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The neural networks of subjectively evaluated emotional conflicts.

ABSTRACT: Previous work on the neural underpinnings of emotional conflict processing has largely focused on designs that instruct participants to ignore a distracter which conflicts with a target. In contrast, this study investigated the noninstructed experience and evaluation of an emotional conflict, where positive or negative cues can be subjectively prioritized. To this end, healthy participants freely watched short film scenes that evoked emotional conflicts while their BOLD responses were measured. Participants' individual ratings of conflict and valence perception during the film scenes were collected immediately afterwards, and the individual ratings were regressed against the BOLD data. Our analyses revealed that (a) amygdala and medial prefrontal cortex were significantly involved in prioritizing positive or negative cues, but not in subjective evaluations of conflict per se, and (b) superior temporal sulcus (STS) and inferior parietal lobule (IPL), which have been implicated in social cognition and emotion control, were involved in both prioritizing positive or negative cues and subjectively evaluating conflict, and may thus constitute "hubs" or "switches" in emotional conflict processing. Psychophysiological interaction (PPI) analyses further revealed stronger functional connectivity between IPL and ventral prefrontal-medial parietal areas in prioritizing negative cues, and stronger connectivity between STS and dorsal-rostral prefrontal-medial parietal areas in prioritizing positive cues. In sum, our results suggest that IPL and STS are important in the subjective evaluation of complex conflicts and influence valence prioritization via prefrontal and parietal control centers. Hum Brain Mapp 37:2234-2246, 2016. © 2016 Wiley Periodicals, Inc.

SUBMITTER: Rohr CS

PROVIDER: S-EPMC6867502 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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The neural networks of subjectively evaluated emotional conflicts.

Rohr Christiane S CS Villringer Arno A Solms-Baruth Carolina C van der Meer Elke E Margulies Daniel S DS Okon-Singer Hadas H

Human brain mapping 20160316 6

Previous work on the neural underpinnings of emotional conflict processing has largely focused on designs that instruct participants to ignore a distracter which conflicts with a target. In contrast, this study investigated the noninstructed experience and evaluation of an emotional conflict, where positive or negative cues can be subjectively prioritized. To this end, healthy participants freely watched short film scenes that evoked emotional conflicts while their BOLD responses were measured. ...[more]

PMID: 26991156

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Project description:Objective: Conflicts of interests resulting from interactions with pharmaceutical companies are pervasive in medicine and can result in an undue influence on physicians' decision-making. The objective of this systematic review is to analyze published and scientifically evaluated curricula for medical students and residents regarding such conflicts of interest. We begin by describing the covered topics and teaching methods; afterwards we analyze the quality of the curricula using the published data on their evaluations and comparing the content with content recommended for such curricula. Methods: We searched Pubmed, PsycInfo, EMBASE, OECD, WISO, SOWI and googlescholar up to and including the 5th of September 2016. Publications describing curricula for residents or medical students on the topic of conflicts of interest in medicine and evaluating them for their effects on the participants' learning were included. We analyzed the covered topics and the teaching methods used and compared them with recommendations by the American Medical Students' Association (AMSA) and Health Action International (HAI). Results: The literature search resulted in 20 publications that fulfilled our search criteria. In five trials, a control group was used, in no trial the participants were randomized to intervention or control group. 16/20 published curricula primarily covered marketing strategies by pharmaceutical companies, especially the interaction with pharmaceutical sales representatives (PSRs). Most curricula only covered a limited number of topics recommended by AMSA/HAI. The most frequent teaching method was a group discussion, which was used in 18/20 curricula; all curricula used at least one interactive teaching method. The evaluation of the curricula was heterogeneous in results as well as design. Some publications described a change of attitudes toward a stronger skepticism regarding interactions with pharmaceutical companies. Four publications described improved knowledge, one publication described a change in behavior toward a reduction of the acceptance of gifts. Conclusion: The trials conducted to this date regarding curricula on conflicts of interests are methodologically flawed and the described curricula lack important topics beyond marketing strategies of pharmaceutical companies. In addition, there are no data so far on the sustainability of the courses' effects on participants' behavior. It is therefore necessary to develop a model curriculum that covers a broader variety of topics and to evaluate it using a well thought-out methodology to create a foundation for the further improvement of teaching conflicts of interest in medicine.

Project description:The proportion of individuals with depression has rapidly increased along with the growth of the global population. Depression has been the currently most prevalent mental health disorder. An effective depression recognition system is especially crucial for the early detection of potential depression risk. A depression-related dataset is also critical while evaluating the system for depression or potential depression risk detection. Due to the sensitive nature of clinical data, availability and scale of such datasets are scarce. To our knowledge, there are few extensively practical depression datasets for the Chinese population. In this study, we first create a large-scale dataset by asking subjects to perform five mood-elicitation tasks. After each task, subjects' audio and video are collected, including 3D information (depth information) of facial expressions via a Kinect. The constructed dataset is from a real environment, i.e., several psychiatric hospitals, and has a specific scale. Then we propose a novel approach for potential depression risk recognition based on two kinds of different deep belief network (DBN) models. One model extracts 2D appearance features from facial images collected by an optical camera, while the other model extracts 3D dynamic features from 3D facial points collected by a Kinect. The final decision result comes from the combination of the two models. Finally, we evaluate all proposed deep models on our built dataset. The experimental results demonstrate that (1) our proposed method is able to identify patients with potential depression risk; (2) the recognition performance of combined 2D and 3D features model outperforms using either 2D or 3D features model only; (3) the performance of depression recognition is higher in the positive and negative emotional stimulus, and females' recognition rate is generally higher than that for males. Meanwhile, we compare the performance with other methods on the same dataset. The experimental results show that our integrated 2D and 3D features DBN is more reasonable and universal than other methods, and the experimental paradigm designed for depression is reasonable and practical.

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The neural networks of subjectively evaluated emotional conflicts.

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The neural networks of subjectively evaluated emotional conflicts.

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