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The dynamics of neuronal feedback pathways are generally not well understood. This is due to the complexity arising from the combined dynamics of closed-loop feedback systems and the synaptic plasticity of feedback connections. Here, we investigate the short-term synaptic dynamics underlying the parallel fiber feedback pathway to a primary electrosensory nucleus in the weakly electric fish, Apteronotus leptorhynchus. In open-loop conditions, the dynamics of this pathway arise from a monosynaptic excitatory connection and a disynaptic (feed-forward) inhibitory connection to pyramidal neurons in the electrosensory lateral line lobe (ELL). In a brain slice preparation of the ELL, we characterized the synaptic responses of pyramidal neurons to short trains of electrical stimuli delivered to the parallel fibers of the dorsal molecular layer. Stimulus trains consisted of 20 pulses, at either random intervals or constant intervals, with varying mean frequencies. With random trains, pyramidal neuron responses were well described by a single exponential function of the inter-stimulus interval—suggesting a single facilitation-like process underlies these synaptic dynamics. However, responses to periodic (constant interval) trains deviated from this simple description. Random and periodic stimulus trains delivered when the feed-forward inhibitory component of this pathway was pharmacologically blocked revealed that inhibition and depression also contribute to the observed dynamics. We formulated a simple model of the parallel fiber synaptic dynamics that provided an accurate description of our data. The model dynamics resulted from a combination of three distinct processes. Two of the processes are the classically-described synaptic facilitation and depression, and the third is a novel description of feed-forward inhibition. An analysis of this model suggests that synaptic pathways combining plasticity with feed-forward inhibition can be easily tuned to signal different types of transient stimuli and thus lead to diverse and nonintuitive filtering properties.
Neuronal feedback is a ubiquitous component of nervous system organization. In many brain structures, feedback projections greatly outnumber primary input projections. Their functional role in information processing is, however, not well understood. In dynamic situations, such as during sensory processing, the analysis of neural systems with feedback is complex. Confounding such analyses are aspects of synaptic plasticity: many feedback synapses exhibit time- and stimulus-dependent dynamics. The development of simple and accurate models of these systems will be critical for understanding the detailed functions of feedback in processing dynamic sensory stimuli.
Neuronal feedback pathways are necessary for effective electrosensory processing (Bastian 1986; Bell 2001). Weakly electric fish use an active electric sense to detect nearby objects and to communicate with one another—behaviors calledelectrolocation and electrocommunication,respectively (Heiligenberg 1991). These fish generate an electric field that can be distorted by objects or the electric organ discharges (EOD) of other fish. Such distortions are encoded by electroreceptors distributed over the skin surface. In the gymnotid electric fish considered here, sensory afferents from these receptors terminate in the electrosensory lateral line lobe (ELL), making either mono- or disynaptic connections with the basal dendrites and somata of pyramidal neurons. The activity in these pyramidal neurons is the primary source of electrosensory information for higher brain areas.
In addition to sensory afferent inputs, ELL pyramidal neurons receive, via their apical dendrites, two sources of feedback input: thedirect and indirect (Fig.1 A) pathways (Berman and Maler 1999). Here, we focus on the indirect feedback from the parallel fibers (PF) of cerebellar granule cells (Berman and Maler 1998a); another recent study has focused on the direct feedback pathway (Oswald et al. 2002). Parallel fibers in the dorsal molecular layer of the ELL make monosynaptic excitatory contacts with pyramidal neuron apical dendrites, as well as disynaptic inhibitory contacts, via three types of inhibitory interneurons (Fig.1 A). While long-term changes (>10 min) in the efficacy of this pathway are well established (Bastian 1998a), there is relatively little known about its short-term dynamics on time scales of less than 1 s—important time scales for electrolocation (MacIver et al. 2001; Nelson and MacIver 1999) and electrocommunication (Bastian et al. 2001; Metzner 1999; Zupanc and Maler 1993). Indeed, plasticity on these time scales is prevalent in the higher order electrosensory neurons of the midbrain (Fortune and Rose 2000). Because short-term changes in efficacy of feedback synapses could greatly influence the responses of pyramidal neurons to electrosensory input, a better understanding of feedback dynamics is necessary to fully understand the function of ELL in processing electrosensory information.
In this paper, we present a quantitative description of the short-term dynamics underlying the PF feedback to ELL in the weakly electric fish,Apteronotus leptorhynchus. An important aspect of our study is that we consider the dynamics arising from inhibitory mechanisms in addition to those associated with traditional short-term synaptic plasticity (i.e., facilitation and depression). We extend a previous model of facilitation and depression at a cerebellar parallel fiber synapse (Dittman et al. 2000) by including a novel description of feed-forward inhibition. This new model, which we refer to as an FDI model because it includes facilitation (F), depression (D), and inhibition (I), provides an accurate description of the PF synapse in the ELL under our experimental conditions. A detailed analysis of our model suggests that not only can this synapse be tuned to exhibit different levels of gain control, but that it also may be tuned to transmit different types of transient stimuli. These diverse filtering characteristics suggest that the PF feedback pathway could play an important role in adaptive sensory processing in the ELL.
ELL slice preparation
The gymnotiform fish, Apteronotus leptorhynchus (male or female, 10–15 cm in length) were anesthetized in oxygenated water containing 0.2% 3-aminobenzoic ethyl ester (MS-222; Sigma). Surgical procedures and slice preparation were performed as previously described (Berman and Maler 1998b; Mathieson and Maler 1988). True-transverse 350-μm slices of the ELL were obtained and transferred to an interface-type slice chamber. Slices were perfused (2 ml/min) with bubbled (95% O2-5% CO2), room-temperature (20–22°C) artificial cerebrospinal fluid (ACSF) containing (in mM) 124 NaCl, 24 NaHCO3, 10 d-glucose, 1.25 KH2PO4, 2 KCl, 2 CaCl2, and 2 MgSO4. A recovery period of 1–2 h was allowed before recordings were made. In experiments aimed at assessing the effects of GABAA-mediated inhibition, the GABAA antagonist SR-95531 (Tocris Cookson) was bath-applied (5 μM in ACSF). All protocols were approved by the University of Ottawa Animal Care Committee.
Stimulation and recording
The ELL comprises several morphologically and functionally distinct layers (Berman and Maler 1999; Maler and Mugnaini 1994): dorsal molecular layer (DML), ventral molecular layer (VML), stratum fibrosum (StF), pyramidal cell layer (PCL), granule cell layer (GCL), deep neuropil layer (DNL), and the deep fiber layer (DFL). There are three main inputs to ELL neurons:1) the primary afferents, which run through the DFL and then form synapses with granule cells and pyramidal cells in the DNL (Fig.1 A), 2) the direct-feedback fibers of the StF, which originate in the nucleus praeminentialis (nP) and form synapses in the VML (not shown), and 3) the cerebellar PF of the indirect feedback pathway, which form synapses in the DML (Fig.1 A). The PFs originate from granule cells in the caudal region of the cerebellum [eminentia granularis posterior (EGp)] and course through the DML perpendicular to the orientation of the apical dendrites of the ELL pyramidal neurons, as they do in the cerebellar molecular layer (Maler 1979; Maler et al. 1981).
Parallel fibers in the DML were stimulated through a stimulus isolation unit (Digitimer; 20-μs pulses, 10–25 V) using two tungsten microelectrodes (2–4 MΩ; FHC, Inc.) in a bipolar configuration, placed in the more dorsal half of the DML and about 300–400 μm lateral to the recording site. The electrode pairs were oriented perpendicular to the parallel fibers, about 100 μm apart. Trains of 20 stimulus pulses were delivered with either constant intervals (periodic trains) or randomly distributed intervals (random trains). The random intervals were computer generated from exponential distributions that were truncated to have a minimum interval of 10 ms (intervals smaller than this made it difficult to resolve the synaptic response). Three different random sequences were generated for each of two mean frequencies, 4 and 16 Hz. Each random train was repeated three times in each slice, with the mean responses over these trials taken as the response for that slice. Depending on the experiment, slice data from periodic trains was a mean of one to three individual trials. The different trains were delivered in a randomized block pattern, with ≥2 min between the delivery of successive trains.
Field potential recordings of the synaptic responses to stimulus trains were recorded using glass microelectrodes (3–10 MΩ filled with 1 M NaCl) as in previous studies (Berman et al. 1997). The electrode tips were placed in the DML of the centromedial segment (CMS) of the ELL at a depth of 30–60 μm and along the parallel fiber axis, medial to the stimulation site. Intracellular recordings were made using sharp microelectrodes beveled to 60–80 MΩ (filled with 3 M KAc) with tips placed in the PCL of the centromedial segment. Both field and intracellular recordings were amplified and filtered (DC-1 kHz, Axoclamp-2A; Axon Instruments), digitized at 5 kHz (ITC-16; Instrutech, Greatneck, NY), and acquired using Pulse Control (Instrutech) and Igor Pro (Wavemetrics, Lake Oswego, OR) software running on a Power Macintosh 7100. We quantified the synaptic responses in both types of recordings by measuring the peak deflection from baseline. The baseline was taken as the average potential in a 2-ms window just previous to stimulus onset. All amplitudes are expressed as mean ± SE in either absolute or normalized units (unless otherwise noted).
Model description
In this paper, we discuss short-term synaptic plasticity (transient facilitation- and depression-like processes) having time scales less than 1 s. Typically, such processes are modeled using so-called FD models (Dayan and Abbott 2001; Fisher et al. 1997). In an FD model, a stimulus-evoked postsynaptic potential (PSP) is typically described by a combination of processes that can either increase (F processes) or decrease (D processes) the PSP amplitude relative to its control value (Ao ). After each stimulus arrives, the values of F and D change by discrete amounts (the update magnitudes) and then decay exponentially, between stimuli, toward a resting value. This general formalism has been used to describe many different synapses with the details of implementation varying among these cases (e.g., Dittman et al. 2000; Hempel et al. 2000; Tsodyks and Markram 1997; Varela et al. 1997). Because a conventional FD model was not able to capture all features of our data resulting from both periodic and random stimulus protocols, we modified a previous FD model of a cerebellar parallel fiber synapse (Dittman et al. 2000) and added a depression-like term that describes the inhibition due to PF activation of interneurons in the ELL molecular layer—we refer to this model as the FDI model. The response of the FDI model to the ith stimulus delivered at a timet i is given by a combination of three different processes (Eq. 1 ) Equation 1The basic formulation of the FD portion of our model has been described in detail previously (Dittman et al. 2000), so we simply outline our modifications in the following sections.
As in the original model of Dittman et al. (2000), our model uses a single facilitation term (F) whose value is given by F C passed through a squashing function (Eq. 3 ) such that F varies between a minimum value of F o at rest and a maximum value of one (i.e., the maximum release probability). The process F C has conventionalFD model dynamics (Eq. 2 ) and is associated with the calcium-dependent vesicle release process. Here, and in all further discussion, the times (in seconds) of stimulus arrival are given byt i. At each timet i, the value ofF C is increased by the update magnitude ΔF and then recovers exponentially to its resting value of zero. The parameter ΔF was the only free parameter for the fitting process because the two other parameters were held constant (the recovery time constantτ F = 0.1 s; and the baseline release probability F o = 0.1) at values close to those of the original model (Dittman et al. 2000) Equation 2 Equation 3In principle, we could describe the data presented in this paper using Eq. 2 alone, but we chose Dittman's original formulation (using both Eqs. 2 and 3 ) because it will enable us, in future studies, to evaluate the dynamic effects of changing the baseline release probabilityF o.
In addition to a single facilitation term, our model contains a single depression term that is identical to that described in Dittman et al. (2000), except that it does not include a calcium-dependent time constant (Eq. 4 ). We have no data in our system suggesting that this time constant may vary, so τD was set to 0.083 s (a value close to the initial conditions used in the Dittman model) and did not depend on stimulus history. The dynamics of this D process are similar to those of the F process. The difference is that whenD is updated at every stimulus, it is decreased by an amount equal to the product FD (see Dittman et al. 2000 for more details). The result of this update rule is that the larger F becomes the more prone the synapse becomes to depression Equation 4
Most models of short-term synaptic plasticity are focused on the dynamics of presynaptic inputs and therefore the experimental conditions usually involve blocking inhibition. However, the combination of presynaptic plasticity and feed-forward inhibition can result in diverse computational properties (e.g., Buonomano 2000; Buonomano and Merzenich 1998). Inhibition associated with PF input to ELL acts on a time-scale of less than 1 s (Berman and Maler 1998a), and so its transient dynamics may be important for ELL processing of transient stimuli. Thus we wished to have a description of the short-term dynamics of the PF synapse in ELL that included inhibition, yet that was of the same level of complexity as conventional FD models.
In ELL, parallel fibers synapse with both pyramidal neurons and inhibitory interneurons in the DML (Fig. 1 A). We assume that this input is identical for both types of neurons and that its dynamics are given by the product of the (presumed presynaptic) facilitation and depression terms, F(t) ·D(t). In other words, the input to the interneurons (s i) is proportional toF(t) · D(t), and it is this that determines the update magnitude for inhibition ΔI at each stimulus pulse (Eqs. 5 and 6 ). The scaling term related to this input,k I, is a free parameter that we refer to as the gain of inhibition. The dynamics of this inhibition (I), assumed to be a lumped contribution of the three interneuron types, are modeled as a conventional FD process (Eq. 7 ). This formulation is such that the inhibition acts to scale the amplitude of the PSP (see Eq. 1 )(Berman and Maler 1998a). The duration of this inhibitory effect was found to be approximately 300 ms (Berman and Maler 1998a), so τ I = 0.3 s. Note that the inhibition at these synapses in ELL is GABAA-mediated and GABABantagonists have no effect (Berman and Maler 1998a) Equation 5 Equation 6 Equation 7At each stimulus (t =t i), the value of I is decreased by the fraction ΔI and then decays exponentially to a resting value of one. The input to the inhibitory process, s i (Eq. 5 ), determines the value of ΔI through the input-output function in Eq. 6 ; for smalls i, ΔI is close to one, resulting in a small inhibitory effect, and for larges i, ΔI is close to zero, resulting in a large inhibitory effect.
To assess the impact of the dynamics of this synapse on signal transmission, we consider a situation in which 100 presynaptic inputs are delivered to a simple "postsynaptic" neuron. Each input consists of a poisson-distributed spike train with a given mean frequency. The postsynaptic neuron is a simple linear integrator (τV = 5 ms) that sums all the PSPs produced by the active inputs at each simulated time step (Eq. 8 ). The set of spike times for the jth input is given by {t } Equation 8We considered three different scenarios for the dynamics controlling the amplitude of each input (PSPj):1) no plasticity condition, where PSPj is equal to one and does not vary throughout the simulation; 2) FD condition, where PSPj is given by the dynamics of F andD processes alone (analogous to blocking inhibition in the full FDI model or setting I equal to one); and3) FDI condition, where PSPj is given by the dynamics of the fullFDI model.
For the results shown in Fig. 8, the mean and variance ofV(t), under each condition, were calculated over 10 s of simulation time after all transient behavior had decayed. To assess the relative performance of the model under the different conditions, the signal-to-noise ratio (SNR, Eq. 9 ) was calculated for the responses to two types of transient inputs:step changes and Gaussian changes in the mean frequency of the poisson inputs. For the results shown in Fig.10, the mean μV and variance ς of V(t) was estimated at two time points, t 1 andt 2 (see Fig. 9) Equation 9For step changes, the time at which the step occurs was denoted as t = 0 s, witht 1 = 0.005 s andt 2 = 1 s. This choice of comparison points was chosen such that a larger SNR would result when the system produced larger transient responses to stimuli and very little responses to constant changes (i.e., a system with gain control would in general do better than one that simply followed the stimulus time course). For Gaussian changes, the time at which the Gaussian peak occurs was denoted as t = 0 s, witht 1 = −1 s andt 2 = 0 s. Estimates of μV and ς were calculated from the sample means and variances of 30 independent simulation trials at each time point.
In this paper, we characterize the short-term dynamics of the parallel fiber synapses that form the indirect feedback pathway to pyramidal neurons in the ELL. These synapses consist of an excitatory component and a feed-forward inhibitory component (see Fig.1 A). Our goal is to formulate a quantitative model of this pathway that captures the dynamics during short periods of activity. Such a model can then be used in larger scale models aimed at understanding the role of dynamic feedback in ELL function. To this end, we delivered stimulus trains of constant (periodic) and randomly distributed (random) intervals to PFs, while synaptic responses were measured using field potential recordings, and in some cases, intracellular recordings.
Responses to short stimulus trains
The synaptic responses from PF stimulation depended on the particular sequence of inter-stimulus intervals. Figure 1 Bshows the field potentials (fEPSPs) recorded during excerpts of random stimulation at two different mean frequencies in the same slice. In this slice, the control response was 0.97 ± 0.04 mV (8 trials), but for some closely spaced stimuli, the responses increased more than twofold in magnitude.
Figure 2 A shows the mean normalized fEPSP (relative to the control amplitude, i.e., the first PSP in the train; 0.73 ± 0.06 mV; n = 9 slices) as a function of the preceding stimulus interval for 4- and 16-Hz random trains. These data, although variable, are fit well by a single exponential (R = 0.86), suggesting that a single facilitation-like process may underlie the dynamics of the PF synapse. For such a process, F* having dynamics similar toF c (Eq. 2 ), the relationship between the successive values of F* and the previous interval can be derived (Eq. 10 ) Equation 10where the {t i} are the stimulus times, the F*(i) are the values ofF* at each stimulus, and the other parameters are similar to those defined for Eq. 2 (update magnitude Δ*, and time constant τ*). Now, if the value ofF*(i) is close to one [i.e., recovery from the (i − 1)th stimulus is nearly complete], then F*(i +1) is a simple exponential function of the stimulus interval,t i+1 −t i (Eq. 10 ). This provides a simple explanation for the exponential curve fits in Fig. 2. These results suggest that as long as multiple high-frequency events are rare (as is the case for these random trains), then the data can be explained by a facilitation process alone. However, other processes come into play under different stimulus conditions. Plotted in Fig.2 B are the mean responses to the 3rd and 20th stimuli of periodic trains (4–64 Hz; see following for details). The amplitude of the third PSP follows the simple exponential relationship with stimulus interval. However, by the 20th stimulus in a periodic train, the responses deviate significantly from this predicted behavior for the two smallest stimulus intervals. As successive high-frequency events occur, as in the case of these periodic trains, other processes exert a greater influence on the overall synaptic responses. This observation necessitated the formulation of a more complicated model that included the effects of inhibition and/or synaptic depression.
Contribution of inhibition to synaptic dynamics
The inhibitory component of the feedback in DML (Fig.1 A) is provided predominantly by the GABAergicstellate and vml interneurons (with a smaller contribution from the GC2 neurons) and mediated by GABAA receptors on ELL pyramidal neurons (Berman and Maler 1998a; Maler and Mugnaini 1994). To determine the contribution of this inhibition to the synaptic responses to PF stimulation, we bath-applied the GABAA-antagonist SR-95531 (5 μM) and delivered a 32-Hz periodic train and a 4-Hz random train (identical pattern of interstimulus intervals in all trials). Blocking inhibition in this way resulted in a significant increase (17%) in the amplitude of the control fEPSP (control mean = 0.52 ± 0.04 mV, SR mean = 0.61 ± 0.05 mV, 7 slices; paired t-test,P = 0.02), in line with previous results (Berman and Maler 1998a). Figure 3summarizes the results of blocking inhibition when each type of train was delivered. Note that the response amplitudes in this figure are normalized to the first PSP of the control condition. In Fig. 3 A, the responses are plotted as a function of time, and the vertical lines denote the times of stimulus delivery. Note that in Fig. 3 B, responses are plotted against stimulus number, but that the interstimulus intervals are constant (periodic train). To determine if the apparent differences in the responses over the course of the trains were not simply due to a scaling component, we normalized the data in a different way, such that the first PSP of all trains (for both control and SR conditions) was equal to one. Comparing these re-normalized trains allows the dynamics to be compared independent of the scaling component of inhibition. Blocking inhibition still had a significant effect on the responses (2-way ANOVA, P< 10−5 for random train and P< 10−7 for periodic train). Thus the dynamics of inhibition influence the pattern of responses to train stimulation at pyramidal neuron feedback synapses. Note also that for the periodic train in the SR-treated condition, there is a slight decrease in response magnitude during the later part of the train (Fig.3 B), suggesting that a component of synaptic depression remains after inhibition is blocked.
Quantitative model of the PF synapse
We have shown that a model of the PF synapse in ELL must include the dynamics of feed-forward inhibition. We attempted to fit the data with a conventional FD model (see methods), in which an independent depression-like process was used to model inhibition. With such models, we could not account for the responses to both random and periodic trains with the same parameter sets. So, we modified a recently described FD model of a cerebellar parallel fiber synapse (Dittman et al. 2000; seemethods for details) to include feed-forward inhibition. A schematic of our model illustrates the three important processes underlying the synaptic dynamics (Fig.4). The first two, F andD, are essentially the same as those described in the previous model (Dittman et al. 2000). As motivated by our results in the previous section, the model also includes the influence of an inhibitory process (I). Because of the feed-forward nature of the inhibition (see Fig. 1 A), we assume that the inhibitory process is driven by the same excitatory processes as the postsynaptic pyramidal neuron (given by the productFD). This is a critical assumption, but as yet, we have no data on the specific dynamics of either the presynaptic inputs to the inhibitory interneurons or the interneurons' release dynamics. It should be noted however, that in cortex there can be differential plasticity at synapses among pyramidal neurons and inhibitory interneurons (Galarreta and Hestrin 1998; Reyes et al. 1998).
The model involves two free parameters: ΔF, the update magnitude of the F process, andk I, the gain of the inhibition. The accuracy of the model in describing a particular data set is given by the root-mean-squared difference (RMS error) between the two. We used a subset of the data to fit the model and another subset to test the model. We considered a fit to be adequate when the RMS error was less than the SD of the individual responses (Hunter and Milton 2001). On average, this trial-to-trial variation was 14% (SD; 9 slices).
Fitting the model
The first step in the fitting process was to consider the data from experiments where inhibition was blocked (Fig. 3). In these cases, the parameter k I was set to zero and the model consisted of F and D processes alone. For simplicity, the data were normalized to the amplitude of the first response in all cases (so A o = 1/Fo). The mean data from periodic stimulation (Fig.3 B, ○) was well described by the model (ΔF = 0.13; RMS error = 3.2%). The model, with this parameter set, was then tested on the data from random stimulation without inhibition (Fig. 3 A, ○). The resulting RMS error of 8.8% suggests that the model provides a good overall description of the dynamics of this synapse in the absence of inhibition.
In the next step of the fitting process, we considered the control data shown in Fig. 3 (●). The parameter ΔF was held constant at the value from the previous fit (ΔF = 0.13), andk I was a free parameter. Again, the model provided a good fit to the periodic data (k I = 10.4; RMS error = 2.6%). Testing this parameter set on the random stimulation data produced an RMS error of 9.2%. These results suggest that the short-term dynamics of the PF synapse can be accounted for by the combination of three simple processes, facilitation (F), depression (D), and inhibition (I).
We also tested the model on an additional set of data in which periodic trains were delivered at various frequencies (Figs.5 and6). With both ΔF and k Iallowed to vary, we fit data from 4, 16, and 64 Hz simultaneously and then tested the fit on data from 8- and 32-Hz stimulation. For this data set as well, the model performed well (the combined RMS error for the fits to 4, 16, and 64 Hz data was 6.4% and those for 8 and 32 Hz were 2.4% and 2.6%, respectively). Figure 6 summarizes these data and the model performance for the responses to the 3rd and 20th stimuli of the periodic trains. An interesting feature of the dynamics here is that on the shorter term (3rd pulse) the synapse is high-pass, where as in the longer term (20th pulse) it is band-pass. This suggests that the PF synapse may be particularly sensitive to burst-like input, where short-duration high-frequency events are separated by periods of relative inactivity.
The conclusions made from field potential recordings were confirmed using intracellular recordings during stimulation with periodic trains of 4, 8, 16, and 32 Hz (3 cells in 3 different slices, data not shown). Overall the means of the intracellular PSPs were well correlated with those recorded using field potentials (R = 0.75). This is in line with previous studies of the direct feedback pathway to ELL, where good agreement between field potential and intracellular recordings was also found (Berman et al. 1997;Oswald et al. 2002).
Accounting for variations in the mean responses
Thus far, the performance of the model has been discussed with respect to data that have been averaged over many individual slices. It is also important to consider the model's ability to account for the responses observed in individual slices. Therefore we fit the model to these data, from both random and periodic stimulation (60 response sets in 21 slices), with the same two free parameters, ΔF and k I. Overall, the average RMS error was 9% and only seven response sets (out of 60) did not meet the criterion for an adequate fit. The resulting values for the two parameters varied over the different response sets (ΔF = 0.11 ± 0.08; k I = 13.4 ± 7.2; mean ± SD), reflecting the variability of the response sets. However, the ability of the model to account for these variations provides further support that the model captures the important features of the short-term synaptic dynamics of the PF synapse.
FDI model: frequency tuning of inhibition
Having a simple description of the PF synapse allows us to assess the contributions of the individual components to the overall synaptic dynamics. Figure 7 A shows the responses of FD and I components separately during periodic trains of different frequencies. At frequencies below 32 Hz, the FD component shows no depression and hence the response of the inhibitory component I increases with frequency. The inhibitory response at 64 Hz, however, is less than that produced at 32 Hz (at least for the later pulses); at this frequency there is evidence of a prominent depression in the FDresponse, and because this is the input to the inhibitory component, inhibition decreases when the FD component is more depressed. These dynamics may play a critical role in signal processing, as we shall see later. Figure 7 B summarizes the tuning of inhibition for both the 3rd pulse and the 20th pulse of periodic trains at different frequencies, for a range of values of inhibitory gain (k I) corresponding to that found in our data (see Accounting for variations in the mean responses). The level of inhibition at the third pulse is relatively small, resulting in a decrease in the PSP of only a few percent for intermediate values of k I. However, by the 20th pulse, the influence of inhibition is substantial and for large values of k I can result in more than a 70% reduction in the control PSP amplitude.
Impact of FDI model dynamics on synaptic inputs
In this section, we consider the effects of 100 independent poisson trains of inputs onto a simple model neuron and evaluate how the dynamics underlying these inputs can affect the neuron's response. In a biophysically realistic model, the effects of synaptic inputs would be a combination of direct effects on membrane voltage and those due to changes in membrane conductance (Hô and Destexhe 2000). But here, as a first step in evaluating the complex effects of the synaptic dynamics due to an FDI model, we chose a simplified approach where the postsynaptic neuron is nonspiking and whose synaptic inputs affect only its membrane voltage.
First, we investigated the response of the model neuron under steady-state input conditions. In these simulations, the mean frequency of the poisson inputs was held constant and the neuron's behavior was characterized over 10 s of simulation time, after transient behavior had decayed (about 1 s). This was done for three different conditions on the dynamics of the inputs: no plasticity, FD dynamics, and FDI dynamics (see methods and Fig. 8legend). It is important to realize that the FD andFDI conditions represent a range of conditions most likely present in ELL, as the gain of inhibition can itself be a dynamic variable, albeit over much longer time scales than those considered here (Bastian 1998a). Figure 8 shows the normalized mean and normalized variance of the voltage trace as a function of mean input frequency for each condition (both measures are normalized to the mean voltage at 1 Hz). For low-input frequencies, the mean voltage increases similarly with frequency in all conditions. In the no plasticity condition, the mean scales linearly with the mean input frequency, as is theoretically predicted by Campbell's theorem (Papoulis 1991). However, beyond a certain frequency, both the FD and FDI (but not the no plasticity) conditions show behavior characteristic of the gain control found in classic models of synaptic depression (e.g.,Abbott et al. 1997). The transition to the gain control regime is different in each case, occurring at about 30–40 Hz for theFD condition and at about 8–10 Hz for the FDIcondition. Overall, the FDI condition results in gain control over a much larger frequency range than the standardFD condition. Thus by simply varying the level of inhibition, the ELL can systematically vary the gain and frequency filtering of its feedback inputs.
The variance of the neuron's voltage also varies with input frequency in a manner dependent on the conditions of the input dynamics. In theno plasticity condition, the variance increases linearly with input frequency, again as predicted by Campbell's theorem (Papoulis 1991). However, in the FD andFDI conditions, the variance increases to a maximum and then decreases at higher input frequencies; it begins at lower frequencies and ends with a lower final value in the FDI conditions. This is a direct consequence of the gain control behavior of theD and I processes, and it may have important implications for the function of this feedback pathway in a closed loop situation (see discussion).
In addition to characterizing the steady-state behavior of this model system, we also tested its responses to two types of transient stimuli:1) step changes and 2) Gaussian changes in mean input frequency. The first stimulus type (step changes) was chosen because synapses that depress are particularly well suited to signal proportional changes in input (e.g.,Abbott et al. 1997; Tsodyks and Markram 1997). To effectively do this, accurate steady-state gain control is required, so this type of stimulus allows us to evaluate the impact of the different input conditions on transient signaling and gain control simultaneously. This type of input may occur in social contexts, during electrocommunication. The second stimulus type (Gaussian changes) was chosen because this is the time-course of input expected from the typical prey of these fish or from self-motion (Bastian 1995; Lewis and Maler 2001; MacIver et al. 2001; Nelson and MacIver 1999). Also, because the input frequency returns to the original baseline after the transient increase, gain control is not critical in the processing of this type of stimulus.
Figure 9 shows responses to the two types of stimuli for the FD and FDI conditions. The step response in the FD condition shows the behavior typical of a depression-dominated synapse: transient increase and return to baseline (Fig. 9 A, middle trace). We begin to see the complexity of the FDI model when its step response is considered (Fig. 9 A, bottom trace). Here, the step is signaled by a brief transient, but because the synapse becomes depressed (i.e., due to the FD component), inhibition is actually relieved, so the net response eventually increases to a value proportional to the step stimulus. The Gaussian response in theFD condition is essentially nil (Fig. 9 B,middle trace); the stimulus is slow enough to be filtered out by the depression process. In the FDI condition, however, the voltage response follows the stimulus very well. Again, this is due to a reduction of inhibition; the FD component becomes transiently smaller due to a relatively greater influence of depression (compared with facilitation), thus decreasing the input to the inhibitory process and allowing a larger net input. It must be emphasized that the behavior of these synapses depends very much on the baseline input frequency (which determines the initial values ofF, D, and I), as well as the gain of inhibition k I, so the previous examples should not necessarily be considered representative.
Now, we present a more general description of the responses to these stimuli as a function of baseline input frequency. To quantify the responses, we calculate the SNR (see Eq. 9 ) between the voltages at two time points (indicated by the arrows in Fig. 9; seemethods for details). The SNR provides a measure of how reliably a signal can be distinguished from a background level. In the case of the step stimulus, we chose our "background" at a time after the step occurred; the SNR calculated in this way takes into account not only the signaling of the transient step but also the ability of the synapse to cancel out constant stimuli (i.e., perform gain control). A more conventional approach for signal detection would be to compare the transient response to the activity before the stimulus. Such an analysis would produce results different from those presented here, because it would emphasize the response transient and not the role of gain control. Figure10, A and B,shows the SNR for both step and Gaussian stimuli under the three different input conditions. The ability of FD synapses to signal step transients at high baseline frequencies is reflected in a large SNR (Fig. 10 A, ○), but the FDI synapse performs relatively poorly in this situation (Fig. 10 A, ●). Conversely, the FDI synapses out-perform theFD synapses when Gaussian stimuli are given against a high baseline frequency (Fig. 10 B). These are the conditions discussed in the context of Fig. 9 (i.e., high baseline frequency). For low baseline frequencies, the FDI synapse is better than theFD synapse at signaling step transients, whereas the opposite is true for Gaussian transients. While the synaptic dynamics considered here always improves the signaling of step changes in input frequency, the no plasticity condition out-performs both theFD and the FDI synapses when Gaussian transients are presented. However, the no plasticity condition would be prone to the effects of saturation of the output neuron, but we have not considered such nonlinearities in the present analysis. In summary, depending on the level of background activity, the level of inhibition (i.e., no inhibition corresponds to the FD condition) can determine what types of signals are best transmitted by these synapses. This potential for differential stimulus filtering at different levels of baseline activity and inhibitory gain is intriguing, but we do not yet understand how it will impact the behavior of ELL pyramidal neurons in a closed-loop situation. Under such conditions, the pyramidal neurons' activity would be governed by sensory input, as well as direct and indirect feedback inputs.
In this paper, we have characterized the short-term dynamics of a PF feedback pathway to a primary electrosensory nucleus (ELL). By repeating different patterns of PF stimulation, under control conditions and when inhibition was pharmacologically blocked, we were able to determine the contribution of inhibition to the overall synaptic dynamics. Thus our description includes the contribution of inhibition, as well as that of classic forms of synaptic plasticity (i.e., facilitation and depression). This is in contrast to many traditional studies of short-term synaptic plasticity in which inhibition is either blocked or analyzed independently of facilitation and depression. We have developed a simple model of the PF synapse (FDI model), that combines previously described features of synaptic facilitation and depression (Dittman et al. 2000), with a novel method of describing feed-forward inhibition. Our analyses show that the combination of these three processes confers diverse and nonintuitive filtering properties to this synapse.
Model of the PF synapse combining facilitation, depression, and inhibition
The indirect feedback pathway of the ELL consists of PFs arising from cerebellar granule cells in the eminentia granularis posterior (EGp) of the cerebellum (Maler 1979; Maler et al. 1981). In ELL, they make monosynaptic excitatory contacts with pyramidal neurons and three types of inhibitory interneurons (Fig.1 A). These interneurons then synapse onto the pyramidal neurons, forming a feed-forward inhibitory component to the PF synapse. The parallel fibers in ELL are ultrastructurally similar in every way to those in mammalian cerebellum (Maler 1979;Maler et al. 1981). Therefore, as a starting point for our model description of the PF synapse, we chose a previous model of short-term presynaptic plasticity in rat cerebellar parallel fibers (Dittman et al. 2000). This model consists of a facilitation process and a depression process, and by choosing different parameters, it was shown to account for a variety of different synapses (Dittman et al. 2000). We chose parameters similar to those found for the PF synapse (seemethods). In doing so, we have assumed that the facilitation and depression occurring in ELL PFs is presynaptic in nature and similar to that observed in rat cerebellum. In addition, our data (when inhibition is blocked) suggest that this is the minimum number of processes that underlie PF synapse short-term plasticity in ELL.
In extending the previous model to include the effects of inhibition, we wished to maintain a similar level of simplicity to make a detailed understanding of the model possible and to allow its practical implementation in network simulations aimed at an understanding of neuronal feedback in closed-loop conditions. We thus made two important assumptions: 1) inhibition scales the amplitude of the PF-evoked PSP in pyramidal neurons (see Eq. 1 ) and2) the direct "input" to the inhibitory process is the same as that received by the postsynaptic pyramidal neuron (i.e., the product of FD, see Fig. 4). The first assumption is not unreasonable because feed-forward inhibition has a gain control mechanism built-in: the larger the excitatory input, the larger the inhibitory input. In addition, previous data from ELL pyramidal neuron responses to single PF stimulus pulses showed the smaller IPSP overlapped in time with the larger EPSP so that when inhibition was blocked, the net excitatory PSP simply increased in amplitude (Berman and Maler 1998a). In other words, the major effect of inhibitory inputs appears to be to control EPSP amplitude. Of course, because the inhibitory process is dynamic, the effect on the EPSP will vary with stimulus history. The second assumption is justifiable only on the basis that it is the simplest situation—we have no data in our system that can separate the PF input to the interneurons and the interneurons input to the pyramidal neurons. However, in the cortex, excitatory and inhibitory synapses among pyramidal cells and interneurons can exhibit differential synaptic plasticity (Galarreta and Hestrin 1998; Reyes et al. 1998). It remains to be seen if this is also the case for the PF synapse in ELL; for the present purpose, we assume that is not.
The manner in which we implement the feed-forward inhibitory process in our FDI model is similar to how an independent depression process would be implemented if we had not pharmacologically isolated the contributions of inhibition. In other words, the overall dynamics of the FDI model could be similar to that of a pureFD model with two depression terms (i.e., F,D 1,D 2). However, we were not able to fit such a model to our data. It is likely that the feed-forward nature of the inhibitory input (i.e., that its influence is controlled by the product FD) would confer different dynamics to theFDI model unless the D 2term depended on both F andD 1, which is typically not the case in such models. One advantage of having inhibition control synaptic dynamics rather than an additional depression term is that it may be easier to regulate. As we show in this paper, simply changing the gain of inhibition can have a significant effect on synaptic filtering. In addition, experimental manipulation of inhibition is easier (i.e., through specific pharmacological blockers) compared with those aimed at presynaptic processes underlying short-term depression—this bodes well for future in vivo experiments aimed at determining the role of feedback inhibition in a closed loop situation.
Gain control in the ELL
In a series of elegant studies (Bastian 1986;Bastian 1998a), the indirect feedback pathway to ELL was shown to be critical for long-term gain control. Long-term synaptic depression (LTD) has been shown to underlie this gain control (Bastian 1998a), and at least in part, this depression is mediated through postsynaptic mechanisms in pyramidal neurons (Bastian 1998b). It is not clear however whether the "depression" is due to increased inhibition, decreased excitation, or both (Bastian 1998a; Roberts 2000).
Our results on the short-term changes at this synapse reveal another form of gain control (Fig. 8). This is due to the steady-state dynamics of the FDI model. A consequence of this is that the variability of this feedback actually goes down with increasing activity in the parallel fibers (Fig. 8 B). An interesting and potentially critical aspect of this gain control is evident when this plasticity is considered in the context of an intact feedback pathway. As previously discussed, gain control is critical in the ELL and is mediated by the indirect feedback pathway. At high levels of sensory input, the feedback pathways are presumably (at least transiently) subject to higher activity levels (Bastian 1993; Bastian and Bratton 1990). Such increased activity would result in more "noise" being injected into the system through the increasingly noisy feedback, potentially resulting in deleterious effects on sensory coding at high levels of sensory input. This would be prevented by the intrinsic gain control mechanisms we describe (due to FDI dynamics), which also results innoise control, i.e., reduction in net synaptic variance at high-input frequencies.
Signal processing in the ELL
The activity in the indirect feedback pathway can be influenced by a number of sensory stimuli. During tail-bending behavior (that occurs over a 200- to 500-ms time period), PF activity is likely to be modulated both by proprioceptive input and by the resulting broad-field changes in the fish's electric field (Bastian 1995). Communication signals, or "chirping" events, may also influence the activity of indirect feedback; these are active high-frequency step-like modulations in electric organ discharge (EOD) (Bastian et al. 2001; Metzner 1999; Zupanc and Maler 1993). In addition, it is possible that local modulations in the electric field, such as those produced by small objects, also influence this feedback pathway (Bastian 1993).
It is not known in detail how these different sensory stimuli are reflected in the firing frequency of the PFs in the indirect feedback pathway. Reversibly blocking the EGp connections to ELL produced complicated effects on pyramidal neurons that cannot be completely explained by the role of this pathway in gain control; the responses of pyramidal neurons to moving objects increased but their baseline firing rates decreased slightly (Bastian 1986). In another study, pharmacologically blocking either glutamatergic or GABAergic input from feedback fibers within the DML did not affect baseline firing, although it strongly affected pyramidal neuron responses to electrosensory stimuli (Bastian 1993). This suggests that the steady-state influence of the indirect feedback pathway is minimal. The nP multipolar neurons that project to EGp granule cells show bursty spontaneous firing rates around 70 Hz, but they can fire as high as 700 Hz during stimuli such as step changes in EOD amplitude (Bastian and Bratton 1990). Additional input to EGp granule cells comes from proprioceptive neurons, which can fire at 50–250 Hz during tail bending (Bastian 1995). Thus it seems reasonable to assume that the parallel fibers have a large range of firing frequencies and may often exhibit burst-like firing at high mean frequencies. Cerebellar granule neurons in turtles can fire at rates higher than 100 Hz and are particularly responsive to bursty inputs (Gabbiani et al. 1994). It will be important to characterize the baseline and evoked firing statistics of EGp granule cells, because this will allow the FDI model to better predict the dynamics of the parallel fiber feedback pathway under in vivo conditions.
To provide insight into the possible functional roles of the feedback dynamics described here, we explored the responses of a simple model neuron to two different types of transient stimuli (Fig. 9): step changes and Gaussian changes in the mean frequency of poisson firing presynaptic inputs. These two types of stimuli can be loosely compared with the stimuli discussed above, namely those produced by chirps, and tail-bending or small objects, respectively. Interestingly, stimuli due to predictable events such as tail-bending are gradually filtered out by active mechanisms that involve the indirect feedback pathway (Bastian 1995; Bell 2001). Inspection of the simple example in Fig. 9 suggests a nonintuitive mechanism for such filtering, specifically that the response to a Gaussian-type transient can be eliminated by the down-regulation of inhibition. This simple example emphasizes the complexity that can result from the combined dynamics of synaptic plasticity and inhibition in an FDI-type synapse.
Another interesting aspect of an FDI-type synapse is that its mean level of activity can result in diverse filtering properties. For low levels of background activity, the FDI synapse is relatively unresponsive to transient changes in input. This can also be the case for high background activity, depending on the level of inhibition. Low levels of inhibition (as for the FDcondition of Fig. 10 A) result in extremely effective signaling of step-like stimuli; high levels of inhibition result in effective signaling of Gaussian-like stimuli (Fig. 10 B). Recently, the dynamics of primary afferent neuron firing has been shown to influence the ability of these neurons to encode dynamic stimuli (Chacron et al. 2001). In this light, it will be interesting to see how such afferent encoding dynamics combine with the dynamics of direct (Oswald et al. 2002) and indirect (the present paper) feedback to influence the encoding properties of ELL pyramidal neurons.
Dynamic role of neuronal feedback
Feedback pathways are prevalent at all levels of the nervous system and they appear to play diverse functional roles. In corticothalamic pathways, feedback can control neuronal firing mode (Sherman 2001), synchronize and control oscillatory discharge (Bal et al. 2000; Blumenfeld and McCormick 2000), contribute to velocity tuning (Hillenbrand and van Hemmen 2001), and provide gain control in orientation tuning networks (Ferster and Miller 2000). In the somatosensory system, feedback has been implicated in transforming a timing code to a rate code (Ahissar et al. 2000). However, how synaptic plasticity affects and contributes to the roles of neuronal feedback is largely unknown. Flexibility of these circuits is undoubtedly crucial, and thus synaptic plasticity over a wide range of time scales must be an essential feature of feedback pathways. An understanding of the detailed mechanisms of feedback control will benefit from a dissection of the different components of the networks involved but will ultimately require the investigation of these networks under closed-loop and dynamic stimulus conditions.
Special thanks to W. Ellis for excellent technical assistance. We thank M. Chacron, B. Doiron, C. Laing, A. Longtin, and A-M Oswald for many discussions, and M. Chacron, B. Doiron, and T. Lewis for comments on the manuscript.
This work was supported by a Canadian Institutes of Health Research (CIHR) postdoctoral fellowship to J. E. Lewis and CIHR operating grants to L. Maler.
Address for reprint requests: J. E. Lewis, Dept. of Cellular and Molecular Medicine, Univ. of Ottawa, 451 Smyth Rd., Ottawa, Ontario K1H 8M5, Canada (E-mail: jlewis{at}uottawa.ca).
- Copyright © 2002 The American Physiological Society


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Well, it really has been a while. I'm still about on Twitter and on Instagram under the same user name but here, not so much for now. My 'Twitter overspill'/blog is being sorely neglected but life, as as it is … Continue reading
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Reuters Staff
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April 11 (Reuters) - Changzhou Qianhong Biopharma Co Ltd :
* Says Zhao Gang resigned as general manager of the compamny
Source text in Chinese: goo.gl/ei1TEK
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I shared a few days ago about my dad's journey through prostate cancer on the way to heaven. For me, walking through this experience left its mark on my life. On the positive side, I became very diligent about getting checkups. I have always believed that dad might still be alive if he had received a simple physical exam every year or so. His generation, though, didn't waste time and money going to a doctor unnecessarily. Sometimes they avoided physicians, even when they needed one.
Another way my life was marked came before dad grew ill. While in my twenties, I started worrying about my health. Fear and anxiety crowded their way into my life. I would become overwrought, carrying these fears for days at a time. Sometimes I would go to a doctor, only to find out that I was fine. On the spiritual side, it was this irrational anxiety that helped me know Jesus in a whole different way when I was about 28 years old. It is a longish story, but the Twitter version is this: I was breaking with worry. I cried out in my misery. Jesus met me there.
Even after Christ spoke supernaturally into my heart -- no, it wasn't an audible voice -- I had seasons of doubts and fears. I would notice some symptom. I would obsess over it with worry; then I would realize I couldn't carry the load. As a result, I handed it to Jesus. He set me free. A few weeks later the cycle would repeat. Over time, those cycles because less severe and far less frequent. Finally they were so rare and so small as to be but a tiny blip on my life.
It was by the grace of God, then, that I received two messages of hope a few months before my surgery. Each message was a promise, a down payment of God's goodness which would see me through this challenge called cancer. The first message came last April in the Dominican Republic. Our church has a partnership there with a wonderful church in Puerto Plata. I have been there many times over the last ten years and count scores of Dominicans and Haitians among my friends. One particular lady named Negra prays for me and my family every day. Each time I go to the DR, I try to say hello to Negra, usually seeing her at a church service. That April Sunday night I saw her and we greeted. I was without an interpreter so she ran to get a friend from the congregation who speaks English. We quickly caught up on essentials about our families, then Negra spoke with wide eyes. "Pastor, God gave me a message for you! He said to tell you, 'Do not fear; He has everything under control!'" This wasn't my first message from Negra. In fact, she usually has something which God has placed upon her heart during her prayers for me. I locked this promise away, not knowing for sure what it might mean, but knowing it did mean something.
Four months later we were having a conference in our church in Arizona. People had joined us from many churches in the region. During one break, I stepped into the rest room. Hank, one of our church leaders, was there. He said, "I wanted to tell you something. God has impressed me to pray for you constantly the past few days. As I have prayed, I have sensed a message He is giving me for you. I don't know what it means, but He wants you to know, "Don't be afraid; He has everything under control!" I knew immediately that God was speaking. By the time I heard this message through Hank, I had just completed the urology appointment in which we determined that I should have a biopsy.
To be continued...


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G Herbo's debut album "Humble Beast" is coming this year.
G Herbo's SXSW interview was mostly about basketball, specifically his chances in a 1-on-1 game against his childhood friend and current tourmate Lil Bibby. He digressed briefly to reveal some exciting information. He has big plans for 2016, visuals, records, and his long-awaited debut album.
"You can definitely expect an album in 2016," he said. "On the low, within a six month radius... maybe." He revealed that the album is entitled Humble Beast. Which is something of an oxymoron, but true to Herbo's character. He's a pretty down-to-earth dude, but he's so nice on the mic that sometimes he can't help himself.
Herbo, 20, ended 2015 on a high note, with the release of Ballin Like I'm Kobe. Previously he released Welcome to Fazoland and Pistol P Project. Stay tuned for more information about the release of Humble Beast.
I Remember What I Use To Be.. What I Use To Do And What I Use To Have.. I'm Humble.. Humble Beast💪🏾— IG:@NOLIMITHERBO (@gherbo) September 30, 2015


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The superbike star heads to the next round of the title race, in Kyalami, South Africa, with his confidence sky high after winning both races in the first round of the world championship in Valencia last weekend.
The former world champion made his intentions clear before the start of the season when he said at the Aprilia team launch in Venice that he would be going for the world championship after his third-place finish behind Honda's Colin Edwards last year.
"This year I'm in it to win - and I think we can do it," he boldly predicted before the first event.
While there is a long way to go (there are 24 races of the season left), Corser showed in Valencia that he is the man to beat.
Corser won five races last year on his Aprilia RSV1000, which has been tweaked - at the Wollongong rider's request - with more mid-range power for this, the bike's third season.
And he made use of the power in Valencia. Corser dominated qualifying and garnered the maximum 50 points. It was a big weekend for Australian superbike riders, with Corser's countryman Troy Bayliss finishing second in both races riding a Ducati.
Corser had started the first race poorly after taking pole, and dropped behind the leading pack. But he showed his maturity and racecraft by quickly reeling in the pacemakers, getting past teammate Regis Laconi - dumped last year as Garry McCoy's team-mate in the Red Bull Yamaha 500cc Grand Prix racing team - after just three laps. He dictated the second race from the front.
Corser has been paying particular attention to his diet and fitness.


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Newmark Grubb Cressy & Everett is a full-service commercial real estate, development and management company that has been serving northern Indiana and western Michigan for more than half a century.
Our team specializes in transaction services and general commercial real estate including sales, leasing, site selection and acquisition for office, industrial, medical, investment and retail properties. Today we represent millions of square feet and almost 2,000 acres of commercial real estate in Indiana and Michigan for our owners and investors. We also provide a full line of property and facility management services. Our current portfolio includes millions of square feet in office, retail, medical and industrial properties, as well as numerous maintenance service accounts for various real estate development associations.


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Jan 13, 2012 - 7:27 am
I got results from second biopsies, chest xray and CT scans. Both biopsies came back squamous, 1 with focal invasion and 1 squamous with displasia. No Adenocarcinoma, thank God! My xray was unremarkable and CT scans were normal. MD plans to present my case to the tumor board next Thursday but he is having his nurse set up an appointment with an Oncologist there. So looks I will have some kind of chemo/radiation protocol and once the plan is determined I can receive at the cancer center in my hometown with Cleveland overseeing. I am feeling very blessed. The hardest part for me has been all the waiting for results.
My employer is more supportive than I could have hoped for and friends and family have "circled the wagons" so to speak. With all of that support I have to say you all have been my rock. Everytime I have posted questions, concerns, YOU all have helped me to hang on and chose the right path. Not sure what I would have done without you. So thanks!
I feel like I can finally take a deep breath.
God bless each of you,
Jan 13, 2012 - 11:36 am
Obviously, you made a very wise decision to go to a facility that has experience in treating anal cancer. I'm glad that everything is falling into place for you and that you won't have a long wait to begin treatment. Please let us know what plan is put into place. That's great that you will be able to get treatment in your own town with the Cleveland Clinic docs overseeing things. How wonderful that your family and friends are surrounding you with love and support to help you through this. We will all be here for you too! I know you'll get through this--just take it one day at a time.
Jan 13, 2012 - 8:16 am
I found the process of all the tests and waiting for results were the most mentally challenging for me. Once I started treatments the mental stress diminished. For me, mentally I treated the daily radiation treatments as my job. This seemed to help my mental frame of mind during treatments.
Hang in there. There will be light at the end of the tunnel as the saying goes.
Jan 13, 2012 - 10:07 am
That lucky number is certainly working for you.
We are here for you.
Jan 13, 2012 - 10:10 am
I am so glad you are getting the answers. The waiting is the hardest part, and once I started tx I knew I would be okay. Sounds like you are in good hands now and I wish you the best. Keep us posted. Lori
Jan 14, 2012 - 1:33 am
Great news. You sound so much better just knowing what the plan is. You are in good hands now. God bless and strengthen you.
Jan 14, 2012 - 8:56 am
Thanks so much for the support! I am geared up and ready to start. My oncologist appt is Monday at 10AM so hopefully gonna get this thing off the ground very soon.
After finding out that I didnt have adeno I have found myself thinking "I never thought I would be relieved, almost happy to have cancer of any sort", but thats how I feel with the diagnosis of squamous. A tremendous weight has been lifted and I feel renewed and for the first time really hopeful. I know the treatment is going to be one of the most difficult things I have ever gone through but I feel up to the challenge.
When it gets rough I going to think of each of you and pull from your strength and resolve.
Phoebe, I think you may be right about the lucky number, I am going to get a T shirt emblazoned with 7-11 hehe.
I know God is with me and guiding my path.
Thanks again all,
Jan 14, 2012 - 10:22 am
I know what you mean about feeling "lucky" that it is squamous cell. When I first heard my colorectal docs words "You have cancer," she followed it with "but I believe it's the 'good kind.'" At the time, I had no idea what that meant, but now I understand. You have EVERY reason to have hope! I wish you all the best with the appt. on Monday and hope that you can get started with treatment ASAP. As my doctor told me, "it won't be fun, but you'll get through it." We are here to make sure you do just that!


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Economics of Food II: Firm Strategic Behavior
- Course Number: FOOD-GE 2008
- Hours: 30
- Units: 3
- Description: The course provides students with an intermediate level understanding of the microeconomics of firm or business behavior, & to apply these tools to current policy issues in the food system. Students explore the effect of firm decision-making on size, scale, & scope, & apply the tools to firms in the food sector. A range of outcomes is explored: free market, firm self regulation, socially responsible firm behavior, shared value firm behavior, & government regulation. The course is designed for policy & food interested students with little as well as no background in economics, or for those who have completed an introductory course that used a text on par with Krugman & Wells.
- Old Course Number: E33.2008


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BugBand Insect Repellent Bead Bags contain a high concentration of Geraniol, which is released slowly to form a protective vapor barrier in a given area. The highly concentrated plastic fragrance beads are packed in an air-flow bag made of nylon mesh, which contains the beads but allows air to pass freely. Available in Single Bags or 12 Count Bottles.Features & Benefits:
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Evergreen Mountain Lookout Trail #1056
A classic hike up to sweeping views at this restored fire lookout.
Total Distance:
2.6 miles
Total Ascent:
Highest Point:
Our Hiking Time:
2h 30m
Required Permit:
To get there, take Highway 2 out just beyond Skykomish to milepost 50. Take a left onto FR 65, also known as the Beckler River Road. After 7 miles the pavement ends at an intersection. Veer left and continue on FR 65 for .7 miles to FR 6550. At this point, you can continue on FR 65 to Jacks Pass to the other end of FR 6550, or cut out a few miles and jump on FR 6550 now. If youre looking to save time, veer right onto FR 6550 and continue for 4.3 miles to FR 6554. Hook right and take FR 6554 another 8 miles to the trailhead at roads end.
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The Ever
Green Mountain
Trail #1056 begins from the forest road, climbing quickly through meadows and past the charred and bleached reminders of the 1967 burn. As you climb, keep an eye out for the huckleberry and mountain blueberry that are plentiful along the route. The narrow trail wastes little time ascending the ridge toward mature stands of hemlock and fir. Plunge into the forest and after two-thirds of a mile enter the Wild Sky Wilderness and the trail begins to level out. Continue through the trees to large alpine meadows filled with wildflowers in season. From here you can see your destination perched in the distance. Push up the last few switchbacks and soon find yourself on Evergreen Lookouts front porch.
The 360-degree views are vast. To the north, Glacier Peak rises above the surrounding mountains. Pick out Columbia, Kyes and Sloan Peaks to the left of Glacier. Continue turning west to first pick out Del Campo Peak and Big Four Mountain, followed by Gunn and Merchant Peak, then Baring Mountain. As you turn south find Mt. Rainier dominating the skyline, rising over nearby
Beckler Peak
and Alpine Baldy. As you turn east find Mount Daniel and Mount Fernow, followed by Mount Stewart and finally the rolling mountains of the Henry M. Jackson Wilderness including nearby Scrabble Mountain and Grizzly Peak. Settle in and see how many more you can pick out.
Despite the roughly 20 miles of forest roads that must be navigated to reach the trailhead, the spectacular views draw plenty of hikers every year. While is a great hike if youre looking for big rewards on a short trail, its a lot of driving for just over 2.5 miles of trail. The trail is probably a little too steep and rugged for the youngest of hikers, but everyone else should be able to tackle this one without too much of a problem. If youre looking for more trail time, we recommend combining this hike with another nearby trail, such as
Beckler Peak
Scorpion Mountain
Green Mountain
is named for the large meadows that cover the flanks of the mountain. Back in 1935, the US Forest Service built a fire lookout cabin on summit as part of its fire-fighting program. During the summer months, a lookout would watch for signs of smoke and radio the ranger station if they saw a fire. During World War II, the cabin was taken over by the Aircraft Warning Service, a band of civilian volunteers organized by the US Army to keep an eye out for enemy aircraft. From 1941 to 1944 members of the Aircraft Warning Service staffed the cabin year-round, ready to scramble fighters to respond to attacking aircraft. In 1944, the US gambled and shifted all of its home defense aircraft to the offensives in Europe and the Pacific. With no one to call if the enemy was spotted, the AWS returned Evergreen Lookout to the US Forest Service.
The lookout continued to be used for fire detection through the 1980s, surviving a large burn that crept up the sides of Ever
Green Mountain
in 1967. Remnants of that fire can still be seen along the trail today. When flooding washed out a forest road and added seven miles to the trail, the cabin fell into disrepair. Luckily, in the 1990s it was adopted by the Seattle Explorer Search and Rescue Group, a group of Explorer Scouts that focus on search and rescue training and wilderness survival skills. The restoration was done with the support of the Mountaineers, the Quest School and 141st Army Reserve Aviation Battalion. Today, you can rent the cabin through the Forest Service and take your turn at watching over the wilderness.
Nearby hikes
Scorpion Mountain
Beckler Peak
Blanca Lake
Similar Difficulty
Mt. Catherine
Skyline Lake
Glacier Vista
Similar Features
Noble Knob
Pinnacle Peak
Jolly Mountain
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Responsibilities: Clinical work plus teaching. The SCI position involves inpatient and outpatient.
You will see about 9 -10 inpatients (with a resident) and consults on acute floors 2 – 3 days a week (average 5 – 6 consults: again residents see them first.).
Benefits: Attractive benefits package to include 4 weeks vacation, 10% pension plan, family health coverage, disability, educational allowance of $5,000.00 to 7,000.00 per year. Health, Dental, Life, Disability and Malpractice insurance covered.
Call: Approximately once in 4 weeks and second on call. They very rarely have any problems that the resident on call can not handle.
Compensation: Base salary plus an incentive bonus program. Base compensation is based on the Clinical FTE, academic rank, extramural grant support, and clinical productivity. There is a very aggressive incentive program in which all faculty participate based solely on clinical productivity (net collections), in addition, an annual academic bonus is available at the end of the fiscal year at the discretion of the Chair.
Qualifications: Board Certified/Qualified physiatrists with excellent interpersonal and communications skills; will consider visaholders; Fellowship preferred for the positions
Program Features: The University Of Kansas Department Of Rehabilitation Medicine has sustained tremendous growth under the direction of the new chair, Dr. Raj Mitra. Under his leadership, the Department mission has expanded from primarily general physical medicine to development of clinical, research, and training programs for the entire spectrum of Academic Physiatry. The mission of the Department is to restore function and decrease pain in patients afflicted with the entire spectrum of musculoskeletal and neurologic disorders, and integration of this mission with world class educational programs and cutting-edge research.
The department has recruited new faculty specializing in Cancer Rehabilitation, Women's Health, Spine and Pain Management, and Neuroscience Rehabilitation. The Department has created two new non ACGME accredited fellowships for Interventional Spine; this fellowship is in its second year. Additionally, a program in Traumatic Brain Injury has also been created with multidisciplinary teaching faculty (from Rehabilitation Medicine, Neurology, and Neurosurgery). There are plans to create additional fellowships in Spinal Cord Injury and Sports Medicine as soon as these positions are filled.
The University of Kansas Hospital has a new 29 bed state of the art acute rehabilitation unit which will house and serve our patients with general rehab, SCI, TBI, amputation and neuro-rehabilitation needs. An additional hospital has been purchased (the Indian Creek Campus) to complement our 33,000 square foot spine center. The director of the spine center is a Pain Fellowship trained Physiatrist within the Department. Additionally, there are plans for the Department to oversee an additional 90 sub-acute rehabilitation beds – which will allow development of subspecialty inpatient services in cancer rehabilitation, cardiopulmonary rehabilitation, and orthopedic rehabilitation. Finally, the department is recruiting both clinical and basic science researchers to focus on disability research, clinical trials and outcomes with a focus on functional restoration in patients afflicted with the entire spectrum of acute and chronic disease. The goal is for the basic science researchers to work closely with clinicians.
Features: The University of Kansas is located in Kansas City, a large metropolitan area that offers an array of arts & entertainment, sports, shopping, affordable housing and top notch school districts. This city preserves the values and the heritage of America's Heartland while dynamically creating a 21st Century urban center. Enjoy over 2 million neighbors in the immediate service area. AAA advertises that the city "boasts more tree-lined boulevards dotted with European statues than Paris and has a horizon with more skyscrapers taller than 30 stories than any midwestern city west of Chicago." Enjoy professional sports at its best, and have access to some of the best dining in the world. One of the school systems in the metro area has been ranked among the nation's top 10 systems for the past 22 years! Many major corporations have their headquarters here as well.


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We help you search for a Enniskillen singing tutor. Singing tuition are an excellent way to start a fun new hobby, acquire a new skill and attain confidence with singing. Please use our service to search for Enniskillen singing tutors and choose which best suits your requirements so you can begin your singing tuition in Enniskillen immediately!
This is the fastest way to find Enniskillen singing teachers in the UK, helping you find Enniskillen singing tuition in your area and Enniskillen tutors to help with any instrument, for example, piano, violin or guitar. We can help you find Enniskillen singing lessons or a one-to-one Enniskillen singing teacher to prepare for singing grades and improve your singing skills! Our search will order Enniskillen singing teachers near you according to their hourly prices and proximity to you.
If you are a singing tutor wishing to offer singing tuition services in Enniskillen or throughout the UK, please register with First Tutors: Music or learn about us here. Becoming a Enniskillen singing teacher is a great way to re-affirm your own skills by giving singing tuition while helping others, all in your local Enniskillen area!


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- Please select a date to see the proper prices!
- Meal can be requested on the spot
Best offer
58 € / person / night, no meal
Description of the accommodation:
Rooms, services Hotel Sälzerhof Salzkotten is offering 12 tastefully furnished rooms to those seeking accommodation in Salzkotten. You are also welcome at the hotel for a fine local meal in the restaurant. If necessary, parking is available nearby. In case you'd bring your laptop along, you may go online via wireless Internet connection (WiFi) available at the hotel. If you wish to learn more about the exact scope of services provided by Hotel Sälzerhof Salzkotten (including any available for an extra fee), you will find them on the information sheet below.
Payment Depeding on the selected room, date and price, you may be asked to provide credit card guarantee or to pay by credit card in advance.
Arrival, opening hours The earliest arrival time is 14:00, the latest time to leave the rooms is 11:00. The personnel can communicate with you in the following languages: English and German.
Hotel Sälzerhof Salzkotten rooms Rooms
- Please select a date to see the proper prices!
Accommodation services
Free WiFi in shared places
Own restaurant
Hairdryer, Desk in the room


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FedEx Office on 1354 W Valley Pkwy, Escondido California
FedEx Office is your local printing company in Escondido, California offering a wide range of printing services, including business card printing, digital color printing, and self-service copying. Come try our professional printers for yourself. Even ship with FedEx®.
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FedEx Office Print & Ship Center
1354 W Valley Pkwy
Escondido, CA 92029 US
Printing with FedEx OfficeStart Online Order
Hours of OperationMonday 7:00 AM–10:00 PM Tuesday 7:00 AM–10:00 PM Wednesday 7:00 AM–10:00 PM Thursday Closed Friday 7:00 AM–10:00 PM Saturday 8:00 AM–8:00 PM Sunday 10:00 AM–8:00 PM
Latest Express DropoffMonday No Pickup Tuesday 4:45 PM Wednesday 4:45 PM Thursday No Pickup Friday 4:45 PM Saturday 4:00 PM Sunday No Pickup
Latest FedEx Ground® DropoffMonday 6:00 PM Tuesday 6:00 PM Wednesday 16:00 Thursday No Pickup Friday 6:00 PM Saturday No Pickup Sunday No Pickup
Reviews for this FedEx Office Print & Ship Center11/7/2017Corie the attendant wo served me really did a great job packaging and giving me a fair price on my shipping needs. She was kind and was not… Read more10/31/2017Staff doesn't recognize returning or repeating business. They are very task oriented in getting the job done. Read more10/22/2017I phoned and received excellent service from Todd at the W. Valley Pkwy, Escondido location. He answered all of my questions. He was very… Read more9/18/2017Andrew F. went out of his way to be helpful. It was late so there were few people in the store. Not being busy, he printed my material while… Read more8/22/2017corie dis great job. Read more8/12/2017Before stopping at FedEx I went to Staples the employee at the print and copy area said , and with an attitude mind you, " I've got other… Read more7/26/2017He did an outstanding job helping customize and get invitations how I wanted. Educated me a little bit on quality of paper and print. Thank… Read more7/7/2017Corie greeted me with a welcoming smile and thanked me for using Fedex. Read more7/7/2017Corie was once again fabulous and always greets me by my first name with her wonderful smile!!! She is always very helpful and answers any… Read more6/29/2017It took me less than a minute to dropped off my box... The staff is very friendly and always happy Everytime I go there particularly Corie… Read more6/28/2017Corie. Very friendly. Read more6/23/2017I had the pleasure of working with Laura yesterday. Unfortunately for me, I was working on last minute posters since my computer had crashed… Read more6/23/2017Todd and Andrew were super this morning! I worked all night on my Uncle's funeral programs, especially since the day prior my computer has… Read more6/22/2017I have attended this particular store for years because the service is excellent. The people who work there are helpful, considerate, and… Read more6/20/2017The team members at the Escondido location are always so pleasant & easy to work with! Asia is always happy & even remembers me when I've… Read more6/7/2017Charlie Thorsten was very knowledgeable and exceptional in his customer service AND finished print job in record time. He also let us know… Read more6/2/2017Rebecca, the young lady who took care of me, was extremely friendly and helpful and explained all the options to ship my documents. I saved… Read more6/1/2017Codie, was very helpful and eger to help and get the order right the first time!. Read more6/1/2017Corie went the extra mile to assist me in all my printing and lamenting projects for my daughter's birthday party. She saved my day and… Read more5/31/2017Great team... amazing customer service. Read more
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Make money the easy way when you let an eBay Valet sell your stuff. Bring your electronics, apparel, sporting goods and more to an eBay Drop-Off Center at FedEx Office, and a valet will list, sell and securely pack and ship them for you.
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Upload your documents online and pick them up at FedEx Office on 1354 W Valley Pkwy or print to any of our 1800 locations. We offer self-service color copying, high-volume digital printing, presentations and postcards to name a few.
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Rent a computer with internet access or get online with free AT&T Wi-Fi access at FedEx Office in Escondido. Check email, browse the web, print copies or scan photos. All in one place.
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When New York State Becomes a Stockholder
Published: July 28, 1991
(Page 2 of 2)
When Regeneron became a publicly traded company in April, it raised $99 million on its first trading day, the second largest amount ever raised by a biotechnology company in its initial public stock offering. (The largest amount, $115 million, was raised by the Cetus Corporation in 1981.) This pleased but did not surprise Dr. Schleifer, who speaks of his company as taking a new approach to developing drugs that could alleviate the symptoms, if not cure the diseases, that affect the nervous systems of 6.5 million Americans. Maintaining Nerve Cells
"The pharmaceutical industry has tended to focus on small molecules, which work to a limited extent, but which do not act to promote the survival of a nerve cell," he said. "Traditional drugs are designed to replace the natural molecules, called neurotransmitters, which nerve cells use to communicate between themselves. Regeneron's product candidates are nerve growth proteins, which act to maintain the vitality of the nerve cells themselves."
In the case of Parkinson's disease, for example, neurons in the brain carrying a substance called dopamine degenerate and die, resulting in a lack of coordination, trembling and rigidity. Current drugs mimic or enhance dopamine, reducing the symptoms of the disease, but over time the brain responds less and less to the increased dopamine and the patient's condition worsens.
These therapies do not treat the underlying causes of Parkinson's, which are not known. But in animal cells in the test tube, Regeneron has shown that a growth factor for nerve cells -- which they call BDNF, for brain-derived neurotrophic factor -- can promote the survival of the dopamine-carrying neurons that degenerate in Parkinson's.
Articles in two leading scientific journals recently described discoveries made independently by two groups of researchers, at Regeneron and at the University of Southern California. Both used BDNF, which was first isolated in 1989 by two scientists at the Max Planck Institute in Munich, Dr. Hans Thoenen and Dr. Yves Barde.
When the Regeneron researchers added BDNF to brain cells in a test tube, they discovered that it stimulated the cells affected in Parkinson's disease. BDNF was also found to protect those cells from being killed by MPTP, a toxic drug that causes symptoms of Parkinson's disease in laboratory animals. Brain Cells May Be Dormant
Parkinson's experts are especially interested in the new findings because of evidence that many cells in the brains of Parkinson's patients are dormant or dying, not dead.
Dr. Jesse Cedarbaum, a neurologist who is program director of the clinical affairs group at Regeneron, said the company's advisory team included three Nobel Prize winners: Michael S. Brown and Joseph L. Goldstein, for their work in cholesterol metabolism, and Arthur Kornberg, for work involving genetic codes.
The discovery stage is followed by "producing for research," which Dr. Cedarbaum said was being done in existing quarters but would be transferred to the new plant. Research-level production is followed by laboratory experiments and then the clinical trial stage.
This last step requires a go-ahead from the Federal Drug Administration and has three phases: administering the drugs to a small number of patients to learn how safe the drug is and how it is tolerated; expanding the patient group to 200 to determine dosages; and, finally, using thousands of patients.
"After that, you can request approval to market the drug," Dr. Cedarbaum said. The first of the test phases can take six months to one year; the other two can last one to two years each.
"In light of AIDS," he said, "the F.D.A. has promulgated fast-track regulations to compress the process from five years to two or three years for diseases where there is no treatment and which are fatal or severely debilitating.
"That's something we're hoping to do for the sake of patients suffering from diseases like Alzheimer's disease and Lou Gehrig's disease, for which no effective treatment currently exists."
Photo: Dr. Jesse Cedarbaum, left, a neurologist and program director at Regeneron Pharmaceuticals, with Dr. Sam Davis, a staff scientist, in the company's Tarrytown laboratory. (Susan Harris for The New York Times)


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Coleman 2 Pack Guyline Illuminator1379626 76501936346
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Never trip over a guyline again with these Coleman Guyline Illuminators.
Key Features
- These Coleman 2 Pack Guyline Illuminators have dual hooks and attach on to most tents and shelters.
- The Coleman Guylnie Illuminators have 2 LEDs on either end powered by 1 AAA battery (include), encased by clear outer tubes with a 24 hour run time.
- These illuminators are water resistant and have glow in the dark ends.
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|Product Type
|Tent Accessories
|Weight (kg)
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|Product Depth (cm)
If you feel your product has failed a Consumer Guarantee (as defined by Australian Consumer Law) then don't worry you can easily return it to your local Harvey Norman store. We'll even pay for the postage if you live in an area where there is no store. Our returns policy covers any purchased item (conditions apply).
Either complete the details below or chat to a staff member online.
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|Construction Year :
|Property Size :
|170 sq.m.
|Land Size :
|1000 sq.m.
|Bedrooms / Bathrooms :
|3 / 3
Also available in: Ελληνικα, Русский, Italiano
This pearl of a villa is set in stunning surroundings of emerald seas and sapphire skies with rugged mountains that were used in the background for the filming of The 'Guns of Navarone'.
From the crystal clear, infinity pool, set on luscious green lawns, a fairytale pathway leads down to a private cove with a cozy and private sandy beach, ideal for swimming, snorkelling.
The property features its own private dock for boats.
Enjoy outdoor living and the views to their fullest by using the barbecue and dining alfresco on the patio.
The ground floor has an open plan living and dining area with extra storage space, and a bedroom with bathroom. The kitchen is fitted and modern with a living area that captivates it's occupants by providing those same infinite, heavenly views. Upstairs are two more bedrooms each with a bathroom and spectacular balcony views.
The property is accessed by a subsidiary road and a gate, ensuring security and privacy.
A pristine property sold furnished and ready to fulfil your dreams and desires of owning a spectacular seafront villa.
You may view our latest video of Navarone Bay here
St Nicolas (Navarone) / Information about the property's locationThe area of St Nicolas is just 1km south of Lindos on the way to Pefkos. There is a striking contrast between the arid landscape and the turquoise water's of St Nicholas Bay. The monastery of St Nicholas dates back to the 16th century and can be easily recognised by its white walls amidst the…


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No More Babies Trailer (2015)
14 June 2015 79 mins
They came to have their babies. They went home sterilized. No Mas Bebés is the story of Mexican immigrant mothers who were pushed into sterilizations while giving birth at Los Angeles county hospital during the 1960s and 70s. Alongside an intrepid, 26-year-old Chicana lawyer and whistle-blowing young doctor, the mothers mounted a civil rights lawsuit that is seminal to the alternative history of Roe v. Wade, and the movement for reproductive justice.
Watch the official No More Babies 2015 trailer in HD below or find more No More Babies videos on Vidimovie.


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... I've kept my phone off today. A conscious decision after sorting through the cerebellum last night. Instead of the usual -- wake up, eat, check Facebook, start working on Nomadness-- I pulled myself away from my patterns, in an essence to (ironically) explore them in a different way. I wrote in my journal for nearly an hour, flushing thoughts and decided to do one of the only things that actively keeps me away from work...indulge in films.
Last night's dream completely f*cked my head up and totally has me one track minded to get back to Japan at some point in 2013. I have to. It's no longer an option. No longer an oasis. To continue feeding the Japanese frenzy, I popped in 'Lost In Translation'. A film that the first time I watched, I didn't get. The silence made me uncomfortable, and at that point in life I wasn't a traveler.
Then I moved to Japan. Within the first few months of living there 'Lost In Translation' became less a film, and more a mantra of my life for the year. It's so on point with its depictions of being foreigners in Tokyo. Today, while in bed viewing the film, I related on another level. The level of allowing people into your life, for however short the time period, and knowing that at some point, you also have to let them go. In my memoir, there is a chapter I wrote called 'Attachment, Detachment'. It's a theory in Buddhism, as well as a recurring theme in the life of this nomad.
...and now. Waking Life. My three favorite films are Dead Poet's Society, Eternal Sunshine of the Spotless Mind..... and Waking Life. Garner from that whatever you will. In a simple sentence the film is based on the exploration of the line in the opening scene 'Dreams are destiny.' Waking Life, is how I live my life, and sometimes I need the reminder...an adamant, aggressive, all encompassing reminder. Peep the clips below from one of the most genius films on the face of the Earth.
For the traveler in me...the curious child inside that will never die... I stick onto the quote that bridges both films for me today.
Waking Life
Boat Car Guy: I feel like my transport should be an extension
of my personality. And this is like my little window to the
world... and every minutes a different show. I may not
understand it. I may not even necessarily agree with it.
But Ill tell you what Ive accepted: just sort of glide along.
You want to keep things on an even key, this is what Im saying.
You want to go with the flow. The sea refuses no river.
The idea is to remain in a state of constant departure while
always arriving. It saves on introductions and goodbyes.
The ride does not require explanation - just
occupance. Thats where you guys come in. Its like you
come onto this planet with a crayon box. Now you may get
the 8 pack, you may get the 16 pack but its all in what you do
with the crayons - the colors - that youre given. Dont worry
about coloring within the lines or coloring outside the lines
- I say color outside the lines, you know what I mean?
Color all over the page; dont box me in! Were in motion to
the ocean. We are not land locked, Ill tell you that.
http://youtu.be/s0TvZRcwz4I - Embedding not allowed, follow clip link to view


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Chocolate-Colored Sensei
By Donald Ash | Foreigners In Japan , Teach English In Japan Hub , Teach in Japan Article Hub , Teaching English In Japan
Unless I have something extremely pressing to do, I always help the students clean after lunch. As my students and I were cleaning on this one particular day, I was in the hallway sweeping and I overheard some of my 2nd graders randomly calling out colors in English. My ears quickly zeroed in on this […]Click Here To Keep Reading >>