Pseudocontingencies – rule based and associative

The present work puts forward a rule-based model for judging the direction of a contingency. A set of “alignment rules” (ARs) is defined, all of which bind frequent observations to frequent observations and infrequent observations to infrequent observations. These rules qualify as possible mechanisms behind pseudocontingencies (PCs, Fiedler, Freytag, & Meiser, 2009). Six experiments, involving social and non-social stimuli, are presented that pit the predictions of the rule-based PCs against associative models for contingency judgments (Van Rooy, Van Overwalle, Vanhoomissen, Labiouse, & French, 2003). Results consistently show that participants associate predictors with criteria that are non-contingent but jointly frequent and rare. Crucially, these illusory contingency judgments are shown to persist (a) in attitude ratings after extended observational learning and (b) at asymptote in operant learning. In sum, the results are evidence for the impact of rule-based PCs under conditions that call for associative learning. In a next step, rational arguments (Anderson, 1990) are used to set the AR apart from other rule-based models with similar empirical predictions. Results of two simulations reveal that the AR performs remarkably well under real-life constraints. Under clearly definable conditions, like strongly skewed base rates and small observational samples, the AR performs even better than other models, like ΔP (Allan, 1993) or the Sum-of-Diagonals (SoD, Inhelder & Piaget, 1958). Finally, the AR is claimed to be a natural by-product of the learning history with strong contingencies. Suggestive evidence from a simulation is provided that shows an increased likelihood of jointly skewed base rates, the precondition for ARs, in the presence of strong contingencies. Thus, ARs might develop from a confusion of the learned above chance probability p ( joint-skew | strong-contingency ) with an above chance probability p ( strong-contingency | joint –skew ) that justifies an AR inference. Possible future research on how joint observations and base-rates interact to influence contingency judgments is outlined

Base-rate neglect based on base-rates in experience-based contingency learning

Predicting criterion events based on probabilistic predictor events, humans often lend excessive weight to predictor event information and insufficient weight to criterion event base-rates. Using the matching-to-sample paradigm established in studies on experience-based contingency learning in animals, Goodie and Fantino (1996) showed that human judges exhibit base-rate neglect when sample cues are associated with response options through similarity relations. In conceptual replications of these studies, we demonstrated similar effects when sample cues resemble the response options in terms of base-rates skewed in the same direction rather than physical similarity. In line with the pseudocontingency illusion (Fiedler & Freytag, 2004), predictions were biased toward the more (less) frequently rewarded response option following the more (less) frequently presented sample cue. Thus, what is a demonstration of base-rate neglect from one perspective turns out to reflect the judges' sensitivity to the alignment of skewed base-rate distributions

The reproduction of base-rates promotes pseudocontingencies

Fiedler and Freytag (2004) proposed an alternative pathway to contingency assessment in terms of pseudocontingencies (PCs). PCs reflect the utilization of base-rate information in the formation of contingency judgments. Here, we introduce an instantiation of the phenomenon based on the mere reproduction of the base rates. Using a relationship-counseling scenario, participants in two experiments produced positive correlations on both indirect and direct measures of the contingency between partners’ responses to the subscales of a relationship inventory, although the objective contingency within each subscale had been negative in an initial learning phase. The magnitude of these effects was predicted accurately by computer simulations reproducing the base rate of ‘yes’ responses for each partner and domain. The findings are discussed within the PC framework

Pseudocontingencies in stereotype formation : extending illusory correlations

Under the notion of illusory correlations, simple learning paradigms (e.g. Hamilton & Gifford, 1976) have been used to study the formation of stereotypes that discriminate between majorities and minorities. In the present paper, limitations of this approach in terms of theoretical explanations and empirical evidence are addressed. Theoretically, we propose pseudocontingencies (PCs, Fiedler, Freytag & Meiser, 2008) as a more robust mechanism behind illusory correlations. In contrast to previous explanations, PCs can explain illusory correlations when groups are never paired with valence. Empirically, we replicate earlier findings, i.e. that the more frequently observed group, the majority, is evaluated more in line with the more frequently observed valence. Crucially, we extend the empirical evidence in that illusory correlations prove robust over a very large number of observations (320) and under increasingly interactive task conditions, involving predictions of valence (Experiment 2) and reinforcement-learning conditions (Experiment 3). The latter provided evidence for illusory correlations on a new measure, participants’ predictions. These predictions reflect the expectations about the valence associated with majority and minority and might well affect real life behavior. The discussion focuses on possible reasons for why PCs are used in stereotypic judgments

Evaluation of the accuracy of musculoskeletal simulation during squats by means of instrumented knee prostheses

Standard musculoskeletal simulation tools now offer widespread access to internal loading conditions for use in improving rehabilitation concepts or training programmes. However, despite broad reliance on their outcome, the accuracy of such loading estimations, specifically in deep knee flexion, remains generally unknown. The aim of this study was to evaluate the error of tibio-femoral joint contact force (JCF) calculations using musculoskeletal simulation compared to in vivo measured JCFs in subjects with instrumented total knee endoprostheses during squat exercises. Using the early but common “Gait2392_simbody” (OpenSim) scaled musculoskeletal models, tibio-femoral JCFs were calculated in 6 subjects for 5 repetitions of squats. Tibio-femoral JCFs of 0.8–3.2 times bodyweight (BW) were measured. While the musculoskeletal simulations underestimated the measured knee JCFs at low flexion angles, an average error of less than 20% was achieved between approximately 25°–60° knee flexion. With an average error that behaved almost linearly with knee flexion angle, an overestimation of approximately 60% was observed at deep flexion (ca. 80°), with an absolute maximum error of ca. 1.9BW. Our data indicate that loading estimations from early musculoskeletal gait models at both high and low knee joint flexion angles should be interpreted carefully

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe