A recent drug interaction study reported that when azithromycin was administered with the combination of ivermectin and albendazole, there were modest increases in ivermectin pharmacokinetic parameters. Data from this study were reanalyzed to further explore this observation. A compartmental model was developed and 1,000 interaction studies were simulated to explore extreme high ivermectin values that might occur.A two-compartment pharmacokinetic model with first-order elimination and absorption was developed. The chosen final model had 7 fixed-effect parameters and 8 random-effect parameters. Because some of the modeling parameters and their variances were not distributed normally, a second mixture model was developed to further explore these data. The mixture model had two additional fixed parameters and identified two populations, A (55% of subjects), where there was no change in bioavailability, and B (45% of subjects), where ivermectin bioavailability was increased 37%. Simulations of the data using both models were similar, and showed that the highest ivermectin concentrations fell in the range of 115–201 ng/mL.This is the first pharmacokinetic model of ivermectin. It demonstrates the utility of two modeling approaches to explore drug interactions, especially where there may be population heterogeneity. The mechanism for the interaction was identified (an increase in bioavailability in one subpopulation). Simulations show that the maximum ivermectin exposures that might be observed during co-administration with azithromycin are below those previously shown to be safe and well tolerated. These analyses support further study of co-administration of azithromycin with the widely used agents ivermectin and albendazole, under field conditions in disease control programs. This paper describes the use of a modeling and simulation approach to explore a reported pharmacokinetic interaction between two drugs (ivermectin and azithromycin), which along with albendazole, are being developed for combination use in neglected tropical diseases. This approach is complementary to more traditional pharmacokinetic and safety studies that need to be conducted to support combined use of different health interventions. A mathematical model of ivermectin pharmacokinetics was created and used to simulate multiple trials, and the probability of certain outcomes (very high peak blood ivermectin levels when given in combination) was determined. All simulated peak blood levels were within ranges known to be safe and well tolerated. Additional field studies are needed to confirm these findings. The operational efficiency of disease elimination programs in developing countries could be improved by integrating delivery of several interventions at local (village and district) levels A recent pharmacokinetic study evaluated co-administration of azithromycin, ivermectin and albendazole The purpose of this analysis was to model the ivermectin pharmacokinetic data from the recently reported interaction study Data from a historical Phase I study with intensive sampling in healthy subjects was used to develop a population pharmacokinetic model for ivermectin Blood samples were collected predose and at 0.5, 1, 1.5, 2, 3, 4, 6, 8, 10, 12, 24, 36, 48, 72, 96, 120, 144, and 168 hours after drug administration during each of the study phases. Samples were collected into heparinized Vacutainers. Blood samples were centrifuged at 3000 rpm for 15 minutes and the plasma samples were collected in plain plastic tubes without anticoagulant and then stored at −80°C. Samples were shipped frozen overnight on dry ice to BAS Analytics  for sample analyses. Ivermectin is detected in the body as two metabolites  and 22,23-dihydroavermectin-B1b (H2B1b), and these were assayed using a validated high performance liquid chromatography system with liquid chromatography/mass spectrographic detection. The assays were linear over the ranges of 2.5–1000.0 ng/mL and 2.5–20.0 ng/mL, respectively. The precision values for both assays were <10%. In terms of accuracy, while the bias was not exceeded (±15%) for H2B1b for either the high or low quality control (QC) samples, they were for H2B1a during long-term stability testing (−21.8% at the low QC and −17.3% for the high QC) see . Plasma Eighteen healthy Caucasian volunteers were enrolled in and completed this study .http://www.GNU.org/). Key pharmacokinetic parameters from the modeling are described in All the data from both arms of the cross-over study were fitted simultaneously. The data set contained pooled pharmacokinetic, demographic/covariate, and dosing information. Data were analyzed using nonlinear mixed-effects modeling with the NONMEM software system, Version V, Level 1.1  with the PREDPP model library and NMTRAN subroutines. Computer resources included personal computers with Intel Pentium 4 processors, Windows XP Professional operating system, the GNU Fortran Compiler, GCC-2.95  squared ).The first-order conditional estimation method with η-ε interaction (FOCEI) was employed for all model runs. Individual estimates of pharmacokinetic parameters were obtained using POSTHOC . The random effect models sufficiently described the error distributions. For this analysis all interindividual errors were described by exponential error models on selected parameters (Equation 1).ijC is the jth measured observation (plasma concentration) in individual i, jth model predicted value (plasma concentration) in individual piji, ε and aijε are proportional and additive residual random errors, respectively, for individual i and measurement j and are assumed to be independently and identically normally distributed, following a normal distribution with mean 0 and variance sigma (σ) squared ). For each treatment arm, separate residual errors were explored. The pharmacokinetic models were evaluated for goodness of fit and were then subjected to predictive check model evaluation. For more detailed technical information on these methods, please see NONMEM user's guide The data could not support a full covariance block for the OMEGA matrix. Modeling began with the assumption of no covariance between interindividual random effects . Later, the covariance between clearance (CL) and volume of distribution in the central compartment (Vc) was estimated. For pharmacokinetic observations in this analysis, the residual error model was described by a combined additive and proportional error model (Equation 2).TVP) was described as a function of individual body weight (iWT), normalized by a reference weight (refWT), which was 70 kg. TVPθ is an estimated parameter describing the typical pharmacokinetic parameter value for an individual with weight equal to the reference weight and alloθ is an allometric power parameter .After the structural pharmacokinetic model was established, known physiologic relationships were incorporated into the covariate-parameter models. For example, the change in physiologic parameters as a function of body size was both theoretically and empirically described by an allometric model (Equation 3) Assessment of model adequacy and decisions about increasing model complexity were driven by the data and guided by goodness-of-fit criteria, including: (i) visual inspection of diagnostic scatter plots  successful convergence of the minimization routine with at least 2 significant digits in parameter estimates; (iii) plausibility of parameter estimates; (iv) precision of parameter estimates; (v) correlation between model parameter estimation errors <0.95, and (vi) the Akaike Information Criterion (AIC), given the minimum objective function (OBJ) value and number of estimated parameters Final model parameter estimates were reported with a measure of estimation uncertainty including the asymptotic standard errors (obtained from the NONMEM $COVARIANCE step). A limited covariate modeling approach emphasizing parameter estimation given the available data, rather than stepwise hypothesis testing, was implemented for this population pharmacokinetic analysis. The study population contained equal numbers of males and females. As such, age, weight and gender were explored as potential covariates. First, pre-defined covariate-parameter relationships were identified based on exploratory graphics, mechanistic plausibility of prior knowledge, and then a full model was constructed, with a fixed allometric relationship of body weight on clearance and volume parameters. Interindividual variability could not be incorporated on all fixed-effects parameters to get successful FOCE runs. For residual variance, a separate residual error was assigned for each of the treatment arms. A combined additive and proportional error model was used with 4 parameters to be estimated for the residual error. Various population models were evaluated, but only two models that best described the data  are presented. The first modeling approach was a population model that included all subjects. Because some of the modeling parameters and their variances were clearly not normally distributed, and showed asymmetric distribution, a mixture model was developed.A second modeling approach was a population mixture model as it met our criteria for model adequacy and provided supporting evidence of the dichotomy of the observed individual data. Each subpopulation would have an associated submodel with different fixed or random effects. This model was adopted to accommodate the fact that only some of the individuals exhibited a pronounced increase in ivermectin bioavailability during the interaction arm of the study. It was preferred over a population model with and without outlier individuals, as it gave a better fit to the data as measured by change in OBJ, and met our criteria for a successful run in terms of a complete successful convergence with reasonable estimate for precision for both fixed and random effects.Model development was guided by various goodness-of-fit criteria, including diagnostic scatter plots. Checking of the individual fits was also employed as part of judging the model performance for each patient. The final model and parameter estimates were then investigated with the predictive check method. This method was similar to the previously described posterior predictive check, but assumes that parameter uncertainty is negligible, relative to interindividual and residual variance One thousand Monte Carlo simulation replicates of the original data set were generated using the final non-mixture and mixture population pharmacokinetic models. Distributions of Cmax across all data simulations were compared with Cmax distribution in the observed data set. The simulated data from each of the 1000 virtual trials (18000 subjects for each treatment period) were assembled, and the similarity between the actual observed data and simulated data was examined by comparing the 95% predictions intervals of the simulated data with the original observed data.2 (0.03).Assessment of the relationship between azithromycin and ivermectin by noncompartmental analysis showed that mean ivermectin AUC and Cmax was increased by 31% and 27%, respectively see , and a vIvermectin concentration-time data were best described by a two-compartment pharmacokinetic model with first-order elimination and absorption . Covariaηs is assumed to be normal . With each model developed, we checked the distribution of ηs, and their mean values. The η distribution indicated a clear violation of the normality assumption. It was necessary to modify the original model to improve η distribution diagnostics. A mixture modeling approach was considered as the distribution of some of the pharmacokinetic parameters and inter-individual variabilities indicated a lack of homogeneity. The final mixture model had 9 fixed-effect parameters and 8 random-effect parameters as shown in The final non-mixture model had 7 fixed-effect parameters and 8 random-effect parameters as shown in Both the population and individual predictions adequately described the AUC profiles for each subject , as dispSimulated maximum concentrations for each individual's Cmax values were summarized across 1000 simulation replicates of the original population pharmacokinetic database and plotted as box plots . The uppThere are a number of interesting findings from this analysis of data from an interaction study of ivermectin and azithromycin. This is the first published population model of ivermectin pharmacokinetics. It demonstrates the utility of population mixture modeling as an approach to explore drug interactions, especially where there may be population heterogeneity. The mechanism for the interaction was identified (an increase in bioavailability in one subpopulation). The model was used to simulate multiple clinical trials, to identify the maximum exposures that might be observed during co-administration, which permits comparison with previously published safety and pharmacokinetic data.50 0.18–0.4 µM; Ivermectin has been approved for use in humans for 2 decades, yet relatively limited pharmacokinetic data have been published. Recent studies using modern assay methods have characterized its pharmacokinetics using noncompartmental methods in the context of drug combination studies for treatment of onchocerciasis and lymphatic filariasis The variability of the magnitude of change in ivermectin pharmacokinetics observed in the interaction phase The final mixture model provided a good description of ivermectin data from both treatment periods. Goodness-of-fit criteria revealed that the final model was consistent with the observed data and that no systematic bias remained. The data points  are scat2; p<0.05, 2df). In the present analysis, the difference was 19.8.Typically, a mixture modeling approach would not be considered at the outset of a population pharmacokinetic analysis. Because of the unexplained remaining variability (see above), in the present analysis, the following decision rules were used in the evaluation of the mixture model: (i) The Estimation step and Covariance step terminated successfully; (ii) 95% CI for Mixture partition did not include 0 nor 1; and (iii) the change in the OBJ between mixture and non-mixture models was >5.99 (χThe mixture model identified the interaction between azithromycin and ivermectin to be due to changes in bioavailability in Subpopulation B. Their mean estimate of bioavailability (F) was 1.37 relative to baseline, whereas F was unchanged for Subpopulation A (0.97). Inspection of noncompartmental data for Subpopulation B were consistent, showing higher Cmax and earlier Tmax values . There were no differences in apparent clearance or volume of distribution. However the mechanism for the increase in bioavailability is unclear. Azithromycin, like ivermectin, is a substrate for Pgp, however it has minimal inhibitory effects on this transporter in vitro peak exposures that are predicted to occur if ivermectin and azithromycin were co-administered would never exceed mean values seen under high dose conditions The model was used to simulate the range of peak ivermectin concentrations that might be encountered if azithromycin and ivermectin were co-administered. These simulated data were then compared with the Cmax data reported in the high-dose ivermectin safety study Interestingly, simulations from both the mixture model and the non-mixture model had generally similar predictions of ivermectin exposures (average estimates and variability). Both models confirmed that the maximum concentration achieved in the interaction phase would not exceed 201 ng/mL . In spitpost hoc to population differences. Indeed, although the mixture model identified two populations on the basis of different effects on bioavailability, it is unclear mechanistically what this difference might be due to. Finally, modeling and simulation can advise but cannot supplant clinical data. The findings from this study should be confirmed in further clinical or pharmacokinetic studies.There are several important caveats to this analysis. The data collected from the drug interaction study was not intended for population analysis, and a larger data set would have been desirable. The use of a mixture model could be criticized on the basis that random variations in the data could be ascribed In conclusion, this analysis demonstrates the utility of a population model approach to analyze drug interaction data. The mechanism for the interaction was identified (an increase in bioavailability in one subpopulation). The model was also used to simulate multiple clinical trials, to identify the maximum exposures that might be observed during co-administration, and provides confidence that the peak ivermectin exposures would never exceed mean exposures that have previously been shown to be safe and well tolerated.


The third-generation aromatase inhibitors (AIS) are largely replacing tamoxifen in the adjuvant treatment of early-stage breast cancer in postmenopausal women with hormone receptor–positive tumours. To date, multiple trials have been conducted comparing tamoxifen treatment with an AI, and all have demonstrated improved disease-free survival with AI treatment. Trials have included direct 5-year comparisons between tamoxifen and an AI, switching to an AI within 5 years after initial tamoxifen treatment, or extending treatment with an AI after 5 years of completed tamoxifen treatment. Some of these trials have been completed; others are ongoing; and head-to-head trial comparisons of individual AIS are also in progress. The present article summarizes the data obtained from various clinical trials of hormonal therapy for early breast cancer. It also reviews recent data so as to shed light on the current status of these therapies. The focus is on the efficacy of treatment with an AI. Toxicity is discussed in the second article in this supplement. The efficacy of tamoxifen as adjuvant therapy for women with estrogen receptor (ER)–positive early breast cancer has been clearly demonstrated. Adjuvant tamoxifen treatment has been associated with a 31% reduction in the annual breast cancer mortality rate among hormone receptor–positive women with early breast cancer Clinically meaningful endpoints are distinct measurements or analyses that reflect how a patient feels, functions, or survives Although OS is the most objective measure of efficacy, its evaluation requires prolonged follow-up, and consequently, the use of surrogate endpoints has become acceptable. In addition, OS measurements are affected by the development of effective salvage treatments for patients with metastatic disease, and they therefore may not be a pure efficacy endpoint in the evaluation of adjuvant therapy. The most widely used surrogate endpoints in oncology are DFS or event-free survival, the latter being the time from the beginning of treatment until a patient experiences a recurrence, a new primary cancer, or death. For some cancers, DFS is now recognized as an acceptable endpoint for evaluating therapies in situ (DCIS and LCIS) within CLBC and others not Early trials of tamoxifen for the adjuvant treatment of breast cancer used OS and DFS as primary efficacy endpoints. However, these early trials were comparing tamoxifen with placebo, rather than with an active drug. The more recent AI trials have used DFS as the primary endpoint, with TTDR and RFS as surrogate endpoints of clinical benefit . AlthougThe use of DFS as a surrogate endpoint for OS is most appropriate in settings in which recurrence of the disease is responsible for a major component of mortality in the treated population, which is the case for most solid tumours p = 0.3); however, DFS was 83% and 77% respectively (p < 0.00001) in the two cohorts With respect to early breast cancer, OS alone was often used as the primary endpoint in early trials of adjuvant therapy. However, in interim analyses of some studies, it became evident that OS benefit would not be apparent and that other measures such as DFS also had to be considered. For example, in the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 randomized trial involving 2644 ER-positive node-negative women, no significant advantage in OS was found after 4 years of follow-up  Women with breast cancer may have tumours with receptors for hormones such as estrogen or progesterone. Circulating estrogen binds to its cognate receptor in women with ER-positive breast tumours, which induces cell proliferation The risk of breast cancer recurrence is highest within the first 5 years of primary chemotherapy et al.Several trials with AIS for adjuvant endocrine treatment in postmenopausal women with early-stage breast cancer are either underway or have been completed. In addition to trials for upfront AI treatment, there have also been trials to evaluate switching from tamoxifen to an AI, or extending treatment with an AI after tamoxifen for 5 years  of a number of AI trials showed that, with AIS, breast cancer recurrences are significantly less frequent than they are with tamoxifen n = 3125), 20 mg tamoxifen alone (n = 3116), or a combination of the two (n = 3125). After the first analysis at 33 months, the combination arm was dropped when no benefit was demonstrated as compared with tamoxifen alone p = 0.005], an improvement in TTR , and a reduced occurrence of CLBC  as compared with women on tamoxifen The ATAC trial enrolled 9366 women from 21 countries, including 635 from Canada, all of whom were postmenopausal with early-stage breast cancer p = 0.0001). That finding suggests a carryover effect for anastrozole, whereby women continue to benefit from treatment with anastrozole after stopping treatment. Although fracture rates overall were higher in women on anastrozole during the treatment period, the incidence was the same for both groups after treatment had been completed Follow-up of the ATAC trial beyond 5 years of treatment and data obtained at 100 months showed significant improvement in DFS, TTR, TTDR, and CLBC in women on anastrozole, although no difference in OS was noted p = 0.003), defined as the time from randomization to the first local, regional, or distant recurrence; a new invasive cancer in the contralateral breast; a second, non-breast cancer; or death without a preceding cancer event p = 0.007), and the 5-year DFS estimates for letrozole and tamoxifen were 84% and 81% respectively. A CLBC occurred in 0.6% of women on letrozole as compared with 1.1% of women on tamoxifen, and a 1.2% absolute decrease in distant recurrence was observed among women on letrozole. Fewer gynecologic and thromboembolic events, but more bone fractures, arthralgia, and low-grade hypercholesterolemia were experienced by women on letrozole as compared with those on tamoxifen The BIG 1–98/IBCSG 18–98 study enrolled 8010 hormone receptor–positive postmenopausal women worldwide, including 20 from Canada p = 0.08); however, whether this trend is real or confounded by the crossover of patients from tamoxifen to letrozole is difficult to assess Updated results at a median follow-up of 76 months (reported at the 2008 San Antonio Breast Cancer Symposium) continued to support improved survival for patients treated with letrozole The Tamoxifen Exemestane Adjuvant Multinational (TEAM) study was initiated in 2001 in 9 countries to examine the efficacy of exemestane versus tamoxifen in 9775 hormone-sensitive women with early breast cancer www.clinicaltrials.gov/ct/show/NCT00066573 for details) and has completed accrual. Results of these trials should yield useful information about the individual effects and relative efficacy of the AIS.Two key head-to-head trials of AIS as adjuvant treatment for women with early breast cancer are underway. The Femara versus Anastrozole Clinical Evaluation (FACE) is a phase III, open-label, randomized, multicentre trial designed to test whether anastrozole or letrozole has superior efficacy as adjuvant treatment for 5 years in postmenopausal women with hormone receptor–positive, node-positive disease p = 0.01). Gastrointestinal complaints, musculoskeletal disorders, fractures, disorders of lipid metabolism, and hyperglycemia were more common in women on anastrozole. Women on tamoxifen developed more venous disorders and gynecologic changes . Notably, however, the trial was unable to fulfil the sample size calculations because of competing trials, and the results are therefore based on the patients who were able to be recruited to the trial.The Italian Tamoxifen Arimidex (ITA) trial has been evaluating a switch to anastrozole after 2–3 years of tamoxifen p ≥ 0.001), representing a 40% reduction in the risk of an event in women switched to anastrozole after being on tamoxifen for 2 years. Although more fractures and bone pain were recorded in the anastrozole group, fewer thromboses occurred Two additional trials, the Arimidex–Nolvadex (ARNO 95) study and the Austrian Breast and Colorectal Cancer Study Group (ABCSG) trial 8, which together involve 3224 women with ER-positive early-stage breast cancer, are also examining the effect of continuation on tamoxifen after 2 years, as compared with a switch to anastrozole for a further 3 years p < 0.0001), event-free survival (p < 0.0001), distant recurrence-free survival (p = 0.002), and OS (p = 0.04) A meta-analysis of the three aforementioned trials confirmed that, among patients who switched to anastrozole as compared with those who remained on tamoxifen, fewer disease recurrences and deaths were observed, resulting in significant improvements in DFS , sequential trial strategies analyze events from the start of treatment. Sequential and switch trials investigate the same intervention, but they are conducted in different patient groups and are therefore expected to provide different results. The ABCSG 8 trial was recently completed, and the sequencing strategy continued to show improved benefit as compared with tamoxifen alone for 5 years The IES is a double-blind randomized trial that compares a switch to exemestane in postmenopausal women with early breast cancer who have been on tamoxifen for 2–3 years with continuation of tamoxifen alone for a total of 5 years The most recent analysis for the BIG 1–98/IBCSG 18–98 trial, in addition to reporting the monotherapy analysis with either letrozole or tamoxifen alone, also included an analysis on sequencing to letrozole for 3 years following 2 years on tamoxifen and vice versa The EBCTG recently carried out a meta-analysis of the ABCSG 8, ARNO 95, IES/BIG 2–97, and ITA trials and showed that AIS are associated with significantly fewer breast cancer recurrences, even in the switch setting, and furthermore, a statistically significant improvement in mortality rates p = 0.4) were observed in the group on extended treatment, but the risk of endometrial cancer was also observed to be doubled. Of interest, an earlier study found no benefit for extended treatment with tamoxifen in women with node-negative cancer p = 0.07) in those who continued to receive it.Several trials have examined the efficacy of adjuvant treatment extended beyond the standard 5-year duration. These have included extended treatment on tamoxifen or an AI beyond 5 years, or sequential treatment with an AI in women who were disease-free after 5 years on tamoxifen. The Adjuvant Tamoxifen, Longer Against Shorter (ATLAS) randomized trial is comparing 10 years with 5 years of tamoxifen in 11,500 women (59% ER-positive). A lower recurrence rate has been observed among women continuing on tamoxifen at a mean of 4.2 years following randomization p < 0.001) The double-blind MA.17 trial from the NCI C Clinical Trials Group is looking at the effect of either letrozole or placebo in women who have already undergone standard 5-year treatment with tamoxifen n = 856) were randomly assigned to receive either 3 years of anastrozole or no further treatment. At a median follow-up of 62.3 months, women who received anastrozole (n = 387) had a statistically significantly reduced risk of recurrence  as compared with women who received no further treatment (p = 0.031) The ABCSG trial 6a is similar to MA.17: It is examining the efficacy of 3 years of anastrozole treatment in women who have completed 5 years of tamoxifen treatment, with or without the first-generation AI aminoglutethimide for the first 2 years of therapy The NSABP B-33 trial was designed to examine whether exemestane treatment (versus placebo) prolongs DFS following 5 years of tamoxifen treatment The addition of 5 years of tamoxifen in premenopausal women with hormone receptor–positive disease is associated with a 40% reduction in recurrence p = 0.01) at a median follow-up of 48 months, and fewer patients on that combination experienced bone metastases Treatment with AI alone has not been recommended in premenopausal women with functioning ovaries following chemotherapy. In these women, though AIs may reduce estrogen production in peripheral tissue to some extent, ovarian estrogen production is maintained or increased, which may lead to unfavourable effects on breast cancer risk of recurrence The IBCSG is currently conducting three trials in European and North American premenopausal women Several trials are being conducted to determine the optimal duration of AI treatment for postmenopausal women with early breast cancer. The MA.17R trial was initiated in 2004  to compare DFS in subjects who receive 5 years of letrozole or placebo after having received approximately 5 years (4.5–6 years) of aromatase inhibitor therapy , including those who have received 5 years of adjuvant letrozole as part of the MA.17 trial. In the ABCSG-16 Secondary Adjuvant Long-Term Study in the Arimidex trial, women who have been free of recurrence after approximately 5 years of endocrine therapy will receive either 2 years or 5 years of extended adjuvant therapy with anastrozole With ongoing studies looking into the benefits of an additional 5 years of treatment with an AI, some physicians question whether patients will be willing to take these medications for this length of time. To address that concern, a survey was recently conducted among patients with early breast cancer and the physicians who treat them. Physicians were asked to indicate the minimum incremental benefit that they believed would justify 5 additional years of AI therapy. Most indicated that they would prescribe an AI for a further 5 years only if it produced an additional 1%–2% benefit in OS. When patients with early breast cancer on an AI therapy were asked the same question, one third responded that they would continue AI therapy for a further 5 years even if it offered a less-than-1% incremental benefit in OS. These results suggest that physicians may be more risk-averse than are their patients; the results are also encouraging in that they show that most patients tolerate their AI medication well enough to consider a further 5 years of therapy for a very small potential benefit de novo) resistance refers to a lack of response at initial exposure to the drug; acquired resistance develops during therapy in patients who are initially responsive. Host factors, treatment type, and the biology of the tumour can all have a role to play in the development of resistance.Because adjuvant endocrine therapy is generally a long-term treatment, the development of resistance and other issues affecting drug efficacy must be considered because these events will have an effect on the benefits of treatment. Drug resistance may be intrinsic or acquired. Intrinsic  are at increased risk of recurrence, while those with high-activity variants have a more favourable outcome neu oncogene encodes a transmembrane tyrosine kinase receptor with extensive homology to the epidermal growth factor receptor and that overexpression of this gene may be associated with tamoxifen resistance Tamoxifen is converted to anti-estrogenic metabolites that are thought to be more potent than tamoxifen itself. One of the active metabolites, endoxifen, is produced through the action of the cytochrome P450 enzyme CYP2D6, and women who have particular allelic variants of the genes encoding this enzyme are poor metabolizers of tamoxifen neu status and AI efficacy, neoadjuvant letrozole has been found to be equally effective in HER2/neu–positive and HER2/neu–negative tumours neu-positive tumours, showed that the prognosis of those patients was less favourable with both letrozole and tamoxifen therapy Because the AIs inhibit the action of aromatase, the degree of expression of this enzyme—and differences in the affinity of drug binding—could have a bearing on drug efficacy The estrogen receptor is a member of the nuclear receptor family of ligand-activated transcription factors. Upon entering a cell, estrogen binds to the receptor, which then undergoes conformational changes and binds to elements upstream of estrogen-dependent genes and alters their transcription either by up- or downregulation Acquired resistance to the AIs has been demonstrated in tissue-culture cell lines in which cells acquire an adaptive hypersensitivity to estrogen through upregulation of estrogen receptors and increased crosstalk between various growth factor receptor signalling pathways Women on tamoxifen experiencing excessive menopausal symptoms such as hot flashes may be prescribed a serotonin reuptake inhibitor (SRI), and these agents have been shown to inhibit CYP2D6 activity. Venlafaxine has been found to be a weak inhibitor of CYP2D6; paroxetine is a potent inhibitor Data so far have unequivocally shown that, as compared with tamoxifen, the AIs offer superior benefit in DFS, and adjuvant AI treatment is accepted as the standard of care in early breast cancer. However, issues for the physician include which AI to use and when to start it. Further, questions such as duration of treatment and the optimal treatment strategy remain to be answered. The data so far point to AI treatment up front, because the risk of recurrence is highest within the first 2–3 years after surgery


Layer-by-layer growth of surface films took place either by step advancement or by a surface nucleation and step advancement mechanisms. Friction vs. applied load data acquired on the films and the calcite substrate were successfully fitted to the Johnson Kendall Roberts (JKR) model for single asperity contacts. Following this model, friction differences between film and substrate at low loads were dictated by differences in adhesion, whereas at higher load they reflect differences in contact shear strength. In most experiments at fixed load, the film showed higher friction than the calcite surface, but the friction-load dependence for the different surfaces revealed that at low loads (0–40 nN), a calcian otavite film has lower friction than calcite; a result that is contrary to earlier LFM reports of the same system. Multilayer films of calcian-otavite displayed increasing friction with film thickness, consistent with the expectation that the film surface composition will become increasingly Cd-rich with increasing thickness. Both load- and thickness-dependence trends support the hypothesis that the contact shear strength correlates with the hydration enthalpy of the surface ions, thereby imparting friction sensitivity in the LFM to mineral-water interface composition.Lateral Force Microscopy (LFM) studies were carried out on cleaved calcite sections in contact with solutions supersaturated with respect to otavite (CdCO The study of ion sorption onto mineral surfaces has received considerable attention in the last several decades. Sorption is, in the broad sense, the change of mass of a chemical in the solid phase as a result of mass-transfer between fluid and solid, which includes, 1) true adsorption , 2) absorption or diffusion into the solid, and 3) surface precipitation to form an adherent phase that may consist of chemical species derived from both the aqueous solution and dissolution of the solid  since th2+(aq), since this ion is known to substitute for Ca2+ in the calcite structure  refers to the activity of ion A in the aqueous solution, KBA refers to the solubility product of the BA end-member and XBA is the mole fraction and γ the activity coefficients. The maximum of the supersaturation function provides a good approximation of the precipitating solid-solution composition; nevertheless it does not take into account the kinetics of the nucleation process. More accurate predictions of the composition of the precipitating solid-solution requires this latter consideration  as has been shown by several authors [where x is the solid composition, [ authors ,61,62. TFf, in an atomic force microscope can be calculated by [The magnitude of the friction force, lated by :(7)VL is the difference in the lateral force signal detected (V), SL is the lateral detector sensitivity (rad/V), KL is the torsional spring constant (nN m/rad), and h is the tip length of the cantilever (≈ 15 μm).where μm/V), it was possible to determine the relative laser spot shift (in μm) for a given voltage difference, VL, measured from friction loops [e.g., [θ) of the cantilever for a given voltage. This calculation yielded a detector sensitivity of 1.26 × 10-4 rad/V.The sensitivity of the detector as a function of the angle of twisting of the cantilever was calculated by accounting for the specific geometry of the laser optical system and detector. Using the four-quadrant photodiode detector sensitivity along its horizontal axis  is related to the normal spring constant by the following expression [The torsional spring constant (pression :(8)KN is the normal spring constant (N/m), L is the length of the cantilever  and υ is the Poisson ratio (0.28 for Si). The normal spring constant for each cantilever utilized was determined experimentally using a calibrated cantilever as a reference and the method described by [KN of every cantilever, it was also possible to calculate its torsional spring constant and calibrate the friction forces in the LFM measurements using Eqn. 7 and 8.where ribed by . TherefoMeasured friction can be influenced by different variables and experimental factors, such as the tip sliding velocity -68, the The shape of the tip-sample contact has a significant influence on the friction force measured as evidenced by the continuum mechanics models discussed previously. Unfortunately tip shape can vary significantly between different tips, leading to different contact areas and/or contact geometries under otherwise invariant conditions. Also, the tip shape will be altered by the wear resulting from scanning over the sample. Several authors have dealt with these issues in the past ,54,70-72For the reasons stated above the direct comparison between calculated friction values even for experiments performed in separate sessions, yet at similar conditions, could be highly misleading and thus has been avoided in the discussion. Unfortunately, some of the experiments performed in this study showed that, even within an experiment, absolute friction values could vary up to 60%. Nevertheless, in this case the variation affected the friction values of the different layers in the same manner, making comparisons within experiments still possible. For those experiments where friction vs. load data was taken, a rapid change in the tip shape could have important implications on the data interpretation. In these cases, however, no significant variation (>20%) of the tip shape was observed before and after the experiment.® code was written to batch process and analyze the lateral force data obtained from the AFM experiments. Friction values were computed by dividing by two the difference in lateral deflection measured by a left-to-right scan and a right-to-left scan. Commonly, the scans do not overlap due to scanner hysteresis (i.e. features observed in forward and backward scans do not correspond to the same pixel position in the fast-scan axis), so the code includes a "matching" subroutine  that automatically overlaps both scans before calculating the friction. Several other features were included in the code for "region of interest" (ROI) statistical analysis in the images to obtain friction values and other statistical parameters or for automated analysis of "friction loops" [A custom Matlabn loops" ,74.2+(aq), Cd2+(aq) and CO32-(aq) in different proportions, including Ca-free solutions. Table To assess the friction of otavite-calcite solid solutions forming on calcite, a series of experiments were performed in which the inlet solution contained CaAs evidenced by the theoretical continuum mechanics models previously discussed, the friction characteristics of a tip-film contact can be dominated by different parameters at different load regimes Fig. . To asseot = 2.75). Five minutes after the solution was introduced into the cell, the steps on the calcite surface CO3 were grown on calcite. They referred to this as the "template effect" because the original surface topography was reproduced after a single layer had grown. Higgins and Hu [Fig. s and Hu  also repAs more of the original calcite was covered by the calcian otavite, single layer nuclei continued to form preferentially on Ot-1 instead of the calcite surface and additional nucleation took place over previously created islands, resulting in the formation of "stacks" of calcian otavite islands up to 4 or 5 layers. None of these "stacks" showed any higher friction than the double layer of calcian otavite (Ot-2). Repeated experiments (Cd.9 and Cd.12) showed a similar nucleation and growth behavior wherein an initial episode of step advancement was followed by nucleation and growth over previously formed surfaces.Multilayer growth produced only by step advancement (i.e. no island nucleation) was observed in experiment Cd.7. In this case, a similar situation as that observed for experiment Cd.6 took place, where the advancement speed of the growing layer decreased by more than one order of magnitude after crossing the underlying calcite-calcian otavite boundary. Nevertheless, the growth of additional layers continued uninterrupted and was not affected by the original position of the calcite steps, meaning that calcite substrate control is limited only to the first layer grown over the original crystal.Fig. ot = 3.35), showed a somewhat different friction behavior. In this case no friction difference between the single and double layers of calcian otavite was observed. Also, the advancement speed of the steps growing over the single, initial layer of calcian otavite was not reduced, thus no "template effect" was observed. The step advancement speed measured on the calcite substrate was 0.27 ± 0.03 nm/s in the Cd.2 experiment, significantly higher than that measured in the Cd.6 experiment (0.14 ± 0.01 nm/s) performed at SIot = 2.75. As in the previous experiments, nucleation started only after most of the original calcite surface was already covered by a single layer of calcian otavite, and proceeded at a higher rate than on the experiments performed at lower supersaturations. Nuclei expanded at the same speed as the single calcian otavite layer.Experiments performed at slightly higher supersaturation, such as experiment Cd.2  showed higher friction than the original calcite surface. Once the steps reached the underlying contact area between the calcite and the new phase  was calculated beforehand by means of equation 3, which relates it to the pull-off force. The pull-off force was obtained by extrapolating the experimental data at low loads (< 25 nN) to zero friction using a JKR type function. Using this approach, an energy of adhesion of 1.7 ± 0.2 mJ/m2 was obtained. Utilizing this value, the full range of experimental data was fitted to a JKR type-curve by adjusting the shear strength, resulting in a value of 0.48 ± 0.05 GPa.As has been pointed out before, Hay et al.  associatυ = 0.3  for Si aFor the calcian otavite contact it was assumed, as a first approximation, that the bulk mechanical properties of otavite applied to a single monolayer of material. Zhang and Reeder  reportedKv is the bulk modulus and υ the Poisson ratio. No value for the Poisson ratio of otavite was found in the literature, but other carbonates' values are in the range 0.35 – 0.3, which was used to calculate a range of otavite Young's moduli (88–117 GPa). Both values are higher than that reported for calcite (76 GPa) and are in accordance with the reported higher hardness for otavite [E for the monolayer compared to calcite will be expected in this case.where  otavite . Still t otavite , where t otavite  found a E and following the same approach as in the calcite data, a JKR-type fit was done on the experimental data collected from the Ot-1 film. The calculated adhesion energy is 0.18 ± 0.02 mJ/m2, which is an order of magnitude smaller than that found for the calcite contact. Two values of shear strength derived from the fit were 0.57 ± 0.05 and 0.65 ± 0.06 GPa, corresponding to the use of E = 88 and 117 GPa, respectively. Although E and τ strongly co-vary in Eqn. 4, the reasonable assumption that a calcian otavite film should have a larger Young's modulus than calcite would lead to lower film friction at high loads unless this film forms a contact with larger shear strength  and calcite (10-8.48). In this context the interaction between Cd2+ and CO32- is expected to be stronger than that of Ca2+ and CO32-. Therefore a higher concentration of adsorbed CO32- is to be expected over the otavite surface. On the other hand the contribution to friction by tip induced dehydration will lead to higher friction for a material with higher hydration energies. In our case the experimental hydration enthalpies of Ca2+ and Cd2+, which are -1659 kJ/mol and -1850 kJ/mol, respectively support the observations at high load where otavite displays a higher friction than calcite. Although the different contributions on friction due to dehydration or interaction with surface species is very difficult to discern, the concentration of water molecules in solution is significantly higher than that of CO32-(aq) (55 M vs. 10-4 M respectively). Hence surface dehydration would be expected to contribute more to the total friction on the basis of bulk concentrations.Relatively few fundamental studies have been reported on the factors governing the contact shear strength of single asperity contacts . ResultsPZC of the tip and substrate. Churchill et al. [2-calcite contact increased as the solution pH decreased from 9.5, which is the pHPZC for calcite. The pH in experiment Cd.1 was 8.4 so a higher adhesion force would be expected in the calcite contact than in that for calcian otavite (assuming similar surface site density) since pHPZC = 9 for otavite [Results from the data fitting show that friction at low loads is controlled by the adhesion energy so the contacts with lower adhesion energy  display lower friction. Adhesion has been found to be controlled  by electrostatic interactions between the tip and surface ,83. Thesl et al.  found th otavite .i, and Vi refers to its advancement speed. In principle two different scenarios can be envisioned to explain the friction variations between a single and double layer of SS: 1) There is no variation in the composition of the different layers  and friction changes between one layer and a double layer reflect only a difference in the mechanical properties due to strain in the overgrowths. 2) There is a variation in the chemistry of the growing layers, which will lead to differing chemical and mechanical properties (the latter possibly strain-related) and thus to a variation in friction.Fig. 3 was more difficult to dissolve than a single layer, but assumed that this was just due to a relaxation of the epitaxial strain which "stabilized" it and not to a change in composition. Studies have shown, in fact, that strain is relaxed in epitaxially grown layers as film thickness increases [Previous AFM studies on the growth of solid solutions have usually assumed that the composition of the precipitating layers does not change with depth -26,29. Hncreases . Neverth3 solid solutions [2+/Cd2+. However, in each experiment it was reported that the composition of the CO3 SS growing over calcite evolved towards the Cd end-member as the film grew thicker. In the case of pure otavite growth [The second possible explanation for the variation of the friction between a single and a double layer of SS could be that there is a variation in the chemical composition between them. Chiarello et al. monitored the growth of COolutions  and pureolutions  over calolutions  they usee growth  they foue growth  does demxSi1-x solid solutions grown epitaxially over Si(111) in the transition thickness for a Stranski-Krastanov growth mode [xSi1-x film the higher the relaxation in the strain. Even in the experiments reported herein where Ca-free solutions were introduced, a small amount of Ca2+ would be present due to the dissolution of calcite in the area where the undersaturated  jet of solution meets the surface. These Ca2+ ions will be carried away, radially, by the flow into the scan area. The presence of Ca2+ near the surface could lead to Ca2+ incorporation into the film thereby reducing film strain. In light of the above discussion, a pure strain-induced friction contrast mechanism is not supported but the film chemistry has a significant influence on the observed friction.A mechanism to explain the variation in the chemical composition will necessarily require a degree of control exerted by the substrate on the composition of the precipitating layer. Several authors have investigated systems where this control occurs. For example, Marek et al.  found thwth mode . They foThe nucleation behavior observed in the experiments performed with Ca-free solutions can be described by the Stranski-Krastanov epitaxial growth mode . This moIn contrast to the high supersaturation experiments, for those performed at low supersaturation it was shown that the measured step advancement speed of the second layer of SS decreased considerably as compared to that measured on a single SS layer. The reduction of step velocity for a second layer of SS has been observed in the growth of different metal carbonate solid solutions over calcite -26,28. A2+ in the surrounding fluid. A higher degree of supersaturation will also drive the system to a higher incorporation of Cd2+ in the precipitating layer. Under these conditions, the composition of the initial single layer will probably be equal to that of subsequent layers producing little or no contrast in friction between film layers and no template effect.Regarding the experiments performed with Cd-rich solutions, supersaturation seems to play an important role not only in the growth process , but alsThe significant geochemical implications of the above observations stem from the need to better predict how minor and trace element composition in minerals is related to the fluid composition from which mineralization took place. While equilibrium thermodynamic principles allow prediction of limiting compositions in systems that rapidly approach equilibrium, reactions of solid solutions with aqueous fluids may not easily achieve an equilibrium state. In the latter case, bulk thermodynamics cannot be used to predict surface or near-surface composition of minerals and therefore, kinetic factors must be incorporated into geochemical models. Identifying and quantifying the rate-controlling mechanisms requires further investigations in which surface and fluid composition are correlated, preferably with spatial resolution sufficient to resolve heterogeneities that may exist at the nanometer scale. These studies, while performed on only one relatively simple mineral-water interface system, demonstrate that LFM may contribute important chemical information with high spatial resolution through its sensitivity to surface ion hydration enthalpy and surface charge, and lead to important developments in geochemical modeling of the mineral-water interface.2+. Differences in adhesion at low loads are probably governed by electrostatic interaction between tip and sample and therefore related to the differences in the pHPZC of the film and calcite substrate.Results presented in this paper corroborate those from previous lateral force studies in that LFM can provide additional useful information to recognize compositional contrast in mineralization studies. This work demonstrated that previous descriptions of friction differences between substrates and films as directed solely by differences in strain may not be universal. Specifically, the observations of friction contrast reversal, arising from differences in the load dependence of friction for calcian-otavite films and calcite, demonstrated a need for additional chemical and mechanical considerations beyond a simple friction-strain relationship. This load dependence was further explored by fitting successfully the experimental data using the JKR continuum mechanics theory for single asperity contacts. These studies showed that higher friction for the calcite-tip contact at low loads was due to significant differences in adhesion between the tip and the film and calcite substrate. At higher loads, the higher friction of the calcian otavite-tip contact indicated larger shear strength associated with this contact. The contact shear strength could correlate with dehydration enthalpy that must be overcome by the scanning tip. Hence, the higher friction of the calcian otavite contact will be related to the higher hydration enthalpy of CdThe observed friction contrast between a single and a double layer of solid solution suggested a difference in composition between layers. Compositional evolution during multilayer film growth reduces strain in the overgrowth by decreasing misfit with the underlayer. The change in layer composition with film depth requires a degree of control by the substrate on the composition of the overgrowths, a process that is not fully understood at this point. As shown in experiments at higher supersaturation where friction was similar on all film layers, the control of the substrate on film composition may be overcome by the higher driving force for film formation. Additional studies using surface sensitive chemical analytical techniques will be required to fully understand this phenomenon, but nanometer-scale friction measurements clearly provide important surface characteristics toward further development of knowledge in the growth of more chemically complex minerals. To facilitate the role of LFM in mineral surface chemistry investigations, future efforts should emphasize inclusion of experimental variables such as tip size and shape to permit multiple experiment comparisons.The authors declare that they have no competing interests.PC performed the AFM and LFM measurements, contributed to the design of experiments, fitting of data and drafted the manuscript. SH contributed to the original concepts for investigation, contributed to the experimental design and manuscript drafts and provided suggestions for the data fitting. Both authors read and approved the final manuscript.


Pseudoephedrine is a drug commonly prescribed as a nasal decongestant and bronchodilator and is also freely available in cold remedies and medications. The structural and pharmacological similarity of pseudoephedrine to amphetamine has led to evaluation of its psychomotor stimulant properties within the central nervous system. Previous investigations have shown that the acute responses to pseudoephedrine were similar to those of amphetamine and other psychostimulants.3H]dopamine uptake in synaptosomal preparations.This study examined the effect of chronic administration of pseudoephedrine in rat nucleus accumbens and striatum and identified three further similarities to amphetamine. (i) Chronic exposure to pseudoephedrine reduced the c-Fos response to acute pseudoephedrine treatment suggesting that pseudoephedrine induced tolerance in the animals. (ii) In animals chronically treated with amphetamine or pseudoephedrine the acute c-Fos response to pseudoephedrine and amphetamine was reduced respectively as compared to naïve animals indicating cross-tolerance for the two drugs. (iii)The known involvement of the dopamine system in the response to amphetamine and pseudoephedrine was further confirmed in this study by demonstrating that pseudoephedrine similarly to amphetamine, but with lower potency, inhibited [This work has demonstrated further similarities of the effect of pseudoephedrine to those of amphetamine in brain areas known to be associated with drug addiction. The most significant result presented here is the cross tolerance effect of amphetamine and psudoephedrine. This suggests that both drugs induce similar mechanisms of action in the brain. Further studies are required to establish whether despite its considerable lower potency, pseudoephedrine could pose health and addiction risks in humans similar to that of known psychostimulants. Pseudoephedrine is a drug commonly prescribed as a nasal decongestant and bronchodilator and is also available in over the counter cold remedy medications. The chemical structure of pseudoephedrine is similar to that of the psychostimulant amphetamine and both are classified as sympathomimetic drugs . NumerouWithin the central nervous system, the nucleus accumbens and the striatum have been identified as important target areas of psychostimulants and opiates whereby repetitive activation of these areas through dopaminergic action is believed to play a major role in the establishment of drug dependence and withdrawal phenomena -5.The expression of immediate-early genes in response to acute administration of potentially addictive drugs is of particular interest with respect to the mechanisms that may trigger dependence. Amphetamine can induce the expression of c-Fos and jun-B and zif:268. This ability to acutely induce immediate-early gene expression in the nucleus accumbens and striatum is now considered to be a general property of psychostimulant drugs . The indWork in our laboratory employing a drug substitution test indicated that pseudoephedrine elicited, in rats, similar internal cues to amphetamine . AdditioAll animal procedures were carried out in compliance with Mahidol University Code of Practice and the National Institutes of Health (USA) Guidelines for treatment of laboratory animals. Male Sprague-Dawley rats (between 200 and 250 g) were obtained from the National Animal Center, Mahidol University, Thailand, housed in groups of 6 and maintained on a 12 h light/dark cycle with free access to water and food. All animals were handled for at least 1 week before the experiment. In acute treatment, rats were injected intraperitoneally (i.p.) with pseudoephedrine  or d-amphetamine  and were killed 1.5 h after the drug injection. In chronic treatment, rats were injected twice a day (8.30 a.m. and 6.30 p.m.) for 8 days with pseudoephedrine  at increasing doses of 25, 30, 35, 40 mg/kg, i.p. on day 1, 2, 3 and 4–8 respectively. To study cross tolerance with amphetamine, rats were chronically injected twice a day (8.30 a.m. and 6.30 p.m.) for 8 days with d-amphetamine at increasing doses of 1, 2, 2.5, 3 mg/kg, i.p. on day 1, 2, 3 and 4–8 respectively. Rats were sacrificed on day 9, 1.5 h after the last injection of either d-pseudoephedrine , d-amphetamine  or saline. The final injection on day 9 was carried out at 8:30 a.m. as during the chronic treatment.Under the stereodissecting microscope, the rat brains were cut coronally at the optic chiasma and 2 mm more frontally. From this section striatum and nucleus accumbens were manually dissected. The striatum was identified as the striated area below the corpus callosum while the nucleus accumbens as the area surrounding the anterior commisure which is easily identifiable as a small white area. The dissected tissues were used for nuclei isolation as previously described . To obtaWestern blots were carried out as previously described . NuclearMale Sprague Dawley rats weighing 200–250 g were killed by decapitation and brains were rapidly removed and cooled on ice. The synaptosomes were prepared as previously described  with som3H]dopamine uptake into synaptosomes was carried out according to previously published methods [d-amphetamine or d-pseudoephedrine) followed by 50 μl [3H]dopamine  were added to synaptosomal suspensions  to give a final volume of 1 ml. The reaction mixture was incubated at 25°C for 5 min in a metabolic shaker water bath. Following incubation, the reaction mixture was rapidly filtered through glass-fiber filter paper (Whatman GF/B) by a vacuum pump and washed twice with 3 ml of Krebs phosphate buffer. The synaptosomes containing radioactive dopamine trapped on filter paper were counted by liquid scintillation spectrometry (Beckman LS 1801) in 5 ml of TritonX-100/Toluene base fluor (1:3) scintillation fluid. The active accumulation of [3H]dopamine was determined as the difference of the radioactivity accumulated in the synaptosomes in the presence and absence of 1 μM nomifensine.Measurement of dopamine uptake was assayed in synaptosomal preparations from rat brain areas. Both amphetamine and pseudoephedrine inhibited the uptake of [3H]dopamine into nucleus accumbens and striatal synaptosomes, with amphetamine being more potent than pseudoephedrine (Fig. 3H]dopamine uptake shifted to the right. The IC50 values for amphetamine and pseudoephedrine inhibition reported here (see legend Fig. 3H]dopamine uptake into striatal and nucleus accumbens synaptosomes, respectively.In order to investigate the mechanism of action of pseudoephedrine and to compare it to that of amphetamine, the effect of pseudoephedrine and amphetamine on [ine Fig. . The ampChronic injection of pseudoephedrine resulted in desensitisation of the acute pseudoephedrine induced c-Fos induction in the striatum and nucleus accumbens. It has previously been shown that chronic treatment with cocaine and amphetamine reduces the immediate-early-gene expression response to these drugs in specific brain areas -21. Pseu3H]dopamine uptake and report that both amphetamine and pseudoephedrine inhibit [3H]dopamine uptake. The role of dopamine in pseudoephedrine induced c-Fos response is further corroborated by the effect of the D1 receptor antagonist SCH23390 which as previously described [To further test the hypothesis that amphetamine and pseudoephedrine work through similar mechanisms, cross tolerance tests were carried out. The results indicate that in amphetamine and in pseudoephedrine chronically treated rats the c-Fos response in the striatum and nucleus accumbens following a final injection with pseudoephedrine and amphetamine respectively, was lower than in naïve animals. This result is consistent with our previous findings that pseudoephedrine has similar effects and mechanisms of action as amphetamine in terms of c-Fos expression  and inteescribed  inhibiteOur studies thus indicate that pseudoephedrine, notwithstanding the higher doses required, acts in manner indistinguishable from amphetamine. This may have sociological and medical implications as pseudoephedrine is a legal over-the-counter drug. Doses of pseudoephedrine in over-the-counter formulations vary between 60–120 mg/pill and a large amount of pills would need to be ingested to equate the doses injected into rats in this study. However, it is unknown whether the efficacy of the pseudoephedrine in humans is different from rats. An additional potential risk of pseudoephedrine is reinstatement of drug seeking behaviour in individuals that have overcome previous addiction to psychostimulants. It would be useful to determine whether pseudoephedrine could induce a reinstatement of drug seeking behaviour in rats that had first been chronically treated with amphetamine and that had then been allowed to extinguish their amphetamine seeking behaviour. Particular attention would need to be paid to the genetic background of the animals as it has been shown to affect relapse behaviour . The datNR carried out all the animal treatment and western blot experiments and drafted the manuscript. WT carried out the synaptosome experiments and contributed to the draft of the manuscript. SOC devised the experiment plan for the western blots and finalized the manuscript. PG devised the experiment plan for the synaptosome work, critically reviewed the final manuscript preparation and provided overall coordination for the project.


The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates. A ubiquitous aspect of brain function is its quasi-modular and massively parallel organization. The paradox is that this extraordinary parallel machine is incapable of performing a single large arithmetic calculation. How come it is so easy to recognize moving objects, but so difficult to multiply 357 times 289? And why, if we can simultaneously coordinate walking, group contours, segment surfaces, talk and listen to noisy speech, can we only make one decision at a time? Here we explored the emergence of serial processing in the primate brain. We developed a spiking-neuron implementation of a cognitive architecture in which the precise sensory-motor mapping relies on a network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold. However, control routing mechanisms result in serial performance at the router stage. Our results suggest that seriality in dual (or multiple) task performance results as a consequence of inhibition within the control networks needed for precise “routing” of information flow across a vast number of possible task configurations. A ubiquitous aspect of brain function is its modular organization, with a large number of processors  operating simultaneously and in parallel. Human cognition relies, to a large extent, on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain (e.g. respond with the right hand to the red square) The psychological refractory period (PRP) provides a classic and clear demonstration in experimental psychology of the coexistence of parallel processing and serial processing bottlenecks within a cognitive task. When performing two tasks in rapid succession on two successively presented targets T1 and T2, delays are observed in some but not all of the T2 processing stages. Analysis of these delays suggests that a “central decision stage” suffers from seriality while perceptual and response operations occur in parallel Until now, the modeling of dual tasks is only specified at a level of mathematical description and functional cognitive architecture per se but to understand the conditions under which a computational model capable of flexible sensory-motor mapping shows patterns of interference when two tasks have to be performed simultaneously or in close succession In accordance with previous theoretical proposals Following classic experimental procedures of the PRP Each element in this sensory hierarchy is a canonical cortical circuit comprising excitatory pyramidal cells and local inhibitory cells, previously shown to be capable of performing elementary functions of working memory and decision making Both sensory modalities project to a router which connects the sensory representations to a set of possible responses. Neurons in the router integrate sensory evidence and trigger a response when their activity reaches a threshold task-setting network. Excitatory populations in this network are activated by the presence of task-relevant stimuli in sensory areas and, through their patterns of projection to “router” neurons (see below), encode different stimulus-response mappings. As with the sensory modalities, we only simulate two task-setting populations which are sufficient for the experiments considered here.An explicit instruction - presented before the stimulus – sets the task for a given trial, i.e. specifies the specific mapping which indicates which response has to be executed when the stimulus is presented. The network that stores task instructions is referred throughout this work as the An important aspect of our model is a circuit which we refer as the “router”. As in previous models of flexible decision making that do not rely on synaptic plasticity to dynamically adjust their behavior As with all other neurons in the network, task-setting neurons are entailed with self excitation and lateral inhibition. Excitatory neurons in the task-setting network are connected to the router through NMDA connections. When an excitatory population of the task-setting network is in an “active” state it excites the subset of neurons in the router receiving inputs from task relevant sensory populations and connecting them to the appropriate motor populations. A neuron in the router which receives excitation from task-setting neurons is set in a mode of integration in which it can accumulate sensory information . This arResponse execution is triggered in response selection networks  both accumulate evidence towards a motor decision and route sensory input to the relevant motor neurons.Each stimulus has four features. The four populations encoding low-level features of a stimulus receive a brief pulse of constant current during stimulus presentation (100 ms). This initial impulse generates a transient response in the earliest input neurons , which iThe last stage in the sensory hierarchy projects to the router using AMPA receptors. Neurons in the router also receive currents from task-setting neurons, but these projections use NMDA receptors. These NMDA currents control the recurrence in the router, and they determine the degree of integration of AMPA currents. As a result of this architecture, neurons in the router act as detectors of the conjunction of stimulus presence and task relevance as observed in The principal aim of this paper is to explore the operation of the model in a classic dual-task paradigm: the psychologically refractory period (PRP), widely studied in the psychophysical literature. We explored the response of the model with two different stimuli, presented simultaneously or at a short stimulus onset asynchrony (SOA). When the separation between stimuli (SOA) is much longer than the response time to the first task (RT1), the neural activations associated with the first and second task do not interfere with each other and the observed dynamics is similar to that observed during single-task performance .The most interesting situation is for SOA values close to or shorter than RT1 , and S2 routing. During queuing, currents in the router reflected a steady level of activity which was significantly larger than during spontaneous activity . Thus, dThe task-switching circuit was endowed with high efficiency inhibition to achieve rapid switching from one task-setting program to another. This endowed the task-setting circuit with high frequency oscillations as can be seen in the raster plots of Rhythmic activity in the sensory neurons showed distinct oscillatory activity during buffering and routing . Spike dAn appealing aspect of the PRP paradigm  is that Specifically, the main experimental characteristics of the PRP phenomenon are RT2 shows a linear decrease with slope of −1 for short SOA and a slope of 0 for large SOART1 is typically unaffected by SOAPre-bottleneck manipulations  additively affect both RT1 and RT2 inside the interference range when the first task is being manipulated. When the second task is manipulated, under-additive effects are seen at short SOA, due to the absorption of pre-bottleneck components while T2 is being queued by T1 processingBottleneck manipulations  additively affect the task that is being manipulatedRT distributions are long-tailed RT2 tightly covaries with RT1, but only for short SOA (i.e. in the interference regime)RT2 variance increases as SOA decreases, since it accumulates the variability of both RT1 and RT2 in the interference regimeWe first explored the main effects of the PRP (without specific task manipulations) by simulating an experiment in which two stimuli were presented at an SOA which varied between 0 and 800 ms, sampled at  ms . ResponsSecond, we observed the classic RT2 profile with varying SOA values: An initial decrease with a slope of −1 . This inBased on typical experimental procedures, we then explored the effect of different manipulations on the first and second task on mean response times, and their interaction with SOA .three) results in an increase in response time which is absorbed during the PRP  First we investigated the effect of changing the complexity of sensory processing. In a number comparison task, changing the notation   the two competing stimuli can be made arbitrarily close, rendering the decision progressively more difficult. This results in increased errors and RTs, and attractor dynamic networks have been very successful in modeling these phenomena ulations . We applulations . This efulations , the firct.org/) .The response times histogram for SOA = 0 ms is displayed in The previous results showed that our model can explain the precise shape of response time distributions in dual-task performance. Here we investigate the underlying physiological markers which result in such distributions, i.e. the relation between neuronal and response time variability. All neurons in the model receive strong background Poisson inputs, which assures a spontaneous activity of 2–5 spikes/s. We hypothesized that in trials in which input noise in the sensory neurons coincides with stimulus presentation (presented for 100 ms) response times would be faster. We also hypothesized that in the case of low-frequency noise (∼5Hz), the coincidence effect of external-stimulus and internal noise fluctuations, should manifest in a phase-locking relation of stimulus presentation to internal rhythms, as observed in both psychophysical We first used a general linear regression model to investigate how noise fluctuations affected response times in the PRP. The explanatory (independent) variables were external noise fluctuations for each population group and temporal bin, and the response (dependent) variable was either RT1  or RT2 .We simulated 900 trials of the PRP for an SOA of 50 ms. For each trial, the population average of ents see  section The time-course of the coefficients of the regression  showed aAs we showed previously, RT2 variability accumulates RT1 variability (due to changes in the onset of the routing of T2) and intrinsic variability of the T2 routing process. To understand the impact of noise on each of these processes, we measured the time-course of the noise input to Task-2 responding neurons locked to the response to Task 1 . SignifiThus, spontaneous Poisson-noise fluctuations were effective when they coincided in time with external stimulus currents. If noise currents were carried by low-frequency oscillations Behavioral experiments which have combined the basic features of different manifestations of central processing such as the PRP (two rapid responses) or the attentional blink (extinction of a second rapidly presented stimulus) have suggested that both forms of processing limitations may arise in part from a common bottleneck To evaluate whether our model could, without modification, also account for AB experiments, we studied the effect of a mask applied after T2. The mask was modeled as a brief stimulation of non-specific excitatory cells in the first layer of the sensory hierarchy, thus modeling the activation of a neural representation competing with the target T2 seen, and those in which it fails to respond as unseen. For example, at SOA = 50 ms we obtained 49±5% seen trials, 47±4.99% unseen trials, and 4±1.96% errors; for SOA = 500 ms, we obtained 90±3% seen trials, 9±2.86% unseen trials, and 1±0.01% errors. As observed in the Attentional Blink and in mixed AB-PRP paradigms, the brief mask after T2 is only effective when T2 is presented within a short temporal window – typically of around 500 ms – following T1 presentation.We simulated 100 trials at each SOA value, varying the SOA between 50 and 500 ms at 50 ms intervals. In contrast to the previous PRP simulations, when the SOA between T1 and T2 was short we observed a small (but significant) number of errors and, most importantly, a large number of trials in which the network failed to respond to T2 . For simseen or unseen responses depending on the inner state of the network. seen and unseen trial and reveals the cause of the blink. In the unseen trial, RT1 was longer and thus at the moment in which inhibition of T2 task-setting neurons was released, T2 sensory activation had faded out. As a consequence, T2 task-setting neurons failed to respond and this impeded the integration and routing of T2. This can also be seen when averaging across all trials (for an SOA of 100 ms) according to whether the network responded or failed to respond to T2  with increased T1 strength. For example, the blink is attenuated when a blank is placed after T1, i.e. masking is delayed We examined this hypothesis performing two different simulations. First, we increased the strength of T1 by 10% relative to the previous PRP and AB simulations. This resulted in an attenuated AB for the second task . Despite perfect performance for T1 in these simulations, RT1 was smaller when T1 was stronger . Thus increasing T1 strength decreases RT1 and increases the probability of retrieving the second stimulus.The second manipulation, conversely, involved masking the first target T1, simulating the most typical AB paradigm in which both T1 and T2 are masked. As for the first manipulation, 100 trials were simulated at a fixed SOA of 50 ms and we now added a mask identical to the one previously used for T2. In this condition, performance in the first task was still accurate (92±3% correct) while T2 visibility was decreased significantly (26±4% correct). This effect can be understood by the increased latency of the inhibitory signal following routing of T1, which increased RT1 from 396±9 ms in the unmasked condition to 869±50 ms when T1 was masked.In summary, our simulations show that T1 manipulations that facilitate the first task and therefore reduce its duration have the effect of reducing the attentional blink for T2, as experimentally observed The present model constitutes, to our knowledge, the first spiking-neuron model of a global architecture capable of simulating the entire sensory-motor chain of processing in a dual-task setting. We could explain the detailed dynamics of behavior (including both mean RTs and RT distributions) during dual-task-performance, by simulating a large-scale network of realistic neurons, comprising about 20.000 spiking neurons and 46.000.000 synaptic connections. For consistency with the majority of previous PRP experiments, we simulated an experimental design in which stimuli involve distinct sensory modalities and the responses distinct effectors. Under these circumstances, interference occurs exclusively at the routing stage, commonly referred to in psychology as the response selection stage Based solely on the known dynamics of neurotransmitter receptors, the model reproduces, in a quantitative manner, a large number of behavioral observations of dual-task interference see :A sequential delay in RT2. This delay decreases with a slope of −1 as SOA increases reflecting a sequential bottleneck.The absence of any effect of the second task on response times to the first task (mean and distribution).Strong correlations between RT1 and RT2 which progressively diminish as SOA increases.Distinct interference patterns associated with different task manipulations: changes which affect the sensory delay processing of Task 2 are absorbed during the slack time separating task 1 and task 2, while changes which affect the accumulation time  propagate additively.Switch from the PRP (delayed response to T2) to the blink (an absence of the response to T2) by adding a mask after the T2 stimulus.An increase in blink probability when T1 visibility is reduced.These results are in full accordance with the central interference model Several brain-imaging experiments implicated a number of cortical systems in the PRP phenomenon. The cerebral basis of processing bottlenecks has been investigated with Event Related Potential studies (ERPs), which have shown that the PRP results in reduced and/or delayed components The spatial resolution of EEG is very imprecise and thus a better characterization of the locus of central processing bottlenecks in the brain comes from fMRI studies, which have pinpointed a broad parietofrontal network that exhibits various manifestations of central capacity limits Our network postulates a hierarchical organization of this system: neurons controlling the whole-task structure (order network) gate neurons controlling the individual tasks (task-setting network), which, in turn, gate the routing from the sensory representations to the motor intention stage. Such a hierarchical organization has been demonstrated in humans in the prefrontal cortex as the Broca region and its homologue in the right hemisphere implement executive processes that control start and end states as well as the nesting of task segments that combine in hierarchically organized action plans Understanding the emergence of serial behavior in the human brain is an important and central theoretical question in cognitive psychology as modularity and parallel processing are hallmarks of brain computations. Different authors have proposed cognitive architectures that can explain how components of the mind work to produce coherent cognition Here we have tentatively proposed that seriality in dual (or multiple) task performance results from the necessity to establish a task set through the activation of a “router” network. This router network is shared by all sensory-motor mappings and its activity can, potentially, code for a virtually infinite number of possible tasks. A task-setting program acts as a gate, permitting routing neurons to propagate information if they receive the appropriate sensory input. This system acts as a control mechanism that avoids erroneous, conflicting or unwanted stimulus-response associations. We showed that a concrete implementation of such a control system results in serial behavior of the routing process when probed in dual-task situations.In our network, seriality and its behavioral manifestations, the PRP and the Attentional Blink, emerged from competition between task-setting neurons which, through a lateral inhibition process, prevented the simultaneous activation of two task settings. This form of control is necessary to ensure correct task performance in conflicting mappings - as classically demonstrated in the Stroop paradigm in which the same stimulus may lead to distinct responses according to task requirements Another possible origin of seriality relates to the coding properties of the router , an effect known as lag-1 sparing In fact, we see the extension of the present model along the lines just discussed: the different types of neurons used in our implementation (briefly reviewed in the next section) have been found in the awake behaving monkey and may serve as a basis from which to construct complex cognitive programs, as those implemented in systems like ACT-R Most, if not all, types of neurons used in our implementation have been observed in studies that measured single-neuron activity in awake behaving monkeys during single-task performance. Here we will briefly mention the main types of neurons in the various areas of our model and compare them to neurophysiological data, a comparison that will have to remain somewhat superficial as we cannot attempt to discuss the precise relationships between the variety of tasks employed in the neurophysiological studies and the PRP task implemented here. Firstly, the properties of the sensory areas of our model are consistent with what is known about representations in areas of sensory cortex. Neuronal activity in low level sensory cortex is largely (but not entirely) determined by the incoming sensory information Our network can also explain timing and latencies of the sequence of events identified in single-task physiological experiments in monkeys Our observations also raise a note of caution on the interpretation of processing latencies from physiological data. A concrete example is conveyed in our model by the measurement of activity in the routing neurons. Spiking activity shows a clear sequential scheme: routing neurons of T2 start integrating only once routing of T1 has completed . Thus, tOur data showed that fluctuation in response time could be accounted by the dynamics of noise fluctuations in relation to the timing of stimulus routing . When noseen and unseen trials. Only in unseen trials should the memory of T2 fade below a threshold (either due to fluctuations in transient response or in the durations of the memory due to the extension of T1) impeding routing and broadcasting to the rest of the network. These predictions will become testable once an awake animal model of dual-task performance is defined.The correlates of the bottleneck have yet to be studied at the single cell level and our simulations therefore generated a number of new predictions that could be tested in future neurophysiological experiments. First the model establishes the existence of routing and task-setting neurons with well distinct dynamics and connectivity with different neuronal populations. At the anatomical level, routing neurons should receive inputs from all sensory modalities and from task setting neurons. At the functional level, they should be characterized by their firing in response to specific conjunctions of stimuli and responses, a preference which may change dynamically according to task context, on a time scale of about 100 ms or more . j and the identity of the receptor mediating the transmission. The dynamics of the gating variables are as follows. When a neuron receives a presynaptic action potential the appropriate gating variable s is increased. Otherwise, these variables decay exponentially. For AMPA and GABA receptors:Recurrent excitation is mediated by AMPA and NMDA receptors, and inhibition is mediated by GABA receptors. The total synaptic currents are given by:k and α = 0.63 controls the saturation properties of NMDA channels. The decay time constants are τNMDA = 100 ms, τAMPA = 2 ms, and τGABA = 10 ms.For NMDA receptors:modules as used in previous studies Neurons are grouped into homogeneous populations. A total of 84 unique populations were included in the simulations. In sensory and routing areas these homogeneous populations were grouped into larger groups, forming local Sensory areas are modeled through a hierarchy of modules, to account for convergence and increased receptive fields at higher levels of processing Within local modules, connections are structured according to a “Hebbian” learning rule: coupling strength between pairs of neurons is considered to be high for neurons inside a selective population, and low when connecting neurons from competing populations. Specifically, for synapses connecting neurons within the same selective population, a potentiated weight Feedforward and feedback connections have different degrees of specificity. Feedforward connections are highly specific: neurons from one excitatory population project exclusively to one excitatory population in the immediate higher level. These connections are mediated exclusively through AMPA receptors  and one inhibitory (100 neurons). Excitatory neurons connect to themselves  which inhibits the portion of the task-setting network responsible for the amplification of the second task, until the response to the first task is emitted. The mechanism by which this occurs is as follows. The order network is a bistable network composed of one excitatory and one inhibitory population of 400 and 100 neurons respectively  must perform two tasks as fast as possible, in a pre-specified order. Each task involves a simple two-alternative decision. In the network, the set of possible task-related stimuli in each modality is restricted to two, as is often the case in real PRP experiments.All neurons receive background Poisson input to maintain a spontaneous activity of a few Hertz. The presentation of a task-relevant stimulus increased the external input of the four selective populations in the first level sensory network, from the background level of 2,400 Hz (as may result from 800 afferent neurons spiking at a spontaneous rate of 3Hz) to 2,717 Hz, for 100 ms .In In the attentional blink (AB) simulations, a mask is presented after the task-relevant stimulus. This was modeled as in previous studies C++, and simulations were performed in the CECAR computer cluster (Buenos Aires University). Equations were integrated with the first-order Euler method, with a time step of 0.05 ms. When run on a Linux 3.16 Ghz Pentium IV PC, each trial takes about 3 minutes to complete.Each simulated trial lasted 3400 ms. The first stimulus was presented at 700 ms, and the second stimulus was presented according to the SOA. The code was written in Figure S1Response perseveration without ‘corollary discharge’ from motor neurons. Smoothed firing rates of selected populations - during one trial of single-task performance - when the ‘corollary discharge’ from motor neurons to inhibitory neurons participating in memory maintenance - last level sensory neurons - is removed. Response times are indicated with red vertical arrows. (A) Stimulus selective neurons from the first sensory level show a phasic response to stimulus presentation. (B) Last level sensory areas maintain high levels of activity until a response is emitted; in the absence of inhibition from motor neurons, these neurons keep feeding routing (C) and task-setting (D) neurons, resulting in response perseveration.(0.55 MB TIF)Click here for additional data file.Figure S2Stochasticity in task choice. In the main simulations the order in which tasks have to be performed is constrained to mimic the condition of most PRP experiments. A recent experiment (0.15 MB TIF)Click here for additional data file.Figure S3Input currents to the router circuit during different processing stages of T2. Input currents to the router during three different processing phases of T2: before stimulus presentation , during the phase in which T1 is being routed and S2 is buffered in memory , and during routing of T2 . The mean recurrent inputs (y-axis) flowing through AMPA (blue trace), NMDA (green trace), and GABA (red trace) receptors were obtained by simulating 50 PRP trials at SOA = 0 ms, recording these currents every 2 milliseconds. The time windows considered for each phase were (x-axis): Rest:  ms relative to stimulus presentation; Queued: window of 150 ms centered  around the time that the T1 task-setting neurons were active; Routing:  ms relative to the response time to the second task. Shades depict the standard error of the mean. To assure that each of these windows overlapped with the corresponding processing stages independently of fluctuations in response time, we filtered the trials, considering only the subset of trials (37 of 50) for which the following conditions were met: T1 task-setting neurons were active for more than 150 ms and less than 350 ms, and RT2 <1000 ms.(0.28 MB TIF)Click here for additional data file.Figure S4www.chronux.org). 1. Pesaran B, Pezaris JS, Sahani M, Mitra PP, Andersen RA (2002) Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nat Neurosci 5: 805–811.Spectral analysis of sensory, router, and task-setting neurons involved in T2 processing. We analyzed the spectrogram of sensory (left panel), routing (center panel) and task setting (right panel) T2 neurons throughout the trial. Colored circles at the top identify the populations analyzed in the notation of (0.45 MB TIF)Click here for additional data file.Figure S5www.chronux.org). Data was obtained from 200 PRP trials at a SOA of 0 ms, and the spike density function was obtained by filtering the time series of spikes from 80 neurons in each population with a Gaussian kernel (σ = 2 ms).Spike-density coherence between sensory and router neurons during different processing stages. We measured the spike density coherence between sensory and router neurons, during three different phases of task processing: before stimulus presentation (left column), during active routing of T1 (center column), and during active routing of T2 (right column). Each phase lasts 100 ms. The top row corresponds to populations selective to T1 and bottom row to T2. Each population is the scheme is colored following the nomenclature of (0.27 MB TIF)Click here for additional data file.Figure S6Combinatorial router. A) In the model, each neuron in the router coded exclusively for particular combinations of stimulus and response. This would lead to scaling issues when the number of possible mappings increases. Here we sketch a different coding schema for the router, one that works on the basis of combinatorial codes. A small portion of the network is simulated, containing only parts of the router and motor networks. See the main text and the model of Lo & Wang  for details of the circuit, specially the disynaptic inhibitory circuit by which the router both excites the different motor neurons and inhibit the tonic inhibition of those same motor units, implementing a threshold detection mechanism for the activity in the router. Two populations of excitatory neurons need to code for three different stimuli, each one mapped to a different response. Thus, the simultaneous activation of both router populations lead to a third response different from the one generated by each population alone, by tuning the synaptic efficacies such that the response in the center of panel A (light brown) receives a larger excitatory input than the other responses only when both router inputs are active. (BCD) Population firing rate of both router populations - during a simulation of the model - for the three possible stimuli. X-axis indicates the time relative to stimulus onset, and y-axis depicts the population firing rate calculated with an exponential causal kernel of 20 ms. The time of the motor burst is indicated by a colored vertical line, with color codes as in panel A. The simultaneous presentations of both Stim1 and Stim3 does not lead to the superimposed execution of the two responses obtained when each stimulus is presented alone (panels B and D), but to a third and different response (panel C). Thus, the implementation of inhibitory control mechanisms to arrange the sequential routing of tasks presented at short SOA is required in a combinatorial code to achieve precise stimulus-response mappings - and may lead to through the same mechanisms discussed in the main text to dual-task interference as observed in the PRP and the AB. Lo, C. C., & Wang, X. J. (2006). Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nature Neuroscience, 9, 956–963.(0.32 MB TIF)Click here for additional data file.Text S1Supporting Notes.(0.02 MB DOC)Click here for additional data file.Table S1Results of the ANOVAs of the interference simulations. Each column corresponds to a different ANOVA. Each line represents a different effect: task manipulation, SOA, and their interaction. The top row indicates the identity of the variable under analysis and the second row indicates the type of manipulation . Red indicates a significant effect.(0.03 MB DOC)Click here for additional data file.