It seems conceivable that in the next 25 years, we will know enough about these mechanisms to begin to devise therapies to correct or ameliorate such dysfunction and possibly even reverse it. These therapies Dasatinib will target circuits in ways we cannot imagine right now, because we lack the refined understanding of neural mechanism at the appropriate level. The findings reviewed in this essay afford insight into mechanisms at a systems and computational level. We might begin our steps toward refinement by listing three open questions about the decision process described in the beginning of this essay. (1) LIP neurons represent the integral of

evidence but we do not know how the integration occurs or whether LIP plays an essential role. (2) The coalescence of firing rate before Tin choices suggests that the mechanism for termination is a threshold or bound crossing, but we do not know where in the brain the comparison is made, how it is made, or how the bound is set. We think the bound is downstream of LIP, and when it is, integration stops, but we do not know how a threshold detection leads to a change in the state of the LIP circuit. We also do not know what starts the integration. There’s a reproducible starting time ∼200 ms after the onset of motion, but we do not know why this is so

long and what is taking place in the 100+ ms between the onset of relevant directional Ketanserin signals in

visual cortex and their representation in LIP. (3) We do not know how values are added to the integral of the evidence. BAY 73-4506 research buy We’re fairly certain that time-dependent quantities, such as the urgency signal mentioned earlier or a dynamic bias signal (Hanks et al., 2011), are added, but we do not know whether they are represented independently of the DV and how they are incorporated into the DV. The answers to these questions will require the study of neural processing in other cortical and subcortical structures, including the thalamus, basal ganglia, and possibly the cerebellum. It makes little sense to say the decision takes place in area LIP, or any other area for that matter. Even for the part of the decision process with which LIP aligns—representation of a DV—it seems unlikely that the pieces of the computation arise de novo in LIP. Still, it will be important to determine which aspects of the circuitry play critical roles. Perhaps the most important problem to solve is the mechanism of integration. It is commonly assumed that this capacity is an extension of a simpler capacity of neurons to achieve a steady persistent activity for tenths of seconds to seconds (Wang, 2002), but this remains an open question. There are several elegant computational theories that would explain integration by balancing recurrent excitation with leaks and inhibition (Albantakis and Deco, 2009, Bogacz et al.

All together, however, with three excitatory afferent pathways and medium spiny neurons themselves all proving capable of eliciting the same behavior, it is likely that glutamate release in the NAc was the main determinant. Comparisons between optical and electrical brain Epacadostat stimulation reward are intriguing. While rats will work to initiate electrical stimulation of the NAc, they will also work to terminate it after a few seconds (Olds and Olds, 1963), suggesting that the stimulation becomes aversive some

time after onset. In response to the low-frequency optical stimulations used here, mice would remain in the laser-paired side of the chamber for minutes at a time. Another difference with classical brain stimulation reward is that the optical stimulations used here did not

necessarily result in increased movement (Glickman and Schiff, 1967). These distinctions may relate to the specificity of the optical manipulations. The fact that bulk activation of NAc shell neurons can also reinforce instrumental behavior underscores the idea that that motivated behavioral responding can be a direct consequence of excitatory drive in the NAc. How this finding relates to the selective stimulation of direct and indirect output pathways of the NAc is unclear. As in the dorsal striatum, these two output pathways have been shown to encode conflicting behavioral signals (Kravitz et al., 2012; Lobo et al., 2010). Indiscriminate stimulation enough of NAc shell neurons, however, appears to elicit behavioral effects SKI-606 concentration that would conceivably be produced by selective direct pathway stimulation. One possibility is that the distinction between output pathways might not be as absolute in the NAc as it is in the dorsal striatum (Bertran-Gonzalez et al., 2008). It could also be that the anatomical nature of the direct pathway is such that it has a leading role in downstream circuits

and is the default option for some behaviors encoded by the NAc. Alternatively, activity in the indirect pathway might not necessarily be a reward-opposing, demotivating force, but it could simply encode a separate dimension of this behavior. In any case, it is important to remember that the artificiality of the optical stimulations, being both massive and instantaneous, can presumably overwhelm inhibitory circuits that might balance activity in these pathways. In conclusion, the data presented here show that vHipp input is predominant in the medial NAc shell, selectively strengthened after cocaine injections, and of consequence to acute cocaine-induced locomotion. Also, discrete activation of three different excitatory inputs to the NAc, as well as NAc neurons themselves, was shown to reinforce instrumental behavior. Overall, this work contributes to our understanding of excitatory input to the NAc shell, as well as the contribution of this region to reward-related behaviors.

, 1995), the G38S mutant p150 protein exhibits a marked reduction in microtubule association ( Figures 1A and S1C). To investigate the consequences of the motor neuron disease-associated G59S mutation on Glued function in vivo, we first generated transgenic flies that express WT

and mutant human and Drosophila p150 ( Figure S1D). Surprisingly, overexpression of human or Drosophila p150WT in multiple independent transgenic lines is extremely toxic, leading to lethality or severe rough-eye phenotypes 3-Methyladenine cost when overexpressed in neurons using the panneuronal driver elavC155-GAL4 (Figures 1B and 5C). In contrast, overexpression of human p150G59S or Drosophila p150G38S in neurons causes a mild rough-eye phenotype ( Figure 1B), suggesting that the G59S mutation causes loss of function (LOF). Our biochemical data suggest that this LOF is due to a reduction in microtubule binding. Whereas

strong overexpression of p150WT is toxic, Lumacaftor research buy we found that low-level expression of Drosophila p150WT fully rescues the early larval lethality of Glued null animals (Gl1–3/GlΔ22; Siller et al., 2005), demonstrating that these transgenes are fully functional ( Figure 1E). Because the toxicity of high-level p150WT overexpression complicates the interpretation of p150G38S phenotypes, we introduced the G38S mutation directly into the endogenous Glued locus in the Drosophila genome by using homologous recombination ( Figure 1C). This knockin approach generates an allelic replacement that changes only a single genomic DNA base pair without introducing exogenous DNA (hereafter referred to as GlG38S), thereby allowing the mutant gene to be expressed under the control of the normal Glued regulatory elements throughout all tissues and stages of development. GlG38S homozygous flies are viable but sterile, whereas

GlG38S/Glnull(1–3 orΔ22) flies are late pupal lethal, demonstrating that the GlG38S mutation is a hypomorphic allele of Glued ( Figure 1E). Thymidine kinase The pupal lethality of GlG38S/Glnull animals is fully rescued to adulthood with ubiquitous expression of p150WT or with a genomic fragment containing the Glued gene (BAC [Gl+]), demonstrating that this lethality is caused by loss of Glued function ( Figure 1E). Western blot analysis shows that the mutant protein is expressed at reduced levels in GlG38S flies compared to controls, suggesting that the mutant protein is unstable ( Figures 1D and S1E). A reduced level of mutant protein expression is also seen in mice in which the G59S mutation was introduced into the endogenous p150 locus ( Lai et al., 2007). GlG38S and GlG38S/GlΔ22 larvae exhibit normal locomotion ( Figure 1F); however, GlG38S adult flies have dramatically impaired locomotor activity and are unable to fly ( Figure 1G). Adult GlG38S animals develop progressive paralysis with age and have a markedly reduced lifespan (median survival 16 days versus 70 days in WT) ( Figure 1H).

Chromatin immunoprecipitation (ChIP) assays revealed that endogenous SnoN occupied the endogenous DCX gene in granule neurons ( Figure 4D). Together, these results suggest that DCX represents a directly repressed target gene of SnoN1 in neurons. Because DCX promotes neuronal migration and SnoN1 represses DCX expression, we asked whether

inhibition of DCX might suppress the SnoN1 knockdown-induced neuronal positioning phenotype in the cerebellar cortex. DCX knockdown on its own in rat pups led to the accumulation of granule neurons in the Navitoclax upper IGL and reduced the proportion of granule neurons in the lower IGL (Figures 4E and 4F) suggesting that DCX plays a critical role in promoting granule neuron migration within http://www.selleckchem.com/products/ulixertinib-bvd-523-vrt752271.html the IGL. In epistasis analyses, we found that while SnoN1 knockdown increased the proportion of granule neurons in the lower domain of the IGL, the phenotype in animals in which DCX knockdown was induced in the background of SnoN1 knockdown was nearly indistinguishable from the positioning

phenotype induced by DCX knockdown alone (Figures 4E and 4F). These results suggest that DCX knockdown suppresses the SnoN1 knockdown-induced neuronal positioning phenotype in vivo. In other experiments, DCX overexpression mimicked the ability of SnoN1 knockdown in completely suppressing the SnoN2 knockdown-induced branching phenotype in primary granule neurons (Figures 4G and 4H and Figure S4A). Collectively, these data suggest that

repression of DCX expression mediates SnoN1′s function to coordinately regulate neuronal branching and migration. As a transcriptional corepressor, SnoN function is contingent upon its association with DNA-binding transcription factors. SnoN forms a complex with the transcription factor Smad2 and thereby represses Smad-dependent transcription in proliferating cells (He et al., 2003 and Stroschein et al., 1999). However, knockdown of Smad2 surprisingly failed to alter levels of endogenous DCX expression in granule neurons (Figure S5A) suggesting that SnoN1 might repress DCX in a Smad-independent manner. Interrogation of the regulatory sequences within the DCX gene revealed an evolutionarily conserved FOXO binding site within a reported DCX gene-silencing region in the first intron of the DCX gene ( Karl heptaminol et al., 2005). We asked whether SnoN1 might operate in concert with a FOXO family protein and thereby repress DCX transcription. We found that exogenous FOXO1 associated with endogenous SnoN1 in transfected 293T cells (Figure 5A). In addition, endogenous FOXO1 interacted with endogenous SnoN1 in primary granule neurons (Figure 5B). These results suggest that SnoN1 forms a physical complex with FOXO1. Expression of SnoN1, but not SnoN2, significantly reduced the ability of FOXO1 to induce the expression of a FOXO-responsive luciferase reporter gene in cells (Figure S5B). These data suggest that SnoN1 represses FOXO1-dependent transcription.

5, p > 0.3, η2 < 0.001). There was no effect BTK inhibitor of gender, age, or education on win-stay or lose-shift (all tests: F(20,661) < 3, p > 0.1). As mentioned in the introduction, probabilistic

discrimination and reversal tasks require subjects to ignore rare events in a stable environment, yet adjust their responses when the environment has changed. Therefore, we next assessed whether the SERT genotype affected response adaptation after any negative feedback, or whether this was specific to either the feedback validity or task epoch (acquisition or reversal). There was no interaction of SERT genotype with feedback validity (F(2,668) = 0.5, p = 0.6, η2 = 0.001), and SERT genotype significantly affected lose-shift whether feedback was invalid (F(2,668) = 4.8, p = 0.009, η2 = 0.014) or valid (F(2,668) = 5.3, p = 0.005, η2 = 0.016). This is not surprising, given that subjects are not aware of feedback validity. There was also no interaction of SERT genotype and task phase (F(2,668) = 1.9, p = 0.15, η2 = 0.006), and the effect of SERT genotype on BIBF 1120 order lose-shift

was significant during both the acquisition phase (F(2,668) = 6.3, p = 0.002, η2 = 0.018) and the reversal phase (F(2,668) = 3.1), p = 0.047, η2 = 0.009). A hierarchical regression analysis showed that DAT1 genotype significantly predicted the proportion of perseverative errors during the reversal phase, such that a higher ratio of 9R:10R alleles led to an increased number of perseverative errors (β = 0.084, t(671) = 2.22, p = 0.029) ( Figure 2C). This effect was specific to perseveration, as evidenced by the finding that there was no effect of DAT1 on chance errors (t(671) = 0.07, p = 0.95) ( Figure 2D), which were defined as single errors that occurred between two correct responses. Furthermore, there was an effect of DAT1 genotype on the interaction between perseveration and the choice history (rate of correct responses during acquisition; β = 0.10, t(671) = 2.72, p = 0.007) ( Figure 2E), in the absence of a main effect of choice history DNA ligase on perseverative error rate (t(671) = 0.44, p = 0.66). Again, there was no such interaction

for chance errors (t(671) = 1.5, p = 0.14). The DAT1 effects of choice history on perseveration were characterized by a dose-dependent reversal of their relationship: in 9R homozygotes perseveration increased with increasing number of correct choices during acquisition (β = −0.34, t(40) = 2.6, p = 0.013), whereas in heterozygotes there was no association (β = 0.061, t(221) = 0.89, p = 0.38), and in 10R homozygotes perseveration marginally decreased (β = −0.092, t(400) = −1.8, p = 0.069). We verified this effect against sensitivity to outliers using a robust regression, which confirmed the dose-response effects (9R9R, β = 0.062, t(40) = 2.31, p = 0.026; 9R10R, β = −0.008, t(221) = −0.61, p = 0.54; 10R10R: β = −0.024, t(400) = −2.7, p = 0.007).

Lastly, there was no apparent change in the levels of GABAB2 receptor protein (Figure 7F), suggesting little METH-dependent degradation of receptor. Dephosphorylation of GABAB2-p-S783 has been previously shown to be regulated by protein phosphatase 2A (PP2A; Terunuma et al., 2010), raising the possibility that in vivo exposure to METH enhances the phosphatase activity in VTA GABA neurons. To address this, we examined the effect of acutely inhibiting PP1/PP2A phosphatases with okadaic

acid (OA; 100 nM). In saline-injected mice, learn more there was no significant difference in the amplitude of IBaclofen with OA in the pipet, suggesting that basal activity of PP1/PP2A does not significantly regulate GABABR-GIRKs (Figures 7G–7J). In METH-injected mice, however, intracellular application of OA promoted recovery of the IBaclofen (Figures 7H and 7J). Note the slow time course of activation for IBaclofen in the presence of OA in METH-injected mice. This increase could reflect insertion of GABAB receptors and GIRK channels on the plasma membrane or restoration of

functional G protein coupling. For control, we examined the effect of PKC(19-36), a peptide inhibitor of PKC (Figure 7K). Unlike OA, the presence MI-773 of PKC inhibitor in the pipet did not restore IBaclofen, similar to the effect of METH alone. Taken together, these findings suggest that in vivo exposure to METH triggers a phosphatase-dependent downregulation of GABABRs and GIRK channels from the plasma membrane of GABA neurons, which results in reduced GABABR-GIRK signaling and accumulation of GABAB receptor complexes in intracellular compartments. To investigate the functional consequence of reduced GABABR-GIRK currents Vasopressin Receptor in GABA neurons of METH-injected mice, we examined the effect of baclofen on the induced firing rate of GABA neurons (Figure 8). We predicted that a loss of GABABR-GIRK signaling would attenuate GABABR-mediated

suppression of firing in GABA neurons. To test this, a series of current steps (20–100 pA) were injected to elicit a train of action potentials in GABA neurons (Figures 8A and 8B). In saline- and METH-injected mice, the input-output (I-O) plot shows a linear increase in firing rate with larger current injections (Figures 8B and 8D). As expected, baclofen (100 μM) significantly suppressed firing in GABA neurons of saline-injected mice, decreasing the slope of the I-O curve (Figures 8A and 8B). By contrast, a saturating dose of baclofen (100 μM) did not significantly change the I-O curve in METH-injected mice (Figures 8B and 8C). These results demonstrate that a loss of GABABR-GIRK currents in GABA neurons removes an important “brake” on GABA neuron firing in the VTA. Drug-evoked synaptic plasticity can cause persistent modifications of neural circuits that eventually lead to addiction.

, 2012). In mouse V1 we observed developmental improvements in coding efficiency for natural scenes after eye opening (increased response selectivity and mutual information rate), which was brought about by an increased neuronal sensitivity for natural scene statistics in the RF surround, but not for surround stimuli lacking the statistical regularities of natural scenes. This emergence of efficient processing of natural

stimuli was dependent on sensory experience, because it was absent in animals reared without visual input. In cat and monkey V1, costimulation of RF and its surround with naturalistic stimuli leads to more sparse and efficient responses than during stimulation of the http://www.selleckchem.com/products/PD-0332991.html RF alone (Vinje and Gallant, 2000 and Haider et al., 2010). Similarly, we found that in mature mouse V1, the full-field naturalistic movie was most effective for reducing spike rate and increasing selectivity and information per spike, consistent with the idea that neural codes are constrained by the same factors across mammalian species (i.e., energy consumption and information transmitted). Our findings reveal the existence of circuit mechanisms for improving coding efficiency beyond that provided by the filter characteristics of the RF alone (Olshausen

and Field, 1996, David et al., 2004 and Felsen et al., 2005b), which depend on the specific structure of natural scenes BI 6727 in vitro spanning the RF and its surround. While phase sensitivity of the surround in general has been suggested before (Guo et al., 2005, Sachdev et al., 2012, Shen et al., 2007 and Xu et al., 2005), we show that the sensitivity to

the spatiotemporal stimulus correlations across RF and surround is a plausible mechanism for improving neuronal selectivity. At the population level in mouse V1, recent experiments indicate on the one hand that surround suppression is orientation tuned (Self et al., 2014) and on the other hand that the representations of natural stimuli are sparser than those of phase-scrambled stimuli most (Froudarakis et al., 2014). Our data not only suggest a circuit mechanism for this increased coding efficiency of natural scenes but also reveal its developmental dependency. Importantly, while surround suppression was apparent albeit weaker already in the first days after eye opening, the surround-induced increase in response selectivity and information per spike were unspecific to the statistical properties of the surround stimuli in these visually inexperienced mice. The circuit mechanisms for increasing response selectivity are therefore present but not yet sensitive to detect the higher-order stimulus correlations of natural scenes in the immature visual pathway. Moreover, neurons in dark-reared, mature V1 were also indifferent to the statistics of surround stimuli.

As one example, SSRIs and KOR antagonism may produce functionally comparable effects

on 5-HT activity within the DRN, though via different mechanisms (i.e., inhibition of SERT versus reduced membrane insertion of SERT). This diversity should enable the selection of new drug candidates that have fewer off-target effects and greater safety. The hypothetical ability of SSRIs to correct a stress-induced dysregulation of 5-HT function within the DRN provides a rationale for retaining this mechanism in future antidepressant medications, including those that simultaneously block the reuptake of other monoamines (e.g., norepinephrine, dopamine). The work also strengthens emerging evidence that KOR antagonists might be useful for not only treating but also preventing stress-related illness (Land et al., 2009 and Carlezon

BMS-777607 manufacturer et al., 2009), particularly when exposure to stressful events can be anticipated in advance. Finally, it has exciting (albeit still theoretical) implications for the development of safer medications for pain. There was once Hydroxychloroquine order considerable interest in developing KOR agonists as nonaddictive analgesic drugs: stimulation of KORs produces analgesia (Pasternak, 1980), while the lack of mu-opioid receptor (MOR) activation minimizes abuse liability. Unfortunately, early clinical studies indicated that KOR agonists produced a variety of effects, including dysphoria and psychotomimesis (Pfeiffer et al., 1986), which made them intolerable and thus poor candidates for medication development. The data of Bruchas and colleagues suggests that loss of p38α MAPK function does not alter pain sensitivity or the ability of stress-induced KOR activation to produce analgesia. As such, it may be possible to design KOR agonists that do not activate p38α MAPK using concepts such as ligand-directed signaling (also called biased agonism or functional selectivity), a process by which a drug can simultaneously act as an agonist and an antagonist at different functions mediated by the

same receptor (Urban et al., 2007 and Bruchas and Chavkin, 2010). The discovery of such drugs would be facilitated by the availability of large chemical libraries and the development of high-throughput screening procedures that identify compounds that activate KORs but not p38α MAPK. Obviously, Rolziracetam it would be important to confirm that compounds that activate KORs but not p38α MAPK are motivationally neutral and do not replace the dysphoric effects of KOR agonists with the euphoric effects of MOR agonists. Several important questions remain. Although the finding that stress increases SERT function within the DRN strengthens long-hypothesized links among stress, 5-HT, and the therapeutic effects of SSRIs, it is well established that acute decreases in 5-HT alone are not sufficient to produce depression in normal humans (Heninger et al.

1; n = 6; p = 0.045; Figure 4A). In the presence of apamin, repeated depolarizing current injections (5 Hz; 3–4 s) neither caused a significant increase in CF response amplitudes http://www.selleckchem.com/products/VX-770.html (98.0% ± 2.1%; p = 0.373), nor in the spikelet number (120.3% ± 16.4%; n = 6; p = 0.283; Figure 4B). These observations show that plasticity of IE was, at least partially, occluded by apamin blockade of SK channels. Apamin also increased the amplitude of dendritically recorded Na+ spikes (151.9% ± 21.6%; p = 0.043), as

well as the spike count (222.8% ± 16.9%; n = 9; p = 0.00009; Figure 4C). SK2 (Kcnn2) is the only member of the SK family expressed in Purkinje cells (Cingolani et al., 2002). To directly test the role of SK2 channels in dendritic plasticity, we performed dual patch-clamp recordings from SK2 null (SK2−/−) mice ( Bond et al., 2004) or wild-type littermates (P17–P35).

In these mouse experiments, dendritic recordings were obtained 40–110 μm from the soma. Dendritic responses to CF stimulations had amplitudes of 20.59 ± 6.27mV (n = 10). Application of the depolarization protocol caused a significant increase in CF response amplitudes for wild-type (137.5% ± 14.4%; n = 6; last 5min; p = 0.048; Figure 4D) but did not elicit an increase of CF responses in SK2−/− mice (84.7% ± 14.9%; n = 4; p = 0.379; Figure 4D). The difference between these two groups was significant (p = 0.01; Mann-Whitney selleckchem U test). These results specifically implicate SK2 channels in this form of intrinsic plasticity. CF stimulation from SK2−/− mice frequently triggered prolonged spike firing rather than an isolated complex spike, preventing an accurate aminophylline measure of the spikelet number. In summary, experiments in the presence of apamin as well as the recordings from SK2−/− mice and wild-type littermates show that the increase in dendritic

IE depends on a decrease of SK2 channel activity. The apamin wash-in experiments show that SK channel blockade, in the absence of tetanization, causes a similar excitability increase, suggesting that a reduction in SK2 channel activity underlies, at least in part, the expression mechanism for this type of intrinsic plasticity. To examine the effect of dendritic plasticity on PF synaptic responses, we applied 10 Hz stimulation (5 pulses) to the PF input, resulting in a train of EPSPs with amplitudes that increased over the first responses. Stimulus strength was adjusted so that the first EPSP in the train was of low amplitude and remained subthreshold (dendritic EPSP 1 = 1.4 ± 0.37mV; n = 9; Figures 5A and 5B). In the somatic recordings, action potentials appeared toward the end of the EPSP trains, which were also seen as small spikelets on top of the dendritically recorded EPSPs (Figure 5B). Depolarizing current injections (5 Hz, 3–4 s) did not change the amplitude of EPSP 1 (dendrite: 99.7% ± 19.3%; p = 0.988; soma: 104.5% ± 6.4%; p = 0.

To remove the IKslowpoke component and hence isolate the Sh-mediated IKfast, recordings were done in low calcium (0.1 mM) external saline. Figure 4B depicts the averaged responses from voltage-clamp recordings in control muscle (heterozygous GAL424B driver, upper trace) and muscle expressing islet (lower

trace). Peak current densities of IKfast (entirely due to Sh-mediated K+ current) and the slow noninactivating currents recorded at +40 mV are shown in Figure 4C. Ectopic expression of islet in muscle is sufficient to produce a significant reduction in IKfast (control 26.6 ± 2.4 versus 24B > islet 15.8 ± 1.0 pA/pF, p selleck screening library ≤ 0.01) while no effect was seen on the slow current. Thus, expression of islet in dMNs is sufficient to reduce

a DTx-sensitive component of IKfast. Similar expression in muscle clearly demonstrates that Islet is sufficient to downregulate a Sh-mediated fast K+ current. Our electrophysiology indicates that Islet is able to repress Sh-mediated K+ current. To identify putative targets of Islet we used DamID, a well-accepted technique for demonstrating direct binding to chromatin or DNA in vivo (Choksi et al., 2006; Filion et al., 2010; Southall and Brand, 2009; van Steensel and Henikoff, 2000). Our analysis identifies 1,769 genes (exhibiting one or more peaks of Islet binding within 5 kb of the transcriptional unit) as direct targets Cytoskeletal Signaling inhibitor of Islet (FDR < 0.1%). Consistent with our model of Islet regulating a Sh-mediated K+ current, we find three significant binding sites within introns of the Sh locus (arrows 1 to 3 in Figure 5). found Intragenic binding of transcription factors is common in both vertebrates ( Robertson et al., 2007) and invertebrates ( Southall and Brand, 2009). A fourth significant peak is found upstream of Sh (arrow 4 in Figure 5). Binding of Islet at this site could regulate the expression of either Sh and/or CG15373 an adjacent, divergently transcribed, gene. By contrast, Shal and slowpoke, which

also encode fast neuronal K+ currents, were not identified as putative targets ( Figure 5). Thus, these data show that Islet binds to the Sh locus and is likely to regulate transcription of the Sh gene directly. To confirm that Islet binds Sh and regulates its transcription, we used qRT-PCR to quantify levels of Sh transcripts. We compared Sh transcript levels in larval CNS between control, islet−/− and panneuronal islet expression (1407 > islet). In comparison to control, the absence of islet−/− resulted in a 27% increase in Sh (1.27 ± 0.01, n = 2, p < 0.05). By contrast, panneuronal expression of transgenic islet resulted in a 45% decrease in Sh transcript (0.45 ± 0.06, n = 2, p < 0.05). We also measured Sh transcript level in body wall muscle following ectopic expression of islet (24B > islet). Similar to the CNS, Sh transcripts were reduced by 31% relative to control (0.31 ± 0.01, n = 2, p < 0.05).