, 2006) and mitochondria may change their positions with time and may be recruited to a subset of presynaptic sites that undergo active vesicle recycling. Mitochondria are bidirectionally transported along the axonal cytoskeleton and anchored at specific positions. Therefore, the distribution processes should be dependent on multiple dynamic factors involving fractions of mitochondria in stationary or mobile state, transition rates between these two states, and

the dynamic properties of mobile mitochondria (Fig. 1A and B). Axonal mitochondrial transport is regulated by the intracellular and mitochondrial matrix Ca2+ concentration (Wang & Schwarz, 2009; Chang et al., 2011). The number of moving axonal mitochondria Trametinib nmr is also regulated by neuronal activity (Chang et al., 2006). However, whether the stop and start of mitochondrial movement are regulated by local cellular conditions, especially those associated with high ATP consumption at synaptic sites, has not been investigated. How changes in the characteristics of mitochondrial transport are related click here to the rearrangement of mitochondrial distribution also remains unclear. Although the signaling pathways and molecules involved in mitochondrial docking have been investigated, how transitions between mobile and stationary state are regulated in response to changes in physiological

conditions is unknown (Wagner et al., 2003; Chada & Hollenbeck, 2004; Kang et al., 2008; Chen et al., 2009). In this study, we analysed the dynamics Avelestat (AZD9668) of axonal mitochondria in cultured hippocampal neurons using live-cell imaging. We demonstrated that both the turnover of stationary mitochondria and behavior of mobile mitochondria were regulated by proximity to synaptic sites, neuronal activity, and maturity of axons. These results indicate that mitochondrial distribution is regulated by multiple dynamic parameters in response

to physiological demands. The C-terminal transmembrane region of mouse mitochondrial outer membrane protein of 25 kDa (OMP) cDNA and mouse VAMP2 cDNA were cloned by polymerase chain reaction. The sequences were verified by DNA sequencing. Human amyloid precursor protein 695 (APP) -venus plasmid was provided by Dr Sakurai (Juntendo University; Sakurai et al., 2008). EGFP-OMP, EGFP-VAMP2 and APP-EGFP were generated by inserting the coding region into Enhanced Green Fluorescent Protein (EGFP) vectors (Clontech, Mountain View, CA, USA). The mCherry-OMP and APP-mCherry were generated by replacing the EGFP coding region with the coding region of mCherry (Shaner et al., 2004). The DNA fragments coding for EGFP and mCherry fusion proteins were inserted into the expression plasmids containing β-actin promoter sequences (Ebihara et al., 2003). G-CaMP6 plasmid was provided by Dr Nakai (Saitama University; Ohkura et al., 2012).

, 2006) and mitochondria may change their positions with time and may be recruited to a subset of presynaptic sites that undergo active vesicle recycling. Mitochondria are bidirectionally transported along the axonal cytoskeleton and anchored at specific positions. Therefore, the distribution processes should be dependent on multiple dynamic factors involving fractions of mitochondria in stationary or mobile state, transition rates between these two states, and

the dynamic properties of mobile mitochondria (Fig. 1A and B). Axonal mitochondrial transport is regulated by the intracellular and mitochondrial matrix Ca2+ concentration (Wang & Schwarz, 2009; Chang et al., 2011). The number of moving axonal mitochondria Tanespimycin cost is also regulated by neuronal activity (Chang et al., 2006). However, whether the stop and start of mitochondrial movement are regulated by local cellular conditions, especially those associated with high ATP consumption at synaptic sites, has not been investigated. How changes in the characteristics of mitochondrial transport are related H 89 mouse to the rearrangement of mitochondrial distribution also remains unclear. Although the signaling pathways and molecules involved in mitochondrial docking have been investigated, how transitions between mobile and stationary state are regulated in response to changes in physiological

conditions is unknown (Wagner et al., 2003; Chada & Hollenbeck, 2004; Kang et al., 2008; Chen et al., 2009). In this study, we analysed the dynamics Lonafarnib of axonal mitochondria in cultured hippocampal neurons using live-cell imaging. We demonstrated that both the turnover of stationary mitochondria and behavior of mobile mitochondria were regulated by proximity to synaptic sites, neuronal activity, and maturity of axons. These results indicate that mitochondrial distribution is regulated by multiple dynamic parameters in response

to physiological demands. The C-terminal transmembrane region of mouse mitochondrial outer membrane protein of 25 kDa (OMP) cDNA and mouse VAMP2 cDNA were cloned by polymerase chain reaction. The sequences were verified by DNA sequencing. Human amyloid precursor protein 695 (APP) -venus plasmid was provided by Dr Sakurai (Juntendo University; Sakurai et al., 2008). EGFP-OMP, EGFP-VAMP2 and APP-EGFP were generated by inserting the coding region into Enhanced Green Fluorescent Protein (EGFP) vectors (Clontech, Mountain View, CA, USA). The mCherry-OMP and APP-mCherry were generated by replacing the EGFP coding region with the coding region of mCherry (Shaner et al., 2004). The DNA fragments coding for EGFP and mCherry fusion proteins were inserted into the expression plasmids containing β-actin promoter sequences (Ebihara et al., 2003). G-CaMP6 plasmid was provided by Dr Nakai (Saitama University; Ohkura et al., 2012).

This was despite the overwhelming anatomical evidence for the many different subtypes of GABAergic inhibitory interneurones

that are found in the brain (e.g. Ramón y Cajal, 1909, 1911; Peters & Jones, 1984; Monyer & Markram, 2004; Butt et al., 2005; Klausberger & Somogyi, 2008). We now know a lot more about inhibitory circuitry and can begin to predict some of the many different roles that inhibitory connections play. In neocortex check details alone there are > 20 different types of inhibitory connection in each of five layers (2–6). While it has been clear for a long time that gross alterations in inhibitory gain control result in coma on the one hand and seizures on the other, more recently, seemingly small or subtle changes in only one part of the inhibitory system have been linked to perhaps less life-threatening, but nevertheless Pexidartinib concentration debilitating and tragic, neurological and psychiatric disease. Similarly, pharmacological or genetic manipulation

of single GABAA receptor (GABAAR) subunits produces rather less dramatic, but nevertheless profound, alterations in mood and behaviour (Möhler, 2006a,b; Möhler et al., 2002; Rudolph & Möhler, 2006, for reviews). One important consequence of this selectivity is that, in many cases, changing the activity of a given GABAAR subtype, either by gene mutation, or by pharmacological Dynein manipulation, modifies the outputs of a given class of presynaptic GABAergic neurone, rather than modifying the inputs to a given class of postsynaptic neurone. These manipulations can, therefore, indicate the role(s) that different classes of interneurones play. Synaptic GABAARs are typically pentomers

containing a γ2 subunit in addition to two β- and two α-subunits. A β-subunit (β1, β2 or β3) is almost obligatory for plasma membrane insertion. Multimers without β-subunits are often destroyed before leaving the endoplasmic reticulum (ER). β-Subunits may also play a role in subcellular compartment-targeting of receptors: to axon, soma or dendrites. The α-subunits appear to convey an even finer level of specificity, a striking example being the inputs provided by two major subclasses of basket cells to the soma of the same pyramidal cell in neocortex and hippocampus. The GABAARs innervated by parvalbumin (PV)-containing basket cells include α1-, β2/3- and γ2-subunits, while α2,β2/3,γ2-GABAARs are innervated by cholecystokinin (CCK) basket cells (Fig. 1; also Pawelzik et al., 1999; Thomson et al., 2000; Ali & Thomson, 2008). Benzodiazepines acting only at α1-GABAARs produce sedative and anticonvulsant effects, but generate anxiolysis only when they act at α2/3-GABAARs (Möhler et al., 2002), indicating the functional and potential therapeutic relevance of this differentiation.

Resistance to at least one PI was observed by RNA but not DNA genotyping in 50% of patients (78 of 156) and by DNA but not RNA genotyping in 7% of patients (11 of 156). The median (IQR) GSS was 1.5 (1.0, 1.5) based on RNA genotyping and 2.0 (1.5, 3.0) based on DNA genotyping (P < 0.001). The GSS was 2 or more in 18% and 58% of patients based on RNA and DNA genotyping, respectively,

suggesting that 20% of patients had at least two active drugs in their regimen (excluding enfuvirtide) based on previous RNA genotyping, compared with 58% of patients based on current DNA genotyping (Table 1). RNA genotyping showed that 160 (95%) of the 169 patients harboured triple-class-resistant viruses, compared with 42 (35%) of Buparlisib purchase the 121 patients with assessable DNA genotypes. Among age, gender, Centers for Disease Control and Prevention (CDC) status, nadir RG7204 cost and baseline CD4 cell counts, and total duration of antiretroviral treatment, only a lower nadir CD4 cell count was significantly associated with triple-class resistance based on DNA genotyping vs. no resistance to at least one of the 3-class (26 vs. 88 cells/μL; P = 0.001). The efficacy of switch drugs for patients receiving a virologically effective regimen depends mainly

on the number and nature of resistance mutations archived in the proviral reservoir following previous TCL therapeutic failures [2-7, 10, 11]. Viraemia is suppressed by the antiretroviral regimen in these patients, so resistance genotyping must be performed only on cell-associated HIV-1 DNA. Here we compared DNA genotyping results at randomization among 169 patients on successful highly active antiretroviral therapy (HAART) enrolled in the ANRS 138-EASIER switch trial [8] with the results of historical RNA genotyping in the same patients. We found that DNA genotyping

detected significantly fewer resistance mutations in the RT and PR genes than previous RNA genotyping. Indeed, mutations conferring resistance to at least one antiretroviral drug were detected exclusively by RNA genotyping or exclusively by DNA genotyping in 63% and 13% of patients for NRTIs, 47% and 1% of patients for NNRTIs and 50% and 7% of patients for PIs, respectively. Despite frequently suboptimal therapy in the past, only 35% of patients harboured triple-class-resistant archived viral DNA, a situation associated with a lower CD4 cell nadir. Our study confirmed the findings of a recent study showing, in a large number of patients with undetectable or low level viral load under an antiretroviral regimen, that the concordance between DNA and RNA was 46.7% for NRTI mutations, 26.3% for NNRTI mutations and 43.7% for PI mutations [12].

Carbon nutrition was determined in mineral base RM2 supplemented with an organic carbon source and 0.03% yeast extract. Growth was monitored by measuring the OD660 nm using an Amersham-Pharmacia Novaspec Plus spectrophotometer, and the final reading was taken after 2 weeks of incubation. Whole-cell buy MK-2206 fatty acids were analyzed by gas–liquid chromatography of their methyl ester derivatives as described previously (Suzuki & Hiraishi, 2007). Quinones were extracted with a chloroform–methanol mixture and analyzed by HPLC as described (Fujii & Hiraishi, 2009). Genomic DNA was extracted and purified according to the method of Marmur (1961). The guanine plus cytosine (G+C) ratio of genomic DNA was determined using the

HPLC method with external nucleotide standards as described by Mesbah et al. (1989). 16S rRNA Selleck ABT-199 gene fragments were PCR amplified, purified, and sequenced directly using an automated DNA sequencer as described previously (Hisada et al., 2007). Sequence data were compiled using the genetyx program (Software Developing Co., Tokyo, Japan) and compared with those retrieved from the database. Multiple alignment of sequence data, calculation of the corrected evolutionary distance (Kimura, 1980), and construction of a neighbor-joining (NJ) phylogenetic tree (Saito & Nei, 1987) were performed

using the arb program package (Ludwig et al., 2004). The topology of the NJ tree was evaluated by bootstrapping with 1000 replicates (Felsenstein, 1985). Tree construction was also carried out by the maximum likelihood (ML) method using the treefinder (Jobb, 2008) program package. The 16S rRNA gene sequences of strains AP8T and AP9 determined (1461 bases) were identical to each other, and were most closely related to that of the type strain of A. capsulatum (96% similarity). An NJ phylogenetic tree based on the sequences showed that the isolates represent a distinct lineage within subdivision 1 of the phylum Acidobacteria with A. capsulatum as their nearest phylogenetic neighbor (Fig. 1). The topology of the ML tree constructed was Edoxaban similar to that of the NJ tree (data not shown). The cells of the two isolates stained Gram-negative and were nonmotile, asporogenous

cocci and coccobacilli measuring 0.5–0.8 μm in diameter (Supporting Information, Fig. S1). Cells occurred singly or occasionally in pairs and reproduced by binary fission. Similar to A. capsulatum, cells of the isolates were capsulated. Colonies grown on GYSG medium for 7 days of incubation were circular (1.0–2.0 mm in diameter), smooth, translucent, mucous, and pale pink. The isolates were strictly aerobic and chemoorganotrophic bacteria that had a respiratory type of metabolism with oxygen as the terminal electron acceptor. Neither anaerobic respiratory growth with nitrate nor anaerobic fermentation with sugars or pyruvate occurred. No chemolithotrophic growth with sulfide, elemental sulfur, thiosulfate, or Fe2+ as electron donors was found.

In two experiments, which differed only in the availability to participants of visual information about their hands and their current posture, we recorded SEPs elicited by vibrotactile stimuli to the palms in uncrossed-hands and crossed-hands postures. Across both

of these experiments, crossing the hands over the midline produced statistically reliable effects from 128 and 150 ms in Experiments 1 and 2, respectively, thus influencing primarily the SEPs in the N140 time window. The excellent temporal resolution of ERPs allows us to conclude with more certainty than is offered by behavioural paradigms (Azañón & Soto-Faraco, 2008; Overvliet et al., 2011) exactly when remapping processes begin. Previous ERP investigations of somatosensory representation across changes in body posture have focused on the effects of posture on the modulation

of ERPs by voluntary attention. In these studies participants are instructed to attend to one stimulus learn more location and actively ignore somatosensory stimuli presented at other locations (e.g. Eimer et al., 2001, 2003; Heed & Röder, 2010; Eardley & Van Velzen, 2011). These studies have shown that modulations of SEP components by voluntary attention occur later and are reduced when the hands are crossed (Eimer et al., 2003; Heed & Röder, 2010; Eardley & Van Velzen, 2011), and this has typically been interpreted as reflecting a disturbance of processes of voluntary attention to a location on the body caused by conflicts between anatomical and external

reference frames for locating tactile stimuli (see, for example, Eimer et al., 2003). Crucially, in our study, no instruction to focus attention on a particular hand was given, and the locations Selleck Ceritinib of the tactile stimuli were unpredictable. This enables us to demonstrate the electrophysiological onset of somatosensory remapping as it occurs independently of processes of voluntary spatial attention. One previous study, by Heed & Röder (2010), has explored the effects of posture on processing of tactile stimuli which are not being attended to. In one part of this larger study Heed and Röder examined effects of posture and attention on ERPs elicited Endonuclease by stimuli to the hands. Examining trials in which participants were explicitly instructed to focus attention on one hand and to ignore stimuli presented on the unattended hand, Heed and Röder observed a reduction of early ERP amplitudes in response to stimuli presented to the unattended hand when the hands were crossed. However, voluntary attention is still very much at play in these effects; the participants were asked to direct their attention to the hand on which the stimulus was not being presented. Indeed, the authors interpreted the effect of posture in this particular condition as being due to voluntary attention being directed (in the crossed-hands posture) towards a location in which the attended tactile stimulus would have occurred should the hands have been in the more familiar uncrossed posture.

epidermidis ATCC 12228, considered as biofilm negative, and some clinical staphylococcal isolates without ica genes (also aap−) can form biofilms on some polytetrafluroethylene PTC124 vascular grafts after several days of incubation under static conditions. The majority of the ica-positive nasopharyngeal S. epidermidis isolates were also able to produce slime, which was monitored using the CRA test. This is in agreement with the data presented by other authors (Arciola et al., 2002; Stevens et al., 2008; El-Mahallawy et al., 2009); the presence of the ica operon was strongly associated with a slime-positive phenotype. However, ica-negative and slime-positive isolates in the CRA test were

also described in the present paper. Arciola et al. (2006) found a rather good concordance between the occurrence of ica genes, monitored using PCR-based analysis, and the CRA test. According to these authors, the MtP method appeared to be less appropriate for an accurate identification of staphylococcal capability of biofilm formation. In our study, there was a relation between the ability of biofilm formation by the MtP method and slime production in the CRA test among the ica-positive staphylococcal isolates. In contrast, most of the ica-negative strains

were positive by the CRA selleckchem test and possessed a biofilm-negative phenotype determined using the MtP method, especially for isolates harboring the aap gene. The literature data available regarding the CRA test yielded contrasting conclusions. Bozkurt et al. (2009) indicate that the CRA test should not be used for a biofilm formation ability assay in vitro of S. epidermidis because of misleading results. The specificity of this test is limited to the determination of staphylococcal ability to secrete slime rather than for the detection of bacterial adhesion and rapid growth in the form of a biofilm on the material’s surface. On the other hand, some authors (Arciola et al., 2006; Jain & Agarwal, 2009) recommended the CRA test as a reliable method to determine biofilm production. In our opinion, CRA and MtP tests are reliable methods to determine the ability of

slime/biofilm formation only in ica-positive S. epidermidis strains. Although previous studies (Vandecasteele et al., 2003; Cafiso et al., Urease 2004) have suggested that there is no strict association between the presence of the icaABCD operon and in vitro biofilm formation in invasive, colonizing and contaminant S. epidermidis, among the colonizing strains tested in our study, most of the biofilm producers (monitored using the MtP method) were the ica positive. In conclusion, S. epidermidis isolates possess the potential ability to form biofilms by ica-dependent and/or ica-independent mechanisms. In our opinion, further studies are needed to determine reliable, short-time criteria for the assessment in vitro of biofilm formation in staphylococci.

jgi.doe.gov/) (Position: scaffold_80:317485–317760) and the entire A3aPro sequence from P. sojae was submitted to GenBank

(accession no. JX118829). Thus, based on the A3aPro sequencing information, we have identified a novel transposon-like DNA element A3aPro in many Phytophthora genomes that could provide a potential target for plant disease diagnosis. In this study, we developed a LAMP assay for P. sojae based on a special identifiable target A3aPro and demonstrated that it was specific and efficient. Phytophthora sojae isolates were obtained from diseased soybean stems collected from various provinces Selleckchem AZD6738 in China from 2002 to 2011. All tested P. sojae isolates were isolated using a leaf disk-baiting method from buy FG-4592 diseased soybean plots (Jinhuo & Anderson, 1998). Using the same method, additional P. sojae isolates were baited from soybean residues and soil carried by soybeans imported from the USA, Brazil, Argentina and Canada. Thirteen known races (R2, R3, R6, R7, R8, R12, R14, R17, R19, R20, R28, R31, and P7071) of P. sojae were provided by B. Tyler and J. Peng. The P. sojae isolates, as well as isolates of Phytophthora spp., Pythium spp., Fusarium spp., and various other pathogens used in this study, are maintained in a collection in the Department of Plant Pathology, Nanjing Agricultural University, China, and are listed in Table

S1. Phytophthora isolates were cultured in tomato juice medium (Zheng, 1995) (L−1, 200 mL tomato juice, 0.1 g CaCO3 and 15 g agar mixed with sterile distilled water, and autoclaved at 120 °C for 20 min). Mycelia of each Phytophthora and Pythium isolate were obtained by growing the isolates in tomato juice broth at 18–25 °C (temperature-dependent isolates) for at least 3 days. Mycelia of the other fungi were grown in potato dextrose broth (Erwin et al., 1996). The mycelia

were harvested by filtration and frozen at −20 °C. Mycelia DNA was isolated using the DNAsecure Plant Kit (TIANGEN) according to the manufacturer’s protocol. DNA concentrations were determined spectrophotometrically or by quantitation on 1% agarose gels stained with ethidium bromide in comparison with commercially obtained standards and stored at −20 °C. A set of four species-specific second LAMP primers was designed based on the P. sojae identifiable target A3aPro. Briefly, using the A3aPro sequence of P. sojae as a bait to do a blastn search did not showed any similarity with other sequenced strains of Phytophthora infestans, Phytophthora ramorum and Hylaperonospora parasitica. Then we obtained similar-A3aPro sequences in the genome databases for P. infestans, P. ramorum and H. parasitica. Phytophthora infestans DNA sequence was available from the Broad Institute (http://www.broad.mit.edu/) (Position: supercontig_1.1849:1900–2350); P. ramorum DNA sequence was available from the JGI (http://www.jgi.doe.gov/) (Position: scaffold_1220:1–342); H. parasitica genome sequence was available from http://vmd.vbi.vt.

, 2009; Vance et al., 2009). FUS/TLS mutations were also found in other populations in Europe, Japan and the US and it is estimated that FUS/TLS mutations cause familial

ALS in 4–5% of cases (Belzil et al., 2009; Blair et al., 2010; Chio et al., 2009b; Damme et al., 2009; Drepper et al., 2010; Ticozzi et al., 2009b; Corrado et al., 2010; Groen et al., 2010; Suzuki et al., 2010). In addition, one de novo truncation mutation was reported (Dejesus-Hernandez et al., 2010). The FUS/TLS gene is located on chromosome 16. Also known as hnRNPP2, it belongs to the FET family of RNA-binding proteins and it is an hnRNP. The protein consists of an N-terminal region rich in glutamine, glycine, serine and tyrosine residues (QGSY region) Ibrutinib immediately followed by a glycine-rich domain. It contains an RNA-recognition motif (RRM) and multiple arginine, glycine, glycine (RGG) repeats implicated in RNA binding,

a zinc finger and a C-terminal region that is highly conserved (Lagier-Tourenne & Cleveland, 2009). FUS/TLS is involved in pre-mRNA splicing as well as in the export of fully processed mRNA to the cytoplasm and thus shuttles between the nucleus and the cytoplasm (Zinszner et al., 1997). It may also play an important role in transport of mRNA (Yoshimura et al., 2006). In addition, it is important in gene regulation and it was recently shown that Selleck Olaparib ID-8 FUS/TLS can serve as a transcriptional regulatory sensor of DNA damage signals leading to gene-specific repression of gene transcription (Wang et al., 2008). FUS/TLS is ubiquitously expressed and

under normal conditions it is mainly localized in the nucleus (Hackl & Luhrmann, 1996). In cultured hippocampal pyramidal neurons, FUS/TLS was localized not only in the nucleus but also in the dendrites (Fujii et al., 2005). This punctuate dendritic localization was dependent on an intact microtubule and actin network, and activation of mGluR5 metabotropic glutamate receptors stimulated FUS/TLS accumulation at the spines of excitatory synapses (Fujii et al., 2005). FUS/TLS-knockout mice die immediately after birth (Hicks et al., 2000) or are rarely alive at weaning (Kuroda et al., 2000). In an outbred strain, FUS/TLS-knockout mice survived but showed male sterility and reduced fertility of females (Kuroda et al., 2000). It was reported that heterozygous FUS/TLS mice were indistinguishable from wildtype littermates (Kuroda et al., 2000). Neurons deficient in FUS/TLS showed abnormal spine morphology and lower spine density (Fujii et al., 2005). It is estimated that FUS/TLS mutations account for ∼5% of familial ALS and thus again for < 1% of total ALS (Lagier-Tourenne & Cleveland, 2009). FUS/TLS-linked ALS is a dominant disease, except in the original Cape Verdian family in which the FUS/TLS mutation is recessive (Kwiatkowski et al., 2009).

They were instructed to ignore the auditory stimulation and watch a Dabrafenib silenced, subtitled movie of their choice on a computer screen in front of them (distance = 120 cm). Figure 1 schematically pictures the experimental design. Stimulus-onset asynchrony (SOA) was set to 150  ms. The onset of first deviant tones was always unpredictable, and violated in the pitch dimension the first-order formal regularity established by standard

tone repetition. We assume that also the repeated deviant tone violated the first-order regularity established by standard tones. In both cases, a first-order prediction error response is elicited. Two ‘repetition probability’ conditions were created: in a ‘high-repetition probability’ condition, deviant tones were always repeated; in a ‘low-repetition probability’ condition, deviant tones were either repeated or followed by a standard tone with equal probability. Two ‘temporal regularity’ conditions were created, producing ‘isochronous’ and ‘anisochronous-onset’ sequences. Large jitter values may induce significant differences in single-trial peak latencies, leading to an artifactual reduction of event-related deflection amplitudes (low-pass effect of averaging procedure; see Spencer, 2005). We thus kept anisochrony to a perceptible minimum, limiting the SOA jitter to ± 20% (in randomized steps of 5 ms, range 120–180 ms, uniform distribution). The same number of deviant pairs was used

in both deviant repetition probability conditions. In the high-repetition probability Osimertinib datasheet condition, there were 1200 standard and 240 deviant stimuli, accounting for 120 deviant pairs. Standard tones had a probability of 83.33%, and deviant tones 16.67% (each deviant considered as a single event). They were administered in one block of about 3.6 min. In the learn more low-repetition probability condition, global oddball values were adapted to 87% standard and 13% deviant tones: 2400 standard, 360 deviant stimuli, accounting for 120 deviant pairs and 120 single deviant tones (one block, about 6.9 min). This way, we could control for refractoriness-dependent

differences on the elicitation of first deviant N1 amplitudes, as the length of standard sequences (mean n = 10) before first deviant onset was the same across higher-order formal regularity conditions: high-repetition probability, 1200 standards/120 first deviants; low-repetition probability, 2400 standards/240 first deviants, pooled from both paired and single events. Block order presentation was randomized within subjects. An additional condition with repetition probability set to 75% was also included. Its effects are reported in the Supporting Information, section A, as they were uninformative to the aims of distinguishing between high and low deviant repetition probabilities. Electroencephalogram (EEG) was continuously recorded using an ActiveTwo amplifier system (BioSemi, Amsterdam, the Netherlands; http://www.biosemi.