Four out of six animals in group A became negative within 1 day post treatment with both ITS1 TD PCR and HCT (Table 1). After 1 day of treatment, one animal was positive in ITS1 TD PCR and negative in HCT, and another animal was positive in HCT and negative in ITS1 TD PCR. From 2 days post-treatment till the end see more of the sampling period (44 days after first treatment), all animals were negative in both the ITS1 TD PCR and the HCT. In group B, all six animals were occasionally positive in ITS1 TD PCR and/or HCT during the follow-up period between 1 and 16 days after treatment and even after retreatment (on day 19) up to day 44 after treatment (Table 2). The parasite

detection rate of ITS1 TD PCR after two treatments in animal group B was higher than that of HCT. Positivity rate of ITS1 TD PCR was 84.85% (56/66), while HCT was 57.58% (38/66). The ITS1 TD PCR could detect relapse up to three days earlier than microscopical parasite detection. Livestock production is considered Autophagy inhibitor the main lifeline for millions of families in many sub-Saharan countries. However, the emergence of drug resistant trypanosomes

presents a serious threat to agriculture in the regions. Therefore, studies on drug resistance and development of novel compounds against trypanosomes are necessary for effective control. These studies greatly benefit from rapid and cost-efficient molecular tools to detect the presence of trypanosomes. Compared to microscopy, PCR-based assays have the advantage that they are more amenable to high throughput processing and that specimens can be stored longer term. In addition, differentiation between trypanosome taxa by microscopy is much more cumbersome than with molecular methods, such as PCR. This study presents an improved ITS1-based

PCR assay for diagnosis of trypanosomosis and for efficacy assessment of trypanocidal compounds where the detection of genomic rDNA of Trypanosoma specific ITS1 serves as surrogate for parasite detection but with higher L-NAME HCl analytical sensitivity. The same primer sequences were employed in a previous survey on AAT in Ethiopia ( Fikru et al., 2012). However, the reaction mixture and cycling conditions of the ITS1 TD PCR are refined for optimal sensitivity and specificity. The “Touchdown” approach that employs more stringent primer-template hybridisation conditions is introduced to minimise potential non-specific amplifications. It favours amplification of desirable products during early cycles that will out-compete potential non-specific products during the remaining cycles ( Korbie and Mattick, 2008). For T. congolense, the newly developed ITS1 TD PCR has a lower detection limit of 10 parasites/ml blood while for T. vivax, this is 100 parasites/ml blood. A similar difference in detection limits between T. congolense and T.

5–4 mm lateral) with

dental acrylic and dental cement. The chamber was filled with sterile cortex buffer (125 mM NaCl, 5 mM KCl, 10 mM glucose, 10 mM HEPES, 2 mM CaCl2, and 2 mM MgSO4 [pH 7.4]) and sealed with a glass coverslip. MK-2206 solubility dmso Intrinsic optical signals (Figures 1A and S1A–S1C) were imaged through the intact skull using an Imager 3001F (Optical Imaging, Mountainside, NJ, USA). For details see Supplemental Experimental Procedures. After imaging, a small, ∼1 × 1 mm piece of bone was removed using a dental drill (centered above the C2 whisker maximum intrinsic optical signal response). The dura was removed, and the craniotomy was covered with agarose (2% in cortex buffer). A glass coverslip was positioned over the agarose (covering more than half of the craniotomy) to reduce heartbeat and breathing-induced motion of the cortex. Whole-cell “blind” patch-clamp recordings were obtained as previously described by Brecht et al. (2003). High-positive pressure (200–300 selleck screening library mbar) was applied to the pipette (5–8 MΩ) to prevent tip occlusion while penetrating the agarose and the pia.

After passing the pia the positive pressure was immediately reduced to prevent cortical damage. The pipette was then advanced in 2 μm steps, and pipette resistance was monitored in the conventional voltage-clamp configuration. When the pipette resistance suddenly increased, positive pressure was relieved to obtain a 3–5 gigaohm seal. After break-in, Vm was measured, and dialysis was allowed to occur for at least 5 min before deflecting the whisker. Data were acquired using a Multiclamp 700B Amplifier (Molecular CYTH4 Devices), and digitized at 10 kHz (National Instruments), using MATLAB (MathWorks)-based Ephus software (http://research.janelia.org/labs/display/ephus;

The Janelia Farm Research Center). Offline analysis was performed using custom routines written in IGOR Pro (WaveMetrics). All neurons were located between 100 and 275 μm below the pia (Supplemental Experimental Procedures). Current-clamp recordings were made using a potassium-based internal solution (135 mM potassium gluconate, 4 mM KCl, 10 mM HEPES, 10 mM Na2-phosphocreatine, 4 mM Mg-ATP, 0.3 mM Na-GTP, 3 mM biocytin, 0.1 mM spermine, pH adjusted to 7.25 with KOH, 285 mOsm). Rs and input resistance (Rin, not including Rs) were monitored with a 100 ms long-lasting hyperpolarizing square pulse 400 ms prior to each whisker deflection, and extracted offline by using a double-exponential fit. Initial Rs and Rin were not different between CTRL and DWE cells (Supplemental Experimental Procedures). Recordings were discarded if one of the following conditions occurred: (1) Vm and Rs exceeded −50mV and 50 MΩ, respectively; (2) spontaneously occurring spikes were not overshooting; and (3) Rs or Rin changed more than 30% over the duration of the experiment. The bridge was usually not balanced, and liquid junction potential was not corrected.

05; MCC permutation test; Figure S5). To investigate whether D-AP5 affects local phase-synchronization of single units, we computed the spike-LFP pairwise phase consistency (PPC; Vinck et al., 2010, 2012). D-AP5 had a three-fold effect (Figures 5C and 5D; p < 0.05, MCC permutation test on T statistics). First, it strongly increased theta locking (∼10 Hz) by about 100%. Second, a beta (20–25 Hz) rhythm emerged, which was absent in the control condition. Third, it increased spike-LFP phase-locking in the supra-gamma range (110–160 Hz). Finally, we tested whether D-AP5 altered the relationship between neuronal

www.selleckchem.com/products/Dasatinib.html discrimination scores and spike-LFP phase-locking patterns. For the 0.5–1.0 s. period of odor sampling (during which ROC values peaked) we correlated the unit’s time-resolved Dcorrected ROC values with their spike-LFP PPC values, separately for D-AP5 and aCSF. Differences in Spearman-rank correlations between the drug and control condition were observed in the theta and supra-gamma range ( Figure 6A; p < 0.05; MCC permutation test). For the control condition, we found that spike-LFP theta PPC positively predicted Dcorrected, with significant correlations peaking ( Figure 6B; p < 0.05, MCC permutation test on difference in Spearman rhos) around the time when the Dcorrected values peaked (0.5–1 s after odor onset; Figure 3). However, in the same time window D-AP5 induced a

negative correlation between Talazoparib molecular weight Dcorrected and supra-gamma PPC values ( Figures 6A and 6C). In conditions where a unilateral NMDAR blockade in rat OFC did not affect task acquisition behavior and modestly increased task-related firing rates relative to baseline, we showed that this receptor plays a significant role in neural representations discriminating between stimulus-outcome conditions and plastic changes in firing patterns associated with learning these representations. Especially during odor processing and decision-making the capacity of OFC neurons to discriminate between cues predictive of different

Tryptophan synthase outcomes was impaired by NMDAR blockade. In addition, NMDAR blockade increased local rhythmic synchronization, as indexed by spike-LFP phase-locking, particularly in the theta (∼10 Hz), beta (20–30 Hz), and high-frequency range (110–150 Hz). Finally, we found a positive relationship between theta phase-locking and neuronal discrimination scores under control conditions, which was abolished by NMDAR blockade. One concern, when examining drug effects on neurophysiological correlates of cognitive processes, is that the drug may affect behavior, which could in turn affect firing patterns in OFC known to represent relevant behavioral task components (Pennartz et al., 2011a; Schoenbaum et al., 2009). Bilateral infusion of NMDAR antagonist in OFC has been shown to increase impulsive responding and impair reversal learning (Bohn et al., 2003b).

These effects of selective

attention on power, and on interareal coherence and GC influences, were consistent across our sample of paired V1-V4 recordings (Figures 4, 5, and 6), although not always as pronounced as in the example. In V1, we selected sites that were primarily driven by one of the two stimuli. By contrast, in V4, we selected sites that were driven similarly by both stimuli (see Experimental Procedures for details). Correspondingly, for V4, condition assignment was arbitrary and Figure 4A shows V4 power changes (relative to prestimulus baseline) averaged across attention conditions, illustrating robust stimulus-induced gamma-band activation. Figure 4B shows the same analysis for V1 sites, split for attention inside and outside the V1-RF. Attention raised the V1 gamma peak frequency selleck chemicals llc (p < 0.001, nonparametric test based on randomization across sites; n = 37 sites) but did not change V1 gamma peak amplitude (not significant [n.s.], same test). Figure 4C shows the coherence

spectra averaged across all V1-V4 pairs of both monkeys, split by whether attention was inside or outside the V1-RF. Selective attention enhanced gamma-band coherence by 76% (p < 0.001, selleck chemical nonparametric randomization test across site pairs; n = 88 pairs of sites). The data from Figure 4C are shown separately per monkey in Figures 4D and 4E; in monkey P, attention enhanced gamma-band coherence by 56% (p < 0.001, same test; n = 68), and this average contained several very clear examples as, e.g., the one shown in Figure 2. In monkey K, attention enhanced gamma-band coherence by 142% (p < 0.001, same test; n = 20). Figure 4F shows the underlying distributions of gamma-band coherence values for each V1-V4 pair and session in the two attention conditions (p < 0.001 based on a paired sign test; n = 400). Figure 5 shows the gamma peaks of the two individual monkeys, Dipeptidyl peptidase scaled to ease comparison of peak frequencies. Between the two individuals, the gamma-frequency bands are distinctly different, as has been reported previously for animals

(Vinck et al., 2010) and humans (Hoogenboom et al., 2006; Muthukumaraswamy et al., 2009; Swettenham et al., 2009; van Pelt et al., 2012). Within the individual gamma-frequency bands, both monkeys showed the same arrangement of gamma peak frequencies: the gamma peak frequency at the relevant V1 site was 2–3 Hz higher than at the irrelevant V1 site and 4–6 Hz higher than at the V4 site. Importantly, the differences in gamma peak frequencies should not be taken as evidence that the respective gamma rhythms were not coupled, because we found clear V1-V4 coherence. The presence of coherence demonstrates that phase relations are consistent across time. By contrast, uncoupled oscillators of different frequency would constantly precess relative to each other, leading to no consistent phase relation and an absence of coherence.

All these goals are for helping children develop life-long physically active lifestyle

to enjoy their productive and healthy lives. Caloric expenditure that this study focused on is but one small aspect of the comprehensive educational experience in physical education. The findings shall not be understood as fulfilling all other important goals of physical education. “
“Falls are defined as an individual PFI-2 mw “inadvertently coming to rest on the ground, floor or other lower level, excluding intentional change in position to rest in furniture, wall or other objects”.1 The direct consequences of falls include devastating injuries and fractures that may lead to decreased mobility, functional decline, depressive symptoms, decreased social activity, and a decline in the quality of life.2 Decreases in balance function are intrinsic factors that can cause falls.3 Selleck SCH 900776 Many factors contribute to poor balance, including reduced strength, flexibility, and sensorimotor

coordination as well as delayed information processing. Oakley et al.4 collected information confirming that physical exercise reduces the risk of falls and may be a significant element in a more extensive program of preventive activities. One method of fall prevention consists of increasing muscular strength and improving body balance.5 Tai Chi, a Chinese martial art, has been used for centuries as a fitness exercise and is particularly popular among the elderly. It offers Tryptophan synthase substantial potential benefits by reducing the incidence of falls among the elderly population.6 A number of cross-sectional and longitudinal studies have shown that Tai Chi practitioners exhibit better balance control

than matched older adults from the general population.7 and 8 In 2001, Wong et al.9 compared the postural stability of older Tai Chi practitioners whose experience ranged from 2 to 35 years with that of healthy non-practitioners of similar ages. They found that elderly Tai Chi practitioners had better postural stability than non-practitioners when faced with disturbed somatosensory and visual input. Li et al.10 found that the Tai Chi group performed significantly better than the non-practitioner group on all functional balance measures. Both groups exhibited deterioration in functional balance measures during post-intervention follow-up. However, the Tai Chi group showed a significantly slower decrease. The results of more recent studies suggest that Tai Chi training may improve strength and flexibility,11 and 12 balance,13 blood pressure,14 and cardiorespiratory function15 in older adults. These findings support the benefits of Tai Chi as an exercise form for elderly men and women. Studies have focused on balance tests, in spite of other physical changes, such as impairments to reaction time (RT) and flexibility due to aging, may affect balance.

These findings are consistent with the presence of an endogenous PAM within nRT of wild-type mice. Christian et al. (2013) provide additional convincing evidence of a PAM residing within nRT by examining an LY2157299 cost adjacent thalamic nucleus—the ventrobasal (VB) nucleus. In contrast to neurons within nRT, a BR antagonist had no effect on the duration of IPSCs of neurons within VB. Might this be due to differences in the nature of GABAARs in the two nuclei? Or might PAM activity be present within nRT but not VB? To distinguish these possibilities, Christian et al. (2013) performed an elegant series of experiments combining “sniffer patches” with GABA uncaging. Outside-out

membrane patches containing GABAARs were obtained from VB cells and then placed into either VB or nRT within thalamic slices. Moving the patches from VB to nRT resulted in an increased duration of the GABA response within nRT compared to VB. These results exclude the Selleck BMS 354825 possibility that differences in composition of GABAARs are sufficient to account for the different responses to the BR antagonist in VB compared to nRT. Instead the results provide powerful support for the presence of a PAM within nRT. In search of the molecular identity of the PAM, Christian et al. (2013) explore DBI—a protein that is highly expressed in nRT and has previously been shown to bind the BR of GABAARs. Using

a mouse lacking a 400 kb region of chromosome 1 (nm1054) containing the Dbi gene plus several others, Christian et al. (2013) detect a reduction of sIPSC duration in the mutant animal compared to wild-type controls. These findings are similar to those observed in mice with a disrupted BR (α3(H126R)). Importantly, the reduced IPSC duration was rescued by viral expression of Dbi, demonstrating

that loss of this gene in particular is sufficient to account for the reduced IPSC duration. These findings Adenylyl cyclase provide strong evidence that the Dbi gene encodes the endogenous PAM within nRT. The fact that inhibition within nRT plays a critical role in regulating thalamic oscillations led Christian et al. (2013) to query whether the reduced duration of IPSCs within nRT neurons might be associated with enhanced sensitivity to absence seizures in a chemoconvulsant model. Indeed, enhanced sensitivity to chemoconvulsant-induced seizures was detected in mice lacking the Dbi gene (nm1054 mice). Similarly, mice with a disrupted BR in their GABAARs (α3(H126R)) exhibited prolonged epileptiform activity in response to the chemoconvulsant. These findings are consistent with the proposal that an endogenous PAM within nRT, specifically encoded by the Dbi gene, reduces susceptibility to absence seizures by enhancing GABAAR function. In sum, this lovely series of experiments establishes the presence of a PAM of GABAAR function that acts through the BR. Additionally, this work narrows the molecular identity of this PAM to a product of a single gene—Dbi; that said, unanswered questions persist.

These can be divided into four main groups: acute injuries (mechanical traumas, ischemic stroke, etc.), neurodegenerative chronic diseases (Alzheimer’s disease, multiple sclerosis, etc.), brain

tumors (glioblastomas), and infections (HIV, drug discovery E. coli, etc.). While there is a lot to discuss regarding the role of innate immunity in infection, stroke, and brain tumors, we will focus this part of the discussion on the implication of the innate immune system in two chronic diseases: Alzheimer’s disease and multiple sclerosis. We will use these complex pathological states to highlight the integration of all cell types of the NVU and how they can be used efficiently to develop new comprehensive ways of targeting such diseases. Alzheimer’s disease is caused mainly

by the deposition of Aβ into plaques in the CNS. The innate immune system plays a role in the development Doxorubicin of the pathology as chronic exposure of microglia to Aβ leads to uncontrolled inflammation, the release of toxic free radicals, and reactive oxygen species, as originally described in postmortem studies (Uchihara et al., 1997; Cagnin et al., 2001). Furthermore, large scale genome-wide association studies (GWAS) of thousands of AD subjects have shown that among the ten genetic polymorphisms most tightly linked to the development of late onset AD, nine play a dominant role in immunological processes (Moraes et al., 2012). In the serum, cerebrospinal

fluid, and the cortex of affected patients, higher levels of IL-1β, IL-6, TNFα, IL-8, and TGFβ have all been reported (for in-depth Reviews, see Rubio-Perez and Morillas-Ruiz, 2012 and Akiyama et al., 2000). Similarly, both TLR2 and TLR4 are overexpressed in peripheral blood mononuclear cells from patients with AD (Zhang et al., 2012). It also appears that the main monocytic chemoattractant CCR2 and its ligand CCL2 are involved in the progression of AD (Naert and Rivest, 2011; Conductier et al., 2010; Westin et al., 2012). Furthermore, Suplatast tosilate while no genetic association at the TLR4 locus was found in GWAS for AD (Moraes et al., 2012), polymorphisms in the TLR4 gene were shown to increase the incidence of late-onset AD in populations from Italy (Balistreri et al., 2008; Minoretti et al., 2006) and China (Wang et al., 2011; Yu et al., 2012; Chen et al., 2012). The reported data on humans state that, in essence, AD is first and foremost an immunological disease. The main genetic risk factor identified in GWAS for late-onset AD is ApoE4 (Bettens et al., 2013). The family of Apolipoprotein E (ApoE) plays a major role in the transport of cholesterol and other lipids, mainly by the binding of LDLRs and LRPs (Mahley, 1988; Holtzman et al., 2012). Humans have three common alleles of apoE gene, apoEε2, apoEε3, and apoEε4, which give rise to three protein isoforms, ApoE2, ApoE3, and ApoE4 (Bell et al., 2012).

, 2005) (Figure S1). Spike width was measured as the width of the extracellular spike waveform at half-amplitude (Barthó et al., 2004). All data analysis was performed in MATLAB (MathWorks). Spindles were detected semiautomatically

from the thalamic multiunit activity (MUA) separately for each shank (for details, see Figure S1). After automatic detection, spindles were verified visually, and false detections were deleted. Spindle phases were estimated at the maximal amplitude of Morlet wavelet transform using scales between 7 and 20 Hz. Jitter was defined as the SD of spike distances from spindle peak during a given cycle. For cycle-by-cycle cross-correlograms, only the reference spikes contained within the given cycle were considered. Number of spikes per burst in a cycle was estimated as the number of spikes fired, given the NVP-BGJ398 cell participated in a given cycle. Spike numbers per cycle, participation probability, and spikes GSI-IX cost per burst (Figures 5D, 6, and S6) were calculated for each spindle length category

averaged across all cells in all animals. Following the neurophysiological recordings, animals were transcardially perfused first with saline, and then with 400–500 ml of fixative containing 4% paraformaldehyde, 0.05% glutaraldehyde in 0.1 M phosphate buffer. Tissue blocks were cut on a Vibratome into 50 μm coronal sections. Electrode tracks were reconstructed from Nissl-stained slices (chronic experiments) or fluorescently counterstained for parvalbumin (acute experiments, the silicon probe

was dipped in DII solution beforehand). After lesion experiments, the fixed brain was cut into 50-μm-thick sections and or fluorescently counterstained for the neuronal marker NeuN to visualize the spread of lesion. The immunofluorescence stainings were performed according to the following protocol. Sections were intensively washed with PB and then treated with a blocking solution containing 5% normal goat serum (NGS) and 1% Triton-X for 45 min at room temperature. The primary antibody against PV (rabbit 1:3,000; Swant) and/or NeuN (mouse 1:300; Millipore) was diluted in PB containing 0.1% NGS and 0.2% Triton-X. After primary antibody incubation (overnight at room temperature), sections were treated with the secondary antibody Alexa-488-conjugated goat anti-rabbit or goat and anti-mouse immunoglobulin (Ig)G and/or Alexa-594-conjugated goat anti-rabbit or goat anti-mouse IgG for 2 hr at room temperature. After further PB washes, sections were mounted in vectashield (Vector) and imaged using epifluorescent microscopy (Zeiss). We thank Drs. G. Buzsáki, Z. Nusser, I. Soltész, J. Szabadics, and A. Lüthi for critical comments on the manuscript. The studies were supported by grants from the Hungarian Scientific Research Fund (OTKA NF101773, K109754 and K81357) the National Office for Research and Technology (NKTH-ANR, Neurogen), the Hungarian Brain Research Program – Grant No.

Strikingly, a primary decrease in the firing of MD neurons selectively disrupted this task-specific increase in MD-PFC beta-synchrony. In conclusion, our results demonstrate a causal relationship between decreased MD activity and deficits in executive function. They further suggest thalamofrontal beta synchrony as a potential mechanism contributing to working memory. A modified human muscarinic receptor, hM4D, was coexpressed along with humanized renilla green fluorescent protein (hrGFP) selectively in the MD using an adenoassociated virus expression system (AAV2-hM4D-IRES-hrGFP) (Figure 1A). The hM4D receptor is activated solely by a pharmacologically

inert compound, clozapine-N-oxide (CNO), and not by endogenous acetylcholine or any other neurotransmitter. Upon CNO activation, hM4D hyperpolarizes neurons through a G protein mediated activation of inward-rectifying selleck chemicals llc potassium channels ( Armbruster et al., 2007). Stereotactic injection of AAV2-hM4D-IRES-hrGFP virus into the MD induced coexpression of both GFP (green) and hM4D as assessed

by anti-HA immunostaining (red) ( Figure 1B). At higher magnification, we observed that the hM4D is localized in the plasma membrane as well as in neuronal processes ( Figures 1B and 1D). Costaining with this website anti-NeuN antibodies revealed that GFP expression was exclusively neuronal ( Figure 1C, top panel). Due to the absence of interneurons in rodent MD ( Kuroda et al., 1998), all infected neurons should be relay projection neurons. Using AAV2.2, an average of 27% ± 6% of the MD neurons expressed the GFP with a peak at 66% ± 9.6%

at the site of injection ( Figure 1C, bottom panel). The virus spread almost entirely among the anterioposterior axis of the MD whereas it stayed constrained within the second dorsoventral and lateromedial axis of the MD ( Figure 1C and see Figure S1A available online). Consistent with the known anatomy of the MD ( Kuroda et al., 1998), infected neurons projected to layers I and III/V of prelimbic and orbitofrontal cortices ( Figure 1D). To determine whether activation of hM4D will hyperpolarize thalamic neurons as has been shown for hippocampal neurons (Armbruster et al., 2007), we performed whole-cell patch-clamp recordings from thalamic slices. Fluorescently-identified neurons expressing hM4D were significantly hyperpolarized after CNO bath application, while the resting membrane potential of cells infected with a control virus expressing only hrGFP were not (Figure 2A). To determine whether activation of hM4D reduces the activity of MD neurons in vivo, we performed multiple single-unit recordings from the MD of freely moving mice injected with AAV2-hM4D-IRES-hrGFP (MDhM4D mice). For this experiment, mice were exploring a familiar environment, specifically a T-maze to which they had been previously habituated.

Similarly, if the subjective values of specific outcomes change as a result of selective feeding or taste aversion, the value functions for actions leading to those outcomes can be revised without directly experiencing

them (Holland and Straub, 1979; Dickinson, 1985). Therefore, the choices predicted by model-free and model-based reinforcement learning algorithms, as well as their corresponding neural mechanisms, might be different. As described above, errors in predicting affective outcomes, namely, reward prediction errors, are postulated to drive model-free reinforcement learning, GW3965 molecular weight including both Pavlovian conditioning and habit learning. An important clue for the neural mechanism of reinforcement learning was therefore provided by the observation that the phasic activity of www.selleckchem.com/products/SB-431542.html midbrain dopamine neurons encodes the reward prediction error (Schultz, 1998). Dopamine neurons

innervate many different targets in the brain, including the cerebral cortex (Lewis et al., 2001), striatum (Bolam et al., 2000; Nicola et al., 2000), and amygdala (Sadikot and Parent, 1990). In particular, the amygdala might be involved in both fear conditioning (LeDoux, 2000) and appetitive Pavlovian conditioning (Hatfield et al., 1996; Parkinson et al., 2000; Paton et al., 2006). Induction of synaptic plasticity in the amygdala that underlies Pavlovian conditioning might depend on the activation of dopamine receptors (Guarraci et al., 1999; Bissière et al., 2003). In addition, the ventral striatum also contributes to several different forms of appetitive Pavlovian conditioning, such as auto-shaping, conditioned place preference, and second-order conditioning (Cardinal et al., 2002). Given the increased range of actions controlled by habit learning, the anatomical substrates for habit learning might be more extensive compared

to the areas related to Pavlovian conditioning, and are likely to span both cortical and subcortical areas. Nevertheless, found the striatum has received much attention due to its dense innervation by dopamine neurons (Houk et al., 1995). The striatum integrates inputs from almost all cortical areas, and influences the activity of neurons in the motor structures, such as the superior colliculus and pedunculopontine nucleus, largely through disinhibitory mechanisms (Chevalier and Deniau, 1990; Mink, 1996). In addition, striatal neurons in the direct and indirect pathways express D1 and D2 dopamine receptors, respectively, and might influence the outputs of the basal ganglia antagonistically (Kravitz et al., 2010; Tai et al., 2012; but see Cui et al., 2013). Dopamine-dependent, bidirectional modulation of corticostriatal synapses might provide the biophysical substrates for integrating the reward prediction error signals into value functions in the striatum (Shen et al., 2008; Pawlak and Kerr, 2008; Wickens, 2009).