These studies indicate a segregation of—potentially autonomous—supragranular and infragranular dynamics. Maier et al. (2010) found that supragranular sites had higher broadband gamma power than infragranular CHIR-99021 cell line sites. This pattern was reversed in the alpha and beta

range, with greater power in the infragranular and granular layers. Finally, the spiking activity of neurons in the superficial layers of visual cortex are more coherent with gamma-frequency oscillations in the local field potential, while neurons in deep layers are more coherent with alpha-frequency oscillations (Buffalo et al., 2011). This finding is consistent with an earlier study by Livingstone (1996) showing that 50% of cells in L2/3 of squirrel monkey V1 expressed gamma oscillations, compared to less than 20% of cells

in L4C and infragranular layers. The different spectral behavior of superficial and deep layers has led to the interesting proposal that feedforward and feedback signaling may be mediated by distinct (high and low) frequencies (reviewed in Wang, 2010; see also Buschman and Miller, 2007), a proposal that has recently received experimental support, at least for the feedforward connections (Bosman et al., 2012; see also Gregoriou et al., 2009). Given this functional and anatomical segregation into parallel streams, the question naturally arises, how are these streams integrated? It has been previously suggested that integration occurs through the synchronized firing of multiple neurons that MLN0128 purchase form a neural ensemble (Gray et al., 1989; Singer, 1999), while others have emphasized interareal phase synchronization or coherence (Varela et al., 2001; Fries, 2005; Fujisawa and Buzsáki, 2011). While a full treatment of this

question is beyond the scope of the current Perspective, we propose that the canonical microcircuit contains a clue for how the dialectic between segregation and integration might be resolved. While top-down and bottom-up inputs and outputs may be segregated in layers, streams, and frequency bands, the canonical microcircuit specifies the circuitry for how the basic units of cortex are interconnected and therefore how the intrinsic activity of the cortical column is entrained by extrinsic inputs. This intrinsic connectivity specifies how the cells of origin only and termination of extrinsic projections are interconnected and thus determines how top-down and bottom-up streams are integrated within each cortical column. The notion of a canonical microcircuit implicitly assumes that each circuit is distinct from its neighbors, which could presumably carry out computations in parallel. Therefore, the canonical microcircuit specifies the spatial scale over which processing is integrated. The most likely candidate for this spatial scale is the cortical column, which can vary over three orders of magnitude between minicolumns, columns, and hypercolumns.

, 2005). Mammals contain two Ark family genes, cyclin G-associated kinase (GAK) and adaptor-associated kinase 1 (AAK1), and both have been implicated in vesicular transport (Conner and Schmid, 2002 and Lee et al., 2005). GAK, best known for its role in the disassembly of clathrin coats from clathrin-coated vesicles,

has multiple functions during clathrin cycle (Eisenberg and Greene, 2007). AAK1 has been shown to bind the α subunit of AP2, phosphorylate the cargo-binding μ2 subunit, and promote receptor-mediated transferrin uptake (Conner and Schmid, 2002, Conner et al., 2003 and Ricotta et al., 2002). AAK1 also selleck participates in transferrin receptor recycling from the early/sorting endosome in a kinase activity-dependent manner (Conner et al., 2003 and Ricotta et al., 2002). Numb-associated kinase (Nak), the Drosophila Ark family member, contains the conserved Ark kinase domain and several motifs (DPF, DLL, and NPF) mediating interactions with endocytic proteins ( Conner and Schmid, 2002 and Peng et al., 2009). Here, to study the function of Nak in development, we generated nak deletion mutants and RNAi lines and showed that depletion of nak activity

in da neurons disrupts higher-order dendrite development. This function of Nak in dendritic morphogenesis is likely mediated through CME, as Nak exhibits specific genetic interactions with components of CME, colocalizes with clathrin in dendritic puncta, and is required for the presence of clathrin puncta in distal higher-order dendrites. More importantly, live-imaging

Onalespib purchase analysis shows that the presence of these clathrin/Nak puncta at basal branching sites correlates with extension of terminal branches. In addition, we present evidence that the localization of Neuroglian (Nrg) in higher-order dendrites requires Nak, implying that regional internalization of a cell adhesion molecule is crucial for dendrite morphogenesis. To study nak function in development, we generated two nak deletion mutants using nakDG17205, which carries a p[wHy] transposable element ( Huet et al., 2002) in the first TCL intron of nak ( Figure 1A). The deletion in nak1 extends 1.1 kb toward the 5′ end from the insertion site, removing most of exon 1 of nak. The nak2 allele deletes a 6.2 kb fragment downstream of the insertion site, removing exons 2–7 including the kinase domain. Western analysis of larval extracts with anti-Nak antibodies showed that Nak expression was reduced in nak1 and undetectable in nak2 mutant larvae ( Figure 1B), suggesting that nak1 and nak2 are partial loss-of-function and null alleles, respectively. Adults homozygous for nak1 and nak2 were viable and fertile, indicating that nak is not an essential gene. To understand its role in development, we examined Nak distribution during embryogenesis using immunohistochemistry.

This is when monkeys, based on learning a few S-R associations, could first start to predict the saccade that would Regorafenib mouse lead to reward. Rise time in STR averaged 130.7 ± 12.9 ms (SEM) across trials of the S-R

association phase. This is in contrast to PFC, where average rise time was significantly later, at 822.1 ± 128.2 ms (p < 5 × 10−4, Figure 3B). Likewise, during the early-trial epoch (exemplar display and the first half of the delay), information about the forthcoming saccade was significantly higher in STR (1.90 ± 0.04) than PFC (1.0 ± 0.04, p < 10−4, Figure 3C, left). In contrast, late in the trial (second half of the delay and during saccade execution), saccade information

was stronger in PFC (2.44 ± 0.05) than STR (0.83 ± 0.05, p < 10−4, Figure 3C, right). These results indicate that STR played a more leading role than PFC when performance relied on specific S-R associations. A comparison of correct and error trials during the S-R phase is shown in Figure 4. In both cases, monkeys execute a right or left saccade. If activity reflects a motor signal per se, information should be equal on both. Yet, early-trial information in STR was greatly reduced on error versus correct trials (0.02 ± 0.04, p < 10−4, Figures 4A and 4B). It was lower when correct and error trials were pooled together and classified according to exemplar (1.38 ± 0.04, p <

10−4, Figure 4C), Trichostatin A purchase or saccade (0.70 ± 0.03, p < 10−4, Figure 4D). Fossariinae There was also a decrease in PFC saccade information late in error trials (error trials alone: 0.85 ± 0.04, p < 10−4; correct and error trials by exemplar: 0.70 ± 0.05, p < 10−4; correct and error trials by saccade: 1.68 ± 0.06, p < 10−4). The lower information on error trials indicate that the STR and PFC are not reflecting a saccade motor plan per se (including “guesses”), but rather are involved in learning the correct saccade. The saccadic motor plan might have been generated and maintained elsewhere. During the category acquisition phase, monkeys were confronted with increasingly larger numbers of novel exemplars (Figure 1C) and had to move beyond simple S-R association and associate the right and left saccades with each category rather than individual exemplars. Performance was maintained at a high level and improved, even though with each block an increasing proportion of novel exemplars was introduced (Figure 3A, middle row). During this phase, strong early-trial, saccade-predicting activity in PFC first appeared. This was reflected in the sharp reduction in rise time (Figure 3B) and increase in saccade-direction information in the early-trial PFC activity, relative to S-R association (p < 0.005 for rise time and p < 10−4 for information magnitude, Figure 3C).

A good possibility to explain the collicular KO phenotype is that the flattening

of the overall ephrinA gradient leaves nasal axons (nn- and n-axons) with insufficient targeting (positional) information to find their proper target zone, resulting in the formation of several TZs at various positions in the caudal SC. Finally, we analyzed the targeting behavior of axons from the temporal periphery (tt-axons), which in wild-type mice form TZs at the very rostral pole (Figure 6E). In full agreement with data published by Pfeiffenberger and colleagues (Pfeiffenberger et al., 2006), we observed (somewhat surprisingly) only very small or no targeting defects of tt-axons in either the collicular (Figure 6F; n = 15), the retinal (Figure 6G; n = 16), or the retinal+collicular ephrinA5 KO (Figure 6H; n = 3). However, in all three KO lines, we did occasionally E7080 research buy observe individual axons that extended caudally past the main TZ. Sometimes these overshooting axons even formed coarse arbors (arrows in Figures 6G and 6H), and in some instances we detected very weak eTZs caudal to the main TZ, particularly in the collicular KO (Figure 6B, arrow; 53% penetrance; see Experimental Procedures).

To further substantiate this finding, we investigated the full KO of ephrinA5 (Figure 6D; n = 4) as well as the ephrinA2/ephrinA5 double KO (DKO; data not SCH 900776 in vitro shown, n = 4). Again, we found only very weak targeting defects for tt-axons in the ephrinA5 full KO with a few axons overshooting caudally, but not forming discernible eTZs (arrows in Figure 6D). The phenotype was more pronounced in the ephrinA2/ephrinA5 DKO; the number of aberrantly projecting axons was markedly increased, but still failed to generate strong eTZs (data not shown). As indicated, these astonishing findings are in agreement with data from Pfeiffenberger et al. (2006). Here it was shown that only in the ephrinA2/ephrinA3/ephrinA5 TKO, and not in the ephrinA2/ephrinA5 DKO, axons from the temporal periphery show robust eTZs, which are confined to the rostral SC (Pfeiffenberger et al., 2006). Cell press We show here that ephrinA5 expression on nasal axons is a key component of repellent axon-axon

interactions, which prevents an intermingling of TZs of temporal and nasal axons during topographic mapping within the central SC. Our data provide in vivo evidence for a guidance principle during retinocollicular map development that is based on target-independent axon-axon interactions. EphrinAs and EphAs show complex expression patterns in the retina and the SC during development of the retinocollicular projection, involving expression of ephrinAs preferentially on nasal axons and of EphAs preferentially on temporal axons. We have revisited in vitro experiments from the Bonhoeffer lab performed in the 1980s, which showed that temporal axons are repelled from contacting nasal axons (Bonhoeffer and Huf, 1980 and Bonhoeffer and Huf, 1985).

We verified whether the slightly enhanced SW-evoked PSP amplitudes had caused an increase in SW-evoked spiking, as was previously observed in this model by Diamond et al. (1994) (data not shown). In control mice the PW elicited on average 0.04 ± 0.11 spikes per deflection (n = 33 cells), whereas the SW elicited only 0.02 ± 0.05 (n = 33 cells), which is in the same range as previous findings by Brecht et al. (2003). DWE had not changed PW-evoked spiking (0.05 ± 0.16, n = 26 cells), whereas the SW-evoked spiking rates had tripled (0.07 ± 0.15;

n = 34 cells). When the analysis was restricted to spiking cells only, this increase proved to be significant (p < 0.001). Together, these data demonstrate that DWE subtly changes SW-evoked PSP amplitudes and thereby increases average SW-evoked spiking rates. We next tested whether DWE had increased the susceptibility for STD-LTP. Similar to the control selleck chemicals conditions, the pairing of PW-evoked PSPs with APs readily induced LTP (142% ± 13%, n = 7; p < 0.05; Figures 5A, 5C, and 5D). The average level of LTP was not

significantly different from controls (Figure 5E). Interestingly, the pairing of SW-evoked PSPs with APs now also induced LTP (127% ± 6%, n = 8; p = 0.002; Figures 5B–5D). The average level of SW-driven LTP was significantly higher as compared see more to controls (Figure 5E) and similar to PW-driven LTP (p = 0.305). This could not be explained by a change in postsynaptic excitability (Figures S3A and S3B). The increase in SW-driven STD-LTP was evident in both peak PSP amplitudes and PSP integrals (Figure 5C). The fraction of cells that displayed significant levels of SW-driven LTP had increased (p = 0.014) and now followed a trend that approached the PW-driven LTP scores (p = 0.479; Figure 5F). Both the average Δ delays in the paring protocol and the baseline SW-evoked PSP amplitudes did not differ between controls and DWE animals (Figures S3C and S3D). In general the baseline PSP amplitude was not correlated with the success rate of LTP induction (Figures S3E–S3H), indicating that the increase in SW-driven LTP upon DWE was not due to a relative change in

baseline SW-evoked all excitatory synaptic responses. Similarly, although the variability in the SW-evoked PSP onset delays had become similar to the PW-evoked responses, this was not significantly correlated to the success rate of LTP induction in our data set (Figures S3I–S3K). What could be the mechanism underlying the facilitation of SW-evoked STD-LTP upon DWE? Sensory deprivation has been shown to reduce feedforward inhibition in vitro (Chittajallu and Isaac, 2010; House et al., 2011; Jiao et al., 2006), and a blockade of inhibition was shown to facilitate tetanic stimulation-mediated LTP in the barrel cortex (Glazewski et al., 1998). We hypothesized that DWE might also suppress SW-evoked inhibitory responses and thereby enhance the susceptibility of this synaptic pathway to STD-LTP.

The solution found two protomers with high rotation and translation Z scores Small molecule library cell line for the glutamate P2221 (RFZ1 = 15.5, TFZ1 = 17.4; RFZ2 = 17.4 and TFZ2 = 52.4) and kainate P2221 (RFZ1 = 12.1, TFZ1 = 20.5; RFZ2 = 14.8, TFZ2 = 40.8) complexes. For the second crystal form of the glutamate complex in the P21212 space group, the molecular replacement solution located four

protomers, also with high Z scores (RFZ1 = 13.8, TFZ1 = 17.6; RFZ2 = 18.6 and TFZ2 = 31.4; RFZ3 = 13.0, TFZ3 = 61.8; RFZ4 = 13.0 and TFZ4 = 67.1). The models were initially built using ARP/wARP ( Morris et al., 2003) and then refined by alternate cycles of crystallographic refinement with PHENIX ( Adams et al., 2010) coupled with rebuilding and real-space refinement with Coot ( Emsley and Cowtan, 2004) using TLS groups determined by motion determination analysis ( Painter and Merritt, 2006). The final models ( Table S2) were validated with MolProbity ( Davis et al., ABT-737 datasheet 2004). Figures were prepared using PyMOL (Schrödinger). This work was supported by the Centre National de la Recherche Scientifique, the Fondation pour la Recherche Medicale, the Conseil Régional d’Aquitaine, the Agence Nationale de la Recherche (contract SynapticZinc), and the intramural research program of NICHD, NIH. Synchrotron diffraction

data were collected at SER-CAT beamline 22 ID. Use of the Advanced Photon Source was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. We thank Remi Sterling for cell culture maintenance, and Françoise Coussen, Séverine Desforges, and Carla Glasser for help with molecular biology. Pierre Paoletti provided insightful suggestions along the

course of this study. We are also grateful for members of the C.M. laboratory isothipendyl for helpful discussions. “
“Most information transfer in the CNS depends on fast transmission at chemical synapses, and the mechanisms underlying this process have been extensively examined. In particular, much attention has focused on presynaptic terminals, characterized by their cluster of neurotransmitter-filled vesicles lying close to a specialized release site (Siksou et al., 2011). Although synaptic vesicles appear morphologically similar, they are, in fact, organized into functionally discrete subpools that are key determinants of synaptic performance (Denker and Rizzoli, 2010; Rizzoli and Betz, 2005; Sudhof, 2004). Understanding the specific relationship between these functional pools and their organizational and structural properties is thus a fundamental issue in neuroscience. Specifically, several key questions merit attention.

We also found that L-LTP induced at one spine facilitates tag formation and consequent L-LTP expression at a neighboring spine where only subthreshold stimulation was given subsequent to the original L-LTP stimulation. This may be caused by one or more of the PrPs altering the excitability locally near the stimulated spines (Johnston and Narayanan, 2008 and Williams et al., 2007). The recent demonstration of branch-specific excitability (Losonczy et al., 2008), though not demonstrated to be protein synthesis dependent, supports this hypothesis. A key consequence of STC is thought to

be for binding together, at the single-cell level, of a relatively Y-27632 nmr less prominent or even an incidental event that occurred during a given episode with an important event; less prominent information, encoded initially as E-LTP-like plasticity, will be bound with some important information that would trigger protein synthesis and encoded as L-LTP-like plasticity into one long-term memory episode (Frey, 2001 and Govindarajan et al., 2006) via “conversion” of E-LTP to L-LTP. Indeed, recent studies have reported behavioral data that are consistent with the STC hypothesis (Ballarini et al., 2009 and Moncada and Viola, 2007). Our finding about the temporal asymmetry of STC suggests selleck chemicals that the storage of a piece of less salient information as part of an engram could be affected depending on whether it came before or after the important information. There

is a wider time window for less prominent information that arrives before, rather than after, the salient information to be bound together as part of the engram secondly (Figures 3B and 3C). On the other hand, the information can be even less prominent if it comes after the salient event, rather than before, for it to become bound (Figures 3E–3G). Lastly, our data showing individual branches as the functional unit of long-term memory storage can be used to refine current computational models of STC (Barrett et al., 2009 and Clopath et al., 2008), which have incorporated neither the spatial nor competition component of the CPH. Detailed procedures are given as part of the Supplemental Experimental Procedures. Briefly,

mouse organotypic slice cultures were prepared from P7 to P10 animals (Stoppini et al., 1991), and Dendra (Gurskaya et al., 2006) was sparsely introduced via biolistic gene transfection. For acute slice experiments, 300 μm slices were cut from 6- to 9-week-old Thy1-GFP (line GFP-M) (Feng et al., 2000) and used after 3 hr of incubation in an interface chamber. Slices were used between DIV 8 and 16, and were perfused with room temperature ACSF (32°C for acute slices) consisting of 127 mM NaCl, 25 mM NaHCO3, 25 mM D-glucose, 2.5 mM KCl, 1 mM MgCl2, 2 mM CaCl2, 1.25 mM NaH2PO4, and 0.0005 mM TTX (no TTX in Figure S2). Two-photon imaging and glutamate uncaging were performed using a modified Olympus FV 1000 multiphoton microscope with SIM scanner with two Spectra-Physics Mai Tai HP Ti:sapphire lasers.

Among these, the most intriguing

is the connection between mitochondria and ER. These two organelles are linked, both biochemically and physically (Csordás et al., 2006), via mitochondria-associated ER membranes (ER-MAM, or MAM) (Rusiñol et al., 1994). Located mainly in the perinuclear region of cells (Area-Gomez et al., 2009 and Schon and Area-Gomez, 2010), MAM has been reported to be enriched in more than 75 proteins, including those involved in calcium homeostasis (e.g., MK-2206 molecular weight inositol-1,4,5-triphosphate [IP3] receptors [IP3Rs] and ryanodine receptors), in lipid metabolism (e.g., phosphatidylethenolamine N-methyltransferase), in intermediate metabolism (e.g., glucose-6-phosphatase), in cholesterol metabolism (e.g., acyl-coenzyme A:cholesterol acyltransferase 1 [ACAT1]), in the transfer of lipids between the ER and mitochondria (e.g., fatty acid transfer proteins 1 and 4), and in ER stress (e.g., glucose-regulated proteins 75 and 78) (Hayashi et al., 2009b). Contacts between the two organelles are maintained by MAM-associated proteins, such as phosphofurin acidic cluster sorting protein-2

(Simmen et al., 2005) and mitofusin-2 (MFN2), which is also required CHIR-99021 in vitro for mitochondrial fusion (de Brito and Scorrano, 2008). Interestingly, fission-1 (FIS1), a protein required for mitochondrial fission, has recently also been localized to the MAM (Iwasawa et al., 2011). The relationship between MAM and calcium trafficking (Csordás et al., 2010) is

worthy of some elaboration. As alluded to above, two cargo adaptor proteins discovered initially in Drosophila—Miro and Milton—are implicated in the specific linkage of mitochondria to kinesin-1 in neurons. Miro is anchored to the mitochondrial outer membrane ( Guo et al., 2005), and binds to the mitochondrial-specific adaptor protein Milton, which CYTH4 is linked to the kinesin-1 heavy chain ( Brickley et al., 2005, Glater et al., 2006 and Koutsopoulos et al., 2010). Miro is a calcium-binding protein ( Fransson et al., 2003), and thus has the potential for being a regulator of mitochondrial motility in neurons, in essence operating as a sensor of local [Ca2+] and ATP. It has been proposed that in the Ca2+-unbound state, Miro binds Milton and mitochondria are attached to microtubules, whereas in the Ca2+-bound state, Miro cannot bind Milton and mitochondria are uncoupled from microtubules ( Rice and Gelfand, 2006). This model is consistent with the “saltatory movement” model proposed by Hajnóczky ( Liu and Hajnóczky, 2009 and Yi et al., 2004), in which mitochondria move only when local [Ca2+] is low, and stop when the local [Ca2+] is high. Notably, only Ca2+ mobilized via IP3Rs (or, in muscle, via the related ryanodine receptors) could generate this result. We note, however, that very few of the experiments supporting this model have been conducted in mammalian neurons.

Photoactivatable GFP has been used to follow particular neural input pathways (Datta et al., 2008 and Ruta et al., 2010). In this type of experiment, one group of neurons is labeled with a reporter, and then a dark or photoconvertible fluorescent protein is expressed in neurons that are potentially connected. The area near the first group is illuminated with the wavelength of light see more required to photoactive the protein expressed in the candidate partners. If these candidates are close enough to the light spot, the fluorescent protein gets activated and diffuses throughout these neurons, labeling them enough that they can

be identified by their morphology. This approach may work best in convergent circuits with areas of dense innervations where a large fraction of the GFP can be photoconverted by a very local illumination. This method demonstrates that two groups of neurons are close enough to form synapses but does not demonstrate that they actually do so. Future development of methodology to demonstrate connectivity and explore the weights of particular synaptic connections is warranted. Trans-neuronal tracers based on lectins and neurotrophic viruses have been used to propose connectivity in vertebrate check details systems (Horowitz et al., 1999 and Wickersham et al., 2007), but none have yet been successfully adapted for use in flies. Electron microscopy can

show that synapses exist between two neurons and identification of the neurons in question is possible by completely reconstructing their trajectories Edoxaban or by labeling them with a genetically encoded

enzyme (such as horseradish peroxidase) that produce an electron-dense reaction product. The optogenetic methods for activating neurons and the genetically encoded calcium indicators of neuronal activity can be combined with electrophysiological recordings to test functional connectivity and synaptic strength. One of the biggest hurdles remaining for deciphering neural circuits in Drosophila is demonstrating functional connectivity. Mutations in genes expressed and required in the nervous system can be generated by reverse genetics (see below) or forward genetics. Forward genetic approaches are focused on phenotypic driven identification of mutations in genes involved in a certain biological process (St Johnston, 2002); for example, axon guidance, synaptic transmission, or behavior. Here, we will discuss and compare different strategies and mutagens and the advantages and caveats of various forward screening methodologies. Forward genetic screens based on transposon mutagenesis to identify new loci affecting neuronal features have so far been based on P elements ( St Johnston, 2002) and piggyBac ( Schuldiner et al., 2008). Two main strategies can be envisaged: one based on using existing collections, and one based on creating and screening a novel collection of transposon insertions.

, 2008), and serve as a target protein for autoantibodies in human rheumatoid arthritis (Tanaka et al., 1998 and Tanaka et al., 2003). However, the receptor for FSTL1 in the body was not identified. Additionally, FSTL1 was found to be expressed in the nervous system (De Groot et al., 2000 and Malik-Hall et al., 2003), but the neuronal function of FSTL1 was unknown. In this study, we found high levels of FSTL1 in small DRG neurons. Surprisingly, unlike neuropeptides and brain-derived neurotrophic factor, which are secreted via LDCVs (Salio et al., 2005), we observed that FSTL1 is transported to axon terminals via small translucent vesicles

and secreted in a manner similar to neurotransmitters. We further found that FSTL1 directly activates α1 subunit-containing NKA (α1NKA). NKA, also known as an Na+-K+ pump, transports three Na+ out of cell and two K+ into cell, thereby playing a crucial role in maintaining the Na+ and Erastin concentration K+ gradient across the plasma membrane. This gradient is essential for maintaining the resting membrane potential and excitable properties Kinase Inhibitor Library concentration of neurons (Hamada et al., 2003, Kaplan, 2002, Morth et al., 2007 and Takeuchi et al., 2008). NKA activity is regulated by direct modulators (ATP, Na+, K+, and cardiotonic steroid inhibitors ouabain and digoxin) and indirect modulators (catecholamines, insulin, angiotensin

II, and morphine) through receptor-mediated mechanisms (Therien and Blostein, 2000). NKA is a heterodimer composed of one α subunit and one β subunit. The catalytic, transport, and pharmacological properties of NKA reside in the α subunit, while the β subunit is involved in cell surface delivery and appropriate insertion of the α subunit. Four isoforms of α subunits (α1–α4) and three isoforms of β subunits (β1–β3) are expressed in a tissue- and cell-dependent pattern. It was unknown whether NKA could be regulated by endogenous agonists. The mRNAs for NKA α1, α3, and β1 subunits were found in however the DRG (Fink et al., 1995, Hamada et al., 2003 and Mata et al., 1991). The α1 subunit is expressed in both small- and large-diameter DRG neurons, whereas the

α3 subunit is mainly distributed in large ones (Dobretsov et al., 1999a and Dobretsov et al., 1999b). Electrophysiology showed that the membrane current produced by NKA activity in DRG neurons was primarily mediated by α1NKA (Hamada et al., 2003 and Mata et al., 1991). Reduction in NKA activity in the peripheral nerve was found to be partly responsible for diabetic neuropathy, which presents sensory symptoms such as paresthesias and pain (Krishnan and Kiernan, 2005 and Vague et al., 2004). We identified FSTL1 as an α1NKA agonist that suppresses synaptic transmission and maintains the normal threshold of somatic sensation. This finding revealed an agonist-dependent mechanism for activating the Na+-K+ pump and provided further insight about the pump’s physiological role.