The involvement of rTPJ, dmPFC, and STS/MTG in updating estimates

The involvement of rTPJ, dmPFC, and STS/MTG in updating estimates about others’ expertise through simulating their own prediction accords with previous demonstrations that these regions encode prediction errors in situations where subjects simulate either the intentions of a social partner (Behrens et al., 2008) or the likely future behavior of a confederate (Hampton et al., 2008). Recent check details studies have examined the relative contributions of structures in the mentalizing network to aspects of social cognition (e.g., Carter et al., 2012). In our study, we did not find any clear differences between these regions in tracking expertise, although multivariate approaches may prove more

sensitive to any such differences. Activity in yet another pair of brain regions, rdlPFC and lateral precuneus, reflected aPEs when subjects revised expectations at feedback, and in parallel to rPEs identified in striatum. Selleck Tanespimycin Similar regions have been implicated in executive control and, intriguingly, have recently been shown to encode model-based state prediction errors (Gläscher et al., 2010). Moreover, activity in rdlPFC elicited by evidence-based aPEs reflected individual differences in subjects’ relative reliance on evidence-based aPEs, compared to simulation-based aPEs, during learning. Activity in this region therefore

reflects individual differences in the extent to which learning is driven by correct agent performance or subjects’ own beliefs about the best prediction. We found that subjects credited people more than algorithms for correct predictions that they

agreed with rather than with correct predictions that they disagreed with. In fact, subjects gave substantial credit to people for correct predictions they agreed with but hardly gave them any credit for correct predictions they disagreed with, whereas this distinction had little impact on crediting algorithms for correct predictions (see Figure 2D). Furthermore, subjects penalized people less than algorithms for incorrect predictions with which they agreed compared to disagreed. This difference in learning about people and algorithms is striking because the only difference between them in our study was the image to which they were assigned. A key open question concerns PDK4 what factors control the construction of the prior categories that lead to this behavioral difference. We speculate that one source of the difference between people and algorithms may be related to the perceived similarity of the agent to the subject. It is likely that subjects thought of the human agents as more similar to themselves, which may have led them to relate or sympathize more with people than with algorithms as a function of their own beliefs about what constituted a reasonable choice. This differential updating for people and algorithms was reflected in brain regions thought to be important for contingent learning in nonsocial contexts (Tanaka et al.

, 2008a) were then used to screen for the best algorithms The re

, 2008a) were then used to screen for the best algorithms. The resulting algorithms

exceeded the performance of state-of-the-art computer vision models that had been carefully constructed over many years (Pinto et al., 2009b). These very large, instantiated algorithm spaces are now being used to design large-scale neurophysiological recording experiments that aim to winnow out progressively more accurate models of the ventral visual stream. Although great strides have been made in biologically inspired vision algorithms (e.g., Hinton and Salakhutdinov, 2006, Lecun et al., 2004, Riesenhuber and Poggio, 1999b, Serre et al., 2007b and Ullman and Bart, 2004), the distance between human and computational algorithm performance remains poorly understood because there is little agreement on what the benchmarks should be. For example, one promising object recognition this website algorithm is competitive with humans under Ribociclib in vivo short presentations (20 ms) and backward-masked conditions, but its performance is still far below unfettered, 200 ms human core recognition performance (Serre et al., 2007a). How can we ask whether an instantiated theory of primate object recognition is correct if

we do not have an agreed-upon definition of what “object recognition” is? Although we have given a loose definition (section 1), a practical definition that can drive progress must operationally boil down to a strategy for generating sets of visual images or movies and defined tasks that can be measured in behavior, Metalloexopeptidase neuronal populations, and bio-inspired algorithms. This

is easier said than done, as such tests must consider psychophysics, neuroscience, and computer vision; even supposed “natural, real-world” object recognition benchmarks do not easily distinguish between “state-of-the-art” computer vision algorithms and the algorithms that neuroscientists consider to be equivalent to a “null” model (e.g., performance of a crude model V1 population; Pinto et al., 2008b). Possible paths forward on the problem of benchmark tasks are outlined elsewhere (Pinto et al., 2009a and Pinto et al., 2008b), and the next steps require extensive psychophysical testing on those tasks to systematically characterize human abilities (e.g., Pinto et al., 2010 and Majaj et al., 2012). At a sociological level, progress has been challenged by the fact that the three most relevant research communities have historically been incentivized to focus on different objectives. Neuroscientists have focused on the problem of explaining the responses of individual neurons (e.g., Brincat and Connor, 2004 and David et al., 2006) or mapping the locations of those neurons in the brain (e.g., Tsao et al., 2003), and using neuronal data to find algorithms that explain human recognition performance has been only a hoped-for, but distant future outcome.

6A–F As shown in Fig 6A, Ficoll gradient 1 077 was used to demo

6A–F. As shown in Fig. 6A, Ficoll gradient 1.077 was used to demonstrate a lower percentage of monocytes (10.2%) compared with the results from Ficoll gradients 1119 and 1077 (17.4%, Fig.

6B). Fig. 6C shows the PBMC profile from the culture plates on the fifth day of culture, which had substantial cell debris and 79% lymphocytes. In contrast, in Fig. 6D, where the lymphocytes were passed again in double Ficoll (1.119 and 1.077), the levels of lymphocytes were higher (91.7%). The percentage of lymphocyte purity using anti-CD4 or anti-CD8 antibodies and the Epacadostat mw sorting using magnetic column demonstrated high levels for CD4 (91.7%, Fig. 6E) and CD8 (92.7%, Fig. 6F) T-cell purification. The immune response against Leishmania sp. is highly dependent on the microbicidal action of macrophages, which, although the host target cells of this protozoan, have full capacity for antigen presentation and establishment of an effective response against the parasite ( Pinelli et al., 1999). This methodology could be employed in immunogenic studies during testing of candidate vaccines against CVL. Thus, the microbicidal ability of antigen-specific CD4 or CD8 T cells co-cultured with Leishmania-infected

macrophages could be investigated in dogs during testing of vaccines or treatment strategies against CVL. Our results indicated that differentiated macrophages after 5 days of culture induced increases in both phagocytic and microbicidal activity (Fig. 1, Fig. 2 and Fig. 3). Moreover, only at this time point was it possible to selleck kinase inhibitor observe multinucleated giant cells and vacuolation of the cytoplasm. These results were encouraging for macrophages at this stage of maturation being satisfactory for application however in in vitro experiments using L. chagasi infection. Furthermore, the differentiation of peripheral blood monocytes into macrophages permits obtaining cells less invasively than puncture through the peritoneal compartment ( Zhang et al., 2008 and Sampaio et al., 2007). From the morphological point of view, the presence of multinucleated giant cells

from cell fusion in cultures of monocytes differentiated into macrophages is reported in humans. However, it is known that a variety of inflammatory conditions can generate these cells (Gerberding and Yoder, 1993). These cells were previously reported in canine macrophages in the 1970s, in the studies of Ho and Babiuk (1979), however, the cell fusion occurred only in cultures after 4 weeks. In addition, they proposed a virtually pure culture, after 10 days of culture, from which macrophages can be maintained for up to 2 months under in vitro conditions. However, it is noteworthy that the longer the duration of culture, the greater the chances of contamination by different microorganisms. Therefore, it would be helpful to standardize these cultures so that experiments could be performed more quickly. In this context, Goto-Koshino et al.

, 2013) Microscopic infarcts (microinfarcts) and hemorrhages (mi

, 2013). Microscopic infarcts (microinfarcts) and hemorrhages (microbleeds) (Figure 5) are independent predictors of cognitive dysfunction, but are commonly associated with

other vascular pathologies, such as leukoaraiosis, lacunar infarcts, large infarcts, and hemorrhage (Smith et al., 2012 and van Norden et al., 2013), as well as CADASIL and AD (Table 1). Microinfarcts are sharply delineated lesions consisting PLX4032 purchase of pallor, necrosis, cavitation, and inflammation (astrocytosis, microgliosis, and macrophage infiltration) (Thal et al., 2012), caused by the small vessel pathology described above (Table 1). Microbleeds are microscopic areas of blood extravasation from leaky arterioles, which are restricted to the perivascular space and do not disrupt the brain parenchyma (De Reuck, 2012). Observed in 17% of demented patients (Cordonnier and van der Flier, 2011), cortical microbleeds are frequently associated with cerebral amyloid angiopathy (CAA), whereas microbleeds in deep regions tend to be associated with white matter disease secondary to vascular risk factors (De Reuck, 2012 and Park et al., 2013a). It is well known that deposits of Aβ in cerebral

blood vessels or CAA are associated with vascular cognitive impairment. Although inherited forms of CAA have been described, CAA is most prevalent selleck chemicals in AD, being present in over 90% of cases (Attems et al., 2011 and Charidimou et al., 2012). CAA is also observed in demented (50%–60%) and nondemented

(20%–40%) elderly people (Attems et al., 2011 and Charidimou et al., 2012). The major risk factor for CAA is advanced age, and cardiovascular risk factors seem to play a lesser role (Charidimou et al., 2012). CAA is a major cause of microbleeds and large hemorrhages, typically located in the cortex (lobar hemorrhages) (Auriel and Greenberg, isothipendyl 2012). The amyloid accumulation occurs in the media and the adventitia of cerebral vessels, leading to degeneration of smooth muscle cells and pericytes (Thal et al., 2012). In extreme cases, the vascular wall develops fibrinoid necrosis and the vessels assume a characteristic double barrel appearance (Thal et al., 2012). Overlap of AD neuropathology (amyloid plaques and neurofibrillary tangles) with cerebrovascular lesions is observed in up to 50% of cases of dementia (Jellinger, 2013). These lesions include atherosclerosis of the circle of Willis and its branches, leukoaraiosis, and lacunar infarcts, microbleeds, microinfarcts, and CAA (Benedictus et al., 2013, Charidimou et al., 2012, Honig et al., 2005, Jellinger, 2013, Richardson et al., 2012, Roher et al., 2004, Toledo et al., 2013 and Yarchoan et al., 2012). Ischemic lesions in regions between arterial territories (watershed infarcts) have also been reported in AD, implicating hypoperfusion and CAA in their mechanisms (Miklossy, 2003 and Suter et al., 2002).

This finding supports the ability of ICMS to selectively target r

This finding supports the ability of ICMS to selectively target restricted ensembles of cortical 3-MA datasheet neurons. The ability to reproducibly evoke distinct complex movements from multiple cortical sites presents an opportunity to perform further investigations of motor circuitry in a widely used model organism. More importantly, it will allow the advantages of genetic engineering in mice to be applied to the problem of motor cortex function and organization, either for optical circuit analysis (Zhang et al., 2007,

Tian et al., 2009 and Chow et al., 2010) or in the search for future treatments for movement disorders, cortical injuries, and paralysis (Hodgson et al., 1999, Dancause, 2006, Murphy and Corbett, 2009, Dawson et al., 2010 and Vargas-Irwin et al., 2010). Animal protocols were approved by the University of British Columbia Animal Care Committee. Channelrhodopsin-2 transgenic mice (Arenkiel et al., 2007) from Jackson Labs (line 18, stock 007612, strain B6.Cg-Tg(Thy1-COP4/EYFP)18Gfng/J) established a breeding colony. Adult mice aged 2–6 months and weighing 20–30 g

were used for these experiments. Isoflurane anesthesia was used during surgery and intrinsic optical signal imaging of somatosensory representations, but was replaced by ketamine/xylazine (100/10 mg/kg, supplemented at 1/10th initial dose as necessary) prior to motor mapping. Craniectomies were performed on transgenic mice used in no acute experiments, but virally transduced mice (see section below for details on injections) were mapped through the intact skull due to concern that multiple cranial surgeries could damage the cortex. Chronic mapping was performed through DAPT research buy a cranial window (Harrison et al., 2009). Light-based mapping methodology has been described in detail (Ayling et al., 2009). Briefly, we used a scanning stage (ASI MS-2000) controlled by custom Igor Pro software (Wavemetrics) to direct a fixed 473 nm laser beam (Crystalaser, focused to 100 μm diameter, 10 ms pulses, 0.5–10 mW total or 63–1,270 mW/mm2) to an array of cortical sites (typically 13 × 13, with 300 μm

spacing between sites). This process was repeated three to five times to obtain a mean value for each pixel of the map. Stimulation was delivered in a semi-random order with identical stimulus intensity for all sites within a map. Movements were detected using laser range finders with mm sensitivity targeted to the forelimb and hindlimb (Keyence LK-081). In order to exclude artifacts (e.g., from breathing or electrical noise), responses were considered to be genuine only if their amplitude exceeded three times the standard deviation of the 500 ms prestimulus period within 100 ms after stimulus onset. Motor maps were generated by plotting the peak amplitude of the mean movement profile corresponding to each cortical site of stimulation. Amplitude was quantified within a 300 ms time window after laser stimulation.

g , Figure 1E) Goldfish (Carassius auratus) were dark-adapted

g., Figure 1E). Goldfish (Carassius auratus) were dark-adapted Vorinostat concentration for 1 hr and killed by decapitation followed immediately by destruction of the brain and spinal cord under Schedule 1 of the UK Animals (Scientific Procedures) Act 1986. Depolarizing bipolar cells were isolated from the retina of goldfish by enzymatic digestion, using methods described by Burrone and Lagnado (1997). The standard Ringer solution contained the following: 110 mM NaCl, 2.5 mM CaCl2, 2.5 mM KCl, 1 mM

MgCl2, 10 mM glucose, and 10 mM HEPES (260 mOsmol l-1, pH 7.3). The solution in the patch pipette to record voltage membrane in current-clamp experiments contained: 110 mM K-gluconate, 4 mM MgCl2, 3 mM Na2ATP, 1 mM Na2GTP, 0.5 mM EGTA, 20 mM HEPES, and 10 mM Na-phosphocreatine (260 mOsmol l-1, pH 7.2). To isolate Ca2+ channel currents, the intracellular solution contained 110 mM Cs-gluconate, 4 mM MgCl2, 3 mM Na2ATP, 1 mM Na2GTP, 10 mM tetraethylammonium chloride, 20 mM HEPES, 0.5 mM EGTA, and 10 mM Na-phosphocreatine (260 mOsmol l-1, pH 7.2). Room temperature solutions were superfused via a fast perfusion system (VC8-S; ALA Scientific). Patch electrodes with 5–7

MΩ tip resistance were pulled from fire-polished borosilicate glass capillary tubes using a micropipette puller (Sutter Instrument). see more The series resistance was typically 8–15 MΩ on rupturing the patch. Holding current in current-clamp configuration was 0 pA. Voltage-clamp and current-clamp recordings were made in synaptic terminals.

In voltage-clamp experiments, the membrane potential was held at −60 mV, and stimuli were delivered by stepping the membrane potential to −10 mV. To construct G/V plots the tail current amplitude measured 0.5 ms after returning to −70 mV was plotted against the preceding voltage step. The voltage dependence of activation was determined from normalized conductance versus voltage curves, which were fitted according to the Boltzmann function: G′=G′max1+exp(V−V1/2k),where G′ is the normalized conductance, V1/2 is the membrane potential at which activation is half-maximal, and k is the slope factor. Signals were recorded using an Axopatch 200A amplifier (Molecular Terminal deoxynucleotidyl transferase Devices), interfaced with an ITC-16 (HEKA) and controlled with Pulse Control 4.3 running under Igor Pro 5 (Wavemetrics). Data were given as the mean ± SEM. We would like to thank all of the members of the Lagnado laboratory for discussions that contributed to this work. We also thank the Wellcome Trust for funding (grant 083220). Experiments were designed by F.E., J.J., J.M.R., and L.L. and performed by F.E., J.J., and J.M.R. Analysis was carried out by F.E., J.J., and L.L. eno2::GCamp3.5 fish were generated and characterized by K.-M.L. The manuscript was written by F.E., J.J., and L.L. “
“Many animals have a diverse repertoire of innate behaviors that can be released by specific sensory stimuli (Tinbergen, 1951).

Brain tissue and neuronal cultures were fixed in 4% PFA, and post

Brain tissue and neuronal cultures were fixed in 4% PFA, and postfixed in ice-cold acetone-methanol (1:1) at –20°C for 10 min. The immunostainings with rabbit anti-Arc and anti-Notch1 antibodies were performed using the TSA fluorescence amplification kit (Perkin Elmer). ImageJ software (NIH) was used to quantify fluorescence intensity of immunostainings with NICD1 (Figure 2A), EGFP

(Figure S3B), and Notch1 (see legend for Figures 3C and 3D). Student’s t test was used to determine p values. Golgi-Cox staining (FD NeuroTechnologies) was performed according to the manufacturer’s instructions. Dendrite and spine lengths/widths were measured using Reconstruct software by the Neural Systems Laboratory ( buy EPZ-6438 Spine length and width data were analyzed using the Kolmogorov-Smirnov selleck chemical statistical test. Transverse hippocampal slices (350 μm) were prepared from Notch1 cKO and control mice, and maintained in artificial cerebrospinal fluid at room temperature. Data were collected using an Axopatch 1D amplifier (Molecular Device); signals were filtered at 2 kHz, digitized at 10 kHz, and analyzed using pCLAMP 8 software (Molecular Device). The authors thank Jason Shepherd, Richard Flannery, Marlin Dehoff, Vera Goh, and Keejung Yoon for technical and intellectual input during the course of this project. We also thank Ted Dawson and Jay Baraban for

critically reading the manuscript. Funding for this work came from the Institute for Cell Engineering

at Johns Hopkins University (N.G.), a NARSAD Young Investigator Award (N.G), the James S. McDonnell Foundation (N.G.), and the National Institute of Mental Health (P.F.W.). “
ent in each arm and number of entries in each arm using the StopWatch Plus software. The social interaction testing was carried out in three sessions using a three-chambered box with openings between the chambers. The Morris water maze Parvulin test was done according to a published protocol (Vorhees and Williams, 2006). Details for all behavioral tests are provided in the Supplemental Information. Neuronal cultures were prepared from the hippocampus of E17.5 embryos and plated on poly-L-lysine-coated 60 mm dishes or 18 mm glass coverslips. Neurons were exposed to pharmacological manipulations after 14 days in vitro (DIV). For Sindbis virus infection, the pSinRep5 vector (Invitrogen) was used to generate viruses expressing either full-length Arc or a nonfunctional form with residues 91–100 deleted (Chowdhury et al., 2006). Synaptosomal fractions were prepared as previously described (Blackstone et al., 1992). Standard western blot protocols were used. Details regarding fractionation, immunoprecipitation, and western blot protocols are provided in the Supplemental Information. Quantitation of individual protein bands was done using ImageJ software. Values were averaged between experiments, and Student’s t test was used to compare samples.

, 1995);

however, as astrocytes are phagocytic cells (al-

, 1995);

however, as astrocytes are phagocytic cells (al-Ali and al-Hussain, 1996), the presence of apoptotic nuclei within astrocytes could be phagocytozed apoptotic neurons. We have observed that majority of prospectively isolated CNS astrocytes (IP-astrocytes) die within 40 hr by apoptosis when cultured without any trophic factors and identified HBEGF and Wnt7a as effective at promoting significant astrocyte survival in vitro. Previous studies have underlined the necessity of EGFR for survival in the cortex; however, the relevant ligand for EGFR has not been identified (Kornblum et al., 1999 and Wagner et al., 2006). Our finding that HBEGF strongly promotes astrocyte survival in vitro, together with Linsitinib datasheet its high level in vascular cells (Daneman et al., 2010), strongly suggests that HBEGF is an excellent candidate for the ligand mediating astrocyte

survival in vivo. Do developing astrocytes compete for a limiting amount of endogenous trophic factor as do developing neurons and oligodendrocytes, which are matched to a limited number of target cells and axons, respectively (Barres et al., 1992)? Indeed, we have observed astrocytic apoptosis during the peak of astrogenesis in vivo. As we found that HBEGF is highly expressed by developing vascular cells, that vascular cells help promote astrocyte survival, and that the majority of the astrocytes HKI-272 nmr we analyzed contacted blood vessels, we hypothesize that a similar matching may occur between astrocytes and blood vessels. Excess, unneeded astrocytes generated where blood vessels are already ensheathed by other astrocytes may undergo elimination by apoptosis. This hypothesis can be tested in future experiments by assessing whether astrocytes fail to survive in adult mice in which blood vessels are eliminated by exposure to hyperoxia (Ndubuizu et al., 2010). It is generally thought that differentiated astrocytes retain a high ability to proliferate.

This hypothesis is based on the existence of highly proliferative glial CNS tumors and as astrocytes in MD-astrocyte cultures are so highly proliferative. However, we show that prospectively purified postnatal astrocytes cultured in HBEGF, a mitogenic signal, display only a modest ability to proliferate, dividing once every 3 days, while MD-astrocytes divide every 1.4 days. Even after astrocytes had reached their plateau numbers in the CNS by about P14 (Skoff and Knapp GPX6 1991), we found that they still retained this modest ability to divide (data not shown). Thus, most cortical astrocytes are not terminally postmitotic, but have a modest ability to divide (Skoff and Knapp, 1991), in keeping with recent findings on the limited proliferation of reactive astrocytes after brain injury (J. Zamanian, L.C.F., and B.A.B., unpublished data). The function of astrocytes has long been an intriguing mystery. As neurons depend on astrocytes for their survival, it has not been possible to get at their functional roles in vivo simply by deleting them.

cerevisiae strain (BY4741), on resistance to a wide variety of ch

cerevisiae strain (BY4741), on resistance to a wide variety of chemical inhibitors, 87 in total, including lipophilic and hydrophilic weak-acids, alcohols, chelating acids, ethers, aldehydes and esters. This was intended to map LGK-974 in vitro the physical and chemical characteristics of compounds to which Z. bailii is resistant. MIC tests were carried out for all compounds and the ratio of MICs between Z. bailii and S. cerevisiae was used as an indicator of extreme resistance. The data are summarised in Table 2 and the full data are recorded in Supplementary Data Table 1. Overall, Z. bailii was consistently far more resistant than S. cerevisiae to weak acids (30 tested), with a mean ratio of 2.98, indicating that the molar inhibitory

see more concentrations of weak acids were 3-fold higher for Z. bailii than S. cerevisiae. These

weak acids are very diverse in structure and properties, ranging from 2,4-dinitrophenol to 3-phenylpropiolic acid and adamantanecarboxylic acid. However, Z. bailii did not show any consistent increase in resistance over S. cerevisiae to aldehydes, alcohols, ketones, ethers or esters. Neither did Z. bailii show resistance to non-permeating ( Conway and Downey, 1950) chelating acids, such as citric acid, succinic acid or EDTA ( Stratford, 1999), which inhibit by absorbing minerals from the growth media. The chemical properties of the weak-acids to which Z. bailii showed extreme resistance were examined further. The aliphatic acid series from acetic acid to nonanoic acid all showed greater resistance by Z. bailii than S. cerevisiae but the overall pattern of resistance did not

change with increasing lipophilicity first ( Fig. 1A). There was an obvious, near logarithmic, fall in the MIC value with increasing chain length for both yeast species, which closely corresponds with the lipid solubility (partition coefficient—clogPoct). However, the ratio of resistance between the yeast species did not change with chain length. Examination of resistance to all other weak-acids in Z. bailii and S. cerevisiae, showed similar results. The data are presented as a scatter-plot in Fig. 1B. Despite the variations in pKa values between the different acids, the overall trend was that more hydrophobic acids with a higher partition coefficient were more toxic, with a lower MIC. However, the linear regression plots of Z. bailii and S. cerevisiae were almost parallel, showing no relative increase in Z. bailii resistance with hydrophobicity, as would be expected if resistance was due to alteration in membrane composition. Similarly, resistance due to altered membrane composition would also be expected to affect hydrophobic alcohols, ketones, esters and ethers in addition to weak acids. The data in Table 2 clearly show this not to be the case. It has been previously shown that resistance to sorbic acid in the spoilage yeast Z. bailii was largely due to small numbers of highly resistant cells within the cell population ( Steels et al., 2000).

The variation in d2– was the only modification that accounted wel

The variation in d2– was the only modification that accounted well for all our observations, including the development of a large steady state

current in the presence of 10 mM glutamate for fast recovering channels (B2P6; compare Figure 2C and Figure 1C). Similarly to our observations for chimeric receptors, the peak current-concentration relation was not changed by variation in the exit rate from AD2 ( Figure 2D). In contrast, reducing CHIR-99021 in vitro bound lifetime on the background of slow recovery (by changing the rates k– and kd–) could not produce the fast recovery of wild-type GluA2 and B2P6. Although slower recovery is possible by slowing dissociation on a fast recovering background, this is accompanied by major shifts and distortions of the concentration

response relation ( Figure 2F). This scenario reproduced well the findings of previous AZD8055 molecular weight reports where mutations at the jaws of the LBDs alter the stability or lifetime of all glutamate bound states ( Robert et al., 2005 and Weston et al., 2006b). However, apparent affinity was altered little in our chimeras, ruling out changes in resting state affinity as the sole explanation for the physiological difference between AMPA and kainate receptors, and between our chimeras. The similar rate of entry to desensitization for AMPA and kainate receptors, and similar peak open probability, rules out significant changes in the transition AR – AD, but variation in the reverse transition (d1–) could conceivably produce different recovery rates – perhaps corresponding to different re-association kinetics of the active LBD dimers. We repeated the simulations, varying the rate of exit from the AD state, again on two backgrounds, slow and fast exit from the AD2 state ( Figure 2G). These simulations failed to give a wide range of recovery rates. Rather, the simulated currents strongly resembled the results of manipulations that stabilize the D1 dimer interface (data not shown). The variation in exit from AD on a background of fast recovery resembled the Cell press effect of the L483Y mutant or allosteric modulators

such as cyclothiazide ( Sun et al., 2002). The same manipulation on a slow background reproduced the effects of stabilizing the GluK2 D1 dimer interface with mutations ( Chaudhry et al., 2009b). More complex covariations of multiple rate constants (or more realistic activation mechanisms) could potentially also recreate our observations. However, the kinetic behavior caused by variation in the lifetime of a deep desensitized state is quite distinct from the effects reported in previously published studies (see above). This distinction drew us to investigate differences between GluA2 and GluK2, located away from previously described sites that could differentially stabilize a glutamate-bound, deep desensitized state.