An important hallmark of C3-C4 propriospinal

neurons is t

An important hallmark of C3-C4 propriospinal

neurons is the establishment of a bifurcating axonal trajectory (Figure 8A). Descending collaterals establish synaptic connections to motor neurons at C6-T1 and interneurons, whereas ascending axon collaterals extend to the lateral reticular nucleus (LRN), which in turn gives rise to mossy fiber inputs to the cerebellum (Figure 8A). A series of lesion studies in the cat proposes an essential role of these relay neurons in target reaching of the MLN0128 concentration forelimb. Both excitatory and inhibitory neurons are contained within C3-C4 propriospinal neurons, but genetic identity of this specialized premotor action reporting system is currently unknown. The spinal cord is the origin of a diverse set of spinocerebellar projection neurons, establishing direct mossy fiber input to cerebellar granule cells (Orlovsky et al., 1999 and Oscarsson, 1965). Details regarding the anatomical and functional diversification of spinocerebellar projection neurons extend beyond the scope of

this Review; however, in considering these issues more broadly, a few important points can be Cell Cycle inhibitor made. Functionally distinct populations of spinocerebellar neurons are generally located at defined rostrocaudal segments in conserved laminar positions and establish projections to stereotyped cerebellar lobules. Ventral spinocerebellar tract (VSCT) neurons reside at lumbar

levels and are active preferentially during the flexion phase of stepping, monitoring intrinsic spinal network activity in the cat (Arshavsky et al., 1978) (Figure 8B). In contrast, Clarke’s column (CC) neurons are located more rostrally, receive direct sensory feedback (Walmsley, 1991), integrate this information with descending corticospinal input, and express the neurotrophic factor GDNF ( Hantman and Jessell, 2010) ( Figure 8B). Spatial and functional diversification of ascending spinal projection neurons highlights the need to understand the developmental and genetic cascades involved in their specification. much At the mechanistic level, neuron diversification along the rostrocaudal axis has been studied most extensively for motor neurons, in which combinatorial expression of different Hox transcription factors plays important roles (Dalla Torre di Sanguinetto et al., 2008, Dasen et al., 2005 and Dasen et al., 2008). Since all spinal neurons arise locally, these include long-distance projection neurons to supraspinal targets. A possible mechanism for generation of required diversity at the molecular level may therefore be an intersection between dorsoventral and Hox transcriptional networks. Recent studies have begun to address how early developmental diversification relates to connectivity and function and have added an important facet to our understanding of motor circuits.

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05, circular ANOVA) Previous V4 studies have shown that selectiv

05, circular ANOVA). Previous V4 studies have shown that selective attention to a single stimulus inside an RF increases not only firing rates, but also gamma-band LFP power, MUA-LFP and MUA-MUA gamma-band coherence (Fries et al., 2001b, Fries et al., 2008 and Gregoriou et al., 2009). Indeed, we observed a significant average

increase (p < 0.001, bootstrap test) in MUA-LFP gamma PPC, with the majority of MUAs (p < 0.001, http://www.selleckchem.com/products/hydroxychloroquine-sulfate.html binomial test, n = 129) having higher gamma PPCs with attention inside their RF (Figures 6A–6D). This effect was strongest at a higher gamma frequency (∼60 Hz) than the observed 50 Hz peak in the SUA and MUA PPC spectrum (Figures 1D and 6B). Considering that the PPC is unbiased by spike count/rate and that the analyzed MUA data set was the same as in Fries et al. (2008), this result demonstrates unequivocally that the

previously reported effect of selective attention on gamma-band synchronization (Fries et al., 2001b and Fries et al., 2008) was not confounded by its effect on firing rates. We predicted that selective attention enhances gamma locking for isolated single units as well. Yet, we found an average decrease (p < 0.05, bootstrap test) in BS cells’ gamma PPCs, with only a minority of units (at 54 Hz, 23%, p < 0.05, multiple-comparison-corrected binomial test, n = 39) having a higher gamma PPC with attention inside their RF (Figures 6A, 6B, and 6E; see Figures S1D–S1F and S5 for monkeys see more M1 and M2). Selective attention had no detectable effect on the average NS cell gamma PPC (n.s., bootstrap test, n = 21), with approximately the same fraction of cells having a positive and negative PPC modulation with selective attention (Figures 6A, 6C, and 6E). To investigate whether the decrease in BS cell PPCs was also present

in the other units recorded from the same electrodes, we examined the same-site MUA’s PPC spectra. We found a significant increase in average gamma PPC for the same-site MUAs, both for same-site MUAs recorded from sites Rebamipide giving NS and BS cells (Figure 6F; p < 0.05, bootstrap test), without a significant difference to the attentional effect in PPC for all MUAs together. The negative (BS) and neutral (NS) effects of selective attention on gamma-band synchronization stood in sharp contrast to the attentional effect on single unit firing rates, which were increased by an average of 11.8% ± 3.7% (68.8% of cells positively modulated, n = 64) with attention inside the RF, with no significant difference between NS (14.1% ± 7.5% increase, 68.2% of cells positively modulated, n = 22) and BS cells (11.1% ± 4.2% increase, 70.0% positively modulated, n = 40). These findings raise the question why the positive modulation of MUA-LFP gamma PPC with selective attention was not mirrored in the SUA-LFP gamma PPC.

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, 2001 and Millar et al , 2000) Additional

linkage studi

, 2001 and Millar et al., 2000). Additional

linkage studies with DISC1 mutations further support its role in influencing risk for psychosis and autistic spectrum disorders ( Chubb et al., 2008). Functional studies in animal models suggest that DISC1 plays a multifaceted role in both embryonic and postnatal neurogenesis in vivo. Exogenous manipulation of DISC1 results in a spectrum of neuronal abnormalities, depending on the timing and anatomical locus of perturbation. During embryonic cortical development, knockdown of DISC1 in E13 embryos accelerates cell cycle exit and neuronal differentiation ( Mao et al., 2009), whereas knockdown at E14.5 leads to inhibition of neuronal BTK inhibitor screening library migration and disorganized dendritic arbors ( Kamiya et al., 2005). During adult CP-690550 purchase hippocampal

neurogenesis, suppression of DISC1 also leads to decreased proliferation of neural progenitors ( Mao et al., 2009) and an array of neurodevelopmental defects in newborn dentate granule cells, including soma hypertrophy, mispositioning, impaired axonal targeting, and accelerated dendritic growth and synaptogenesis ( Duan et al., 2007, Faulkner et al., 2008 and Kim et al., 2009). The signaling mechanisms by which DISC1 regulates neurogenesis in vivo have just begun to be explored. For example, DISC1 regulates proliferation of neural progenitors through interaction with GSK3β (Mao et al., 2009), whereas it regulates development of newborn dentate granule cells through direct interaction with KIAA1212/Girdin in the hippocampus (Enomoto et al., 2009 and Kim et al., 2009). NDEL1 (nuclear distribution gene E-like homolog 1) also directly interacts

with DISC1 (Morris et al., 2003 and Ozeki et al., 2003). Knockdown of NDEL1 in newborn neurons in the adult hippocampus leads to primary DNA ligase defects in neuronal positioning and appearance of ectopic dendrites, representing some, but not all, of phenotypes observed with DISC1 suppression (Duan et al., 2007). This result suggests the existence of additional mechanisms by which DISC1 regulates other aspects of neuronal development. Indeed, early biochemical and yeast two-hybrid screens have identified a large number of DISC1 binding partners, many of which are known to be involved in neurodevelopmental processes (Camargo et al., 2007). While these studies established DISC1 as a scaffold protein, the functional role of the majority of these potential interactions in neuronal development remains to be demonstrated in vivo. Understanding mechanisms by which DISC1 differentially regulates distinct neurodevelopmental processes through its binding partners may reveal how dysfunction of DISC1 contributes to a wide spectrum of psychiatric and mental disorders.

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, 2009) Paip2a−/− mice performed better in this task than WT lit

, 2009). Paip2a−/− mice performed better in this task than WT littermates ( Figure 2F). We found no differences between the two genotypes in the novel object recognition task (

Figure 2G), which examines recognition memory. Taken together, our data indicate that Paip2a−/− mice display enhanced spatial learning and memory as compared to WT littermates. To study memory consolidation, we used contextual fear conditioning, a hippocampal-dependent task that engenders robust protein synthesis-dependent long-term memory for a training context following a single session of pairing the context to a foot shock (Kelleher et al., 2004b). Since a weak stimulation (1HFS) in Paip2a−/− slices elicited L-LTP, we first examined the SCH 900776 price effect of training using a weak experimental paradigm (single 0.3 mA foot shock for 1 s). Long-term contextual fear memory was assessed 24 hr later by reintroducing the mice to the training context. Paip2a−/− mice froze significantly more than WT littermates (WT: 32.6% ± 3.1%; Paip2a−/−: 46.76% ± 4.0%, p < 0.05; Figure 2H), indicating an enhancement of long-term memory. No difference in freezing between the two groups was found 1 hr after the training, demonstrating that the acquisition of the task was intact ( Figure S3A). To rule out possible nonspecific effects of nociceptive sensitivity or motor ability, we examined pain

sensation in the radiant heat paw withdrawal ( Figure S3B) and von Frey tests ( Figure S3C) and motor coordination in the rotarod test ( Figure S3D). No differences between Paip2a−/− Dolutegravir concentration and WT mice in these assays

were observed. Next, we assessed long-term memory of Paip2a−/− mice using pairing of context to a strong foot shock (strong training, two foot shocks of 0.5 mA for 2 s separated by 1 min). Paip2a−/− mice exhibited reduced freezing 24 hr after strong training, thus demonstrating an impairment of long-term contextual memory ( Figure 2I). Freezing 1 hr after strong training was not altered, demonstrating intact acquisition ( Figure S3E). Extinction of contextual fear memories in Paip2a−/− mice was impaired as well ( Figure S3F). We also assessed cued associative memory of Paip2a−/− mice using auditory from fear conditioning, an amygdala-dependent task that leads to association of the tone with the foot shock, with weak and strong training protocols ( Costa-Mattioli et al., 2005). No difference in freezing in response to the tone was detected 24 hr after training ( Figures S3G and S3H), demonstrating that long-term auditory fear memory is not altered in Paip2a−/− mice. Taken together, these results show that hippocampus-dependent long-term memory is enhanced in Paip2a−/− mice as compared to their WT littermates following weak training and is impaired after strong training.

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Of roughly 140 miRNA expressed in five regions of the rat brain (

Of roughly 140 miRNA expressed in five regions of the rat brain (cortex, hippocampus,

cerebellum, brainstem, and olfactory bulb), the majority (79%–97%) were also found in synaptosomes from each region (Figure 2D). While a significant number (up to ∼25%) of the miRNA detected in the study showed region specificity, the fact that about 100 of the detected miRNA were found in all regions suggests that most miRNA are part of core neural machinery. Interestingly, a small subset of miRNA was exclusively detected in synaptic material in each region (3%–9%), implying dedicated synaptic functions. When a subset of the synaptic miRNA was then quantified after kainic acid-induced seizure, the majority (five out of six) showed www.selleckchem.com/products/BMS-777607.html a significant activity-dependent change in the synaptic find more material even though changes in whole tissue were often not detected (Pichardo-Casas et al., 2012). Of particular interest, several of these activity-dependent miRNA displayed strikingly different changes in different brain regions; for example, miR-150 is increased over 5-fold in cortical synaptosomes but is reduced about the same fold in hippocampus, whereas miR-125 displays the opposite trend. Although this comparative analysis has only been applied to a handful of synaptic miRNA, it suggests that future functional analysis may reveal many new synaptic functions for miRNA

and that there may be dramatic specificity Megestrol Acetate in these functions in different neural circuits. If miRNA expression, localization, or function can be controlled by neural activity or other influences of neighboring cells and the environment, then miRNA can serve as agents of adaptive state change. Sensory input to the nervous system from the environment appears to trigger significant

changes in miRNA stability in the visual system (e.g., Krol et al., 2010). Moreover, from a developmental perspective, a substantial body of evidence shows that miRNA production and activity is controlled by several canonical cell-signaling pathways known to be important for many stages in the construction of neural circuits (reviewed by Saj and Lai, 2011). In addition to hardwiring neural circuits, some of these pathways are also known to link synaptic form and function to neural activity (e.g., brain-derived neurotrophic factor [BDNF]; Schratt et al., 2006). Multiple studies have surveyed miRNA levels in models of activity-dependent synapse plasticity (reviewed by Olde Loohuis et al., 2012). For example, in hippocampal slices subjected to long-term potentiation (LTP) or depression of synaptic output, the majority of detected miRNA (55 of 62) showed more than 2-fold up- or downregulation (Park and Tang, 2009). The temporal dimension adds another layer of complexity in the adaptive response.

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The findings of reduced

The findings of reduced GS-7340 cost DA soma size and DA output are consistent with earlier reports that chronic morphine decreases levels of neurofilament proteins in VTA and impairs axoplasmic transport from VTA to NAc (Beitner-Johnson et al.,

1992 and Beitner-Johnson and Nestler, 1993). Some of these neuroadaptations may also contribute to withdrawal symptoms from chronic morphine, as decreased VTA DA soma size (Spiga et al., 2003), neuronal activity (Diana et al., 1995), and output to NAc (Pothos et al., 1991, Rossetti et al., 1992a and Rossetti et al., 1992b) are reported in morphine-withdrawn rats. Our observation that chronic morphine increases the intrinsic excitability of VTA DA neurons in brain slices is consistent with previous findings of increased VTA neuronal firing rate in morphine-dependent rats in vivo (Georges et al., 2006). Previous data and our current findings suggest that chronic morphine induces this increased

excitability of VTA DA neurons by at least two mechanisms: downregulation of AKT which reduces GABAA currents in these neurons (Krishnan et al., 2008), and repression of KCNAB2 and perhaps other K+ channel subunits ( Figure 3). The reduced expression of K+ channel genes, which see more reflects a transcriptional effect based on our ChIP assays, appears to be mediated by reduced AKT signaling, as overexpression of IRS2dn was sufficient to decrease expression of several K+ channel subunits. Downregulation of mTORC2 is also required for the morphine-induced increase in VTA excitability, since Rictor overexpression, which prevented morphine Thalidomide downregulation of AKT activity, was sufficient to rescue this morphine effect, although whether

this action was through AKT modulation of GABAA channels, K+ channels, or another mTORC2 target has yet to be determined. Since we only observed the rescue of firing rate in VTA DA neurons that overexpressed Rictor, and not in nearby GFP-negative DA neurons, we believe that restoration of AKT/mTORC2 activity within DA neurons is sufficient to rescue opiate-induced changes. However, this does not preclude the possible influence of VTA GABA neurons in morphine-induced changes, as our viral manipulations were not specific for DA neurons. For example, HSV-dnK might also increase the activity of VTA GABA neurons, which would then decrease the activity of nearby DA neurons. However, we see a decrease in DA soma size with morphine, which is known to decrease GABA activity, making dnK activation of GABA neurons an unlikely contributor. A direct test of this hypothesis awaits the development of viral vectors that target specific neuronal subpopulations.

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Since there is a brief window between phagocytosis and degradatio

Since there is a brief window between phagocytosis and degradation of lysosomal contents, EM studies

may underestimate the synaptic content of microglial lysosomes. Together, these experiments suggest microglia can engulf presynaptic terminals of RGCs, though they do not rule out the engulfment of nonsynaptic Erastin supplier or postsynaptic structures, as has been seen in hippocampus ( Paolicelli et al., 2011). Microglia are exquisitely sensitive to injury and inflammation, and the above studies involved intraocular injections, which might cause microglia to target RGCs. To control for this possibility, a genetically encoded marker was used to label RGCs, eliminating the need for injections, and similar

microglial engulfment of RGC material was still seen. The idea that microglial engulfment is part of a normal developmental pathway is further supported by the fact that engulfment of RGC components in vivo roughly paralleled the timing of developmental remodeling. Previous work demonstrated that C3 is present at synapses during the early postnatal period and is required for normal developmental remodeling of retinogeniculate axons (Stevens et al., 2007). Given that microglia are the only known resident brain cells to express the C3 receptor, CR3, Schafer et al. (2012) hypothesized that AG14699 C3-CR3 interactions might recruit microglia to RGC axons as they remodel. To directly test the requirement for CR3 in remodeling, similar RGC-tracer experiments were performed in transgenic mice lacking functional CR3. Overlap between inputs from the two eyes was increased, Dipeptidyl peptidase and engulfment of RCG material by microglia was reduced, in CR3-deficient mice, effects that were mimicked by pharmacologically inhibiting microglial activity in WT animals. The increase in overlap in CR3-deficient mice was paralleled by an increase in synapse density in adults, as assessed by colocalization of VGlut2 (a marker for RGC presynaptic terminals)

and GluR1 (a marker of postsynaptic sites) by array tomography. These and other results show that in the absence of complement C3 or its microglial receptor, CR3, microglia contain less RGC-derived material than in WT, and inappropriate axon projections and synapses are present. Interestingly, CR3-deficient mice showed increase in both VGlut2-containing synapses and VGlut2 puncta not associated with synapses. Some of the nonsynaptic VGlut2 could represent retracting RGC axons that successfully underwent elimination in the absence of CR3-dependent mechanisms. This is likely, since significant pruning still occurs in CR3 knockouts. However, these recently pruned inputs should also be present in WT dLGNs. In fact, if pruning is impaired in CR3-deficient animals, this might be expected to lead to fewer recently pruned inputs than WT, not more.

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In the null direction, preceding inhibition might underlie the re

In the null direction, preceding inhibition might underlie the reduced spike activities and the increased temporal jitters, because it strongly suppressed the earlier phase of the excitation, but not the later phase (Figure 1 and Figure 2) (Gittelman et al., 2009, Ye et al., 2010 and Zhang et al., 2003). Moreover, although excitation and inhibition were proportionally balanced in response to both directions at nonoptimal

speeds, with inhibitory inputs spreading out over a longer time window than that at the optimal speed, the spikes were highly scattered, which is consistent with Ku-0059436 mouse previous modeling work (Figure 2; Figures S4C and S4D) (Wehr and Zador, 2003). Previous studies show that DS is largely reduced or eliminated when inhibition is blocked (Fuzessery and Hall, 1996, Koch and Grothe, 1998 and Razak and Fuzessery, 2006), and inhibition underlies the spike generation mechanisms that sharpens DS by gain control (Gittelman et al., 2009 and Ye et al., 2010). Our results suggest that inhibition not only scales down the response level Selleckchem Wnt inhibitor in the null direction of FM sweeps, but also increases the temporal precision of a DS neuron’s firing by locking to excitation in the preferred direction. The synaptic input circuits that generate DS appear to be different from those that shape DS. In primary auditory cortical neurons,

inhibition sharpens direction selectivity, which can be attributed to the asymmetric and skewed pattern of their synaptic TRFs (Zhang et al., 2003). Synaptic TRFs of those neurons are marked

by covaried tone-evoked excitatory and inhibitory synaptic inputs (Wehr and Zador, 2003 and Zhang et al., 2003). This balanced inhibition suggests a feedforward inhibition circuit: the presynaptic GABAergic neurons may be innervated by the same set of thalamocortical afferents as the recorded A1 cell, which is similar to previously proposed circuitry for other sensory cortices ADAMTS5 (Miller et al., 2001). In the present study, from recordings made in the IC, the excitatory and inhibitory inputs of DS neurons were not covaried. It suggests that an imbalanced inhibition might come from the interneurons innervated by a larger group of projection neurons in the cochlear nuclei, whereas the excitatory inputs have fewer innervations from the cochlear nuclei or recurrent connections. Until recently, imbalanced inhibition had not been observed for normal sensory processing. Recordings of cortical intensity-selective neurons demonstrated that temporally imbalanced inhibition sharpened the intensity selectivity that was inherited from afferent inputs, although the excitatory and inhibitory synaptic TRFs were still overlapped (Wu et al., 2006). Our study reveals that imbalanced inhibition is prominent in the subcortical nucleus to a much larger extent.

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Thus, the initial spikes in a response to cortical input may alre

Thus, the initial spikes in a response to cortical input may already be part of a gamma-synchronized response (Fries et al., 2001). While a pure selleck rate code may be feasible as means to provide an initial cortical representation of sensory stimuli, one cannot rule out an interaction with gamma rhythms as a temporal code here either. Many different modes of gamma rhythm generation can be experimentally induced

(Whittington et al., 2011), but none of the known manifestations truly behave as a “clock” for principal cell spike timing. Principal cell inputs to interneurons are vital to drive the observed rhythm and changes in principal cell spike behavior can alter the gamma rhythm on a period by period basis (Whittington et al., 1995). The main differences lie in the way fast spiking interneurons are recruited into the population rhythm by principal cells—they can be recruited by tonic excitation through glutamate overspill at synapses activating metabotropic receptors, convergence onto excitatory synapses on interneurons of ectopic action potentials generated in principal cell axons, or conventional somatic spike generation. Persistent, highly frequency-inert gamma rhythms associate with sparse somatic spiking (Miller, 1996) in

superficial neocortex. Gamma rhythms can also be generated in hippocampus that are associated with high spike rates in individual neurons (an order of magnitude greater than in persistent gamma rhythms) and are considerably more frequency—and thus spike rate—variable (Whittington et al., 1997). In neocortex, spike rates are closely related to gamma rhythm generation BTK inhibitor (in conjunction with slower changes in membrane potential (Mazzoni et al., 2010), with gamma rhythms being the single most important determinant of spike-density function (Rasch et al., 2008). But many in vivo studies show sensory-induced spike rate changes that peak at mean rates from way above the classical

gamma band frequency (e.g., Zinke et al., 2006). If it is assumed that spike timing is precisely determined by the trains of GABAergic inhibition that are the signature of population gamma rhythms, then how is this possible? One explanation for these data is that there are at least two gamma rhythm generators in neocortex. First, a persistent rhythm provides relatively rigid temporal structure despite low principal cell spike rates and low population gamma frequencies (ca. 40 Hz). Such a rhythm has been documented in superficial layers of primary sensory and association cortices (Cunningham et al., 2004; Ainsworth et al., 2011; Figure 5), where spike rates favor sparse coding (Wolfe et al., 2010). Such a scheme is particularly evident in local representations of sensory stimuli (Ohiorhenuan et al., 2010) where input increases quiescence but also increases temporally brief periods of common (population) activity. This sparseness has been proposed to be due to increases in surround inhibition (Haider et al.

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, 2001) and has characteristically distinct gene profiles (Thomps

, 2001) and has characteristically distinct gene profiles (Thompson et al., 2008; Dong et al., 2009). In return, the septal and temporal segments of the hippocampus broadcast to different streams of structures (Amaral and Lavenex, 2007; Cenquizca and Swanson, 2007). In contrast to its afferent and efferent connections, the internal organization of the hippocampus suggests that the widespread neocortical representations are integrated (cf., Bannerman et al., 2003; Bast et al., 2009; Kjelstrup et al., 2002; Moser et al., 2008; Small, 2002; Royer et al., 2010) by the

extensive recurrent collateral system of CA3 pyramidal neurons (Ishizuka et al., 1990; Li et al., 1994). The physiological mechanisms of communication between click here the hippocampus and the

neocortex are not well understood. Neuronal recording studies from the septal and more temporal segments of the hippocampus are controversial and range from emphasizing the unity of hippocampal Vorinostat supplier operations (O’Keefe and Nadel, 1978; Bullock et al., 1990; Jung et al., 1994; Kjelstrup et al., 2008; Lubenov and Siapas, 2009; Maurer et al., 2005) to more localized and specialized computations (Hampson et al., 1999; Royer et al., 2010; Segal et al., 2010; Wiener, 1996). A fundamental mode of hippocampal operations is reflected by theta oscillations during explorative behavior and REM sleep (4–10 Hz; cf., Buzsáki, 2002). In a recent elegant study Lubenov and Siapas (2009) have observed that the phase of theta waves advances systematically in the dorsal hippocampus (Lubenov and Siapas, 2009) and hypothesized a full cycle (i.e., 360°) phase shift between the septal and temporal poles. The implication of a full-cycle phase shift of theta waves is that outputs from not the two poles of the hippocampus would affect their joint targets in a temporally synchronous manner, while the intermediate parts would remain temporally segregated from either pole.

To examine the spatial organization of theta patterns, we recorded LFP and neuronal discharge activity in the subiculofimbrial (transverse) axis and from the entire length of the septotemporal (longitudinal) axis of the hippocampal CA1 pyramidal layer during behavioral exploration and REM sleep. LFP and unit activity were recorded during REM sleep in the home cage and during navigation (RUN sessions) either while the rat was chasing small fragments of randomly dispersed froot loops on an open field and/or running for a water reward in an 11-compartment zig-zag maze (Royer et al., 2010). Since the phase of theta oscillation in the CA1 region varies along the somatodendritic (depth), subicular-CA3 (transverse), and septotemporal (dorsoventral or longitudinal) axes (Buzsáki, 2002; Lubenov and Siapas, 2009; Patel et al., 2008, Soc. Neurosci., abstract, 435.

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