We have Yaacov Trope, New York University, visiting and giving a talk in the Social, Economic, and Decision Psychology Colloquium this week (title and abstract follow).

Expansive and contractive regulatory scope

Adaptive functioning requires both being able to immerse ourselves in the here and now, with people who are like us and with us, contracting our Regulatory Scope, and being able to move beyond the local social environment to expand our Regulatory Scope. In order to effectively pursue desired ends that vary from the immediate to the very distant, humans have evolved a range of mental and social mechanisms to support both contractive and expansive Regulatory Scope and the ability to switch between them. Across these mechanisms, it is possible to distinguish a hierarchy of levels that vary in level of abstractness from a low-level concrete mode to a high-level abstract mode. The research that I will describe suggests that low-level modes of operation support contractive Regulatory Scope, whereas high-level modes of operation support expansive Regulatory Scope.

We have Alex Koch, University of Cologne, visiting and giving a talk at our Social, Economic, and Decision Psychology colloquium this Thursday (Oct 5th, 13:00; title and abstract follow).

(Why) good is more alike than bad: Implications for social cognition and judgment

Humans process positive information and negative information differently. These valence asymmetries are often summarized under the observation that ‘bad is stronger than good’, meaning that negative information has stronger psychological impact (e.g., in feedback, learning, or social interactions). This stronger impact is usually attributed to people’s affective or motivational reactions to evaluative information. We present an alternative interpretation of valence asymmetries in processing based on the observation that positive information is more similar than negative information. We explain this higher similarity based on the non‑extremity of positive attributes, discuss how it accounts for observable valence asymmetries in processing (classification, categorization, generalization, recognition etc.), and show how it predicts hitherto undiscovered phenomena.

This week, Marcus Grüschow from the University of Zürich is visiting us and will give a talk about effects of arousal on decision making and stress resilience. Marcus is a postdoctoral researcher in the lab of Christian Ruff at UZH’s Department of Economics. Here are title and abstract of his talk on Thursday at the SWE colloquium:

Arousal-state influences on human decision-making and stress resilience

Arousal-related influences on brain states are ubiquitous in the mammalian brain and vary with neuromodulatory catecholamine levels. How such endogenous fluctuations in brain state impact on behaviour is only poorly understood. During the first part of the talk I will report on our investigations regarding the neural mechanisms by which spontaneous arousal-related fluctuations in brain state, indexed by pre-stimulus pupil dilation, impact on everyday perceptual and value-based choices in humans. Moreover, pathological changes in the arousal system can lead to severe behavioural alterations, as evident in multiple neuropsychiatric disorders including depression and anxiety. Such malfunctions of the arousal systems may be triggered by stress and traumatic events which are common features of life in modern societies. Even though stressful life events are on average associated with heightened vulnerability to psychopathology, the majority of individuals exposed to even severe stressors do not develop psychological problems. In the second part of the talk I will aim to elucidate the neurobiological basis of stress resilience, by identifying neural processes that predict who is resilient and who succumbs to stress, thereby offering possible neural pathways promoting stress resilience.

Our guest this week at the SWE colloquium is Christopher Summerfield from Oxford University. Christopher studies both perceptual and value-based decision making and combines mathematical modeling with neuroscientific approaches. Here are the title and abstract of his talk:

Optimality and “irrationality” in human decision making

Humans make “near-optimal” category judgments about noisy sensory stimuli, but on cognitive tasks they often exhibit systematic biases that fail to maximize economic outcomes. In my talk, I will discuss why. I will argue that because the “ideal” observer framework considers only noise that arises during sensory encoding, it frequently misspecifies the decision policy that will maximize rewards. When we also consider “late” noise (that arising during information integration) cognitive biases can often be reframed as efficient, reward-maximizing policies. I will discuss with reference to data and modeling from tasks involving perceptual averaging, transitive choices and decoy effects in multialternative choices.

In this and next week, we will have two speakers at the SWE Colloquium who are interested in the neural basis of behavior and cognition.

This week (Thursday, Nov. 17, 13:00), Maël Lebreton from the Center for Research in Experimental Economics and Political Decision-Making at the University of Amsterdam will give a talk about interactions of valuation and confidence in the brain. Maël is a post-doctoral researcher with a background in Biosciences and has conducted (and published) quite a few studies using functional magnetic resonance imaging.

Next week (Thursday, Nov. 24, 13:00), we will have Tobias Sommer with us, a prinicipal investigator at the Department of Systems Neuroscience at the University Medical Center Hamburg-Eppendorf. He is an expert in the field of episodic memory research and will talk about modulations of memory consolidation.

This week we have Dr. Christoph Eisenegger from the University of Vienna visiting us and giving a talk in the Social, Economic, and Decision Psychology colloquium (Thursday,  June 2, 2016, 13:00, title and abstract follow).

The role of testosterone in human social decision making

While experimental animal research has investigated the role of the androgen system in animal behavior extensively, research in this area in healthy humans is strongly driven by theoretical models and less by empirical evidence. I will present data on the role of the androgen system in competitiveness and strategic gambling. The approach involves combinations of baseline measures of testosterone, single-dose drug administration, genetic analysis, with decision making paradigms of competition. The results extend our limited understanding of the role of testosterone in human social interaction by providing supporting evidence for a role of this hormone in social dominance.

This week we have Prof Dr. Charles Judd from the University of Colorado Boulder visiting us and giving a talk in the Social, Economic, and Decision Psychology colloquium (Thursday,  May 26, 2016, 13:00, title and abstract follow). We’re looking forward to seeing you there.

Experiments in which samples of participants respond to samples of stimuli: Designs, analytic models, and statistical power

Many psychological experiments ask participants to judge faces, memorize words, or solve analytic problems under different experimental conditions. The interest is in the mean condition differences in participants’ responses. Most typically differences due to the specific stimuli (i.e., faces, words, and problems) are ignored in the analysis of the resulting data. I will show that this can result in serious bias if the goal is to generalize conclusions to other samples of participants and other samples of stimuli that might have been used. I will then provide an introduction of the use of linear mixed models for analyzing data from designs involving two random factors, participants and stimuli. I will briefly discuss a range of such designs and then discuss issues of statistical power. I will argue that many failures to replicate experimental results may be due to the failure to treat stimuli as a random factor in the analysis of data from experiments involving  samples of both participants and stimuli.

Dr. Rani Moran, from Tel-Aviv University, visited us last week and gave talk on mathematical modeling of visual search (title and abstract follow).

Accounting for benchmark RT distributions in visual search

Historically, visual search models were mainly evaluated based on their account of mean reaction times (RTs) and accuracy data. Recently, Wolfe, Palmer, and Horowitz (2010) demonstrated that the shape of the entire RT distributions imposes important constraints on visual search theories and can falsify even successful models such as Guided Search, raising a challenge to computational theories of search. Moran et al. (2013) met this important challenge by developing a novel search-model, Competitive Guided Search (CGS). The model is an adaptation of Guided Search, featuring a series of item-selection and identification iterations with guidance towards targets. The main novelty of the model is its termination rule: A quit unit, which aborts the search upon selection, competes with items for selection and is inhibited by the saliency map of the visual display. The model was successfully fitted to data from three classical search tasks that have been traditionally considered to be governed by qualitatively different mechanisms, including a spatial configuration, a conjunction, and a feature search, thus providing a unifying framework for visual search. More recently, Moran et al. (2015) examined the possibility that a parallel search model can account for these benchmark data. Towards that purpose, we developed a parallel model in which each item is represented by a diffusor and the different diffusors run in parallel and independently of each other. The search is self-terminating if a target is found, and otherwise terminates when a distractor triggers a quit unit. The model was endowed with ample flexibility to allow it to compete with the serial model: it allowed for different capacity regimes, for set-size dependent adjustment of the diffusion-thresholds, and for liberal search-termination policies. Consequently, the model had many more free parameters than CGS. Still, model-comparisons revealed that CGS was superior even prior to penalizing the parallel model for its increased complexity. I discuss the insights we gleaned, with respect to search mechanisms, by modeling RT distributions using these models.

This week, Prof. Dr. Thorsten Hens, Professor of Financial Economics, University of Zurich, will visit us and give a talk at the SWE colloquium (abstract follows).

Designing a risk profiler: Which measures predict risk taking?

In this paper we assess the suitability of different risk profiling measures when individuals are involved in a process of discovering their willingness to take risks over different decision modes. The latter involve decisions under ambiguity, decisions after gaining experience and receiving outcome information on previous decisions. We find that risk taking is associated with individuals’ risk preferences in all decision modes but not with their investment experience. Although simulated experience improves the risk awareness and supports a higher risk taking, it cannot substitute the assessment of risk preferences and in particular the assessment of individual’s loss aversion. In contrast, self-assessed risk tolerance measures are not suitable for predicting risk taking in any decision mode. If risk preferences cannot be assessed, only the gender can be used as a predictor of risk taking.

Elliot Ludvig, Assistant Professor in the Department of Psychology at Warwick University, UK will be visiting us next Thursday and giving a talk in the Social, Economic, and Decision Psychology Colloquium (abstract follows). He earned his Ph.D. from Duke University in Psychological and Brain Sciences and did post-doctoral research in Neuroscience at Princeton University and in Computing Science at the University of Alberta. His research builds and tests computational models of how humans and other animals learn to make decisions

Memory biases in risky decisions from experience

When faced with risky choices, people often choose differently pending whether they learn about the odds and outcomes through explicit description or through repeated experience. In the latter case, when deciding based on past experiences, people must rely on their memories to guide choice. These memories, however, need not be veridical. In this talk, I discuss two ways in which memories of past outcomes can be distorted, affecting choice in risky decisions from experiences. First, people tend to remember the most extreme outcomes encountered (both best and worst), making them more risk seeking for gains than losses. Second, subtle reminders of past wins can induce people to gamble more. These biases are not uniquely human, and similar patterns of risky choice have been observed in pigeons and monkeys. I interpret these results through a reinforcement-learning model, derived from studies on animal learning, that learns similarly from both real and replayed experiences.

Peter Mohr, Junior Professor and head of the Dahlem International Junior Research Group „Neuroeconomics” at the Freie Universitaet Berlin, will be visiting us this Thursday and giving a talk in the Social, Economic, and Decision Psychology Colloquium (abstract follows).

Context Effects in Risky Choices

Context effects are defined as preference changes, depending on the set of available options. The mechanisms that lead to their emergence are, however, still under debate. Unlike utility-based models of choice, more sophisticated evidence accumulation frameworks like Multialternative Decision Field Theory (MDFT) are generally able to account for these effects. In a first experiment, we show that one specific context effect, namely the attraction effect, is present in risky choices and can be explained by MDFT. In a second experiment we extend these findings by showing, that another context effect, namely the compromise effect, is also present in risky choices. Similarly to the first experiment, MDFT is able to explain both context effects in risky choices. Recently, however, visual attention has been ascribed a more constructive and active role in preference formation, leading to the development of attention-based models of choice. Eye-tracking data in our second experiment suggests a strong relation between choice and visual attention, replicating the so-called gaze cascade effect and demonstrating both context effects also in visual attention. Finally, the inclusion of visual attention into existing models of choice substantially increased their ability to explain context effects in risky choices.