Abstracts of latest lectures

Assist. Prof. Dr. Gijs Bijlstra (Radboud University, Nijmegen, the Netherlands)

Abstract: Biased perception has a profound effect on our judgments and behavior. Although in many cases the expectations we have about the world hold predictive value, sometimes they may lead to discriminatory behavior with detrimental consequences. In the Radboud Social Cognition lab, we study (I) the fundamental processes involved and (II) aim to develop and test interventions to reduce discrimination, stimulate diversity and inclusion. In this presentation, I will outline the various perspectives we study, with a strong focus on how the expectations we hold affect person perception. That is, I will provide an overview of ongoing research in our lab and present a series of studies on how prejudices and stereotypes influence emotion perception. Finally, I will discuss our most recent studies on whether group associations can be modified using reinforcement learning strategies, and whether this is reflected in the perception of emotions.

Assoc. Prof. Dr. Ilka Gleibs (London School of Economics and Political Science)

Abstract: The current global landscape, shaped by the Covid-19 pandemic, ongoing conflicts, economic challenges, and climate threats, underscores a period of mulple crises. Effective crisis management requires adept leadership, particularly in guiding societal responses and alleviating emotional distress associated with crises (Goldman et al., 2014; Leung et al., 2022). Social identity theory, rooted in the understanding of group memberships and their significance, provides valuable insights into crisis leadership (Haslam et al., 2022). In times of crisis, leaders must cultivate shared group identities among citizens to foster collective engagement and responsibility (Haslam et al., 2020). This shared identity is crucial for promoting adherence to crisis mitigation measures and fostering adaptability among populations (van Bavel et al., 2022). Based on our previous work around the Ukraine war (Gleibs, Bachmann & Rüsch, 2024) and during the Covid-19 crisis (Gleibs, Mühlemann, & Heliot, 2024), we develop a model of social identity leadership for crisis. This examines how crisis management hinges on understanding social psychological theories of leadership that emphasizes the importance of collective responses and shared identities in navigating crises. Thus, effective crisis leadership faces challenges in maintaining inclusivity and sustainability over time and leaders must navigate fault lines and diverse realities sensitively to sustain collective identities and promote collective action. Continued research and adaptive leadership strategies are essential for addressing the multifaceted challenges.

Abstract: Perception with new sensory signals

Prof. Dr. Marko Nardini, Department of Psychology, Durham University, Durham, UK

I will begin by describing recent research taking a new, model-based approach to perceptual development. This approach uncovers fundamental changes in information processing underlying the protracted development of perception, action, and decision-making in childhood. For example, the operation of reliability-weighted averaging – widely used by adults to improve perception – is often not used until surprisingly late into childhood, as assessed by both behaviour and neural representations. This approach forms the basis for a newer question: the scope for the nervous system to deploy useful computations (e.g. reliability-weighted averaging) to optimise perception and action using newly-learned sensory signals provided by technology. Our initial model system is augmenting visual depth perception with devices translating distance into auditory or vibro-tactile signals. This problem has immediate applications to people with partial vision loss, but the broader question concerns our scope to use technology to tune in to any signal not available to our native biological receptors. I will describe initial progress on this problem, and our approach to operationalising what it might mean to adopt a new signal comparably to a native sense. This will include testing for its participation in reliability-weighted averaging alongside the native senses, assessing the level at which this averaging happens in the brain, and measuring the degree of ‘automaticity’ with which it is used, compared with native perception.