001 (measured at a resting potential of −54 2 ± 0 4 mV; input res

001 (measured at a resting potential of −54.2 ± 0.4 mV; input resistance 32.7 ± 0.6 MΩ, n = 111 pairs). We then activated excitatory synaptic input to the neurons and increased stimulus strength until the evoked excitatory postsynaptic potentials (EPSPs) reliably induced spiking (spiking probability averaged over both cells ≥0.5). For each pair, we recorded the electrical coupling by alternating delivery of negative current pulses to each cell for a baseline period.

This was followed by an induction protocol consisting of 50 synaptic stimuli at 1 Hz, with steady-state depolarizing current such that the neurons fired the characteristic burst of spikes observed in olivary neurons in response to sensory stimulation in vivo (Chorev et al., LY294002 2007 and Khosrovani Dabrafenib et al., 2007). Following the induction protocol, the average coupling coefficient was significantly lower in nine out of ten pairs of connected cells (Figure 1; average reduction of 47% ± 9.9% from an initial

coupling coefficient of 0.012 ± 0.003; p < 1 × 10−5, n = 10 pairs). This depression of coupling was sustained for more than 15 min, with the longest recordings showing plasticity 25 min after induction. Consistent with the reduction in coupling, input resistance was also increased following induction (mean input resistance 38.4 ± 18 MΩ after induction; 21.8% ± 7.5% increase; p < 0.01). Only small changes were seen in resting membrane potential (6% ± 3% hyperpolarization, n = 20 cells, p = 0.067) and sag ratio (decrease by 13.9% ± 4.5%, n = 20 cells, p = 0.054)

following induction. Changes in coupling can result from either changes in input resistance or junctional conductance, and this conductance can be estimated indirectly by combining transfer resistances and input resistance. Using this estimate of gap junctional conductance confirms that coupling remains significantly reduced after induction (48% ± 12% reduction; p < 1 × 10−4; Figure S1A available online). Experiments were also performed in voltage clamp to provide a more direct readout of coupling (Figures S1B–S1D). Cells were held at −55 mV during the baseline and postinduction period. For plasticity induction, synaptic stimuli were paired with short (10 ms), 10 mV depolarizations to allow the cells to fire bursts of unclamped spikes. After induction, coupling was significantly first reduced (by 15% ± 1% of control; p < 0.01, n = 7 cells), consistent with our current-clamp experiments. Finally, we tested the effect on coupling coefficient of higher-frequency olivary spiking in the presence of more intense synaptic input. Spikes at 4 Hz, evoked by depolarizing current pulses, were paired with 25 Hz bursts of synaptic input timed to provide synaptic glutamate release throughout the postsynaptic spike (Figure S2A). This “theta”-like activity was designed to mimic pairing protocols that are typically used to induce synaptic plasticity in other brain areas.

Covariations in coordinated preparation in this model could give

Covariations in coordinated preparation in this model could give rise to saccade and reach RT correlations. Analyzing the link between RT and neural activity might reveal shared representations that control both movements together. We trained two monkeys to make either coordinated reaches and saccades (Figure 2A)

or saccades alone (Figure 2B) to a visually cued Caspase activation target. Before coordinated movements, saccade RTs (SRTs) were correlated with reach RTs (RRTs; example in Figure 2C; R = 0.69, mean SRT = 190 ms, mean RRT = 280 ms). Across 105 experimental sessions, SRT-RRT correlations were 0.50 ± 0.24 (mean ± std). Mean SRT across the population was also significantly faster when the saccade was made with a reach (243 ± 0.6 ms, mean ± SEM) than when it was made alone Selleckchem Lonafarnib (252 ± 0.6 ms; p < 0.001). These results demonstrate that correlations exist between RTs for saccades and reaches such that saccades can be initiated more quickly when made with a reach. We recorded spiking and LFP activity from 105 sites in area LIP (74 in Monkey H; 31 in Monkey J), 135 sites in PRR (53 in Monkey H; 82 in Monkey J) and 36 visually responsive sites in V3d (36 in Monkey J; Figures 3A and S1). We first present example activity from a single session recorded in area LIP during the reach and saccade task. Spiking and LFP activity in area LIP showed robust selectivity for the preferred (Figure 3Bi) compared

with the null (Figure 3Ci) direction. Spatial tuning was present in LFP activity with different dynamics at different frequencies. One pattern of power changes was present before movements to the

preferred direction (Figure 3Bii), and another pattern was present before movements to the null direction (Figure 3Cii). LFP power was generally greatest around 15–17 Hz below in the beta-frequency band and decreased relative to baseline for preferred direction trials (Figure 3D). In contrast, LFP power increased at frequencies above ∼30 Hz in the gamma-frequency band, and the opposite pattern was present for trials in the null direction (Figure 3E). Thus, reach and saccade movements influence the rate of spiking as well as LFP power in both gamma- and beta-frequency bands. To build a link between neural activity and coordination, we then related LFP power and spike firing rate to saccade and reach RTs. We started by considering LFP power. We examined whether LFP activity predicts movement RTs by grouping LFP power during trials with the slowest or fastest RTs. We selected LFP activity from 72 sites in area LIP with at least 60 trials in each direction and for each task (Monkey H: 57 sites; Monkey J: 15 sites). Before reach and saccade movements in the preferred direction, beta-band LFP power (15 Hz) was significantly greater during the 33% of trials with the slowest SRTs than for the 33% of trials with the fastest SRTs (Figure 4A; p < 0.05, rank-sum test).

Participants were aged between 12 and 18 years of age Seventy ei

Participants were aged between 12 and 18 years of age. Seventy eight girls had been vaccinated against HPV, four had refused the HPV vaccination, and four had delayed vaccination

as they were undecided; data were missing for one girl. Typically, participants knew very little about HPV infection GSK1349572 and its transmission. They were asked if they knew how to protect themselves from HPV infection. Some girls mentioned the HPV vaccine, others mentioned that condoms would prevent transmission, or that avoiding sexual intercourse altogether would offer the best protection from contracting HPV. It was common for the girls who did know that HPV was sexually transmitted to believe that their own risk of contracting it was low because they associated HPV infection with girls who “sleep around” (FG S5: Noelle 13). Only two of the girls mentioned that they knew HPV infection is highly prevalent. Discussions about prevalence rates of HPV tended to lead onto conversations about whether HPV Cisplatin clinical trial could be detected through routine STI testing. Although no routine test for HPV infection is available, it was common for girls to believe that boys were the vector of infection and should be routinely tested for HPV and given treatment if infected. This notion arose spontaneously in three groups. Further discussion revealed that girls were

applying their general knowledge about STI prevention to HPV, although they were also unsure about whether HPV testing really was part of routine STI testing, as illustrated by the the following extract from one group discussion: Sally: Boys should be tested.

This comment that boys could be screened for cervical cancer rather than HPV infection went unchallenged by the group members. This lack of a clear understanding of how HPV infection could be prevented and what the girls could do to protect themselves was particularly evident in the younger groups. For example, when one younger group was asked how they could protect themselves against HPV infection, they replied: Tess: Take the pill. Around half of the girls were aware that HPV infection could lead to the development of cervical cancer, but there was also some confusion about whether cancer could actually be prevented. As one girl considered: Cervical cancer. I thought it was just like any cancer, like kind of like lung cancer, it just kind of appears… like one minute you’re all right and the next minute it’s like you’ve got cancer. I thought it was like that, I thought cancer was one of those random things. I didn’t know cancer could be caught like sexually transmitted at all (FG S5: Lisa 15). It was common for girls to discuss broader ideas about cancer and to mention a belief that cancer was difficult to control through any preventative measures.

, 2010) Moreover, the Hiw-Wnd pathway does not regulate Dscam pr

, 2010). Moreover, the Hiw-Wnd pathway does not regulate Dscam promoter activity, because the expression of a Dscam[TM2]::GFP transgene, under the control of the Dscam promoter, was not significantly different between wild-type and hiw mutant brains ( Figure S3C).

These results suggest that Hiw-Wnd pathway regulates Dscam expression possibly at the level of protein translation. The UTRs of mRNAs are key components of protein translational control (Wilkie et al., 2003). In order to determine the requirement of the UTRs in Dscam expressional control, we generated Dscam transgenes fused to GFP with or without Dscam 5′ and/or 3′ UTRs ( Figure 4). The expression of a Dscam transgene lacking both UTRs (Dscam::GFP) was not affected by hiw mutations ( Figure 4A). Similarly, expression Gemcitabine purchase buy BAY 73-4506 of a transgene with only the 5′ UTR (5′-Dscam::GFP) was also unaffected by hiw function

( Figure 4B). In contrast, the expression levels of a transgene with both the 5′ and 3′ UTRs (5′-Dscam::GFP-3′) and those of the transgene with only the 3′ UTR (Dscam::GFP-3′) were significantly elevated in hiw mutant neurons ( Figures 4C and 4D). Consistently, overexpressing Wnd enhanced the expression of the Dscam transgene with only 3′ UTR in C4 da neurons ( Figure 4E) as well as Drosophila Schneider 2 (S2) cells in culture ( Figure 4F). These results denote that Hiw-Wnd pathway controls Dscam expression through the 3′ UTR of Dscam mRNA. Next, we

tested whether the Dscam 3′ UTR is sufficient for translational control by the Hiw-Wnd pathway. We generated reporter transgenes by fusing EGFP cDNA with either the 3′ UTR of Dscam mRNA or that of SV40 as a control ( Figures 5A and 5B). Hiw mutations specifically enhanced the expression of the Dscam 3′ UTR reporter in C4 da neurons ( Figures 5A and 5B). Consistently, expression of Wnd in cultured S2 cells markedly increased expression of the Dscam 3′ UTR reporter ( Figure 5C). We further found that the first 202 nucleotides of Dscam 3′ UTR are sufficient for the Wnd regulation ( Figure 5D). Taken together, these results suggest that the Dscam 3′ UTR is necessary and sufficient for translational regulation by the Drosophila DLK pathway. The RNA-binding protein fragile X mental retardation many protein (FMRP) is involved in the posttranscriptional regulation of a number of target mRNAs ( Santoro et al., 2012). FMRP has been reported to bind to Dscam mRNA in mammalian neurons ( Brown et al., 2001; Darnell et al., 2011), but the functional relevance of this binding is unknown. We wondered whether FMRP might also regulate Dscam protein translation. We tested the association between Drosophila FMRP (dFMRP) and Dscam mRNA in larval brain lysates by RNA immunoprecipitation. Compared to a control antibody, anti-dFMRP antibody pulled down more Dscam mRNA as assessed by real-time PCR ( Figure 6A).

F B, principal investigator) and a fellowship

F.B, principal investigator) and a fellowship http://www.selleckchem.com/products/NVP-AUY922.html from the Autism Science Foundation (M.S.). A.M. and M.S. performed experiments, wrote the manuscript, and participated in the study design. L.L. and M.F.B. designed and directed the study and wrote the manuscript. T.M.B. and L.O. performed experiments. G.J. contributed CTEP. J.G.W. and W.S. contributed to the writing of the manuscript. The following experiments were performed at F. Hoffmann-La Roche (A.M., T.M.B., L.O., W.S., J.G.W., G.J., and L.L.): CTEP pharmacokinetic and receptor occupancy studies and modeling, hormone measurements,

pharmacological rescue of inhibitory avoidance extinction deficit, elevated locomotor activity, hypersensitivity to auditory stimuli, elevated synaptic spine density, ERK/mTOR signaling alterations, and macroorchidism. The following experiments were performed at the Picower Institute for Learning and Memory, MIT (M.S. and M.F.B.): rescue of elevated audiogenic seizure sensitivity and elevated hippocampal LTD. “
“The immature brain shows a higher susceptibility to epileptic seizures compared to the mature one (Holmes et al., 1998). Although

there is more resistance to acute seizure-induced cell loss than in the adult brain, both clinical (Baram, 2003 and Lombroso, 2007) and experimental (Holmes et al., 1998) studies have confirmed Autophagy inhibitor purchase that frequent or prolonged seizures lead to long-term impairments in brain development and functional abnormalities. Transient gamma-frequency oscillations (GFOs; >40 Hz) occurring at the onset of most seizures are a marker of a chronic epileptic condition (Worrell et al., 2004). GFOs have been proposed to participate in the induction of alterations of immature networks (Khalilov et al., 2005). These GFOs

occur simultaneously in different brain regions, suggesting a wide network-pacing system. Yet, the mechanisms Liothyronine Sodium underlying the emergence of GFOs and the control of their spatial synchronization are still unknown. In adult networks, the mechanisms underlying GFO genesis involve synaptic interactions between glutamatergic and GABA neurons, as well as gap junctions (Bartos et al., 2007 and Whittington and Traub, 2003). At early stages of postnatal development, pyramidal cells are poorly developed, and most function depends upon activation of GABA synapses (Ben-Ari et al., 1997). In this context, GFO mechanisms may differ from the adult situation and reflect the particular anatomical and functional organization of immature networks (Khalilov et al., 2005). Hence, our goal was to identify the cellular and network mechanisms underlying the generation and synchronization of GFOs in various conditions during development. We used the intact in vitro septohippocampal preparation, in which various stimuli can be used to trigger epileptiform discharges characterized by GFOs at their onset (Khalilov et al., 2005 and Quilichini et al., 2002), thus enabling the study of their underlying mechanisms.

, 1991 and Falchier et al , 2002); in primary motor cortex, the h

, 1991 and Falchier et al., 2002); in primary motor cortex, the head and leg regions are connected with different areas ( Tokuno et al., 1997 and Hatanaka et al., 2001). In human cortex, internal heterogeneity Dactolisib ic50 within a single area can exceed the connectivity differences between corresponding topographic locations in neighboring areas; as illustrated below, this can result in marked differences in boundaries revealed by connectivity versus architectonic methods. (3) Topographic complexity. Topographic organization is precise and orderly in early sensory areas (e.g., visual

area V1). It becomes coarser and more disorderly for areas that are progressively farther from the primary area; some areas also have an incomplete or biased representation of the contralateral sensory space, e.g., the visual field or body surface ( Maunsell and Van Essen, 1987, Hansen et al., 2007, Kolster et al., 2009 and Kolster et al., 2010). Genuine irregularities in topographic organization make it difficult to delineate areal boundaries, and this can buy GSK1120212 be compounded by methodological noise or bias. (4) Individual variability. Comparisons across individuals are vital for crossmodal validation and for assessing the

consistency of any given parcellation scheme. However, such comparisons must cope with individual variability in the size (surface area) of each cortical area and in its location relative to cortical folds. Well-defined

cortical areas such as V1 vary in areal size by 2-fold or more in humans and nonhuman primates ( Andrews et al., 1997, Amunts et al., 1999 and Amunts et al., 2000). MTMR9 The relationship of areal boundaries to gyral and sulcal folds is reasonably consistent in the moderately gyrencephalic macaque ( Van Essen et al., 2012a) but is much more variable in humans, especially in regions of high folding variability ( Amunts et al., 1999 and Van Essen et al., 2012b). A corollary of this observation is that perfect alignment of cortical areas (and hence cortical function) cannot be achieved using any registration method that relies exclusively on folding patterns or other shape features. Fortunately, novel approaches now enable registration based on function and other areal features (see below). The next three subsections provide an update on cortical parcellations in the mouse, macaque, and human, along with reference to key historical milestones in order to provide perspective. Visual cortex warrants special consideration owing to the recent identification of many more visual areas than envisioned in classical schemes. Early studies of rodent visual cortex suggested that area V1 was surrounded by only one or two neighboring retinotopically organized visual areas (E. Wagor et al., 1977, SfN, abstract).

To address this issue, it is tempting to simply instruct particip

To address this issue, it is tempting to simply instruct participants to maintain fixation. However, saccade suppression would likely become more difficult when participants are attempting to retrieve specific perceptual details, which is important because the dorsal attention network is also associated with the suppression of

saccades ( Brown et al., 2008). Whereas differences in saccade suppression across conditions cannot be measured directly, differences in eye movements across conditions can click here be measured very accurately. Our approach was thus to allow participants to move their eyes freely and to integrate the resulting measurements into the analysis of the fMRI data. We used a hierarchical regression approach to control for the effects of eye movements on the fMRI data prior to analyzing differences between conditions. In order to ensure that the model was sufficiently flexible to accurately model the effects of eye movements on the data, a series of fourth-order polynomials were used Galunisertib mouse to model a potentially nonlinear relationship. Multiple eye tracking measures (saccades between related pictures and total number of saccades) were regressed out, as well as reaction time. Engagement of the dorsal attention

network during episodic retrieval was minimally affected by these statistical controls, strongly suggesting that activation of the dorsal attention network in the present task is dominated by top-down, volitional attention rather than eye movements per se. A control analysis in which the hierarchical regression was not performed produced very similar results, indicating that our findings do not hinge on the method of analysis and that critical attention or memory related activity Idoxuridine was not inadvertently removed from the data. Of course, any statistical correction can only be as good as the statistical model and the measurements obtained. To evaluate whether the findings reflect measurement error or an inadequately modeled

residual effect of eye movements, we subjected the data to a strong test: we subsampled the data to substantially reverse the direction of eye movement effects across conditions. We found some evidence for a residual effect of eye movements in early visual cortex. However, activation of the dorsal attention network was still clearly present despite these modest residual effects ( Figure 3), once again suggesting that activation of the dorsal attention network in the present task is dominated by top-down, volitional attention. Although we cannot unequivocally rule out that there are any residual effects of eye movements in the present findings, it is clear that the dorsal attention network activation is robust against even very aggressive statistical controls for eye movements.

, 2008 and Pfeifer and Thiele, 2005), are effective against human

, 2008 and Pfeifer and Thiele, 2005), are effective against human epileptic seizures that are refractory to anticonvulsant drugs. These diets mimic fasting by reducing the carbohydrate supply and forcing the

breakdown of fatty acids and utilization of ketone bodies as predominant carbon substrates. Whether it is reduced glucose metabolism per se, increased ketone body metabolism, or a combination of both that mediates seizure protection is under active investigation. However, this metabolic shift clearly reduces the incidence of seizures. In experimental animals, glycolytic inhibition can alter gene regulation and reduce epileptogenesis in a kindling model (Garriga-Canut et al., 2006 and Stafstrom et al., 2009). The reduced capacity to metabolize glucose and a simultaneous increase Bortezomib mw IDH inhibitor in the propensity to metabolize ketone bodies upon BAD modification is consistent with fuel competition (Hue and Taegtmeyer, 2009) and recapitulates the actual change in fuel consumption by the brain in fasting (Owen et al., 1967) or on KD (DeVivo et al., 1978). However, these BAD-dependent changes occur in the absence of dietary manipulation. Compared with systemic effects of dietary alterations, the seizure resistance in Bad null and S155A mice appears to likely arise from alterations in brain cell metabolism rather than systemic

changes. In support of this idea, liver knockdown of Bad is not sufficient to produce ADP ribosylation factor seizure resistance ( Figure S5) while it mimics the metabolic phenotype of the Bad null allele in the liver (data not shown). In addition, serum levels of circulating ketone bodies are not elevated in BAD-deficient mice under steady-state conditions (data not shown), thus it seems unlikely that changes in brain metabolism are driven by systemic changes. The BAD-dependent metabolic shift can be demonstrated at the cellular level with changes in carbon substrate consumption in primary neuron or astrocyte cultures, consistent with cell-autonomous metabolic effects of BAD. These metabolic changes have the

consequence of elevating the open probability of KATP channels, as seen in both whole-cell and cell-attached recordings from DGNs in brain slices. Either glucose deprivation or ketone body metabolism can produce elevated KATP channel activity, and these effects can be augmented by increased neuronal firing (Ma et al., 2007 and Tanner et al., 2011), as seen during seizures. The exact mechanism of KATP channel activation by BAD-dependent metabolic changes is not known; changes in ATP and ADP are a possible mechanism, though other metabolites, such as PIP2, are also known to regulate the activity of KATP channels (Nichols, 2006), and we cannot rule out changes in the properties of the channel through some unknown signal resulting from genetic alteration of Bad. Total cellular ATP levels and the ATP/ADP ratio in whole brain under steady-state conditions are comparable in WT and Bad−/− brains ( Figures S6A and S6B).

Aspects of the conceptual inspiration for optogenetics can be tra

Aspects of the conceptual inspiration for optogenetics can be traced to the 1970s. In 1979 Francis Crick, taking note of the complexity of the mammalian brain and the fact that electrodes cannot readily distinguish different cell types (Crick, 1979), suggested that a major challenge facing neuroscience was

the need to precisely control activity in one cell type while leaving the others unaltered. BMS-777607 supplier Crick later speculated in lectures that light might be a relevant control tool, but without a concept for how this could be done. Yet years earlier (in an initially unrelated line of research), bacteriorhodopsin had been identified (Oesterhelt and Stoeckenius, 1971 and Oesterhelt and Stoeckenius, 1973) as a microbial single-component light-activated ion pump. Further work in thousands of papers over the ensuing decades led not only to deeper understanding of bacteriorhodopsin but also to the discovery of many new members of this microbial opsin family, which includes membrane-bound ion pumps and channels such as halorhodopsins (Matsuno-Yagi and Mukohata, 1977) and channelrhodopsins (Nagel et al., 2002) that transport Trametinib chemical structure various ions across the membrane in response to light (Matsuno-Yagi and Mukohata, 1977, Lanyi and Oesterhelt, 1982, Schobert and Lanyi, 1982, Béjà et al., 2000, Nagel et al., 2002, Nagel et al., 2003,

Ritter et al., 2008 and Zhang et al., 2008). It took decades for these two concepts to be brought together by neuroscientists,

although microbial opsin genes were widely known and had long been understood to give rise to single-component light-activated regulators of transmembrane ion conductance. But there were fundamental caveats for those who considered such a possibility for optical neural control over the decades, including the presumption that photocurrents would be too weak and slow to control neurons efficiently, the presumption that microbial membrane proteins in fragile mammalian neurons would be poorly expressed or toxic, and most importantly the presumption that additional cofactors such as all-trans retinal (the separate organic light-absorbing chromophore employed by microbial Thiamine-diphosphate kinase opsins) would have to be added to any intact-tissue experimental system. These preconceptions (strikingly similar to those that slowed the development of green fluorescent protein) were all reasonable enough to deter experimental implementation, and efforts were therefore focused elsewhere. Yet in the summer of 2005 it was reported that introduction of a single-component microbial opsin gene into mammalian neurons (without any previously tested or other component) resulted in reliable sustained control of millisecond-precision action potentials ( Boyden et al., 2005); many additional papers from work conducted contemporaneously appeared over the next year ( Li et al., 2005, Nagel et al.

The amplitude of the persistent Na+ current (i e , INaP) was inde

The amplitude of the persistent Na+ current (i.e., INaP) was indeed markedly reduced in L5 axons without a first branch point (Kole, 2011), and the role of INaP is confirmed with local pharmacological agents: burst firing was selleck chemicals llc abolished when Na+ channels were pharmacologically inactivated with local application

of tetrodotoxin (TTx) or solution containing zero Na+ at the FNoR but not at the first internode. In summary, Kole’s study adds an important piece to the axon puzzle by clearly assigning a specific function to the FNoR. It further confirms that the function of the axon is not purely limited to the conduction of the action potential, but that the computational capabilities of an axon are much wider than initially thought

(Debanne et al., 2011). However, all issues are not yet resolved regarding the cellular mechanisms of intrinsic bursting. If bursting primarily originates in the FNoR, what is the role of the dendrites? Are there one or two modes (Figure 1) of burst electrogenesis in pyramidal neurons? How should the experiments on dendritic inactivation/amputation be reinterpreted in light of Kole’s results? These questions will certainly challenge theoreticians and experimentalists in the near future. But we can already propose that two forms of bursting may coexist in pyramidal neurons, calcium and sodium-dependent bursting that respectively depend on the somatic and axonal compartments 17-DMAG (Alvespimycin) HCl (Figures 1A and 1B). In fact, these two forms of bursting share a common feature: selleckchem the need for a slow depolarizing event generated outside the site of spike initiation but electrically coupled to it. The results reported by Kole are not only important because they allow a better understanding of the elementary mechanisms underlying intrinsic bursting. They also raise

the critical issue that the mechanisms of activity-dependent regulation of burst firing in pyramidal neurons must be reconsidered. Usually attributed to the dendrites, this form of plasticity may in fact involve the axon and more specifically the FNoR. It can be expected that these findings will spur us on to determine the contribution of the FNoR to plasticity of intrinsic bursting. “
“We remember the events of our lives as episodes framed by space and time. Such memories require structures in the medial temporal lobe (MTL), especially the hippocampus. People with MTL damage are amnesic, “lost in time,” and unable to recall the recent past or imagine the future. Early efforts to model human amnesia and analyze MTL function in animals led to the discovery of hippocampal place cells and the theory that the hippocampus supports memory by constructing cognitive maps that define spatial contexts (O’Keefe and Nadel, 1978).