Research

Sequential effects in cognitive psychology: Same but different?

Description:

We are faster at finding the same object in two different searches than at finding two different objects (for example, when playing Dobble). We are also faster when performing the same task twice in a row than when switching tasks. What do these phenomena have in common? Do they share something, or do they occur merely by coincidence?

Sequence effects appear in various experimental paradigms in cognitive psychology, such as visual search (Found & Müller, 1996), two-choice tasks (Soetens et al., 1985), interference tasks (Gratton et al., 1992), or task switching (Jersild, 1927). Although these quite different paradigms produce the same behavioral effects—namely, faster reaction times and fewer errors in repetitions compared to alternations—it remains largely unexplored which mechanisms these paradigms truly share. Are there common mechanisms that ensure sequence effects occur across all paradigms? Answering this is the goal of the present project.

Team:

Anne Voormann, DFG VO, in cooperation with Jeff Miller, Otago University

Funding:

DFG

References:

• Found, A., & Müller, H. J. (1996). Searching for unknown feature targets on more than one dimension: Investigating a “dimension-weighting” account. Perception & Psychophysics, 58(1), 88–101. https://doi.org/10.3758/BF03205479
• Gratton, G., Coles, M. G. H., & Donchin, E. (1992). Optimizing the use of information: Strategic control of activation of responses. Journal of Experimental Psychology: General, 121(4), 480–506. https://doi.org/10.1037/0096-3445.121.4.480
• Jersild, A. T. (1927). Mental set and shift. Archives of Psychology, Whole No. 89. https://archive.org/details/mentalsetshift00jers/page/16/mode/2up?ref=ol&view=theater
• Soetens, E., Boer, L. C., & Hueting, J. E. (1985). Expectancy or automatic facilitation? Separating sequential effects in two-choice reaction time. Journal of Experimental Psychology: Human Perception and Performance, 11(5), 598–616. https://doi.org/10.1037/0096-1523.11.5.598

The influence of experienced hand-arm vibrations on our cognitive performance

Description:

When using many power tools (e.g., rotary hammers, angle grinders, etc.), users are exposed to hand-arm vibrations that vary in frequency and intensity, thereby affecting perceived vibration comfort and discomfort (Hägele, 2023). At the same time, however, such situations also impose high cognitive demands—for example, on attention—to avoid both material damage and injuries.

While vibration discomfort has been frequently studied and attempts made to reduce it in technical contexts (e.g., through handle adjustments), the effects of experienced hand-arm vibrations on cognitive task performance have scarcely been investigated (for an initial study on bus drivers, see Rahmani et al., 2021). The goal of this project is, therefore, to examine more closely how experienced hand-arm vibrations influence our cognition (attention, cognitive control).

Team:

Anne Voormann, Andrea Kiesel, in cooperation with Andreas Lindenmann, Sven Matthiesen, IPEK, KIT

References:

• Rahmani, R., Aliabadi, M., Golmohammadi, R., Babamiri, M., & Farhadian, M. (2021). Evaluation of Cognitive Performance of City Bus Drivers with Respect to Noise and Vibration Exposure. Acoustics Australia, 49(3), 529–539. https://doi.org/10.1007/s40857-021-00248-z
• Hägele, D. (2023). Vibrations(dis)komfort von Power-Tools – der Einfluss von Personenvariablen und Studienumgebung [nicht publizierte Masterarbeit]. Albert-Ludwigs-Universität Freiburg.

Predicting Attitudes and Behaviors Toward Living Materials: Assessing the Reliability of the CAM Method as a Measurement Tool

Description:

In this research project, we aim to examine the CAM method from a methodological perspective, focusing on reliability as one of the key classical quality criteria in psychological test construction. In an initial study, we applied a classical approach to assess test-retest reliability by measuring a stable psychological construct twice. Subsequent studies will investigate (1) how CAM can best be implemented to achieve high reliability, and (2) the level of CAM reliability in group settings. The overarching goal is to strengthen CAM research through a better understanding of its reliability and to provide a robust tool for assessing the acceptance of living materials systems.

Team:

Wilhelm Gros, Andrea Kiesel, Michael Stumpf, Oliver Müller

Programme:

Exzellenzcluster Living, Adaptive and Energy-autonomous Materials Systems livMatS

Timescale:

8/2022 – 7/2025

Assessing Emerging Technologies: Ethical and Societal Perspectives

Description:

This project develops and applies innovative methods to evaluate the ethical and societal dimensions of emerging technologies—particularly lifelike materials systems. Key methodological tools include:

• CAM-EL (Cognitive-Affective Maps Extended Logic):
  A software tool for visualizing and analyzing belief systems that captures both emotional and cognitive evaluations. CAM-EL enables the identification of perceived trust, risks/benefits, and argumentation structures related to technologies such as materials systems and soft robotics. Recent advancements integrate large language models (LLMs) to partially automate data analysis. For more details, visit our website: https://drawyourminds.de/ .
• ESTA (Ethics Scale for Technology Assessment):
  A theory-based, empirically validated survey instrument for measuring the moral acceptability of emerging technologies, grounded in diverse ethical frameworks (e.g., deontology, utilitarianism, virtue ethics, contractualism, relativism, hedonism). ESTA facilitates ethical evaluations across different stakeholder groups and supports the implementation of “real-time ethics.”

Overarching Goal:
The development and application of CAM-EL, ESTA, and related methods are based on an integrated approach to empirical ethics that bridges normative theory with empirical research. This interdisciplinary framework—drawing from philosophy, psychology, and sustainability science—enables context-sensitive, participatory, and responsive assessments of emerging technologies.

Team:

Julius Fenn, Michael Gorki, Wilhelm Gros, PI: Andrea Kiesel

Programme:

Exzellenzcluster Living, Adaptive and Energy-autonomous Materials Systems livMatS

Cognitive-Motor Interference in Aging

Description:

With an interdisciplinary background spanning cognitive psychology, computer science, and human factors, my research examines the unconscious modulation of cognitive processes and the age-related decline in executive functions.

Currently, I am analyzing a large-scale geriatric database with a focus on cognitive-motor dual-task performance in older adults. This research is conducted in close collaboration with an interdisciplinary team of psychologists, sports scientists, and gerontologists, integrating task performance data with spatiotemporal gait parameters and clinical diagnoses.

This multi-perspective approach enables a differentiated retrospective analysis of risk factors for falls in later life. The ultimate goal is to develop complex statistical models to better understand the interplay between cognitive-motor dual-task performance, postural control, and fall risk.

Team:

Tian Zhou, Elisa Straub, Andrea Kiesel, in cooperation with Dominic Gehring, Urs Granacher, Aaron Haslbauer, Reto Kressig and Roland Rössler

Programme:

Statistical Modeling in Psychology (SMiP)

Resource Allocation in Young Adults During the Timed Up-and-Go Test Under Dual-Task Conditions

Description:

The Timed Up-and-Go (TUG) test is an ecologically valid clinical assessment frequently used to evaluate overall mobility in older adults. In clinical practice, the TUG is often combined with an additional cognitive task—particularly in the context of movement-based therapeutic interventions. However, comparable studies focusing on younger adults remain scarce.

The aim of our investigation is to analyze how young adults allocate their attentional resources under varying levels of difficulty within this experimental paradigm. Furthermore, we examine the extent to which functional reserve and metacognitive abilities influence their performance under dual-task conditions, as well as their choice of strategies.

Team:

Tian Zhou, Elisa Straub, Andrea Kiesel, in cooperation with Dominic Gehring, Urs Granacher, Aaron Haslbauer, Reto Kressig and Roland Rössler

Programme:

Statistical Modeling in Psychology (SMiP)

Cognitive Modeling of Weight Bias

Description:

This project aims to analyze the cognitive processes underlying implicit weight bias—that is, unconscious negative attitudes toward individuals with overweight or obesity—and, based on these insights, identify potential intervention points for anti-bias measures. Our methodological approach integrates experimental paradigms with advanced statistical modeling, specifically hierarchical Bayesian methods.

First, we employ the drift-diffusion model (DDM) to dissect the core cognitive mechanisms of implicit bias. The subsequent phase focuses on interindividual differences in the direction and magnitude of bias. Using hierarchical Bayesian cluster analysis, we will identify distinct bias profiles and predict their occurrence based on factors such as demographic characteristics or explicit attitudes.

Team:

Katja Pollak, Andrea Kiesel, Raphael Hartmann, Julius Fenn, in cooperation with Hanna Wachten, Jana Strahler, Constantin Meyer-Grant, Veronika Lerche

Timescale:

10/2021 – Middle of 2026

Cognitive-motor interference

Description:

We often find ourselves in situations where we have to do several things at once—like answering a difficult question while walking down a crowded staircase. These multitasking moments demand more from our mental resources and can actually affect how we move and keep our balance.

In our research, we’re looking at how cognitive and emotional factors—such as mental conflict or emotional distractions—influence our ability to stay balanced. Participants stand on a force plate that detects even the smallest shifts in stability.

Our goal is to better understand how thinking, feeling, and balance interact, and to use these insights to develop targeted training and preventive strategies—especially for people who are at higher risk of balance problems or falls.

Funding:

DFG Grant No. KI 1388/11-1, collaboration project with Leif Johannsen and Iring Koch (RWTH Aachen) and Hermann Müller (University Giessen)

Software:

R package forceplate

Team:

Elisa Straub und Andrea Kiesel, in Kooperation with Leif Johannsen and Anton Koger

Generalizability of cognitive control

Description:

In everyday life, we must regulate impulsive reactions and quickly adapt to changing demands. Emotional information can interfere in this process—sometimes enhancing performance, but often impairing it. Cognitive control helps us stay focused, manage distractions, and flexibly adjust our behavior to new situations.

In our research, we investigate how different forms of cognitive control interact—specifically, how control in one task can influence responses in another, unrelated task, and how cognitive control operates in emotional contexts.

Our goal is to better understand whether cognitive control is limited to specific tasks or reflects a more general mental state that influences behavior across diverse situations.

Team:

Elisa Straub and Andrea Kiesel, in cooperation with Eldad Keha and David Dignath

Temporal expectations across sensory modalities

Description:

The anticipation of specific events at particular moments—referred to as time-based expectancy (TBE)—represents a core cognitive mechanism that facilitates efficient perception and goal-directed action (Nobre & van Ede, 2018; Thomaschke & Dreisbach, 2015). While TBE has been extensively studied in the visual domain, its manifestation in other sensory modalities, such as tactile and auditory perception, remains comparatively underexplored (Ball et al., 2018). Furthermore, it is largely unclear to what extent TBE supports performance under cognitively demanding conditions that require concurrent processing of multiple tasks and high cognitive flexibility.

This project addresses this research gap by investigating how time-event contingencies are learned in tactile and auditory contexts, and whether such predictive processing mechanisms remain beneficial under dual-task conditions. The aim is to gain a deeper understanding of how the cognitive system leverages temporal structures to optimize behavior across different modalities and levels of task demand.

Team:

Alejandra Rodríguez-Velásquez, Andrea Kiesel and Roland Thomaschke

Funding:

DFG, Grant No. TH 1554/3-2, Priority Program (SPP 1772) Multitasking

Impact of Non-Contingent Rewards on Cognitive Functioning

Description:

The role of incentives in shaping cognitive processes and decision-making is a central topic in both economics and psychology. Inspired by my collaboration with the Freiburg Institute for Basic Income Studies (FRIBIS), my dissertation project specifically examines the effects of performance-independent compensation compared to performance-contingent compensation. My primary interest lies in their differential impacts on cognitive processes.

In a first step, the project aims to conduct a comprehensive review of the existing literature to establish a robust foundation for subsequent empirical investigations. This step will also help validate the proxy chosen within the FRIBIS collaboration—performance-independent rewards—as a meaningful experimental approximation of complex constructs, in this case, universal basic income.

Building on insights from the literature, which suggest that performance-independent rewards may influence cognitive mechanisms differently than performance-contingent incentives, I am developing—together with other researchers—a series of experimental studies. These investigations will employ the self-organized task-switching paradigm, first introduced by Mittelstädt et al. (2018), which allows for the observation and nuanced analysis of individual decision-making processes within a flexible yet controlled context.

Through this work, I aim not only to contribute to the current debate on the mechanisms underlying different compensation schemes but also to highlight the potential of cognitive psychological research to inform seemingly distant fields of study—a potential that can deepen our understanding of human behavior more broadly.

Team:

Larissa Walter, Irina Monno, Anne Voormann, Andrea Kiesel

Zeitrahmen:

Middle of 2021- Middle of 2026

Programme:

Freiburg Institute for Basic Income Studies (FRIBIS)

Investigation of Computer-Based Programs and Non-Digital Techniques for Enhancing Cognitive Functions and Validation of Executive Function Measurement Reliability

Description:

One aim of this project is to synthesize the existing literature on computer-based and non-digital cognitive training programs through a comprehensive meta-analysis, evaluating their efficacy in enhancing executive functions (EFs) in healthy individuals. The analysis will focus on both near- and far-transfer effects, examining impacts on tasks measuring lower-level executive functions (e.g., working memory) as well as higher-order domains (e.g., problem-solving).

Additionally, we will analyze how various factors—such as training schedule, type of control group, participant age, and task characteristics—influence intervention outcomes.

In a subsequent phase, the meta-analysis findings will be further investigated through a randomized controlled trial with a healthy adult sample. The project will also evaluate the test-retest reliability of several widely used executive function assessment tasks to ensure the robustness of outcome measurements. Finally, we will examine a broad range of alternative and indirect approaches to enhancing executive functions, including meditation, physical activity, martial arts, breathing exercises, and other methods.

Key Research Themes:

• Meta-analysis of transfer effects on executive functions following digital and non-digital cognitive training
• Study on test-retest reliability of EF assessment tasks
• Randomized controlled trial with healthy adults
• Systematic investigation of implicit methods for cognitive enhancement

Timescale:

2024–2027

Funding:

German National Academic Foundation

Team:

Anastasiia Perevoznikova and Andrea Kiesel

Self-organized task switching, Balancing switch costs; Reinforcement-learning model, selective- influence assumption

Description:

In this project we want to better understand the interplay of decision regarding task switching or repetition and performance in the execution of tasks in voluntary task switching. Based on experimental research and cognitive modeling of voluntary task switching, we investigate how decisions affect task performance and how task performance (in terms of expected effort) influences future (task) decision processes. To elicit strategic task decisions, we apply the paradigm of self-organized task switching (Mittelstädt, et al., 2018), in which participants have to weigh their switch costs against experimentally induced waiting times. To model task decisions, we propose a reinforcement learning (RL) model that describes the processes involved in task-switching decisions at the algorithmic level and represents a measurement model that makes it possible to evaluate the contributions of the processes involved more validly and purely than is possible with ad hoc indices (such as switch SOA, switch rates, reaction time switch costs). These modeling goals require i) demonstrating the model’s ability to describe the data well and better than alternative and simpler models, as well as ii) demonstrating the stability of the model parameters and – with the help of selective influence studies and correlational relationships – their construct validity.

To achieve these goals, work packages are planned for the formal development of the model (WP 1), for evaluating the test-retest stability of indices of task-switch performance and the model parameters (WP 2) and for empirical validation of the model and its parameters by means of selective influence studies (WP3 – WP5). Finally, we want to expand the validated model to take errors into account, to model switches between tasks with different levels of difficulty, and, in collaboration with other projects in the research group, to explain data from related paradigms.

Funding:

DFG Grant No. KI 1388/12-1, Research Unit 6047 Voluntary task switching: Cognitive processes and models to account for task choices

Keywords:

Self-organized task switching, weighing of switch costs; reinforcement learning model, hypothesis of selective influence

In our behavioral laboratories, we measure task performance in terms of accuracy and response speed. For example, we investigate how well people can multitask by analyzing participants’ reaction times and error rates when they have to switch back and forth between different tasks.

Cognitive-Affective Maps (CAMs) are an innovative tool for capturing and representing individual attitudes, beliefs, and feelings. They visualize how people think about certain topics – and, most importantly, how they feel about them. CAMs consist of concepts (e.g., “climate change,” “car,” “freedom”) represented as colored shapes. The color and shape indicate whether the concept is perceived as positive, negative, neutral, or ambivalent. The strength of the emotional evaluation is represented by the thickness of the lines. Concepts are connected by lines that indicate supporting (solid line) or inhibiting (dashed line) relationships. Unlike traditional mind maps, CAMs not only capture thoughts but combine them with emotional evaluations – that is, how pleasant or unpleasant certain ideas are perceived.

Electroencephalography (EEG) is a method known for its high temporal resolution. It allows for the continuous recording of electrical activity on the scalp, which is generated by brain activity. Certain functional states of the brain can be associated with characteristic EEG patterns, either through the analysis of so-called event-related potentials (ERPs) or through oscillatory patterns of neural activity captured by EEG. Both ERPs and oscillations can be used to study brain activity and to better understand how our brain processes information under specific conditions. In our lab, we use EEG to investigate how the human brain organizes itself when confronted with various cognitive tasks.

An eye tracker is a device that uses infrared light to determine the position of the eye. This method is useful for studying where a person is focusing their gaze (fixations) or where their eyes are moving (saccades). Fixations and saccades can be used as a measure of attention processes, for example. In addition, eye tracking can be used to measure pupil dilation – an indicator that can signal, among other things, surprise, cognitive load, or arousal. In our lab, we are currently investigating anticipatory processes during goal-directed actions through eye movement measurements.

Force plates are highly precise measurement instruments used in biomechanics, movement research, and sports science to capture the forces acting between the body and the ground. They measure parameters such as ground reaction force, torque, and the position of the center of mass. These data provide insights into stance stability, balance control, and individual components of movement sequences. Force plates enable researchers to detect and analyze even the smallest fluctuations in balance while participants simultaneously perform cognitive tasks. By using cognitive tasks, the influence of cognitive processes on postural control (balance) can be studied.

Using event-related analyses, postural measures (e.g., balance fluctuations) are examined during brief time intervals corresponding to cognitive events (e.g., 100 ms after stimulus onset or after the participant’s response to the stimulus) – similar to the analysis of event-related potentials in EEG. For the preparation of raw data for event-related analysis, we use the R package “forceplate.”

Online surveys are an efficient tool for quick and uncomplicated data collection. Since responses can be given independently of space and time, they allow for the collection of large national and international datasets. Unlike paper-and-pencil surveys, online data collection can also be continuously monitored. This ensures that the data is automatically transferred to statistical programs, reducing input errors. Online surveys can be used to analyze public opinion on a variety of issues.

In our lab we use SoSci Survey.

The vibration plate is a small device built for us by KIT, in which a speaker generates vibrations that are transferred to the hands via a 13×13 cm recessed plate. With this plate, we aim to investigate the impact of hand-arm vibrations on cognition.