Sozial-, Wirtschafts- und Entscheidungspsychologie


Social, Economic, and Decision Psychology Blog

Archive for March, 2016

Laurenz Meier

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Dr. Laurenz Meier from the University of Friburg will visit us this week and give a talk in the SWE colloquium (Thursday, March 17th, 13:00; abstract follows).

Conflicts and Incivility at Work

The experience of interpersonal conflicts and incivility at work is part of daily life for many employees. I will talk about consequences as well as antecedents of antisocial behavior at work, thereby focusing on the role of work conditions and personal characteristics. I devote special attention to the vicious circle between stressful work conditions, impaired well-being, and antisocial behavior towards supervisors, co-workers, and family members.

The Great Escape

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I’ve finished reading Angus Deaton’s The Great Escape and can highly recommend it to those interested in the issues of well-being. The substantive issues discussed concerning health and wealth inequality make it an important read but there are other aspects that add to its appeal.

First, I particularly enjoyed that Deaton actually discusses data(!) and presents it in a very clear visual manner (yay for bubble charts). Second, I found it reassuring that Deaton seems simultaneously a strong advocate for the behavioural sciences while at the same time having a clear understanding of their limitations. For example, when discussing the theory and practice of survey design in measuring poverty, Deaton discussed the use of retrospective reports, in particular, questioning individuals about their household consumption in the past 30, or, alternatively, 7 days. Deaton makes clear that these small differences lead to very different reports and, consequently, very different conclusions about poverty in a country (India). Soberingly, Deaton concludes “To put it more brutally, the truth is that we have little idea what we are doing, and it is certainly a mistake to let anything important depend on such numbers.”

More research is needed.

 

Sharing information about ourselves online means connecting, which applies to people and brain regions!

A new study has just been published in Scientific Reports that I was involved with at the Free University of Berlin. Dar Meshi, the lead author of the paper, is interested in how social information is processed in the brain, and in this paper we investigated whether individual differences in sharing information about oneself on Facebook translate into individual differences in region-specific neural connectivity. Basically, the idea was to see whether there is an association between how active people say they are on Facebook with regards to sharing self-related information (e.g. frequent changes or updates to one’s profile picture, information, status; frequent tagging and posting of pictures or videos) and how strongly different cortical regions connect when the brain is at rest (i.e. not involved in any particular task). Interestingly, our results support the idea of a brain-behavior association, for we found that how much people share about themselves on Facebook was associated with differential connectivity of cortical midline regions.

To read the full paper and find out how these regions are hypothesized to sub-serve self-related information sharing, go to http://www.nature.com/articles/srep22491.

Meshi, D., Mamerow, L., Kirilina, E., Morawetz, C., Margulies, D.S., & Heekeren, H.R. (2016). Sharing self-related information is associated with intrinsic functional connectivity of cortical midline brain regions. Scientific Reports, 6, 22491. DOI: 10.1038/srep22491

Rani Moran

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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.