Positive intergroup contact modulates fusiform gyrus activity to black and white faces.

In this study, we investigated the effect of intergroup contact on processing of own- and other-race faces using functional Magnetic Resonance Imaging (fMRI). Previous studies have shown a neural own-race effect with greater BOLD response to own race compared to other race faces. In our study, white participants completed a social-categorization task and an individuation task while viewing the faces of both black and white strangers after having answered questions about their previous experiences with black people. We found that positive contact modulated BOLD activity in the right fusiform gyrus (rFG) and left inferior occipital gyrus (lIOC), regions associated with face processing. Within these regions, higher positive contact was associated with higher activity when processing black, compared to white faces during the social categorisation task. We also found that in both regions a greater amount of individuating experience with black people was associated with greater activation for black vs. white faces in the individuation task. Quantity of contact, implicit racial bias and negatively valenced contact showed no effects. Our findings suggest that positive contact and individuating experience directly modulate processing of out-group faces in the visual cortex, and illustrate that contact quality rather than mere familiarity is an important factor in reducing the own race face effect

Endogenous games and mechanisms: Side payments among players

We characterize the outcomes of games when players may make binding offers of strategy contingent side payments before the game is played. This does not always lead to efficient outcomes, despite complete information and costless contracting. The characterizations are illustrated in a series of examples, including voluntary contribution public good games, Cournot and Bertrand oligopoly, principal–agent problems, and commons games, among others

Modeling Brain Resonance Phenomena Using a Neural Mass Model

Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect

What’s retinoic acid got to do with it? Retinoic acid regulation of the neural crest in craniofacial and ocular development

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151310/1/dvg23308.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151310/2/dvg23308_am.pd

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)