Because TPSM was observed in both running and sleeping behaviors and did not correlate with animal’s speed or acceleration, we propose that it does not directly depend on motor behavior but is rather generated endogenously

in see more the brain. What is the physiological relevance of TPSM? More specifically, does it influence neuronal firing during sleep and awake behaviors? Analysis of population firing indicated significant (p < 0.05, Rayleigh test) but rather weak locking of CA1 pyramidal multinit activity to TPSM-phase in all behavioral conditions tested (modulation strength for sleep, κ = 0.1 ± 0.03, n = 4/4 recording sessions from 4 animals; for open field, κ = 0.07 ± 0.01, n = 8/9 recording sessions from four animals; for

maze, κ = 0.07 ± 0.02, n = 9/10 recording sessions from three animals; for wheel running, κ = 0.05 ± 0.004, n = 10/10 recording sessions from three animals). Although no significant difference (p > 0.05, two sample t test) in preferred firing phase was observed between conditions (preferred firing phase for sleep, μ = 0.87 ± 0.07π; for open field, μ = 1.04 ± 0.05π; for maze, μ = 1.2 ± 0.15π; for wheel running, μ = 0.93 ± 0.07π), further investigation revealed a real diversity at the single cell level. During sleep (Figure 5A), we found that 34% of the recorded neurons (47 out of 138, n = 4 animals) were significantly TPSM phase locked (p < 0.05, Rayleigh test) and displayed a preferred firing phase of 0.9π, Kinase Inhibitor Library ic50 nearly corresponding to the time of maximal theta power. In the many awake rat, there is a strong spatial correlate

to hippocampal firing (Huxter et al., 2003, 2008; Jensen and Lisman, 2000; O’Keefe and Dostrovsky, 1971). For open field and maze running, we therefore focused our analysis on place cells (n = 123 neurons from 4 animals in open field, 264 neurons from 3 animals in the maze) and examined separately the spikes discharged within (IN-PF) each neuron’s place field. We observed significant (p < 0.05, Rayleigh test) TPSM-phase locking of IN-PF firing for 36% of place fields in open field (Figure 5B) and 72% of place fields during maze running (Figure 5C), with a higher diversity of preferred phases than during REM sleep (compare circular plots in Figure 5B [open field] and 5C [maze] to 5A [sleep]). An interesting equivalent to the location-dependent firing of place cells is the time-dependent firing of “episode cells” reported by Pastalkova et al. (2008), a data set that we used for further analysis in the present study. While the animals were to run for a fixed amount of time in a wheel between successive maze runs, each moment in time (like each spatial position during spatial navigation) was characterized by the activity of a particular set of neurons, as members of self generated sequences of neuronal firing potentially encoding elapsed time during this fixed-delay period.

This multiplexing of motor-related information in a sensory neuron’s response could not be evidenced

in earlier experiments where behavior and electrophysiology were carried out separately (Fotowat and Gabbiani, 2007) or when animals were restrained to a trackball (Santer et al., 2008). Although our results strongly suggest multiplexing, they do not definitively prove it. This will require specific manipulation of the DCMD activity during ongoing behavior. Multiplexing of sensory information across populations of neurons has been documented earlier, particularly in the vertebrate visual and olfactory system, but its relation to behavior remains to be determined (Meister, 1996 and Friedrich et al., 2004; for a review see Panzeri et al., 2010). In invertebrates, several examples of neurons that contribute to distinct, and sometimes mutually exclusive, motor see more behaviors have been studied as well. These neurons can be thought of as being multiplexed, but on a very different time scale as that evidenced here (Kristan and Shaw, 1997). Our finding that distinct aspects of a complex, time-dependent motor behavior can be Epigenetics inhibitor encoded by distinct attributes of the time-varying

firing rate of a single sensory neuron suggests that similar encoding may occur at the sensory-motor interface in other systems, including vertebrates. We designed and built a custom integrated circuit that performs the amplification, analog to digital conversion, multiplexing, and wireless transmission of four low-noise channels: two for neural and two for muscle recordings (Figure S1). not The neural and muscle recordings are amplified with gains of 1000 and 100, respectively,

and filtered in the range of 300 Hz–5.2 kHz and 20 Hz–280 Hz, respectively. A 9 bit analog-to-digital converter samples them at 11.52 kHz and 1.92 kHz, respectively. The digital wireless transmitter operates based on a frequency-shift keying scheme at 920 MHz. The size of the packaged chip is 5 × 5 mm2 and was mounted on a 13 × 9 mm2 printed circuit board (PCB). Data from an accelerometer mounted on the PCB were also transmitted (ADXL330, Analog Devices, Norwood, MA; sampling rate: 1.92 kHz, bandwidth: 0–500 Hz). The accelerometer provided high temporal resolution but saturated for accelerations above ∼3.8 gn (gn = 9.8 m/s2). Therefore, we estimated the peak acceleration based on the video recordings. For this purpose, we tracked the position of the locust eye frame-by-frame and computed numerically its second derivative around the time of the peak. Wireless telemetry ran for 2 hr on a pair of 1.5 V batteries (#337, Energizer, St. Louis, MO). The weight of the system including batteries was 0.79 g (1.2 g after connecting and fixing the transmitter to the animal).

, 2008). Our study supports the notion that mutant HDL2-CAG protein can perturb CBP-mediated transcription, in part, but not necessarily

exclusively, through the sequestration of CBP into NIs. Our current study does not rule out the possibility that mutant HDL2-CAG protein may also disrupt the function of other critical nuclear transcription factors such as TBP ( Rudnicki et al., 2008). Additional gene expression and epigenetic profiling, along with functional manipulation of these molecular pathways in HDL2 mice, will be necessary to critically evaluate their contribution in disease pathogenesis. Finally, our study reveals the complexity of disease pathogenesis mediated by trinucleotide repeat expansion. Together with Compound Library SCA8 (Moseley et al., 2006), our models provide another compelling example in which bidirectional transcription across an expanded CTG/CAG repeat leads to the expression of an antisense CAG transcript and previously unrecognized polyQ protein toxicity. Because the predicted HDL2-CAG protein has no known homology to any other protein in the human proteome beyond the polyQ stretch (data not shown), the function of this transcript and the small protein it encodes remains to be explored. Given the recent

discovery that antisense transcription is nearly ubiquitous throughout the mammalian genome (Katayama et al., 2005), our study highlights the BIBW2992 importance of examining antisense repeat-containing Cediranib (AZD2171) transcripts and their ORFs in the pathogenesis of other brain disorders. Human BAC (RP11-33A21) containing the JPH3 genomic locus from BACPAC Resource Center (Oakland Children’s Hospital, Oakland, CA) was engineered by using homologous recombination and microinjected into FvB/N embryos to generate the BAC transgenic mouse lines, BAC-HDL2, BAC-HDL2-STOP, and BAC-JPH3 (Yang et al., 1997 and Gong et al., 2002). These mouse lines were maintained in FvB/NJ inbred background. A second

BAC control mouse that was generated by using the wild-type JPH3 BAC (CTD-2195P9) was created and maintained in the C57/BL6 background (BAC-JPH3b6). More details about the transgene constructs and initial characterization of the mouse lines are in Supplemental Experimental Procedures. For RT-PCR analyses of JPH3 sense strand and antisense HDL2-CAG transcripts, total RNA was extracted by using the RNeasy Lipid mini-kit (QIAGEN, Valencia, CA). Synthesis of cDNA was primed by using either oligo(dT)20 (Invitrogen, Carlsbad, CA) or strand-specific oligonucleotide primers (see Table S1 for primers). Both 5′ and 3′ RACE analyses were performed by using FirstChoice® RLM-RACE kit (ABI) following the manufacturer’s instructions. A random-primed reverse transcription reaction and nested PCR was used to amplify 5′ and 3′ ends of the transcript (see Table S1). Quantitative RT-PCR analyses of BDNF transcripts in BAC-HDL2 and control cortices were performed by using published protocol ( Gray et al., 2008).

Neither the frequency of bursts (control: 15.02 ± Selleck RG 7204 2.06 min−1, TTX: 17.92 ± 1.23 min−1), the frequency of local calcium transients per synapse (control: 0.58 ± 0.09 min−1, TTX: 0.72 ± 0.11min−1), nor the density of functional synapses (control: 39.5 ± 14.8 mm−1, TTX: 57.6 ± 23.6 mm−1) was significantly different between control and TTX treated cells. And, as expected, the fine-scale organization of synaptic

inputs in control cells was indistinguishable from that in our first set of experiments (compare Figure 5C and Figure 6). In contrast, the relationship between distance and input correlation was entirely abolished in cells that developed in the absence of neuronal spiking (Figure 6A). Interestingly, we observed not only a significant reduction of coactivation at neighboring synapses, but also an increase in coactivation in synapse pairs of intermediate distances (50–100 μm). This suggested that spiking activity

led to the stabilization of neighboring coactive synapses and a depletion of synapses that are coactive at intermediate distances. The latter conclusion is further supported by the observations that very distant synapse pairs (>100 μm) exhibit higher correlations than those of intermediate distance (Figures 5D and 6A) and that the correlation of very distant synaptic pairs was identical in TTX treated and control cells (Figure 6A). Finally learn more we investigated whether NMDA receptors, which mediate calcium signaling at the synapse (Figure 1H), but are dispensable for bursting, are required for the activity-dependent

secondly development of synaptic clustering. Slices were incubated in medium containing APV for 3–4 days. Subsequently, APV was washed out and synapses were mapped functionally. Very similar to TTX, APV abolished the clustering of functional synaptic inputs (Figure 6B), indicating that sorting functional inputs along developing dendrites is mediated by network firing activity and NMDA mediated synaptic plasticity. The patterns of synaptic activation received by a developing neuron are crucial for the fine-tuning of its synapses. Here, we mapped the spatiotemporal activity patterns of large populations of synaptic inputs onto hippocampal pyramidal cells using calcium imaging combined with patch-clamp recordings. Our analysis gave several new insights into the fine-scale synaptic organization during development. First, we found that different sets of synapses are activated during successive bursts of synaptic inputs. Second, even though activation patterns vary from burst to burst, they are not completely random: synapses that are located close to each other are much more likely to be coactive than more distant ones. Third, the emergence of this fine-scale input organization requires spiking activity and NMDA receptor activation.

, 2002) and transmit the major input signals to the motion detection circuitry ( Rister et al., 2007). In both neurons, onset and offset of histamine release cause transient hyperpolarizing and depolarizing dendritic responses, trans-isomer cost respectively, with a small sustained hyperpolarization

in between ( Laughlin and Hardie, 1978 and Laughlin et al., 1987). L1 and L2 relay their signals via long axons to separate layers in the second-order neuropil, the medulla. Here, information is picked up by mostly unidentified neurons that constitute the motion detection circuit and finally transmit their output to the third-order neuropil consisting of lobula and lobula plate. In the lobula plate, large directionally selective tangential cells extend their elaborate dendrites and spatially integrate see more the output of local presynaptic motion detectors ( Single and Borst, 1998 and Borst et al., 2010). Their responses to large-field motion in the preferred direction (PD) are positive (membrane depolarizations, or firing rate increases) and negative (hyperpolarizations, or firing rate decreases) in the

opposite, the so-called null direction (ND). In this study, we build on the recent discovery that the lamina neurons L1 and L2 constitute the input channels to the motion detection circuitry in Drosophila. Joesch et al. (2010) recorded from directionally selective tangential cells in the lobula plate while genetically blocking synaptic transmission from L1 and/or L2. Blocking both L1 and L2 removed motion-sensitive responses in lobula plate tangential cells. Importantly, blocking either L1 or L2 revealed that in flies, similar to vertebrates, the visual input is split into an ON and an OFF component. Here, we adapt the Reichardt Detector to incorporate these new findings, giving rise to two alternative models. Both models require a more elaborate internal structure of the detector to allow for an implementation of separate ON- and OFF-input signals. The first model, the “4-Quadrant-Detector” (Figure 1B) (Hassenstein and Reichardt, 1956) consists of four parallel detectors that cover all four possible combinations of input signals (ON-ON, ON-OFF, OFF-ON, and OFF-OFF). From

its input-output behavior, a 4-Quadrant-Detector mafosfamide is mathematically identical to the original Reichardt model. The second model, proposed by Franceschini et al. (1989), contains just two subunits, an ON-ON and an OFF-OFF detector (Figure 1C). Notably, this “2-Quadrant-Detector” is no longer equivalent to the original Reichardt Detector since input signals of opposite sign do not interact. These differences in response behavior should allow us to decide between the two models experimentally. We first presented apparent motion stimuli consisting of sequences of spatially displaced, persistent light increment (ON) and decrement (OFF) steps to two different fly species, Calliphora and Drosophila, while recording from lobula plate tangential cells.

To assay for elevated receptor expression across different brain structures, we performed autoradiographic radioligand binding assays

with iodinated epibatidine, which mainly binds α4β2∗ and α3β4∗ nAChRs (Perry CHIR-99021 cost and Kellar, 1995) (Figures 5A and 5B). Competition with cold cytisine, which binds with higher affinity to α4β2∗ than to α3β4∗ receptors (Marks et al., 2010), was done to distinguish α3β4∗ from overlapping α4β2∗ binding sites (Zoli et al., 1998) (Figures 5C and 5D). In WT mice, discrete brain regions resistant to cytisine competition labeled well-known α3β4∗ sites such as MHb, IPN, and superior colliculus (Figure 5C). In Tabac mice, increased radioligand binding to cytisine-resistant sites was detected in these areas and in additional brain structures, including the VTA, SuM, substantia

nigra, and striatum (Figure 5D). A strong correlation between radioligand signal and eGFP fluorescence was detected in all analyzed CNS structures (Figure 5E and Table S1). Densitometric analyses indicated significantly increased cytisine-resistant signals in α3β4∗-expressing regions in Tabac mice (Table S1), while α4β2∗ epibatidine binding sites such as cortex and thalamus did not differ between control and Tabac mice (Figures 5A and 5B), indicating that elevated surface receptors are present in sites corresponding to endogenous β4 expression sites. To exclude the possibility that the increased radioligand signal could reflect increased cell number, we quantified the cell density in MHb of Tabac and WT mice and observed no significant http://www.selleckchem.com/products/ch5424802.html differences (Figure S3). These data show that the enhanced nicotine-evoked currents in Tabac mice result from β4-mediated recruitment of additional functional α3β4∗ nAChR complexes on the cell surface. Taken together, the anatomic mapping and ISH results presented in Figure 3 and the receptor binding assays presented in Figure 5 provide compelling evidence that α3β4∗ nAChRs are located both on the cell soma and in the axon termini. For example, the relatively

light staining of the IPN by ISH in Tabac mice strongly suggests that the very heavy expression of functional α3β4∗ receptors, detected in this structure by receptor binding, results because from both local synthesis in the IPN and the presence of receptors synthesized in the MHb and transported to presynaptic termini in the IPN. This is consistent with the well-documented effects of presynaptic nAChRs on synaptic release and neurotransmission (McGehee et al., 1995), and suggests that Tabac mice will be an important tool for further dissection of the roles of presynaptically and postsynaptically expressed nAChRs. We were next interested in the effects of elevated nAChR expression on the behavioral responses of Tabac mice to nicotine.

These results indicate that JNK continues

to impact presynaptic pattern after its initial establishment. To understand where JNK might function within the neuron, we further examined the subcellular localization of JKK-1 and JNK-1 in DA9 using functional GFP fusion proteins. Consistent selleckchem with a presynaptic function, both JKK-1::GFP and JNK-1::GFP are highly enriched at the presynaptic terminals and colocalize with mCherry::RAB-3 (Figures S4B–S4J and S4K–S4S). This presynaptic enrichment requires the anterograde motor for STVs, UNC-104/KIF1A (Hall and Hedgecock, 1991); JKK-1::GFP and JNK-1::GFP are absent from the presynaptic terminals and accumulate in the cell body and dendrite in unc-104 mutants (data not shown). Axonal transport is critical for the establishment and maintenance of presynapses (Hirokawa et al., 2010). Alterations in the cell-wide distribution of presynaptic components could originate from changes in their axonal transport dynamics. We previously showed that presynaptic protein mislocalization in arl-8 mutants probably results from premature clustering of STVs during trafficking ( Klassen et al., 2010). To further investigate the role of the JNK pathway in regulating STV clustering during transport, we performed time-lapse

imaging of STVs labeled with GFP::RAB-3 in vivo. Within the proximal axon of wild-type DA9, small mobile and stationary GFP::RAB-3 puncta can be visualized with a high-sensitivity charge-coupled device camera, evident Epacadostat as diagonal and vertical lines in the kymographs, respectively, with the mobile puncta representing trafficking STVs, which pause frequently en route and form stationary puncta ( Klassen

et al., 2010; Figures 3A and 3B). arl-8 mutants did not exhibit changes in the directionality or velocity of STV movements ( Klassen et al., tuclazepam 2010). However, we observed significant increases in the number and fluorescence intensity of stationary puncta ( Figures 3C, 3F, and 3G). Meanwhile, there was a decrease in the number of moving events ( Figure 3H). The jkk-1 mutation strongly alleviated the STV trafficking abnormalities in arl-8 mutants; the number of stationary puncta en route and their fluorescence intensity were significantly reduced in the arl-8; jkk-1 double mutants ( Figures 3D, 3F, and 3G). Accordingly, there was a significant increase in the number of moving events ( Figure 3H). The jkk-1 single mutants showed no significant difference from wild-type animals ( Figures 3E–3H). The coexistence of stable and motile puncta is consistent with previous findings that STVs undergo intermittent moving and stationary phases en route to the presynaptic terminals (Ahmari et al., 2000; Sabo et al., 2006). The transitions between these two states might serve as regulated switches to control the trafficking and aggregation of STVs.

Two-way chi square analysis showed no significant differences in the distribution between groups (CP-FMS vs. CP-C) and between GMFCS levels (χ2 = 1.67, df = 2, p = 0.435). For the second study group, two classes of typically developing (TD) children without disability were recruited from a primary school (n = 26; 13 girls, 13 boys) and were allocated to either FMS training (TD-FMS; n = 13; mean age: 7.17 ± 2.77 years) or control (TD-C; n = 13; mean age: 6.82 ± 2.51 years). All participants from both groups met the following inclusion criteria: (1) no known health conditions that were contraindicated to engagement in moderate PA, (2) able to follow a minimum of 2-step commands, (3)

gave verbal assent, and (4) returned signed parental informed consent. No significant differences were found in the age and BMI selleck compound of the study groups. This pilot study used a pre–post-test design see more over a period of 8 weeks. Each participant completed 1-week baseline PA monitoring, followed by an FMS pre-test in the second week. Training sessions (45 min) were

conducted once per week for the FMS groups over 4 weeks, while the control groups received either their regular physiotherapy session (CP) or PE classes (TD). An FMS post-test was conducted in the subsequent week after completion of training, followed by post-training PA monitoring in the final week. All the study procedures were approved by the institutional review board of the University of Hong Kong. PA was monitored by uni-axial accelerometers (Actigraph 7164 model, Actigraph LLC, Pensacola, FL, USA) worn on the hip for 7 days23 at pre-training and post-training. The accelerometers were calibrated to a 15-s epoch to account for intermittent short bursts of activities that are typical of children. Evidence supports the validity of the Actigraph as a PA measure in children with

CP24 and 25 and children without disability.26 Data were analyzed for those who met a required minimum monitoring of 5 days (3 weekdays, 2 weekend days). Trost et al.27 determined that in children and adolescents, at least 4 monitoring days are needed to achieve acceptable reliability. Consistent with published standards for PA monitoring using the Actigraph, days with a total monitoring time of <5 h and >18 h were excluded28 and continuous Urease accelerometer counts of zero for ≥20 min were considered non-wear times.29 Log diaries were also distributed to enhance monitoring compliance and verify data.27 The cut-points suggested by Evenson et al.30 were used to estimate the time spent in sedentary, light physical activity (LPA), and MVPA. The cut points have been shown to be valid among children without disability30 and those with CP.25 FMS proficiency was measured using five components (locomotor: run, jump; object-control: throw, catch, kick) of the Test of Gross Motor Development-2nd edition (TGMD-2).

This occurs because

sequential activation of neurons in a recurrent network drives LTP at synapses in the forward direction but LTD in the reverse, thus creating directional connections (Clopath et al., 2010). The result is tuning for learned sequences, direction-selective visual responses, spontaneous repeated spike sequences Perifosine cost for motor patterning, and the ability to predict future events from past stimuli (e.g., Mehta et al., 2000; Buchs and Senn, 2002; Engert et al., 2002; Fiete et al., 2010). STDP also enforces synchronous spiking during signal propagation in feedforward networks, which is a common feature in vivo. To understand this, consider a feedforward network in which neurons exhibit a range of spike latencies to a synchronous network input. With STDP, feedforward synapses onto neurons that spike earliest are weakened, thereby increasing spike latency, while

synapses onto neurons that spike later are strengthened, reducing their spike latency (Gerstner et al., 1996; Suri and Sejnowski, 2002). This has been directly observed in the insect olfactory system (Cassenaer and Laurent, 2007). find more STDP can also mediate temporal difference learning (Rao and Sejnowski, 2003) and reinforcement learning (Farries and Fairhall, 2007; Izhikevich, 2007; Cassenaer and Laurent, 2012) and can tune neurons for temporal features of input (Masquelier et al., 2009). For anti-Hebbian STDP, fewer computational properties are understood. In the cerebellum-like electrosensory lobe of electric fish,

the LTD component of this plasticity (anti-Hebbian LTD) stores negative images of predicted sensory input, so that novel (unexpected) sensory inputs can be better represented (Roberts and Bell, 2000; Requarth and Sawtell, 2011). Anti-Hebbian LTD at parallel fiber-Purkinje cell synapses in mammalian cerebellum may perform a similar computation. Anti-Hebbian STDP is also prominent in distal dendrites of pyramidal cells (Sjöström and Häusser, 2006; Letzkus et al., 2006). This may serve to not strengthen late-spiking distal (layer 1) inputs which would have been weakened under Hebbian STDP (Rumsey and Abbott, 2004). Alternatively, anti-Hebbian LTD may keep distal synapses weak, thereby requiring greater firing synchrony for effective transmission and specializing distal versus proximal synapses for different computations (Sjöström and Häusser, 2006). Theory has also shed light on the basis and functional properties of multi-factor STDP. In an early study, the firing rate and timing dependence of plasticity was predicted from dynamic activation and calcium-dependent inactivation of NMDA receptors during pre- and postsynaptic spike trains (Senn et al., 2001). More recent biophysically realistic models of NMDA receptors, AMPA receptors, and cannabinoid signaling support and extend this unified model of plasticity (Shouval et al., 2002; Badoual et al., 2006; Rachmuth et al., 2011; Graupner and Brunel, 2012).

Both acute block of Sh activity (DTx) and loss of function of Sh expression significantly reduced IKfast ( Figure 3B; WT 40.5 ± 1.9 versus WT + DTx 29.3 ± 2.7 versus Sh[14] 26.1 ± 1.7 pA/pF; p ≤ 0.01 and p ≤ 0.01, respectively). Moreover, the IKfast recorded in dMNs under both conditions JAK phosphorylation (WT + DTx 29.3 ± 2.7 and Sh[14] 26.1 ± 1.7 pA/pF) was indistinguishable from that of vMNs in WT (26.1 ± 2.3 pA/pF, DTx p = 0.38, Sh p = 1), which is in full agreement with our model. To further support the notion that the difference in IKfast that exists between dMNs and vMNs is due, at least in part, to expression of Sh in dMNs, we recorded IKfast in vMNs under the same conditions. As expected,

neither the presence of DTx, nor loss of Sh, had any marked effect on IKfast in vMNs (p = 0.51 and 0.23, respectively; Figure 3B). To further verify the differential expression of Sh in dMNs versus vMNs we assessed transcription of Sh in these two cell types by in situ hybridization. We designed probes that specifically recognize the Sh pre-mRNA. These intron probes label the unspliced Sh transcript at the site of transcription within the nucleus, but not the fully mature message in the cytoplasm. We detected Sh transcription in dMNs, labeled with Eve antibody ( Figure 3C, black arrowheads), but not in vMNs, labeled by expression of

GFP (Lim3 > nlsGFP; Figure 3D, white arrowheads). Taken together, both electrophysiology and in situ hybridization are consistent Autophagy animal study with dMNs expressing Sh while the vMNs do not. Next, we tested whether Islet is sufficient to repress Sh-mediated K+ currents in cells where Sh, but not islet, is normally expressed. We used two different preparations for these experiments. First, we ectopically expressed islet in dMNs. Driving a UAS-islet transgene with GAL4RN2-0 significantly reduced IKfast (34.4 ± 2.6 versus 41.2 ± 1.9 pA/pF, experimental versus controls which consisted of WT and heterozygous GAL4 driver line, p

≤ 0.05; Figure 4A). These recordings were carried out in the presence of external Cd2+ to eliminate Ca2+-dependent K+ currents. The observed reduction in IKfast in dMNs could, however, be due to a reduction in either Sh- or Shal-mediated K+ currents. To distinguish between these two possibilities, we tested for DTx sensitivity, which is observed in WT dMNs and is an indicator for the presence of Sh currents. Casein kinase 1 DTx sensitivity was lost when islet was ectopically expressed in dMNs ( Figure 4A). In addition, when we expressed ectopic islet in dMNs in a Sh−/− background, there was no further reduction in IKfast compared to ectopic islet expression in a WT background ( Figure 4A). We conclude from this that ectopic expression of islet in dMNs is sufficient to downregulate Sh-mediated IKfast. The second preparation we used takes advantage of the fact that IKfast in body wall muscle is solely due to Sh and Slowpoke (the latter of which can be easily blocked [Singh and Wu, 1990]).