Prior multisensory learning can facilitate auditory-only voice-identity and speech recognition in noise

We thank Laura Smith for her work on the project including data collection and preparation. We also thank Nicola Frasson for help with additional data collection and Juliane Liebsch for supporting data analysisPeer reviewe

Lost to translation: How design factors of the mouse-tracking procedure impact the inference from action to cognition

From an embodiment perspective, action and cognition influence each other constantly. This interaction has been utilized in mouse-tracking studies to infer cognitive states from movements, assuming a continuous manifestation of cognitive processing into movement. However, it is mostly unknown how this manifestation is affected by the variety of possible design choices in mouse-tracking paradigms. Here we studied how three design factors impact the manifestation of cognition into movement in a Simon task with mouse tracking. We varied the response selection (i.e., with or without clicking), the ratio between hand and mouse cursor movement, and the location of the response boxes. The results show that all design factors can blur or even prevent the manifestation of cognition into movement, as reflected by a reduction in movement consistency and action dynamics, as well as by the adoption of unsuitable movement strategies. We conclude that deliberate and careful design choices in mouse-tracking experiments are crucial to ensuring a continuous manifestation of cognition in movement. We discuss the importance of developing a standard practice in the design of mouse-tracking experiments

Linguistic Naturalism and Natural Style. From Varro and Cicero to Dionysius of Halicarnassus

NWO276-30-009Classics and Classical Civilizatio

Attractor Dynamics in Delay Discounting: A Call for Complexity

The outcomes of intertemporal choices indicate that people discount rewards by their delay. These outcomes are well described by discounting functions. However, to fully understand the decision process one needs models describing how the process of decision-making unfolds dynamically over time. Here, we validate a recently published attractor model that extends discounting functions through a description of the dynamics leading to a final choice outcome within and across trials. We focus on the decision dynamics across trials. We derive qualitative predictions for the inter-trial dynamics of sequences of decisions that are unique to this type of model. We test these predictions in a delay discounting game where we sequentially manipulated subjective values of options across all attribute dimensions. Results confirm the model’s predictions. We discuss future challenges on integrating attractor models towards a general attractor model of delay discounting to enhance our understanding of the processes underlying delay discounting decisions

Choice History Bias in Intertemporal Choice

Human decision making is prone to many biases that either result from properties of the actual decision or from properties of the decision environment. We investigated the influence of the choice history on the actual decision in the domain of intertemporal choice, known as choice history bias from perceptual decision making. Over a series of three experiments, we demonstrate that the choice history bias also operates in intertemporal choice, but only under specific circumstances. We identified the inter-trial interval to be a determinant of the bias. Our results corroborate recent findings investigating path-dependence of perceptual and preferential decisions, and consolidate the overall mechanistic interpretation that the choice history bias arises due to residual activity in the neural system. Hence, our study bears two implications: First, models of intertemporal choice need to consider the dependency of choices across trials; second, the study of intertemporal choices empirically asks for considering this path-dependence to avoid biased conclusions about individual choices

From high- to one-dimensional dynamics of decision making: testing simplifications in attractor models

Computational models introduce simplifications that need to be understood and validated. For attractor models of decision making, the main simplification is the high-level representation of different sub-processes of the complex decision system in one dynamic description of the overall process dynamics. This simplification implies that the overall process dynamics of the decision system are independent from specific values handled in different sub-processes. Here, we test the validity of this simplification empirically by investigating choice perseveration in a nonverbal, value-based decision task. Specifically, we tested whether choice perseveration occurred irrespectively of the attribute dimension as suggested by a simulation of the computational model. We find evidence supporting the validity of the simplification. We conclude that the simplification might capture mechanistic aspects of decision-making processes, and that the summation of the overall process dynamics of decision systems into one single variable is a valid approach in computational modeling. Supplement materials such as empirical data, analysis scripts, and the computational model are publicly available at the Open Science Framework (osf.io/7fb5q)

From high- to one-dimensional dynamics of decision making: Testing simplifications in attractor models

Primary data (csv), analysis scripts (Matlab, JASP, Rmd) and simulation of the computational model (Matlab) for the article 'From high- to one-dimensional dynamics of decision making: Testing simplifications in attractor models' published in Cognitive Processing (2020, DOI: 10.1007/s10339-020-00953-z