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risons with future new agents.<br /><br />Meta-analyses confirmed the benefit of all DMTs in terms of relapse rate compared with placebo with a comparable rate of SAEs for the DMTs that could be included in the network. The rigor and transparency of reporting in this study provide a benchmark for comparisons with future new agents.Visual attention allows selecting relevant information from cluttered visual scenes and is largely determined by our ability to tune or bias visual attention to goal-relevant objects. [https://www.selleckchem.com/products/wortmannin.html Wortmannin ic50] Originally, it was believed that this top-down bias operates on the specific feature values of objects (e.g., tuning attention to orange). However, subsequent studies showed that attention is tuned to in a context-dependent manner to the relative feature of a sought-after object (e.g., the reddest or yellowest item), which drives covert attention and eye movements in visual search. However, the evidence for the corresponding relational account is still limited to the orienting of spatial attention. The present study tested whether the relational account can be extended to explain attentional engagement and specifically, the attentional blink (AB) in a rapid serial visual presentation (RSVP) task. In two blocked conditions, observers had to identify an orange target letter that could be either redder or yellower than the other letters in the stream. In line with previous work, a target-matching (orange) distractor presented prior to the target produced a robust AB. Extending on prior work, we found an equally large AB in response to relatively matching distractors that matched only the relative color of the target (i.e., red or yellow; depending on whether the target was redder or yellower). Unrelated distractors mostly failed to produce a significant AB. These results closely match previous findings assessing spatial attention and show that the relational account can be extended to attentional engagement and selection of continuously attended objects in time.Human decisions often deviate from economic rationality and are influenced by cognitive biases. One such bias is the memory bias according to which people prefer choice options they have a better memory of-even when the options' utilities are comparatively low. Although this phenomenon is well supported empirically, its cognitive foundation remains elusive. Here we test two conceivable computational accounts of the memory bias against each other. On the one hand, a single-process account explains the memory bias by assuming a single biased evidence-accumulation process in favor of remembered options. On the contrary, a dual-process account posits that some decisions are driven by a purely memory-driven process and others by a utility-maximizing one. We show that both accounts are indistinguishable based on choices alone as they make similar predictions with respect to the memory bias. However, they make qualitatively different predictions about response times. We tested the qualitative and quantitative predictions of both accounts on behavioral data from a memory-based decision-making task. Our results show that a single-process account provides a better account of the data, both qualitatively and quantitatively. In addition to deepening our understanding of memory-based decision-making, our study provides an example of how to rigorously compare single- versus dual-process models using empirical data and hierarchical Bayesian parameter estimation methods.In 1956, Brunswik proposed a definition of what he called intuitive and analytic cognitive processes, not in terms of verbally specified properties, but operationally based on the observable error distributions. In the decades since, the diagnostic value of error distributions has generally been overlooked, arguably because of a long tradition to consider the error as exogenous (and irrelevant) to the process. Based on Brunswik's ideas, we develop the precise/not precise (PNP) model, using a mixture distribution to model the proportion of error-perturbed versus error-free executions of an algorithm, to determine if Brunswik's claims can be replicated and extended. In Experiment 1, we demonstrate that the PNP model recovers Brunswik's distinction between perceptual and conceptual tasks. In Experiment 2, we show that also in symbolic tasks that involve no perceptual noise, the PNP model identifies both types of processes based on the error distributions. In Experiment 3, we apply the PNP model to confirm the often-assumed "quasi-rational" nature of the rule-based processes involved in multiple-cue judgment. The results demonstrate that the PNP model reliably identifies the two cognitive processes proposed by Brunswik, and often recovers the parameters of the process more effectively than a standard regression model with homogeneous Gaussian error, suggesting that the standard Gaussian assumption incorrectly specifies the error distribution in many tasks. We discuss the untapped potentials of using error distributions to identify cognitive processes and how the PNP model relates to, and can enlighten, debates on intuition and analysis in dual-systems theories.<br /><br /> A previous FDA study reported a favorable benefit risk for apixaban compared with warfarin for stroke prevention in older non-valvular atrial fibrillation (NVAF) patients (≥ 65years). However, it remains unclear whether this favorable benefit risk persists in other populations including younger users. We examined if a similar benefit risk was observed in the Sentinel System and if it varied by age group.<br /><br /> To examine the risk of ischemic stroke, gastrointestinal (GI) bleeding, and intracranial hemorrhage (ICH) in apixaban users compared with warfarin users in Sentinel Distributed Database (SDD).<br /><br /> A retrospective new user cohort study was conducted among patients, 21years and older initiating apixaban and warfarin for NVAF, between December 28, 2012, and June 30, 2018, in the SDD.<br /><br /> Cox proportional hazard regression was used to estimate the hazard ratios (HR) and 95% confidence intervals (95% CI) for each outcome (ischemic stroke, GI bleeding, and ICH) in propensity score matched apixaban users compared with the warfarin users.