g., Feng et al., 2004 and Benzing et al., 2000). Therefore, our results suggest a model ( Figure 10) in which Sema/Plex interactions activate PlexA GAP activity, which inactivates Ras/Rap and disables Integrin-mediated adhesion. However, these Sema/Plex-mediated effects are subject to regulation, such that increasing cAMP levels activates PlexA-bound PKA to phosphorylate PlexA and provide a binding site for 14-3-3ε. These PlexA-14-3-3ε interactions occlude PlexA GAP-mediated inactivation of Ras family GTPases and restore Integrin-dependent adhesion.

In conclusion, we have identified a simple mechanism that allows multiple axon guidance signals to be incorporated during axon guidance. Neuronal growth cones encounter both Selleckchem EPZ 6438 attractive and repulsive guidance cues but the molecular pathways and biochemical mechanisms that integrate these antagonistic cues and enable a discrete steering event are incompletely understood. One way in which to integrate these disparate signals is to allow different axon guidance receptors to directly modulate each other’s function (e.g., Stein and Tessier-Lavigne, 2001). Another means is to tightly regulate the cell surface expression of specific receptors and thereby actively prevent axons from seeing certain guidance cues (e.g., Kidd et al., 1998, Brittis

et al., 2002, Keleman et al., 2002, Nawabi et al., 2010, Chen et al., 2008 and Yang et al., 2009). Still further results are not simply explained by relatively slow modulatory mechanisms like receptor trafficking, endocytosis, and local protein synthesis but indicate that interpreting a particular guidance cue is susceptible to rapid Cyclopamine intracellular modulation by other, distinct, signaling pathways (e.g., Song et al., 1998, Dontchev and Letourneau, 2002, Terman and Kolodkin, 2004, Parra and Zou, 2010 and Xu et al., 2010). Our results now indicate a means to allow

for such intracellular signaling crosstalk events and present a logic by which axon guidance signaling pathways override one another. Given this molecular link between such key regulators of axon pathfinding as cyclic nucleotides, phosphorylation, and GTPases, our observations on silencing Sema/Plex-mediated repulsive axon guidance also suggest approaches to neutralize axonal growth inhibition Parvulin and encourage axon regeneration. Yeast two-hybrid setup, protein expression analyses, and screening were performed following standard procedures (Terman et al., 2002). Drosophila husbandry, genetics, imaging, and characterization of axon guidance were performed using standard methods ( Terman et al., 2002 and Hung et al., 2010). GST pull-down (Oinuma et al., 2004) and coimmunoprecipitation (Terman et al., 2002) assays were performed using standard approaches. GDP and GTPγS-preloading was assessed by GST pull-down assays using GST-RBD proteins (Diekmann and Hall, 1995 and Benard et al., 1999).

Application of high glucose concentrations to fibroblast cell cultures leads to acute transcriptional repression of the Per1, Per2, and Bmal1 genes, thereby synchronizing fibroblast clocks ( Hirota et al., 2002). This is reminiscent of glucocorticoid or glucocorticoid analog synchronization of cell cultures ( Balsalobre et al., 2000), with the difference being that they induce Per1

and Per2 gene expression that leads to a repression Dabrafenib of their own transcription and subsequent synchronization of all cells within hours. Glucose appears to upregulate TIEG1 (KLF10), a negatively acting zinc-finger transcription factor ( Hirota et al., 2002). It binds to two GC-rich elements in the Bmal1 promoter and thereby represses Bmal1 transcription. In vitro experiments have shown that siRNA-mediated knockdown of TIEG1/KLF10 causes

period shortening of cellular bioluminescence rhythms driven by Bmal1-luciferase and Per2-luciferase reporters ( Hirota et al., 2010a). Interestingly, Tieg1/Klf10 is regulated by BMAL1/CLOCK and thus appears to be part of a feedback loop involving the circadian clock and glucose levels ( Guillaumond selleck compound et al., 2010) ( Figure 4). Accordingly, glucose absorbed with food or generated by gluconeogenesis will stimulate Tieg1/Klf10 expression and reduce the expression of Bmal1 and genes encoding for enzymes involved in gluconeogenesis. In line with this notion is the observation that Klf10 knockout mice display postprandial and fasting hyperglycemia, although curiously, this has only been observed in male mice. However, KLF10 is implicated in circadian lipid and cholesterol homeostasis in females ( Guillaumond et al., 2010). Collectively, it appears that TIEG1/KLF10 is a transcriptional regulator that links the circadian clock to energy metabolism in the liver. One measure of metabolic state is the ratio between AMP and ATP. Once the ratio increases either (high AMP levels), cells reduce the

activity of ATP-consuming pathways and increase the activity of ATP-generating pathways. A major sensor for the AMP/ATP ratio is adenosine monophosphate-dependent protein kinase (AMPK), which becomes activated when AMP binds to its γ-subunit. This binding elicits a structural change in the AMPK catalytic α-subunit, making it a substrate for liver kinase B1 (LKB1). LKB1 then phosphorylates a threonine in the α-subunit of AMPK, leading to activation of AMPK (Carling et al., 2011). It appears that AMPK impacts circadian clock mechanisms in various ways. It can directly phosphorylate CRY1, leading to destabilization and degradation of this core clock protein (Lamia et al., 2009) and consequently affecting the negative limb of the circadian clock mechanism (Figure 4). The activity of AMPK kinase also appears to modulate PER2 protein stability via an indirect mechanism involving casein kinase 1ε (CK1ε).

Thus, these projections have been difficult to study in the context of spinal cord Akt signaling pathway injury. By injecting retrograde tracers into the stumps of sciatic nerve grafts or tubes placed in sites of complete spinal cord transection it has been shown that intraspinal neurons extend axons into permissive matrices placed in lesion sites (Xu et al., 1997). New advances involving genetic labeling of defined neuron types hold the potential to make this population

of neurons amenable to experimental study (more on this below). No discussion of axonal growth after spinal cord injury, whether resulting from regeneration or sprouting, is complete without reference to the problem of “false resurrections.” This refers to the risk of mistaking an unintentionally spared axon for a newly growing axon.

This issue in spinal cord regeneration see more research is no less important—or problematic—today than when it was addressed in detail in 2003 (Steward et al., 2003). Few additional comments can be added to the original commentary. It remains vitally important that any description of new axonal growth avoid this major pitfall, which can divert the field for years in pursuit of ephemeral notions that ultimately fail the test of replication. Two other potential sources of error in judging axonal growth after injury merit discussion. Depending on the type of spinal cord lesion created, and particularly in the case of compressive/contusive type injuries, the lesion gradually expands over several weeks into an oval or cigar-shaped cavity extending along the rostral-caudal spinal cord axis (Gruner et al., 1996). Thus, what begins as a small lesion can become an enlarged, elongated lesion. In judging axonal growth into and beyond this type of lesion, it is critical to define the boundaries of the expanded lesion so that one does not Cediranib (AZD2171) mistakenly assume axons have regenerated beyond a lesion when in fact they remain within a (larger)

lesion. Immunostaining for GFAP provides one way to define lesion margins, and immunostaining for vimentin, nestin, or NG2 can also be useful (Fitch and Silver, 2008). A second issue to consider in judging the effect of an experimental manipulation on axonal growth is the “dying back” phenomenon (Ramon y Cajal, 1928), wherein lesioned axons typically retract from the site of injury. Myelinated axons often retract approximately one myelinated segment to a node of Ranvier proximal to the lesion site. If an experimental therapy reduces axonal dieback, then it is possible to mistakenly interpret this as new axonal growth up to the lesion margin. This error can be avoided by sampling several time points shortly after the lesion, to determine whether axonal dieback followed by new growth has actually occurred.

2 mm ventral to the pial surface). In a subset of animals (n = 14), the second stimulating electrode was placed into the right thalamus (2.8 mm posterior to bregma, 3.0 mm lateral to midline, and 4.2 mm ventral to the pial surface) instead of the fimbria. Current pulses through the stimulating electrodes were generated by ISO-Flex stimulus isolation units (AMPI, Jerusalem, Israel) driven by a Master 8 Stimulator (AMPI). Intracellular microelectrodes were pulled from borosilicate glass tubing (1 mm outer diameter; World Precision Instruments, Sarasota,

FL, USA) to a resistance of 40–110 MΩ using a P-97 Flaming-Brown microelectrode puller (Sutter Instruments, Novato, CA, USA). Recording electrodes were filled with 2% Neurobiotin (Vector Laboratories, Burlingame, CA, USA) in 2 M potassium acetate and lowered into the right limbic striatum (1.2–1.8 mm anterior to bregma, 1.2–1.4 mm

lateral to midline, CX-5461 order and 3.5–6.5 mm below the pial surface) using a model 2662 Direct Drive Micropositioner (David Kopf). In 15 animals, 200 μM picrotoxin (Sigma-Aldrich, St. Louis), the GABAA open-channel blocker, was included in the intracellular solution contained in the recording electrode. Electrical signals from impaled cell membranes passed through a chloride-coated silver selleck compound wire housed inside the glass microelectrode via a headstage to an intracellular amplifier (IR-283, NeuroData, Delaware Water Gap, PA, USA). Intracellular signals were low-pass filtered at 2 kHz

(FLA-01, Cygnus Technologies, Delaware Water Gap, PA, USA), digitized (Digidata 1322A, Axon Instruments, Union City, CA, USA), sampled at 10 kHz using Axoscope (Axon Instruments), and stored on a PC. Once impaled, neurons were recorded in current-clamp mode at baseline for at least 5 min to ensure stability of membrane properties. Only cells exhibiting a resting membrane potential of at least −65 mV and action potential amplitude of at least 40 mV from threshold were used in this study. A series of positive and negative current steps delivered through the recording electrode (0.1– 0.5 nA, 100 ms) were used to assess the input resistance of recorded cells. Subsequent to baseline recordings, the responses of stable cells to medial PFC and fimbria TCL stimulation were assessed using the following protocol once every 15 s for 8–15 repetitions. A single-pulse stimulation of the fimbria (1.0 mA; 0.5 ms; F1) was delivered 500 ms before train stimulation of the mPFC (50 Hz train of ten pulses; 0.4–1.0 mA; 0.5 ms). A second fimbria pulse (1.0 mA; 0.5 ms; F2) was then delivered either 50 ms or 500 ms after the last pulse in the train stimulation of the PFC. This protocol was intended to test the effect of burst-like PFC stimulation on MSN responses to hippocampal inputs in the limbic striatum.

Such activity was only found in the left and right TPJ. No other brain region revealed BOLD signal changes that Selleckchem Alpelisib reflected such illusory changes in self-location. Although activity in right and left EBA and occipital cortex also revealed a three-way interaction, activity in these regions did not reflect self-location

(see the Supplemental Information). The left TPJ activation was centered on the posterior part of the superior temporal gyrus (pSTG). Mimicking behavioral changes in self-location and the reported first-person perspective, left TPJ activation in the Up- and Down-groups differed between synchronous and asynchronous stroking only during the body conditions (Figure 4A). In the Up-group, the BOLD response during the synchronous-body condition

http://www.selleckchem.com/screening-libraries.html (−0.14%) was lower than in the asynchronous-body condition [0.73%; F(1,20) = 6.1; p < 0.02]. The opposite effect was found in the Down-group, where the BOLD response during the synchronous-body condition (1.22%) was higher than in the asynchronous-body condition (0.42%; p < 0.03). The difference between synchronous and asynchronous stroking in the control conditions was not significant in both groups (all p > 0.15; Supplemental Information). We also found a significant Perspective by Stroking interaction (Supplemental Information). No other main effect or interaction was significant in this region (Supplemental Information). The cluster at the right TPJ was also centered on the pSTG,

and the BOLD response in this region also differed between synchronous and asynchronous stroking during the body conditions for both groups (Figure 4C). In the Up-group we found a lower BOLD response during synchronous (0.11%) than asynchronous stroking [1.14%; F(1, 20) = 7; p < 0.016], whereas in the Down-group we found the opposite trend with a higher BOLD response during the synchronous (1.03%) than the asynchronous stroking Rutecarpine condition (0.34%; p = 0.09). The BOLD response was not significantly different between synchronous and asynchronous stroking in the control conditions in both groups (all p > 0.32). No other main effect or interaction was significant in this region (Supplemental Information). To target brain regions reflecting self-identification (as measured by the questionnaire; question Q3; Figure 3) we searched for activity that could not be accounted for by the summation of the effects of seeing the body and feeling synchronous stroking. To this aim, we searched for brain regions showing an interaction between Object and Stroking characterized by a difference between the two body conditions, but not the control conditions. Such activity was only found in the right EBA. The ANOVA performed on the BOLD signal change in right EBA (Supplemental Information) showed a significant two-way interaction between Object and Stroking [F(1,20) = 6.56; p < 0.02], accounted for by the higher BOLD response in the body/asynchronous condition (1.

ADAM10 is a type I membrane protein synthesized as an inactive proenzyme and has an N-terminal prodomain that is removed by furin or proprotein convertase 7 (PC7) in the trans-Golgi network in order for the protease to become active ( Figure 1B). GSK3 inhibitor Mature ADAM10 resides on the cell surface, where it performs ectodomain shedding of diverse membrane protein substrates, including APP. Although a major function of the ADAM10 prodomain is to maintain the enzyme in an inactive state during synthesis and maturation, the prodomain also functions as an intramolecular chaperone that assists in the correct folding of the enzyme’s various domains. The importance

of prodomain chaperone function is underscored by the observation that expression of a prodomain-deleted ADAM10 construct results in a proteolytically inactive enzyme, whereas coexpression in trans of the prodomain with prodomain-deleted ADAM10 rescues enzyme activity ( Anders et al., 2001). Given the role of ADAM10 as the major APP α-secretase in the brain, Rudy Tanzi and colleagues at Massachusetts General Hospital and Harvard University assessed the candidacy of ADAM10 as a LOAD susceptibility gene. In a previous

study, the group genotyped 30 SNPs that spanned ADAM10 and then performed targeted resequencing of the gene. This investigation identified two rare highly penetrant nonsynonymous mutations (Q170H and R181G) associated with LOAD in the prodomain of ADAM10 ( Kim et al., 2009). These mutations occurred in 11 of 16 Panobinostat affected individuals from seven LOAD-affected families. In cell-culture experiments, ADAM10 with either the Q170H or the R181G prodomain mutation exhibited α-secretase activity that was reduced by greater than 70%. In Levetiracetam addition, in cells coexpressing the prodomain mutants with APP, Aβ production was increased 1.5- to 3.5-fold. These results indicate that ADAM10 is indeed a LOAD susceptibility gene and suggest the intriguing possibility that the ADAM10 prodomain mutations reduce proteolytic

activity, even though they are located far from the active site of the enzyme. In their article in this issue of Neuron, the Tanzi group tested the role of the ADAM10 prodomain mutations in AD pathogenesis by generating transgenic mouse lines that express ADAM10 harboring the Q170H or R181G mutations in the brain ( Suh et al., 2013). They also made control mouse lines expressing an artificial dominant-negative (DN) mutation, E384A, or wild-type (WT) ADAM10. Multiple lines of each transgenic construct were created, and expression levels across the various transgenes were matched. In addition, the team crossed the different ADAM10 transgenic lines with the well-characterized APP transgenic mouse, Tg2576, to determine the effects of the ADAM10 prodomain mutations on Aβ generation and amyloid deposition in the brain.

3). Even though only IL-13 was directly correlated with IFN-γ, the concomitant increase in IL-12 and IL-4 suggests an up-regulation of expression of IL-13 cytokine, reflecting a complex regulatory role of the mixed cytokine profile that is conducive to a protective response in Leishmania-infected dogs ( Fig. 3). In conclusion, the findings reported in this study are pertinent to understanding the dynamics of the immunological events associated with clinical status and skin parasite density during ongoing CVL. It

has been demonstrated that inflammatory cytokine profiles, particularly those driven by IFN-γ, TNF-α and IL-13, associated with enhanced expression of the GATA-3 transcription factor suggest that these genes MK-2206 order could be biomarkers for asymptomatic clinical forms in CVL. Moreover, IL-12 could play a protective www.selleckchem.com/products/chir-99021-ct99021-hcl.html role against parasite replication. On the other hand, in order to guarantee the survival and persistence of amastigotes in the skin compartment, the establishment of a regulatory profile, triggered by an increase in the immunoregulatory

cytokines IL-10 and TGF-β, is crucial. The results indicate that a concomitant expression of mixed cytokines, without the necessity for an absolute polarised profile, can tilt the immune system toward either a progressive or protective response in CVL. An advance in our knowledge of the mechanism that determines the protective immune response to L. chagasi infection in dogs will permit the establishment CYTH4 of a rational strategy for the development of vaccines and immunological therapies against CVL. The study was supported by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Brazil (PRONEX 2007). RCO, GCO, ABR, ATC and OAMF thank CNPq for fellowships. The authors wish to express their appreciation of the hard work carried out by the

staff of the Fundação Nacional da Saúde during the execution of this project. The authors are also grateful for the use of facilities at CEBIO, Universidade Federal de Minas Gerais and Rede Mineira de Bioterismo (FAPEMIG), and for support with the provision of experimental animals. “
“The identification of infectious agents in wild animals is not only crucial for the preservation of species but also provides valuable information regarding the epidemiological chain of diseases. This is particularly important with regard to members of the Cervidae, for example, whose natural habitat has been transformed significantly as a result of intense deforestation driven by the needs of farmers and cattle breeders. One consequence of such changes is that many cervids have started living in close proximity with domestic ruminants, hence favouring the interchange of infectious microorganisms between the populations.

Homogenates were centrifuged for 30min at 13,000 × g, 4°C to pellet cell debris and unsolubilized material. Mouse-anti-c-Myc (sc-40; Santa Cruz Biotechnology), mouse-anti-Ago2(2E12-1C9; Anova) or mouse IgG1 (Molipore)

conjugated protein G Dynabeads (Invitrogen) were added into supernatant, and the mixture was incubated in 4°C with end-over-end rotation for 4 hr. Beads were washed twice with low-salt NT2 buffer (50 mM Tris-HCl [pH 7.5], 150 mM NaCl, 1 mM MgCl2, 0.5% NP-40, 1 mM DTT, 100 U/ml RNasin) and twice with high-salt NT2 buffer (50 mM Tris-HCl [pH 7.5], 600 mM NaCl, 1 mM MgCl2, 0.5% NP-40, 1 mM DTT, 100 U/ml RNasin) and treated with Ivacaftor cost 0.6 mg/ml proteinase K for 20 min at 55°C. RNA was extracted by acid phenochloroform (Ambion), followed by chloroform, and precipitated with sodium

acetate and glycoblue (Ambion) in ethanol overnight −80°C. RNA pellet was washed once in 75% ethanol find more and resuspended in water for further application. Neocortex and cerebellum were dissected and cut into small pieces on ice before dissociation. Tissue dissociation was performed using Papain Dissociation System (Worthington Biochemical Corporation, Lakewood, NJ) according to manufacturer’s instruction. Cells were washed once with FACS buffer (1% BSA in PBS, 50 U/ml RNasin, 12.5 U/ml DNase), resuspended in 2ml FACS buffer with 1 μg/ml RNase-free propidium iodide for dead-cell discrimination. GFP-positive PI-negative single cells were FACS-sorted directly into Trizol-LS (Invitrogen) for RNA extraction according to manufacturer’s instruction. Real-time RT-PCR analyses of RNA purified by miRAP or from FACS sorted cells were carried out using Taqman MicroRNA Assays (Applied Biosystems) on 7900 HT real-time PCR machine (Applied Biosystems) according to the manufacturer’s instruction. All reactions were run in triplicate. Data were normalized to miRNA-124. When deep sequencing data was compared with RT-q-PCR data, the per million reads number for also each miRNA was log2 transformed and normalized to miRNA-124. Libraries for deep sequencing

were prepared from RNAs extracted from immunoprecipitation products following standard protocol. Briefly, RNA was successively ligated to 3′ and 5′ adaptors, gel purified after each ligation, reverse transcribed, and PCR amplified using Solexa sequencing primers. PCR product was gel purified, quantified, and sequenced for 36 cycles on Illumina Genome Analyzer II. Radiolabeled synthetic RNA oligos (M19, CGUACGGUUUAAACUUCGA; and M24, CGUACGGUUUAAACUUCGAAAUGU) were spiked in to trace RNA on UREA-PAGE during library preparation, and were depleted by PmelI digestion after PCR amplification. Significant amount of oligos were retained in the libraries and were used as spike-in oligo control for RNA editing analysis. Raw Illumina sequencing reads were trimmed from 3′ linker, filtered for low-quality reads, and collapsed to unique sequences retaining their individual read count information.

carneum, P. paneum or P. psychrosexualis. The latter three species produce several mycotoxins ( Frisvad and Samson, 2004 and Houbraken et al., 2010) and have often been referred to as P. roqueforti ( Engel and von Milczewski, 1977, von Krusch et al., 1977, Olivigni and Bullerman, 1978, Engel and Prokopek, 1980, Teuber and Engel, 1983 and Erdogan and Sert, 2004). However, P. roqueforti itself can produce the secondary metabolites

PR-toxin, roquefortine C, mycophenolic acid and andrastin A in pure culture ( Frisvad et al., 2004 and Nielsen et al., 2005). One of these secondary metabolites is regarded as a mycotoxin, PR-toxin. This mycotoxin is unstable Epigenetics Compound Library mw in cheese and is converted to PR-imine ( Engel and Prokopek, 1979 and Siemens and Zawistowski, 1993). Mycophenolic acid ( Lafont et al., 1979 and López-Díaz et al., 1996), roquefortine C ( López-Díaz et al., 1996 and Finoli et al., 2001) and andrastin A ( Nielsen et al., 2005 and Fernández-Bodega et al., 2009) have been found in blue cheese, but the consequences to human health are probably minor ( Larsen et al., 2002). Yet another species, Penicillium solitum is found on naturally fermented lamb meat on the Faroe Islands, and may be used as a starter selleck chemicals llc culture. This

species does not produce any known mycotoxins ( Frisvad et al., 2004). On other meat products, Penicillium nalgiovense and few strains of Penicillium chrysogenum are used ( Nout, 2000 and Frisvad and

Samson, 2004), especially for mold-fermented salami. However, P. nalgiovense was originally found on cheeses from Nalzovy, and may be used for fermenting cheeses too. Verticillium lecanii has changed to Lecanicillium lecanii ( Zare and Gams, 2001), and this strain has been listed as potentially through useful for cheese ripening (see Table 2 and Table 3). Finally, some fungi can be used to produce food colorants, including Epicoccum nigrum and Penicillium purpurogenum, but these fungi are not used directly for food fermentation ( Stricker et al., 1981 and Mapari et al., 2010). The list of microorganisms with a history of use in food originally included 31 genera in the 2002 IDF inventory, and was essentially limited to the microbial use in dairy matrices. By also considering other food matrices, we consider 62 genera in the 2011 update. One was rejected as its usage in food has not been documented and the initial reference in the 2002 IDF inventory was inadequate. The evolution in taxonomy, the extension of varied usages in other matrices, yeast fermentations and fungal foods have also resulted in a growing number of species; from 113 to 264 species with demonstration of food usage. There are many new possibilities, however, and these should be explored to a much greater extent. Either in traditional fermented foods or as new opportunities, the rationalized use of microorganisms in our diet opens new perspectives.

(2010) study (seven animals). In this task, animals learned the locations of three new goals where food reward were hidden each day. The animal’s memory performance was assessed before and after the learning (preprobe and the postprobe sessions) and the animals were allowed to sleep before and after the learning in presleep and postsleep sessions (Figure S1). During learning some of the place cells remapped their place fields. Moreover, the successful recall of newly learned goal locations in the postprobe session was associated with the reinstatement of the new place field representations that were developed during learning (Dupret et al., 2010). First, we examined whether spatial learning was accompanied by interneuron

Veliparib firing rate changes as reported during exploration BKM120 mw of novel environments (Frank et al., 2004; Nitz and McNaughton, 2004; Wilson and McNaughton, 1993). Firing rate changes of interneurons were observed during learning on the cheeseboard maze, and these followed a similar time course to the reorganization of pyramidal cell assemblies. About 25% of interneurons exhibited significant increases in their rate, while an additional 43% showed significant decreases (Figure 1). Such mean rate changes of interneurons were not observed when the animals performed the task without the allocentric learning context where reward locations were indicated by intramaze cues (Figure S2). Since

the behavioral patterns of the animals during the cued and the allocentric conditions were similar, it is unlikely that interneuron rate changes were attributed L-NAME HCl to behavioral changes or related factors such as the speed of the animal. Instead, the observed interneuron rate changes might have signaled the formation of new associations to new pyramidal assemblies that were developed during the allocentric learning of reward locations. To test for the development of interneuron associations to new pyramidal assemblies, we examined whether interneuron rates mirrored the dynamic reorganization of pyramidal assemblies during map formation. High-fidelity associations would

require interneurons to fire stronger in time periods when new maps are accurately expressed. In contrast, a negative association may signal that interneurons reduce their firing when the newly formed pyramidal patterns are present. Pyramidal cell assemblies can rapidly switch across theta cycles when certain environmental features are rapidly altered (Jezek et al., 2011). In our analysis we also used theta cycles (5–12 Hz) as time windows to measure the instantaneous firing rate of interneurons and to quantify the firing association of interneurons to pyramidal assembly patterns (Figure 2). The expression of the new maps was assessed in each theta cycle by testing whether the ongoing pyramidal network activity was more similar to the old or the new assembly patterns representing the current location.