The Role of Expectations and Habitual Emotion Regulation in Emotional Processing: An ERP Investigation

Available evidence from separate lines of event-related potential (ERP) research has highlighted the role of expectations and emotion regulation on emotional processing by revealing that (i) expectations can alter emotional responses, and (ii) the instructed use of emotion regulation strategies may modulate emotional responses. Yet, little is known about the interplay between expectations and habitual emotion regulation strategies prior to and at the onset of an emotional event. The present study aimed to investigate this potential relationship. Participants completed an affective-cueing task consisting of cues (red squares and blue circles) signaling the likely valence of upcoming target images (negative or neutral). This task allowed us to examine the impact of expectations at 2 temporal stages, Cue Interval and Target Interval, by measuring the late positive potential (LPP) as an index of emotional processing. Habitual use of emotion regulation strategies was assessed through the Emotion Regulation Questionnaire (ERQ), which measures the use of cognitive reappraisal and expressive suppression in everyday life. In the Cue Interval, LPP amplitude was greater for negative versus neutral cues (p < .001). In the Target Interval, LPP amplitude was greater for negatively cued versus neutrally cued targets, regardless of target valence (p = .003). ERQ reappraisal, but not suppression, negatively correlated with LPP modulation as a function of cue valence during both intervals (ps < .05). These findings provide novel insights regarding the interplay between expectations and habitual emotion regulation in emotional processing both prior to and at the onset of an emotional event

Attenuated Face Processing during Mind Wandering

Mind wandering (MW) has been recently investigated in many studies. It has been suggested that, during MW, processing of perceptual stimuli is attenuated in favor of internal thoughts, a phenomenon referred to as perceptual decoupling. Perceptual decoupling has been investigated in ERP studies, which have used relatively simple perceptual stimuli, yet it remains unclear if MW can impact the perceptual processing of complex stimuli with real-world relevance. Here, we investigated the impact of MW on behavioral and neural responses to faces. Thirty-six participants completed a novel sustained attention to response task with faces. They were asked to respond to upright faces (nontargets) and withhold responses to inverted faces (targets) and to report intermittently if they were “On task” or “Off task.” Behavioral analyses revealed greater intraindividual coefficient of variation for nontarget faces preceding Off task versus On task. ERP analyses focused primarily on the N170 component associated with face processing but also included the P1 and P3 components. The results revealed attenuated amplitudes to nontarget faces preceding Off task versus On task for the N170, but not for the P3 or P1. These findings suggest decoupled visual processing of faces during MW, which has implications for social neuroscience research

Variability in the analysis of a single neuroimaging dataset by many teams

: Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de PsicologíaTRUEpu