NB temporal identity. By contrast, a transient induction of transgenic Kr severely perturbed adPN development. Single-cell clones, as well as the drastically reduced NB clones, no longer targeted dendrites to specific glomeruli; and their axons barely reached the LH (data not shown). Such rudimentary morphologies prevented any meaningful assessment of neuron types or temporal identity. To determine whether ectopic Kr can specify additional VA7l adPNs may require more sophisticated control over when, where, and at what level the Kr transgene should be induced.

Here, we explored the latter issue by recording the responses of

Here, we explored the latter issue by recording the responses of dlPFC neurons of two macaque monkeys during a task that yielded measurable changes in the animals’ behavioral performance at

filtering out a target from a distracter. The experimental design was based on the previous observation that when comparing the ranks of two stimuli within an ordinal scale (e.g., numbers or quantities), humans and monkeys respond faster and more accurately the greater the interstimulus ordinal distance (distance effect; Buckley and Gillman, 1974, Dehaene et al., 1998, Jou and Aldridge, 1999, Moyer and Landauer, 1967 and Nieder et al., 2002). We hypothesized that when monkeys select and sustain attention on a target stimulus that differs

in ordinal rank from a nearby distracter, changes in the animals’ ability to do so would be accompanied by corresponding changes in the cancer metabolism inhibitor activity of dlPFC neurons. We found that animals better detected changes in the target as the ordinal distance to the distracter increased (distance effect). More importantly, neurons in the dlPFC better filtered out the target from the distracter through their response rate as ordinal distance between the two stimuli increased. The latter effect was due to a gradual suppression of responses to distracters as a selleck kinase inhibitor function of ordinal distance to the target. We trained two adult monkeys (Macaca mulatta, Se and Ra) to hold gaze on a fixation spot at the center of a projection screen, and to attend to one of two moving random dot patterns (RDPs) appearing to the left and right of the spot. The dots in the two RDPs moved in the same direction

but differed in their color ( Figure 1). The attended mafosfamide (target) and ignored (distracter) RDPs were defined according to a color/rank-order selection rule (gray < pink < green < blue < red < turquoise). The animals were rewarded for releasing a button after a change in the target’s direction of motion while ignoring similar changes in the distracter (see Figure 1 inset and Experimental Procedures). Within 3–5 months of training, both animals reached stable performances in the task. First, we tested the hypothesis that they did so by learning, from the pattern of hits and errors, the position of the different colors in the ordinal scale according to our color/rank-order selection rule. As an alternative hypothesis, the animals may have learned, for each color pair, which RDP was the target and which one the distracter. The former hypothesis predicts a distance effect in the pattern of reaction times and proportion of correct button releases (hits). The latter predicts no systematic relationship between reaction time and proportion of hits, and rank/ordinal distance between the colors. In animal Se, we found that the hit rate ((number of hits − number of false alarms)/number of trials) increased (p < 0.

Log10 transformed frequency of each word was used to scale the er

Log10 transformed frequency of each word was used to scale the error derivatives. This level of frequency compression was employed to reduce the training time in this large model (Plaut et al., 1996). The error (difference between the target and the output patterns) was estimated with the cross-entropy method (Hinton, 1989). No error was backpropagated from a unit if the difference between

the output and the target was <0.1 (i.e., zero-error radius parameter was set to 0.1). Momentum was not used in this study. All the units in the hidden and output layers had a trainable bias link, except for the copy and Elman layers. Weights were initialized to random values between −1 and 1 (0.5 for recurrent connections). Weights Ruxolitinib nmr from the bias unit to hidden units were initialized at −1, so as to avoid strong hidden unit activation early in training (Botvinick and Plaut, 2006). A sigmoid activation function was used for each unit with activation ranging from 0 to 1. At the beginning of each trial, activations for all units in the hidden layer (including vATL-output layer) were set to 0.5, and for all units in the insular-motor output layer to zero. This work was supported selleckchem by an

MRC programme grant to M.A.L.R. (G0501632), a Royal Society travel grant to M.A.L.R. and S.S., and a Study Visit grant from the Experimental Psychology Society to T.U. T.U. was supported by an Overseas Research Scholarship (UK) and an Overseas Study Fellowship from the Nakajima Foundation (Japan). “
“Language processing depends not only on cortical regions, but also on the

white matter fiber bundles that connect them (Geschwind, PD184352 (CI-1040) 1965, Wernicke, 1874 and Friederici, 2009). Traditionally the arcuate fasciculus was considered to be the main pathway connecting frontal and temporal language areas (Geschwind, 1965). However, recent studies using diffusion tensor imaging (DTI) have revealed that frontal and temporal language regions are connected by multiple dorsal and ventral tracts. Dorsal tracts include not just the arcuate fasciculus, but also other branches of the superior longitudinal fasciculus (SLF) (Catani et al., 2005, Frey et al., 2008, Glasser and Rilling, 2008, Makris et al., 2005 and Makris and Pandya, 2009). Ventral tracts include the extreme capsule fiber system (ECFS), which connects the frontal operculum to mid-posterior temporal cortex, and the uncinate fasciculus (UF), which connects the orbitofrontal region to anterior temporal cortex (Anwander et al., 2007, Croxson et al., 2005, Frey et al., 2008, Friederici et al., 2006, Makris and Pandya, 2009, Parker et al., 2005 and Saur et al., 2008). Syntax is one important component of language and has been shown in functional imaging studies to depend on both frontal and temporal language regions (Bornkessel et al., 2005, Wilson et al., 2010a and Pallier et al., 2011).

In some experiments, the pipette solution included ∼0 1%–0 3% bio

In some experiments, the pipette solution included ∼0.1%–0.3% biocytin (Sigma). Alexa Fluor 488 or 594 fluorescence or biocytin labeling with immunoperoxidase reaction was used for post hoc verification of the localization of neurons along the proximodistal axis of CA3. Series resistance was <30 MΩ. CA3 neurons had resting membrane potentials between −60 and −76 mV (average: −68.0 ± 0.2 mV, n = 381). CA3PCs were usually kept at −68

to −72 mV, unless otherwise indicated. GSK1349572 molecular weight CA1 PCs were held at ∼−65 mV unless otherwise indicated. A dual galvanometer-based two-photon scanning system (Prairie Technologies) was used to image Alexa Fluor 488-loaded neurons and to uncage glutamate at individual dendritic spines (Losonczy and Magee, 2006, Losonczy et al., 2008 and Makara et al., 2009). Two ultrafast pulsed laser beams (Chameleon Ultra II; Coherent) were used, one at 920 nm for imaging Alexa Fluor 488 and the Fasudil price other at 720 nm to photolyze MNI-caged-L-glutamate (Tocris; 10 mM) that was applied through a puffer pipette with an ∼20- to 30-μm-diameter, downward-tilted aperture above the slice using a pneumatic ejection system (Picospritzer III [Parker Hannifin] or PDES-02TX [NPI]). Laser beam intensity was independently controlled with electro-optical modulators (Model

350-50, Conoptics). Local dendritic spikes were evoked by uncaging of MNI-glutamate at a spatially clustered set of visually identified spines (see also Supplemental Experimental

Procedures) with the highest synchrony our system allows, using 0.2 ms uncaging duration with 0.1 ms intervals between synapses (termed synchronous stimulation), unless otherwise indicated. For clarity, throughout the paper the term “Na+ spike” refers to local Na+ channel-mediated dendritic spikes, whereas the axosomatically generated spike is termed action potential or AP. Dendritic Na+ spikes were usually evoked using 5–20 synapses. NMDAR-mediated nonlinearity was measured in dendritic segments 61–193 μm (basal dendrites) or 152–315 μm (apical dendrites) from the soma. NMDA spikes were generated using 20–40 synapses activated synchronously (0.2 ms out uncaging duration and 0.1 ms intervals between synapses), except in some experiments (Figures 4G and 4H) in which longer intervals (1–5 ms) were used. To avoid variability in kinetic parameters of NMDA spikes due to distance-dependent distortion of voltage responses, we performed pharmacological experiments, spatiotemporal distribution experiments, and paired-pulse experiments exclusively on basal dendrites. For determining input-output function, the expected amplitude was calculated as the arithmetic sum of the physiologically sized unitary gluEPSPs at the given temporal input pattern. Unitary gluEPSPs were measured repeatedly (usually two to five times) interleaved with synchronous stimulations, using 205–420 ms intervals between the individual synapses (see also Supplemental Experimental Procedures).