See Bachelor thesis

Cognitive Psychology

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BCP1 - The role of fingers used when executing practiced movement sequences while listening to tones


An important issue is how people develop movement automaticity. This is the capacity to execute a series of successive movements requiring little attention for executing them. It is as if the limbs know what to do. Such motor skills can be investigated with a sequential key pressing task. In the proposed study, participants will develop motor automaticity by practicing two fixed 6-element key pressing sequences.  After a practice phase, they will produce the same sequences using different fingers and hands. The research question concerns the effect of changing the fingers that are being used, and whether this is affected by a second task. In the proposed bachelor thesis project, this hypothesis will be tested in a laboratory experiment in BMS lab.

Abrahamse, E. L., Ruitenberg, M. F. L., De Kleine, E., & Verwey, W. B. (2013). Control of automated behaviour: Insights from the Discrete Sequence Production task. Frontiers in Human Neuroscience, 7(82), 1-16.

BCP2 - Is learning movement sequences influenced by eye fixation location?


When people are developing serial movement skills, they are assumed to develop memory representations of those sequences. These representations eliminate the need to select the individual movement in the series. Little is known about the content of these representations. This project entails an experiment testing the hypothesis that one of these movement representations involves spatial coordinates relative to the eye fixation location. In the experiment, participants will develop motor automaticity by practicing two fixed 6-element key pressing sequences.  While practicing they will focus a particular screen location. This may mean that the participants learn the location of the key-specific stimuli in terms of their relative location to the fixation location. In the ensuing test phase, participants will execute the practiced and new sequences with the same and with a different fixation location. This study will be carried out in the cubicles of the BMS lab.  

Abrahamse, E. L., Ruitenberg, M. F. L., De Kleine, E., & Verwey, W. B. (2013). Control of automated behaviour: Insights from the Discrete Sequence Production task.
Frontiers in Human Neuroscience, 7(82), 1-16.

BCP3 – Conceptual Learning



Concepts and their relations play a crucial role in human cognition. In particular, they are the building blocks of our semantic cognition, with which we understanding our environment. Concepts can vary from concrete, as given by the concept "dog", to abstract, such as the concept "honesty". Learning concepts can be based on learning perceptual classifications, such as learning the concept "dog" from classifying individual dogs, or by classifying or recognizing actions as performed by certain agents. But concepts can also be learned by combining other concepts and their relations. So, the concept "animal" could be learned from understanding the similarities between concepts such as "dogs" and "cats" and their differences with other concepts like "chair" or "house". In this way, we also learn relations between concepts, for example that a dog is an animal, but not every animal is a dog. Because concepts (such as actions) are typically learned in (certain) relations to each other, a 'conceptual space' (or knowledge base) can arise, which forms the basis for our semantic cognition.  

How we learn concepts and conceptual spaces, and how they are represented in the brain, is a topic of very active research. Learning of concepts and relations is also an important theme in machine learning. The key issue in this project concerns the way in which concepts and their relations in a given domain are learned and how they are combined to form a conceptual space. The domain can be chosen one, such as the "sport domain" (with concepts like "player" or "game") or the "health domain" (with concepts like "virus" or "medicine"). Or it could be designed for the project to study how humans learn such a new domain. The chosen topic can be studied with experimental techniques such as card sorting or priming studies. Or the conceptual space in a chosen domain could be designed (e.g., for use in machines) and evaluated by humans, for example by using questionnaires. Aspects of concept learning and conceptual spaces can also be modelled with computer modelling, such as Deep Learning or other techniques. 


Rouder, Jeffrey; Ratcliff, Roger (2006). "Comparing Exemplar and Rule-Based Theories of Categorization". Current Directions in Psychological Science. 15: 9–13. doi:10.1111/j.0963-7214.2006.00397.x. 

Lambon-Ralph, M. A., Jefferies, E., Patterson, K. and Timothy T. Rogers, T. T. (2017). The neural and computational bases of semantic cognition. Nature Reviews Neuroscience 18, 42–55. doi:10.1038/nrn.2016.150

Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., & Gallant, J. L. (2016). Natural speech reveals the semantic maps that tile human cerebral cortex. Nature, 532(7600), 453-458. doi:10.1038/nature17637

BCP4 – Short-Term Memory for Color, Form or Orientation

SUPERVISOR: DR. ROB VAN DER LUBBE (2 students necessary)

Recent ideas on working memory or short-term memory (STM) propose that STM may be better conceptualized as a limited resource that is flexibly distributed among items to be maintained in memory rather than holding a fixed number of elements active. Many aspects of STM are still unknown. In this project, we will especially focus on memory for colors/form/orientation. How precise are our memories for color/form/orientation and how does this preciseness depend on the number of presented objects?

BCP5 – Mental Effort, Frontal Theta, and Working Memory

SUPERVISOR: DR. ROB VAN DER LUBBE (2 students necessary)

Earlier research suggests that mental effort is reflected in increased electroencephalographic (EEG) activity in the frontal theta band (~ 4-8 Hz). Mental effort may be related to working memory (WM) capacity. Goal of the project is to replicate and extend earlier observations with a Sternberg Memory task, and the Add-N task. WM capacity can be assessed with a standard procedure from the WAIS intelligence test.