Live time-lapse imaging was done in an environmentally controlled

Live time-lapse imaging was done in an environmentally controlled chamber with 5% carbon dioxide at 37°C, using an Axiovert 200M (Zeiss) confocal system equipped with spinning-disk (Perkin Elmer). The 100× objective and the 561 nm laser line were used for acquisition. Cultured hippocampal neurons (DIV20) were imaged every 10 min for 40 min. Z-space slices (0.5 μm) were captured and flattened by maximum projection. Image analysis was performed with the Volocity High-Performance Imaging System.

Live time-lapse imaging was performed in an environmentally Tenofovir in vivo controlled chamber with 5% carbon dioxide at 37°C, using an Axiovert 200M (Zeiss) confocal system equipped with spinning-disk (Perkin Elmer). The 100× objective and the 561 nm laser line were used for acquisition. Cultured hippocampal neurons (DIV20) were imaged every 10 min for a total period of 40 min. Z-space slices (0.5 μm) were captured and flattened by maximum projection. Image analysis was performed with the Volocity High-Performance Imaging

System. Live hippocampal neurons (DIV15–18) were incubated (10 min, 37°C) with antibody against the GluA2 extracellular Selleckchem Cabozantinib region (Chemicon, concentration 10 μg/ml). After washing in PBS with 1 mM MgCl2 and 0.1 mM CaCl2, neurons were returned to growth medium at 37°C for 0, 5, or 10 min, fixed for 7 min at room temperature in 4% paraformaldehyde/4% sucrose without permeabilization, and stained with a Cy3-conjugated secondary antibody for 1 hr at room temperature to visualize surface receptors. The neurons were then stained with a Cy5-conjugated secondary antibody for 1 hr at room temperature under permeabilizing conditions with GDB buffer (30 mM phosphate buffer pH 7.4 containing 0.2% gelatin, 0.5% Triton X-100, and 0.8 M NaCl), to visualize internalized receptors. In some experiments, dynasore (80 μM, Tocris Bioscience)

was added for 30 min to block receptor internalization; primary antibody was then applied. Whole-cell patch clamp recordings were performed at room temperature on 10–13 DIV primary hippocampal pyramidal neurons perfused continuously with artificial cerebrospinal fluid (aCSF). mEPSCs were recorded at holding potential −70 mV over Oxalosuccinic acid 5–15 min. The 10%–90% rise time (Rt) and weighted decay time constant (Dt) of mEPSCs were calculated as described (Cingolani et al., 2008) and were unaffected by TSPAN7 knockdown: Rt/Dt: 0.58 ± 0.02/2.72 ± 0.14 (control) 0.57 ± 0.02/2.90 ± 0.17 (siRNA14); 0.58 ± 0.03/2.86 ± 0.13 (siRNA47); 0.54 ± 0.03/2.73 ± 0.24 (rescue WT). Whole-cell paired-recordings from monosynaptically connected primary hippocampal pyramidal neurons were performed at 11–15 DIV. See Supplemental Experimental Procedures for details. Hippocampal neurons were infected at DIV11 with siRNA14 or scrambled siRNA14. Chemical LTP was induced at DIV18 by treating the neurons for 3 min with an extracellular solution (140 mM NaCl, 1.

Our results, showing that the basal ganglia in songbirds is neces

Our results, showing that the basal ganglia in songbirds is necessary for learning spectral, but not temporal, aspects of vocal output add important nuance to this question. Whether this reflects a general difference in how the basal ganglia contributes to motor skill learning remains to be explored, but our current study strongly suggests

that the distinction between timing and motor implementation (Figures 1A–1C) is a crucial one to make when considering basal ganglia function in the context of motor learning. Control of motor timing in humans is thought to involve prefrontal regions (Halsband et al., 1993 and Harrington and Haaland, 1999), yet little is known about how these circuits represent the temporal structure of motor output, and whether they are involved in learning. HVC, the equivalent structure in songbirds, has been studied in far greater detail. It is thought to control song timing in Selleckchem Ruxolitinib the form of a synaptically connected chain of

neurons, where each node represents a specific time point in the song (Li and Greenside, 2006 and Long et al., 2010) (Figure 1H). Our HVC recordings during temporal learning, however, show HVC to be Selleck Lonafarnib more than an immutable time keeper. We observed activity patterns in this premotor nucleus stretch and shrink with the song (Figure 7), suggesting that temporal structure is modified by locally tuning the propagation speed within the network. Thus, rather than representing time, our result suggests that neurons in HVC encode specific parts of the song, e.g., the starts and ends of syllabic or subsyllabic elements,

the relative timings of which can be adjusted independently from other features of the song. Modulating dynamics in HVC by means of temperature has previously been shown to uniformly alter song tempo without interfering with spectral content (Aronov and Fee, 2012 and Long and Fee, 2008). Our results show that similar changes to HVC dynamics and song can be induced and consolidated through reinforcement learning. Moreover, we show that the temporal changes to song structure can be specific to certain parts of the song. The ability to shape the temporal structure of birdsong in such a specific manner is likely to be ethologically relevant: temporal features, such as syllable duration, distinguish Chlormezanone song dialects (Wonke and Wallschläger, 2009) and can be shaped by exposure to different habitats (Kopuchian et al., 2004). The ability to adaptively modify timing without interfering with other aspects of behavior may be critical to the acquisition and refinement of many motor skills also in humans (Gentner, 1987). Subtle changes to the temporal structure of syllables in human speech, for example, do not unduly change spectral aspects of vocal output (Cai et al., 2011). Furthermore, when a targeted syllable segment is experimentally lengthened (Cai et al., 2011), subsequent speech patterns are similarly delayed to account for the increase in target duration, i.e.

Indeed, it has recently been suggested that interneurons might as

Indeed, it has recently been suggested that interneurons might assist in the organization of pyramidal cell assemblies during learning (Assisi et al., 2011; Buzsáki, 2010). For instance, the abrupt change of interneuron firing rates observed while the animal is exposed to a novel environment could promote the formation of new maps and the associated reorganization of pyramidal assemblies (Frank et al., 2004; Nitz and McNaughton, 2004; Wilson and McNaughton, 1993). If interneurons have a role in shaping pyramidal cell assemblies, it is possible that spatial learning and the

associated formation of new pyramidal assemblies may be accompanied by alterations in interneuron circuitry as well. One possible circuit change may occur on local pyramidal inputs targeting

MDV3100 interneurons, which itself could contribute to the interneuron firing rate changes during spatial learning. Indeed, glutamatergic synapses targeting GABAergic interneurons in the hippocampus are modifiable in an activity-dependent manner (Alle et al., 2001; Lamsa et al., 2005, 2007; Perez et al., 2001). Given that a single presynaptic pyramidal cell can reliably excite its postsynaptic interneurons in the hippocampus, the modification of pyramidal cell-interneuron connections can exert wide-ranging impact on circuit function (Csicsvari et al., 1998; Fujisawa et al., 2008; Gulyás et al., 1993; Marshall et al., 2002; Maurer et al., learn more 2006; Miles, 1990). In this study, we examined whether old and newly established network assemblies flicker to test the hypothesis that hippocampal map competition occurs

during spatial learning. In addition, we investigated the contribution of inhibitory circuits by testing the hypothesis that the formation of behaviorally-relevant pyramidal cell assemblies involves the modification of inhibitory microcircuits. We found that the flickering of old and new maps takes place during spatial learning. Surprisingly, many interneurons reorganized their firing patterns during learning, unless forming dynamic associations to the new assemblies in relation to the assembly flickering. Moreover, by measuring spike transmission probability between monosynaptic pyramidal cell-interneuron pairs, we assessed changes of local excitatory connections onto these interneurons. We found that pyramidal cell connections to interneurons exhibited map-specific changes that were developed during learning, which in turn can explain the newly formed associations between interneuron firing and pyramidal assemblies. To explore how interneurons change their coupling strength to pyramidal cell assemblies during spatial learning, hippocampus circuit activity from the CA1 pyramidal cell layer was recorded using multichannel extracellular techniques in rats performing a spatial learning task on a cheeseboard maze (see Figure S1 available online; Experimental Procedures; Dupret et al., 2010).

Electron microscopy confirmed the presence of synaptic contacts b

Electron microscopy confirmed the presence of synaptic contacts between OT immunoreactive axon terminals and dendrites in the CeL. Furthermore, colocalization of the glutamate transporter VGLUT2 indicated that these synapses are likely to release

glutamate in addition to OT. The presence of OT axonal projections in the CeA leads to the question of how their stimulation affects information processing in the CeA. The authors, as well as others, have shown that CeM output cells are under tight inhibitory control by GABAergic interneurons located in CeL and that exogenous application learn more of OT in the CeL results in inhibition of neuronal activity in the CeM (Cassell et al., 1999, Huber et al., 2005, Ehrlich et al., 2009 and Viviani Apoptosis Compound Library nmr et al., 2011). The CeM, in turn, is well known as the major output by which the amygdala determines the expression of fear-related behaviors (LeDoux, 2000 and Maren and Quirk, 2004). A microcircuit within CeA important for acquisition as well as expression of fear has recently been characterized (Haubensak et al., 2010). Pharmacological inactivation of CeL in mice resulted in freezing, a characteristic fear behavior, and this effect could also be triggered by optogenetic activation of CeM (Ciocchi et al., 2010). Does local, endogenous release of OT affect neuronal activity within this microcircuit? In the present study, this question was initially

addressed using an in vitro optogenetic approach in acute brain slices. Fiber terminals of channelrhodopsin-2 (ChR2)-expressing OT neurons in the CeL were exposed to blue light during whole-cell recordings of CeL neurons. Interestingly, one-third of the recorded

cells responded to light exposure with an increase in action potential frequency, an effect many that was blocked by application of an OT antagonist to the slice. The authors then investigated the downstream consequences of this increased activity of CeL neurons by recording from their targets in the CeM. Light stimulation of OT fibers in the CeL resulted in a dramatic increase in the frequency of inhibitory postsynaptic currents in CeM neurons. Again, this effect could be prevented by blocking OT receptors. Knobloch et al. (2012) next investigated whether local axonal release of OT within CeL would have an effect on fear-related behavior in vivo. To accomplish this, optical fibers targeting the CeL were implanted in rats expressing ChR2 in hypothalamic OT neurons (Figure 1). The authors hypothesized that evoked OT release within CeL should lead to attenuation of fear. To test this, rats were first run through a contextual fear conditioning procedure during which they received several mild electrical shocks in a novel environment. When these rats were put back into the context in which they had been shocked, they exhibited strong freezing responses indicative of high fear levels.

Only areas AL and RL were statistically indistinguishable from ea

Only areas AL and RL were statistically indistinguishable from each other across all mean tuning metrics.

A formal comparison of the proportion of responsive cells in each area revealed statistical differences between AL and RL (χ2 = 31.535, 1 degree of freedom, p < 0.0001 for TF proportion, χ2 = CAL-101 clinical trial 5.047, 1 degree of freedom, p < 0.05 for SF proportion). These results demonstrate that the mouse visual areas investigated in this study are functionally distinct and are specialized to represent different spatiotemporal information. In terms of general trends in encoding combinations of visual features, some relationships were evident in the mean tuning across visual areas and in cell-by-cell population correlations of each visual area. In most cases, significant correlations in the populations of individual

neurons were generally low (generally less than or equal to R = 0.3, Figure S6). This seemed to indicate that populations of neurons in each area were more or less evenly distributed Cisplatin nmr in terms of tuning for pairs of stimulus parameters. Still, some trends were observed, and they may be informative in understanding relationships between tuning for different stimulus parameters. For example, orientation and direction selectivity appear closely related across areas in terms of mean OSI and DSI and are positively correlated in terms of cell-by-cell correlations in areas V1 and LM (Figure 7B and Figure S6B). Areas that prefer high SFs tend to prefer low TFs, except for areas AM and especially LI, which have particularly high mean preferences for both (Figure 7A). Area LI is the only area with a strong negative correlation between SF and TF tuning on a population level (R = the −0.77, p < 0.05, Bonferroni corrected), suggesting that neurons in this area tend to either encode high TFs or high SFs, but not the combination of both (Figure S6A). Areas with high mean preferred TF tend to have higher mean OSI and DSI (Figures 7C and 7D). Positive correlations between these metrics were found for areas V1 and AL for OSI and areas

V1, LM, AL, and RL for DSI across each population of neurons (Figures S6C and S6D). The relationships between SF tuning and orientation and direction selectivity are most apparent in cell-by-cell correlations, which show positive correlations between preferred SF and OSI in areas V1, LM, and AL (Figure S6E). SF and DSI are negatively correlated in areas AL, RL, and PM and weakly positively correlated in V1 (Figure S6F). In the present study, we found that mouse visual cortex contains a highly organized arrangement of distinct visual areas, which each encode unique combinations of spatiotemporal features. Our nearly complete, high-resolution retinotopic maps reveal a continuous fine-scale organization across mouse visual cortex, comprising at least nine independent representations of the contralateral visual field.

, 2001 and Toepper et al , 2010) These studies have largely emph

, 2001 and Toepper et al., 2010). These studies have largely emphasized hippocampal—not PRC—contributions to working memory, which is not immediately consistent with the intact performance of the individuals with selective hippocampal damage reported here. Nonetheless, it seems likely that the conjunctive representations contained in PRC are essential to maintain information buy Erastin while shifting attention from one complex object to the other. It is important to note, however, that other studies have demonstrated that PRC damage impairs complex object perception on tasks with no working memory component (e.g., perception of single objects), suggesting the

deficits observed here are unlikely to be due entirely to working memory (Barense et al., 2011b and Lee and Rudebeck, 2010). That said, both perception and online maintenance of complex objects require the ability to represent conjunctions of object features, and thus, impoverished representations will cause deficits in both processes.

As such, we prefer to consider these findings in terms of a representational deficit, rather than a deficit in a given psychological construct (e.g., working memory versus perception). Here, across four experiments, we present results from a perceptual discrimination task that was shown with eye tracking to emphasize processing conjunctions of object Paclitaxel features (experiment 1) and with fMRI to recruit the PRC (experiment 2). Individuals with MTL damage that included the PRC, but not those with damage limited to the hippocampus, were impaired on this task (experiment 3). Critically, when we minimized perceptual interference

through by reducing the number of repeating features across successive trials, we recovered performance of the MTL cases to normal levels (experiment 4). In contrast to conventional accounts of MTL amnesia, the performance of the MTL cases with PRC damage reported here offers the somewhat paradoxical conclusion that intact memory for irrelevant, lower-level features processed on previous trials can impair perception in cases with memory disorders. These data are thus not consistent with the view of the MTL as a unitary, dedicated memory system. The data are, however, perfectly consistent with the predictions of the representational-hierarchical theory, which states that the PRC is necessary for representing the conjunctions of features that distinguish perceptually similar objects. These representations become especially critical when the capacity of more posterior regions in the ventral visual stream is exceeded by presentations of multiple, similar features across trials. Indeed, these data provide the first conclusive evidence from humans to complement the related findings from rat lesion studies and computational modeling: namely, that performance of individuals with PRC damage can be rescued by reducing the degree of perceptual interference ( Bartko et al., 2010, Burke et al., 2010, Cowell et al., 2006 and McTighe et al.

AAV-CaMKIIa-eNpHR3 0-eYFP or AAV-CaMKIIa-eYFP (from Gene Therapy

AAV-CaMKIIa-eNpHR3.0-eYFP or AAV-CaMKIIa-eYFP (from Gene Therapy Center at University of North Carolina at Chapel Hill, courtesy of Dr. Karl Deisseroth) was injected bilaterally in OFC under stereotaxic guidance at AP −3.0 mm, ML ± 3.2 mm, and DV 4.4 and 4.5 mm from the brain surface. A total 1–1.2 μl of virus (titer ∼1012) per hemisphere was

delivered at the rate of ∼0.1 μl/min by Picosptrizer microinjection system (Parker, Hollins, NH). Two rats that received eNpHR3.0 transgene were saved for later slice work; the remaining rats designated for behavioral testing had optic fibers (200 μm in core diameter; Thorlab, Newton, NJ) implanted bilaterally at AP −3.0 mm, ML ± 3.2 mm, and DV 4.2 mm. At the end of the study, these rats were perfused with phosphate buffer saline and then 4% PFA. The brains were then immersed in 30% sucrose/PFA for at least 24 hr. The brains were sliced at 40 μm with a microtome. The Selleck R428 brain slices were then stained with DAPI (through Vectashield-DAPI, Vector Lab, Burlingame, CA) or NeuroTrace (Invitrogen, Carsbad, CA) and mounted to slides with Vectashield (in the case of staining with NeuroTrace)

mounting media. The location of the fiber tip and NpHR-eYFP or eYFP expression was verified using an Olympus confocal microscope. The Z-stack images were merged and processed in Image J (National Institutes of Health). Approximately 2 months after surgery, two rats that had received AAV-CaMKIIa-eNpHR3.0-eYFP injection were anesthetized with isoflurane and perfused check details transcardially with ∼40 ml ice-cold NMDG-based artificial CSF (aCSF) solution containing (in millimoles) 92 NMDG, 20 HEPES, 2.5 KCl, 1.2 NaH2PO4, 10 MgSO4, 0.5 CaCl2, 30 NaHCO3, 25 glucose, 2 thiourea, 5 Na-ascorbate, 3 Na-pyruvate, and 12 N-acetyl-L-cysteine (300–310 mOsm, pH 7.3∼7.4). After perfusion, the brain was immediately removed and Isotretinoin 300 μm coronal brain slices containing the OFC were made using a Vibratome (Leica, Nussloch, Germany). The brain slices were recovered for less than 15 min at 32°C in NMDG-based aCSF and then transferred and stored for at least 1 hr in HEPES-based aCSF containing

(in mM) 92 NaCl, 20 HEPES, 2.5 KCl, 1.2 NaH2PO4, 1 MgSO4, 2 CaCl2, 30 NaHCO3, 25 glucose, 2 thiourea, 5 Na-ascorbate, 3 Na-pyruvate, and 12 N-acetyl-L-cysteine (300–310 mOsm, pH 7.3∼7.4, room temperature). During the recording, the brain slices were superfused with standard aCSF constituted (in millimoles) of 125 NaCl, 2.5 KCl, 1.25 NaH2PO4, 1 MgCl2, 2.4 CaCl2, 26 NaHCO3, 11 glucose, 0.1 picrotoxin, and 2 kynurenic acid, and was saturated with 95% O2, and 5% CO2 at 32°C–34°C. Glass pipette (pipette resistance 2.8–4.0 MΩ, King Precision Glass, Claremont, CA) with K+-based internal solution (in millimoles: 140 KMeSO4, 5 KCl, 0.05 EGTA, 2 MgCl2, 2 Na2ATP, 0.4 NaGTP, 10 HEPES, and 0.05 Alexa Fluor 594 [Invitrogen, Carlsbad, CA], pH 7.3, 290 mOsm) was used throughout the experiment.

Similar to results in mass cultures, NGF treatment of distal axon

Similar to results in mass cultures, NGF treatment of distal axons leads to a reduction (24% decrease) in phosphorylated dynamin1, in comparison to control treatment (Figure 5C and 5D). To test whether NGF regulates phosphorylation of dynamin1 in axons in vivo, we analyzed the levels of phospho-dynamin1 in a sympathetic target tissue, the salivary glands, in both wild-type and heterozygous NGF (NGF+/−) mice. Given that dynamin1 is neuron specific ( Urrutia et al., 1997), immunoblotting of salivary gland lysates with the phospho-dynamin1 antibody should reveal the status of dynamin1 phosphorylation FG-4592 solubility dmso locally in sympathetic nerve terminals that innervate

the target tissue. If target-derived NGF regulates dynamin1 phosphorylation

in vivo, then we would expect to see increased dynamin1 phosphorylation levels under conditions of reduced NGF signaling. We employed NGF+/− mice for this analysis because these mice display haploinsufficiency with reduced levels of NGF and sympathetic target innervation ( Brennan et al., 1999 and Ghasemlou et al., 2004), in contrast to homozygous selleck chemicals llc NGF null mice, which completely lack sympathetic innervation ( Glebova and Ginty, 2004). We found that NGF+/− mice have higher levels of phosphorylated dynamin1 on Ser-778 in sympathetic axons innervating the salivary glands, compared to wild-type animals (11.2% ± 2% increase;

Figures 5E and 5F). These findings provide in vivo evidence for NGF-dependent phosphoregulation of dynamin1 locally in sympathetic axons. To assess the role of dynamin1 dephosphorylation in supporting neurotrophin-dependent axon growth, sympathetic neurons were exposed for 24 hr to a cell-permeable peptide spanning the dynamin1 phospho-box (amino acids 769–784, incorporating Ser-774 and Ser-778) in which the two serines 774/778 were replaced with alanine (Ser774/778-Ala, dyn1769-784AA). The dyn1769-784AA peptide blocks dephosphosphorylation-dependent dynamin1 functions by binding and sequestering downstream effector molecules, such as syndapin1 (Anggono et al., 2006). Delivery of dyn1769-784AA (300 μM) into sympathetic neurons reduced NGF-mediated axon growth from an MYO10 average of 177 ± 14 μm/day to 90.6 ± 7.2 μm/day (Figures 5G, 5H, and 5M). In contrast, introduction of the phospho-mimetic peptide dyn1769-784EE (in which the serines 774/778 were substituted with glutamate) had no effect on NGF-mediated axon growth (Figures 5I and 5M). NT-3-mediated axon growth was not affected by delivery of either dyn1769-784AA or dyn1769-784EE (Figures 5J, 5K, 5L, and 5M). Together, these results provide evidence that calcineurin-mediated dephosphorylation of dynamin1 is a key signaling mechanism necessary for NGF-mediated, but not NT-3-mediated, axon growth.

JNK3 indeed phosphorylates APP at T668P in FAD brains, without af

JNK3 indeed phosphorylates APP at T668P in FAD brains, without affecting the total APP protein levels ( Figure 5G): while the human APP levels in whole-cell

lysates were not very different between FAD:JNK3+/+ and FAD:JNK3−/− mice, p-T668P signals as well as human APP protein levels were significantly reduced when membrane fractions were analyzed ( Figure 5G). It should be noted that sw192 antibody is specific to Swedish mutation in human APP ( Haass et al., 1995), thus it was used as a marker for FAD mice. In particular, p-T668P levels in membrane fractions were reduced to a much greater extent in α and β CTF than in the full-length APP with JNK3 deletion. This finding closely parallels the observation in human AD brains, wherein increased T668P phosphorylation mainly associated with α and β CTF and not the full-length APP ( Lee et al., 2003). In addition, total protein levels of α and β CTF were also reduced to a much CSF-1R inhibitor greater extent than those in the full-length APP in the membrane fraction ( Figure 5G). These results correlate faithfully with our Aβ42 Elisa results at 6 months. We therefore interpret these results as suggesting that JNK3 phosphorylates APP preferentially in membranous compartments, such as vesicles/endosomes,

thereby promoting APP processing. It should be noted that although BACE1 and PS1 levels were increased in FAD mice compared to those in normal mice as reported ( O’Connor Paclitaxel in vitro et al., 2008), JNK3 deletion did not affect their levels greatly ( Figure 5H). Similarly, neither the levels nor the extent

of tau phosphorylation old was altered by JNK3 deletion in FAD mice (data not shown). In a preliminary RNaseq-based transcriptome analysis of 3-month-old FAD mice with and without JNK3 and the control cortices from JNK3+/+ and JNK3−/− mice, we obtained the results that suggest that there is a general translational block in FAD:JNK3+/+ mice; genes involved in translation, such as ribosomes and translation-initiation factors, were dramatically reduced in FAD:JNK3+/+ compared to JNK3+/+ mice and JNK3 deletion restored the effect on these genes to nearly normal levels (data not shown). We therefore tested whether there is indeed a global translational block in FAD mice by western blotting cortical lysates with an antibody against phospho-S6235/236 ribosomal protein, a marker for active translation. Indeed, the p-S6 signal was reduced by 48% in FAD: JNK3+/+ mice, compared to that in the normal mice and FAD:JNK3−/− mice ( Figures 6A and 6B). Immunohistochemistry with p-S6 antibody also revealed similar findings: both the number of cells that are positive for p-S6 signals and the intensity of its signals decreased significantly in the cortex of FAD:JNK3+/+ mice, compared to those in other genotypes ( Figure 6C). It should also be pointed out that p-RaptorS792 levels were increased by 4-fold in FAD:JNK3+/+ compared to those in FAD:JNK3−/− ( Figures 6A and 6B).

We have previously shown that reactivation occurring during quies

We have previously shown that reactivation occurring during quiescent SWRs tends to be a less faithful recapitulation of stored memories than activity during awake SWRs (Karlsson and Frank, 2009). We therefore asked how gamma oscillations during quiescent SWRs, defined as SWRs that occurred in the rest box when animals had been still for >60 s, differed from gamma seen during awake SWRs. Quiescent SWRs were accompanied by transient increases in gamma power in CA1 and CA3 (Figure 8A; Kruskal-Wallis ANOVA, post hoc tests; power > baseline; CA1: −100 to 400 ms relative to SWR onset,

peak p < 10−5; CA3: 0–400 ms, peak p < 10−5). Furthermore, gamma power in both CA1 and CA3 was significantly predictive of the presence of an SWR during rest sessions (Figure S8). There was a small but significant increase in CA3-CA1 gamma coherence during quiescent SWRs (Figure 8B; Kruskal-Wallis ANOVA, Selleckchem GDC 0068 post hoc tests; coherence > baseline; 100 ms p < 10−5; 0, 200–400 ms, p < 0.05) that was significantly predictive of SWR occurrence (Figure S8), but there MI-773 mouse was no consistent increase in gamma phase locking (Figure 8C). The smaller increase

in gamma synchrony during quiescent SWRs could be explained in large part by an increase in baseline synchrony during quiescence. The baseline gamma coherence and phase locking were higher during quiescent SWRs (Figures 8B and 8C; rank sum test; baseline quiescent > awake; coherence p < 10−5; phase locking p < 10−5). Furthermore, while gamma synchrony reached a slightly higher level during quiescent SWRs as compared to awake SWRs (Figures 8B and 8C; rank sum tests; quiescent > awake 100 ms following SWR; coherence Phosphoprotein phosphatase p < 10−5; phase locking p < 10−5), the higher baseline synchrony means that SWR-associated increases reflected a smaller change than seen during awake periods. Do gamma oscillations clock the replay of previous experiences

when animals are at rest? The spiking of putative excitatory neurons in both CA1 (n = 11,794 spikes from 375 neurons) and CA3 (n = 8,249 spikes from 391 neurons) was significantly phase locked to gamma oscillations during quiescent SWRs (Figure 8D; Rayleigh tests; CA1 p < 0.01; CA3 p < 0.01). However, there was less modulation of CA1 and CA3 spiking during quiescent SWRs as compared to awake SWRs (bootstrap resampling; CA1 p < 0.01; CA3 p < 0.05). Furthermore, there was no significant difference in the modulation of either CA3 or CA1 spiking during SWRs as compared to the 500ms preceding SWR detection. Thus, although CA3 gamma oscillations modulate CA3 and CA1 spiking throughout quiescent states, gamma modulation during quiescence is never as large as observed during awake SWRs. We then asked whether gamma could serve as an internal clock for quiescent memory replay.