Distinct Brain Mechanisms for Conflict Adaptation within and across Conflict Types

Cognitive conflict, like other cognitive processes, shows the characteristic of adaptation, that is, conflict effects are attenuated when immediately following a conflicting event, a phenomenon known as the conflict adaptation effect (CAE). One important aspect of CAE is its sensitivity to the intertrial coherence of conflict type, that is, behavioral CAE occurs only if consecutive trials are of the same conflict type. Although reliably observed behaviorally, the neural mechanisms underlying such a phenomenon remains elusive. With a paradigm combining the classic Simon task and Stroop task, this fMRI study examined neural correlates of conflict adaptation both within and across conflict types. The results revealed that when the conflict type repeated (but not when it alternated), the CAE-like neural activations were observed in dorsal ACC, inferior frontal gyrus (IFG), superior parietal lobe, and so forth (i.e., regions within typical task-positive networks). In contrast, when the conflict type alternated (but not when it repeated), we found CAE-like neural deactivations in the left superior frontal gyri (i.e., a region within the typical task-negative network). Network analyses suggested that the regions of ACC, IFG, superior parietal lobe, and superior frontal gyrus can be clustered into two antagonistic networks, and the ACC–IFG connection was associated with the within-type CAE. This evidence suggests that our adaptation to cognitive conflicts within a conflict type and across different types may rely on these two distinct neural mechanisms.

Exploring the Impact of Emotional Intelligence on Family Farm Member Conflict Experiences

Family farm sustainability traditionally focuses on economic and environmental issues. However, sustaining family farms also relies on understanding how to sustain the relationships contained therein. Emotional intelligence (EI) is an important means through which family farm members can sustain relationships, especially when handing conflict between members. This paper focused on how four EI dimensions (awareness of own emotion, management of own emotion, awareness of others’ emotions, management of others’ emotions) could prevent four types of conflict within family farms (task, relational, process, and status). Family farm participants (N = 204) were recruited through social media posts and emails to specialty agricultural groups and agencies, and students at a university. Hierarchical regression results showed that awareness of own emotions, management of own emotions, and management of others’ emotions negatively predicted task, relational, process, and status conflict. Awareness of others’ emotions did not predict any conflict types. Theoretically, this article points to the importance of considering all four EI dimensions, since they impact conflict types differently. For the family farm members, being aware of their own emotions and being able to manage emotional responses in themselves and others can help prevent conflict from occurring, thereby sustaining both family and business relationships for the future.

Distinct Brain Mechanisms for Conflict Adaptation Within and Across Conflict Types

Cognitive conflict, like other cognitive processes, shows the characteristic of adaptation, i.e., conflict effects are attenuated when immediately following a conflicting event, a phenomenon known as the conflict adaptation effect (CAE). One important aspect of CAE is its sensitivity to the intertrial coherence of conflict type, i.e., behavioral CAE occurs only if consecutive trials are of the same conflict type. Although reliably observed behaviorally, the neural mechanisms underlying such a phenomenon remains elusive. With a paradigm combining the classic Simon task and Stroop task, this fMRI study examined neural correlates of conflict adaptation both within and across conflict types. The results revealed that when the conflict type repeated (but not when it alternated), the CAE-like neural activations were observed in dorsal anterior cingulate cortex, inferior frontal gyrus, superior parietal lobe, etc. (i.e., regions within typical task-positive networks). In contrast, when the conflict type alternated (but not when it repeated), we found CAE-like neural deactivations in a range of regions including bilateral superior and medial frontal gyri, bilateral angular cortex, bilateral temporal cortices, etc. (i.e., regions within the typical task-negative network). Moreover, this CAE-like neural deactivation predicts behavior performance. Network analyses suggested that these regions (for CAE-like neural activities within and across conflict type[s] respectively) can be clustered into two antagonistic networks. This evidence suggests that our adaptation to cognitive conflicts within a conflict type and across different types may rely on these two distinct neural mechanisms.

Mapping the common and distinct neural correlates of visual, rule and motor conflict

Flexible behaviour requires cognitive-control mechanisms to efficiently resolve conflict between competing information and alternative actions. Whether a global neural resource mediates all forms of conflict or this is achieved within domainspecific systems remains debated. We use a novel fMRI paradigm to orthogonally manipulate rule, response and stimulus-based conflict within a full-factorial design. Whole-brain voxelwise analyses show that activation patterns associated with these conflict types are distinct but partially overlapping within Multiple Demand Cortex (MDC), the brain regions that are most commonly active during cognitive tasks. Region of interest analysis shows that most MDC sub-regions are activated for all conflict types, but to significantly varying levels. We propose that conflict resolution is an emergent property of distributed brain networks, the functional-anatomical components of which place on a continuous, not categorical, scale from domain-specialised to domain general. MDC brain regions place towards one end of that scale but display considerable functional heterogeneity.

TRAFFIC CONFLICT IDENTIFICATION OF E-BIKES AT SIGNALIZED INTERSECTIONS

The increase of e-bikes has raised traffic conflict concerns over past decade. Numerous conflict indicators are applied to measure traffic conflicts by detecting differences in temporal or spatial proximity between users. However, for traffic environment with plenty of e-bikes, these separate space-time approaching indicators may not be applicable. Thus, this study aims to propose a multi-variable conflict indicator and build a conflict identification method for e-bikes moving in the same direction. In particular, by analysing the conflict characteristics from e-bikes trajectories, a multi-variable conflict indicator utilizing change of forecast post encroachment time, change of relative speed and change of distance is derived. Mathematical statistics and cluster discriminant analyses are applied to identify types of conflict, including conflict existence identification and conflict severity identification. The experimental results show: in mixed traffic environments with many e-bikes, compared with time-to-collision and deceleration, accuracy of identifying e-bike conflict types based on proposed method is the highest and can reach more than 90%; that is, multi-variable indicator based on time and space are more suitable for identifying e-bike conflicts than separate space-time approaching indicators. Furthermore, setting of dividing strip between motor vehicle and non-motorized vehicle has significant influence on number and change trend of conflict types. The proposed method can not only provide a theoretical basis and technical support for automated conflict detection in mixed transportation, but also give the safety optimization sequence of e-bikes at different types of intersections.

Conflict Types in Hungarian Film History

The article introduces the collective research project entitled The Social History of Hungarian Cinema, 1931–2015, executed by the staff of Film Studies Department Eötvös Loránd University. This data-driven research aims to examine how and why Hungarian films have changed over time. Using the case study of conflict types in the plots of Hungarian films this study discusses the methodological problems of longitudinal explanations of change in Hungarian film history (periodization and dividing film between genre-based film and auteur films/art cinema). Based on the analysis of statistics and trends, the study presents the most important types of conflict in Hungarian film history. With respect to the political turning points and the periodization of Hungarian film history, the article states that each of the three broad periods (1931–1944, 1945–1989, 1990–2015) is characterized by its own distinctive set of prominent conflict types. The pre-1945 era is characterized by a massive number of love conflicts, the socialist period by the highest rate of political conflicts (and the lowest rates of love and crime conflicts), and the post-socialist period by a high rate of crime and generational conflicts. Furthermore, by analysing the connections between conflict types and genres, the study reveals recurring patterns and trends of shorter periods: it shows how the range of conflicts narrowed considerably over the 1970s and discusses the extent to which this is related to the dominance of auteur films in the era.