This was shown in anesthetized animals, where simultaneous deflection of all whiskers (to mimic normal whisking) evokes L4 spikes reliably

before L2/3 spikes, whereas deflection of all but one whisker (to mimic acute whisker deprivation) immediately causes L4-L2/3 firing in the deprived column to decorrelate and firing order to reverse (Celikel et al., 2004). These findings suggest that STDP may be the primary mode for induction of LTD at L4-L2/3 synapses during deprivation-induced plasticity. In V1, whether STDP contributes to deprivation-induced plasticity is unclear. In a focal retinal lesion model of plasticity, neurons SB203580 price in a visually deprived region of V1 acquire novel visual receptive fields via functional and anatomical reorganization of intracortical horizontal connections (Yamahachi et al., 2009). A computational study found that the pattern of acquired receptive fields was consistent with STDP at intracortical synapses, but not with classical correlation-dependent plasticity (Young et al., 2007). An STDP model of ocular dominance plasticity has been proposed in which monocular deprivation alters the precise temporal patterning of V1 spikes, thus inducing STDP in deprived-eye

or open-eye pathways (Hensch, 2005; Hofer et al., 2006). Direct evidence for STDP is lacking, but the dynamics of plasticity in fast-spiking interneurons may be consistent with STDP (Yazaki-Sugiyama et al., 2009). Ruxolitinib datasheet Hebb predicted that the temporally asymmetric nature of synapse strengthening drives

learning of sequences. Blum and Abbott (1996) modeled temporally asymmetric LTP in hippocampus, and showed that it learns sequences of spatial positions (i.e., spatial paths). They predicted that place fields will shift backward along well-learned paths due to LTP for at synapses from earlier- to later-activated place cells. This shift was observed experimentally by Mehta et al. (1997) and was shown to be consistent with both simple Hebbian STDP (Mehta et al., 2000) and with a biophysically inspired, unified model of rate- and timing-dependent plasticity (Yu et al., 2008). Recently, Bush et al. (2010) showed that a rate- and timing-dependent plasticity model explains both learning of spatial sequences and increased functional connectivity between neurons with overlapping place fields. Thus, STDP is an appropriate candidate to mediate learning within the hippocampal cognitive map. Sensory systems must distinguish true external sensory stimuli from behaviorally irrelevant, self-generated sensory signals. Anti-Hebbian LTD plays a major role in this process, which has been studied in electrosensation in fish (for review, see Requarth and Sawtell, 2011). Weakly electric fish emit electric currents, and detect nearby objects by sensing object-induced distortions in the electric field via body surface electroreceptors. Self-motion (e.g.

We defined not coherent cells as those cells

whose activity is not significantly correlated with nearby beta-band LFP activity. Thirty-four cells (34/59, 58%) were significantly correlated with LFP at 15 Hz in the late-delay epoch, 500–1,000 ms after target onset (coherent cells; p < 0.05). The remaining 25 cells (25/59, 42%) were not significantly correlated with LFP activity (not PD0332991 price coherent cells; p > 0.05). The firing rate of coherent cells showed stronger spatially tuning than the activity of not coherent cells (Figure 5). The difference in firing rate before movements in the preferred and null directions was greater for coherent cells than not coherent cells for both tasks (Figures 5A and 5B; coherent cell average firing rate = 14.9 sp/s; not coherent cell average firing rate = 7.3 sp/s). In general, firing rate was higher for coherent versus not coherent BIBF 1120 molecular weight cells throughout the trial, including during the baseline epoch. Note that although firing rate is elevated during the delay as opposed to the baseline epoch, LFP directional selectivity and power (see Figure 3Bii) drop off at frequencies > 60 Hz

during the delay. This suggests that the band-limited effects that we see at frequencies < 60 Hz are not due to increased spiking activity associated with upcoming movements in the preferred direction. To determine whether the definition of a cell as coherent or not coherent was consistent across the trial, we also analyzed spike-field coherence during the target epoch, 0–500 ms after target onset,

and during the baseline epoch, 500 ms immediately before target onset. Almost the same proportion of cells was defined as coherent during the target epoch (coherent: 35/59, 59%; not coherent: 24/59, 41%) as during the late-delay epoch. The definition of a cell as coherent was consistent between target and late- DNA ligase delay epochs for 44 out of 59 cells (44/59, 75%). We observed consistent results based on the baseline epoch. A similar proportion of cells was defined as coherent during the baseline epoch (coherent: 31/59, 53%; not coherent: 28/59, 47%). The definition of a cell as coherent was again consistent between baseline and late-delay epochs, with 42 cells (42/59, 71%) having the same definition for both epochs. Therefore, the definition of a cell as coherent or not coherent did not vary substantially across the trial. Because we observed beta-band selectivity for RT in the LFP during the delay, we chose to focus our analysis of spiking using the definition of coherence during the delay. The difference in spike-field coherence was not simply due to an increase in firing rate. First, coherence is normalized by the firing rate. Second, if coherence were an artifact of higher firing rates, we would expect that the largest differences in firing rate between coherent and not coherent cells would be present during the late-delay epoch, when coherence was estimated.

This might be caused GW-572016 chemical structure by the conversion of phenylalanine to tyrosine by hydroxyl radicals generated during the decomposition of peroxynitrite (Ferger et al., 2001). In accordance with this, there was no reactivity toward Aβ1-42 bearing a Y10A mutation after incubation with peroxynitrite (Figure S1).

Using this antiserum, we were able to detect 3NTyr10-Aβ in the supernatant of NOS2 overexpressing HEK293 cells after exogenous addition of nonaggregated Aβ, demonstrating that NOS2 is able to induce this posttranslational modification before Aβ deposits form (Figure S1). Immunohistochemical analysis of AD and control brains by 3NTyr10-Aβ antiserum revealed a lack of immunoreactivity in control brains, whereas in AD brain, the core of amyloid plaques was intensively labeled, as confirmed by IC16 double staining (Figure 1C). Measuring the relative amounts of 3NTyr10-Aβ by sandwich ELISA in SDS-soluble fractions of human brain samples, we detected 3NTyr10-Aβ in the SDS fraction of AD patients and only to very low amount in Crizotinib nondemented controls (Figure 1D). Further, the relative signal ratio of 3NTyr10-Aβ between control and AD patients was comparable to that of Aβ1-42 (Figure 1D).

Of note, we failed to detect any 3NTyr10-Aβ in human cerebrospinal fluid (CSF) of control, mild cognitive impaired, and AD patients underlining the insoluble properties of this species (Figure S1). Analysis of brain sections from 5- and 12-month-old APP/PS1 mice revealed a colocalization of antibody IC16 against Aβ with the 3NTyr10-Aβ antiserum from beginning of plaque formation starting at 5 months of age in this AD mouse model (Figures 2A and 2B). This costaining was observed in all brain areas where amyloid

plaques are formed. Casein kinase 1 In addition, colocalization was observed independently of plaque size, since it was already detectable in tiny plaques of 10 μm diameter in 5-month-old animals (Figure 2C), suggesting that formation of 3NTyr10-Aβ is an early event in plaque development. Similar to human AD brain, in APP/PS1 the 3NTyr10-Aβ immunoreactivity was localized to the core of the plaque surrounded by IC16 immunoreactivity (Figure 2D). Evaluation of individual Aβ plaque sizes by immunohistochemistry with antibody IC16 and the area of the 3NTyr10-Aβ positive core of 5- and 9-month-old APP/PS1 mice revealed that there are no changes in the average 3NTyr10-Aβ core size (Figures 2E and 2F), suggesting that the core, once formed, does not substantially increase in size any further. Nevertheless, we observed plaque growth between 5 and 9 months that was solely caused by accumulation of nonnitrated Aβ, as detected by IC16 immunoreactivity (Figures 2E and 2F). As a consequence, there was a highly significant drop in the 3NTyr10-Aβ/Aβ ratio (Figure 2G). In addition, we were able to immunoprecipitate 3NTyr10-Aβ of brain homogenates sequentially extracted with PBS, RIPA, SDS, and HIFP using 3NTyr10-Aβ antiserum.

We determined that the overexpression of WT-DISC1 led to a small increase in cAMP levels; however, it was not statistically significant (Figure S3B). Evaluation of the different

DISC1 variants in this assay further revealed no difference in cAMP levels compared with GFP controls. Therefore, our data suggest that the DISC1 variants do not specifically regulate cAMP levels in a dominant-negative manner. Taken together, the analysis of human LCLs demonstrates that the R264Q variant directly regulates Wnt signaling by regulating the activation of Wnt signaling proteins. Since all of our studies suggest the S704C variant does not affect Wnt signaling or neural progenitor proliferation, we hypothesized this variant might regulate another Wnt-independent

neurodevelopmental event. Since this variant lies in the C terminus of DISC1, which interacts with selleckchem the neuronal migration genes Ndel1 and Dix domain containing 1 (Dixdc1), we asked whether it alters the migration the newborn neurons. Using in utero electroporation, we tested the ability of WT-DISC1 versus the DISC1 variants to rescue the neuronal migration defect caused by downregulation of DISC1. We found that first, expression of human WT-DISC1 rescues the GFP-positive cells that are normally arrested in the intermediate and subventricular zones due to DISC1 downregulation, restoring their migration to the upper layers of the cortex, similar to control shRNA (Figure 6A). We then tested the different DISC1 Dorsomorphin supplier variants in this paradigm and found that the A83V, R264Q, and L607F variants functioned similar to WT-DISC1 Parvulin and

also restored the migration of arrested GFP-positive cells to the upper cortical layers (Figure 6A). However, we determined that the S704C variant was not able to completely restore migration, since there a significant number of GFP cells still remaining in the VZ/SVZ and IZ compared with the other conditions, suggesting this C-terminal variant is required for neuronal migration (Figure 6A). Given that we found the S704C variant affects neuronal migration, we asked whether overexpression of this variant alone could cause a neuronal migration defect in a dominant-negative fashion. We overexpressed the different DISC1 variants and found that only the S704C variant disrupted neuronal migration compared with the other DISC1 variants, demonstrating S704C has consistent effects on migration using two different experimental paradigms (Figure S4). To determine the mechanism by which the S704C variant inhibited migration, we hypothesized this variant might have disrupted interaction with Ndel1 and/or Dixdc1, and therefore tested the ability of all the variants to bind these molecules. Interestingly, we found that there was reduced binding between the S704C variant and Dixdc1, but not Ndel1 (Figures 6B and 6C), whereas all other DISC1 variants all had equal interaction with Ndel1 and Dixdc1.

Taken together, these defects confirm that B3gnt1 and ISPD function in the same genetic pathway to regulate dystroglycan glycosylation in vivo, and establish B3gnt1LacZ/M155T Z-VAD-FMK order and ISPDL79∗/L79∗ mice as mouse models of dystroglycanopathy. The defects observed in B3gnt1, ISPD, and dystroglycan mutants suggests a role for dystroglycan in mediating axon guidance in vivo. The axons of both the descending hindbrain projections and the dorsal funiculus extend along the basal surface of the hindbrain and spinal cord, respectively, suggesting

that dystroglycan may be required in the hindbrain and spinal cord for the proper development of these axonal tracts. In contrast to the well-characterized role of dystroglycan in the developing cortex, its function in the spinal cord is unclear. Similar to the developing cortex, levels of total dystroglycan protein in the spinal cord of B3gnt1LacZ/M155T and ISPDL79∗/L79∗ mutants are normal, while glycosylated alpha-dystroglycan and laminin binding activity are reduced to an undetectable amount ( Figures 3A and 3B). Examination of dystroglycan localization in the spinal cord by immunostaining shows that dystroglycan is enriched in the FK228 mw radial neuroepithelial endfeet, where it colocalizes with several extracellular matrix proteins including laminin, perlecan, and collagen IV to form a continuous

basement membrane surrounding the spinal cord ( Figures 3C and S5A). In B3gnt1LacZ/M155T, ISPDL79∗/L79∗ and Sox2cre; DGF/− embryos, the loss of functional dystroglycan results in the progressive fragmentation of the basement membrane beginning around E11.5 which is accompanied by detachment of radial neuroepithelial endfeet from the basal surface ( Figures S5A and S5B). This fragmentation first appears in the lateral portion of the spinal cord and progresses ventrally and dorsally as the spinal cord continues to develop.

Interestingly, in addition to its localization to the basement membrane surrounding the spinal cord, we found that dystroglycan is enriched in the floor plate, a specialized glial structure in the ventral neuraxis that spans Thalidomide the CNS anteroposterior axis from the midbrain to caudal spinal cord (Figures 3C and 3D). The spinal cord floor plate functions both as an organizer of ventral cell fates and as an intermediate target for commissural axons whose cell bodies reside within the dorsal spinal cord. The axons of commissural neurons are initially attracted ventrally to the floor plate by a number of floor plate derived cues, including Netrin, Shh, and VEGF (Charron et al., 2003; Ruiz de Almodovar et al., 2011; Serafini et al., 1996). Once commissural axons reach the floor plate, these attractive cues are silenced and repulsive floor plate-derived cues, including Slits (Long et al., 2004) and Sema3B (Zou et al.

, 2008). Thus, an intrinsic temporal switch may be involved in sensitizing the axons to these longitudinal gradients. Extrinsic factors in the spinal cord would add an additional level of regulation to modulate and fine-tune the guidance program. Extrinsic spatial and intrinsic temporal regulation might act together to switch commissural axon trajectory from DV to AP at the floorplate, ensuring high fidelity in axon turning at this intermediate

target. See Supplemental Experimental Procedures for further details on the experiments. All animal work was performed in accordance with the Canadian Council on Animal Care Guidelines and approved by the IRCM Animal Care Committee. Embryos were fixed in 4% Veliparib cell line paraformaldehyde (PFA) in PBS. Neural tubes were dissected from the fixed embryos, pinned open, and small 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindocarbocyanine

perchlorate (DiI; Molecular Probes, Eugene, OR, USA) crystals were inserted to the medial neural tube dorsal of the motor column to label five to nine individual cohorts per embryo (Farmer et al., 2008). The DiI was allowed to diffuse for 1 or 2 days, and the neural tubes were then mounted open book and imaged. Dissociated commissural neuron cultures were prepared from the dorsal fifth of E13 rat neural tubes as previously described (Langlois selleck inhibitor et al., 2010; Yam et al., 2009). Neurons were assessed at 2 DIV (50–55 hr after plating) and 3–4 DIV (76–102 hr after plating). The Dunn chamber axon Casein kinase 1 guidance assay, imaging, and analysis were performed as previously detailed (Yam et al., 2009). Gradients were generated with 0.1 μg/ml recombinant human Shh (C24II; R&D Systems),

0.2 μg/ml recombinant Netrin (a gift from T.E. Kennedy), or buffer containing BSA (the vehicle for Shh) as the control in the outer well. Open-book preparations of rat E13 spinal cords were isolated and cultured as previously described by Lyuksyutova et al. (2003). After 1 hr in culture, Tat-YFP-R18 or the control Tat-YFP- WLKL was added to the culture media to a final concentration of either 100 or 150 ng/ml and cultured for 24 hr. Open-book explants were fixed at room temperature with 4% PFA, washed with PBS, and labeled with DiI. Chick spinal cord electroporation was performed at HH st. 18/19 as described by Luria et al. (2008). A total of 5–10 μg/μl solution of plasmid DNA was injected into the lumbar neural tube. The embryos were electroporated using platinum/iridium electrodes (FHC) with an ECM 830 Electro Square Porator (BTX; Harvard Apparatus; 30V, 5 pulses, 50 ms, at 1 s interval). Shells were sealed with Parafilm and incubated at 38°C until harvesting at HH st. 28/29. We thank E. Ruthazer for critical reading of the manuscript. We are grateful to K.K. Murai for access to his spinning-disc confocal microscope. We thank J. Barthe, J. Cardin, S.D. Langlois, I. Rambaldi, and T. Shimada for expert assistance. We thank D. Rowitch for Math1-Cre mice, P.T.

We also used the GEO data set GSE15222 ( Myers et al., 2007) to analyze the association of MAPT, RFX3, SLC1A1, and PPAPDC2 genes and case-control status. None of the other genes (GLIS3, GEMC1, IL1RAP, OSTN, FOXP4) were found in this data set. This data set includes genotype and expression data from 486 late onset Alzheimer’s disease cases and 279 neuropathologically clean individuals. Association of mRNA levels with case control status or the different SNPs was carried out using ANCOVA.

Stepwise regression analysis www.selleckchem.com/products/pfi-2.html was used to identify the potential covariates (postmortem interval, age at death, site, and gender) and significant covariates were included in the analysis. SNPs were tested using an additive model

with minor allele homozygotes coded as 0, heterozygotes coded as 1, and major allele homozygotes coded as 2. Data used in the preparation of this article were obtained from the ADNI database (www.loni.ucla.edu/ADNI). The ADNI was launched in 2003 by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, the Food and Drug Administration, private pharmaceutical companies, and nonprofit organizations, as a $60 million, 5 year public-private selleck partnership. The Principal Investigator of this initiative is Michael W. Weiner, MD. ADNI is the result of efforts of many coinvestigators from a broad range of academic

institutions Fossariinae and private corporations, and subjects have been recruited from over 50 sites across the US and Canada. The initial goal of ADNI was to recruit 800 adults, ages 55 to 90, to participate in the research—approximately 200 cognitively normal older individuals to be followed for 3 years, 400 people with MCI to be followed for 3 years, and 200 people with early AD to be followed for 2 years. For up-to-date information, see www.adni-info.org. This work was supported by grants from NIH (P30 NS069329-01, R01 AG035083, R01 AG16208, P50 AG05681, P01 AG03991, P01 AG026276, AG05136 and PO1 AG05131, U01AG032984, AG010124, and R01 AG042611), AstraZeneca, and the Barnes-Jewish Hospital Foundation. The authors thank the Clinical and Genetics Cores of the Knight ADRC at Washington University for clinical and cognitive assessments of the participants and for APOE genotypes and the Biomarker Core of the Adult Children Study at Washington University for the CSF collection and assays.

These peptides elicit “late slow” depolarization that lasts minutes (Jan and Jan, 1982 and Kuffler and Sejnowski, 1983). In addition to suppressing

K+ currents such as the M-current, the neurotransmitters can also excite the neurons through activation of a Na+-dependent basal cation current that is apparently carried by the basal Na+ leak conductance (Brown and Adams, 1980, Jones, 1985 and Kuba and Koketsu, 1978). Such a mechanism of excitation through the activation of Na+-leak-like basal conductances has also been found in the excitation of serotonin neurons in the dorsal raphe nucleus by orexin (Liu et al., 2002), VTA dopaminergic neurons by SP and neurotensin Veliparib molecular weight (Farkas et al., 1996), locus coeruleus neurons by SP and muscarine (Shen and North, 1992a and Shen and North, 1992b), and pre-Bötzinger complex neurons by serotonin

and SP (Peña and Ramirez, 2004 and Ptak et al., 2009). Similarly, suppression of a Na+ leak-like current can lead to hyperpolarization by driving the RMP toward EK, as suggested in the gastrin-releasing peptide containing retinorecipient neurons in the suprachiasmatic nucleus Dasatinib (SCN). In these neurons, a one-hour light exposure causes a large reduction (>100 pA) of what appears to be a Na+-leak current and a hyperpolarization of membrane potential by 15 mV (LeSauter et al., 2011). Background Na+ leak conductances are also implicated in the generation and/or maintenance of spontaneous firing of neurons. Neurons with autonomous firing have been

found in many regions in the nervous systems (Häusser et al., 2004 and Llinás, 1988). The ability to generate rhythmic firing in some neurons is clearly the cell’s intrinsic property as it persists in dissociated neurons in culture and in slices when synaptic transmission is blocked. Subthreshold conductances such as the TTX-sensitive persistent Na+ conductance, resurgent Na+ conductance, voltage-activated Ca2+ channels and Ih have been shown to be the major determinants in the autorhythmicity in many neurons such as cerebellar Purkinje neurons (Raman Isotretinoin and Bean, 1997 and Raman et al., 2000) and substantia nigra pars compacta neurons (Chan et al., 2007, Guzman et al., 2009 and Puopolo et al., 2007). In some neurons such as the cerebellar nuclei neurons (Raman et al., 2000), cerebellar unipolar brush cells (Russo et al., 2007), SCN neurons (Jackson et al., 2004), dopaminergic VTA neurons (Khaliq and Bean, 2010), and substantia nigra pars reticulata neurons (Atherton and Bevan, 2005), the autonomous firing also involves conductances similar to the TTX-insensitive background Na+-leak conductance. The presence of such a conductance is proposed to set the “resting” membrane potential close to the threshold (for example −50 mV) above which voltage-sensitive channels are activated, or to depolarize the cells to the threshold potential during inter-spike interval (Khaliq and Bean, 2010).

What mechanisms could contribute to these striking findings? Although speculative at this point, it has been proposed that processes occurring both at the synapse level and at larger scales, including rapid intracortical remodeling of dendritic spines and axonal terminals, glial hypertrophy, and synaptogenesis, might play a contributory role (Draganski and May, 2008, May and Gaser, 2006 and Anderson et al., 1994). Consistently, rapid (within an hour) formation of postsynaptic dendritic spines has been detected in vivo in the pyramidal neurons of the mouse motor cortex following motor training (Xu et al., 2009), and the extent of spine remodeling has been shown to correlate with behavioral improvements

after learning, suggesting that this mechanism of synaptic plasticity may contribute to motor selleckchem memory

formation (Yang et al., 2009). On the other hand, it should be noted that other animal studies demonstrated significant increases in synapse numbers in the rat M1 only after extensive training (Kleim et al., 1996 and Kleim et al., 2004). Slow learning has been linked with structural plasticity in white matter architecture as well (Table 1). Diffusion MRI-based measures, such as fractional anisotropy (FA), are believed to reflect white matter integrity (Fields, 2008), providing HDAC inhibitor a distinctive insight into the microstructural properties of white matter in vivo (Le Bihan et al., 2001 and Mori and Zhang, 2006). Cross-sectional studies, primarily with highly trained musicians, examined white matter correlates of skilled behavior (Bengtsson et al., 2005, Han et al., 2009 and Schmithorst and Wilke, 2002). Fractional anisotropy in the almost posterior limb of the internal capsule, which contains descending corticospinal fibers from the primary sensorimotor and premotor cortices, correlated with number of

practice hours during childhood in skilled musicians (Bengtsson et al., 2005). It has been proposed that these results may reflect experience-induced plasticity during a critical developmental period (Bengtsson et al., 2005). A recent pioneering study provided more direct evidence for experience-induced changes in white matter architecture, resulting from a relatively short period of practice (Scholz et al., 2009). In this study, it was shown that 6 weeks of juggling practice resulted in increased FA in a region of white matter underlying the intraparietal sulcus. Localized increases in gray matter were detected in close proximity to these white matter regions. Yet the magnitude of changes of gray and white matter showed no correlation and developed over markedly different time courses. Interestingly, individual differences in white matter mictrostructure appear to be related to variation in learning (Johansen-Berg, 2010, Della-Maggiore et al., 2009 and Tomassini et al., 2011).

Furthermore,

reduced behavioral responding to A1 was inversely correlated with neural summation measured earlier, in the first compound training session (Figure 4G, right). In other words, the stronger the signaling of novel summed expectancies for reward during compound training in a given rat, the weaker responding to the A1 cue was at the start of extinction training. Thus, Anticancer Compound Library neural estimates of outcomes in OFC were predictive of both behavior and learning. The neural data described above suggests that elevated activity in OFC to the compound cue is critical for learning. This is consistent with earlier data in which we showed that pharmacological inactivation of OFC during compound training prevented learning, assessed later during the probe test. However as noted earlier, this work is also consistent with other explanations, since activity within

OFC is suppressed throughout compound training in a nonspecific manner. To provide a more specific causal test of this hypothesis, we next used optogenetic methods to inhibit activity of OFC neurons just at the time of presentation of the compound cue. Rats received bilateral infusions of either AAV-CaMKIIa-eNpHR3.0-eYFP (halo, n = 11 C59 wnt cell line including nine that underwent behavioral testing and two additional rats used for ex vivo recording) or AAV-CaMKIIa-eYFP (control, n = 9) into OFC at the same location as our recording work; expression was verified histologically postmortem (Figures 5A–5C). Light-dependent inhibition of OFC neurons was tested using ex vivo recording in two rats

(Figure 5D). The remaining rats (n values = 9) received fiber optic assemblies immediately over the injection sites. Three weeks after surgery, these rats began training in else the same overexpectation task described above, except that light was delivered into the OFC bilaterally during the presentation of the compound cue (Figure 5E). While there were neither main effects nor any interactions of group on conditioned responding across either conditioning (F values < 0.91; p values > 0.61) or during the compound sessions (F values < 2.41; p values > 0.08; Figure S5 available online), there were significant differences during the subsequent probe test. Specifically, NpHR rats in whom light was delivered during the compound cue failed to show any difference in conditioned responding to the A1 versus A2 cues in the subsequent probe test (Figure 5F), whereas eYFP rats that received the same treatment responded much less to A1 than to A2 (Figure 5G), particularly on the very first trial of the extinction probe test. This impression was confirmed by a two-factor ANOVA (cue X group) comparing responding to A1 versus A2 on the first trial, which revealed a significant main effect of group (F(1,16) = 9.68; p < 0.