SUPERVISOR: PROF.DR.ING. WILLEM VERWEY; 35EC
In collaboration with prof. Michael Nitsche at Ifado (http://www.ifado.de/neurowissenschaft/neuromodulation/), Transcranial Magnetic Stimulation (TMS, https://en.wikipedia.org/wiki/Transcranial_magnetic_stimulation) studies will be carried out while participants are executing a motor sequencing task. Earlier studies suggest that the supplementary motor area (SMA) is heavily involved in learning and producing motor sequences. We previously tested this in two studies with TMS at the preSMA and the SMAproper (Ruitenberg et al., 2014, Verwey et al., 2002), and found different effects, suggesting different functional roles for preSMA and SMAproper. However, these studies were somewhat different and carried out in different laboratories. In this master assignment, we intend to re-examine the different roles of the preSMA and the SMAproper in a single study, possibly including 1 or experiments.
Ruitenberg, M. F. L., Verwey, W. B., Schutter, D. J. L. G., & Abrahamse, E. L. (2014). Cognitive and neural foundations of discrete sequence skill: A TMS study. Neuropsychologia, 56, 229-238.
Verwey, W. B., Lammens, R., & van Honk, J. (2002). On the role of the SMA in the discrete sequence production task: a TMS study. Neuropsychologia, 40(8), 1268-1276.
SUPERVISOR: DR. ROB VAN DER LUBBE; 35 EC
Several authors argued that retrieval of an item from visual short term memory (internal spatial attention) and focusing attention on an externally presented item (external spatial attention) are similar. In a recent EEG study (Van der Lubbe et al., 2014) we presented four-stimulus arrays and observed increased power in the alpha and theta bands at ipsilateral sites above occipital cortex with precues and with postcues appearing 3,000 ms after array offset. These findings indeed support the idea of a common underlying mechanism. Nevertheless, this support may crucially depend on the time interval between the stimulus array and the postcue. In the planned research project we want to examine whether participants shift to a more abstract non-spatial type of representation in the case of longer time intervals. Thus, goal of the project is to determine the boundary conditions for overlapping mechanisms by systematically varying the array-postcue time interval.
SUPERVISOR: DR. ROB VAN DER LUBBE; 35 EC
Behavioral experiments with the change blindness paradigm indicate that the detection of a changing feature, even as large as the removal of an engine from an airplane, may be quite difficult, suggesting that we have only limited awareness of our surroundings (e.g., see Rensink, 2002). Mostly, it is argued that attentional orienting is the limiting factor. Goal of the project is to demonstrate that the attentional state at a specific moment can indeed predict when people will notice the change. A method to assess the attentional state is by measuring the electroencephalogram (EEG). Earlier research revealed that attentional orienting towards a specific location is accompanied by a decrease in contralateral alpha power (e.g., see Van der Lubbe & Utzerath, 2013). Thus, goal of the project is to examine whether detection of a changing feature is preceded by a contralateral reduction in alpha power.
SUPERVISOR: PROF.DR. FRANK VAN DER VELDE; 25/35EC
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 modeled with computer modeling, such as Deep Learning or other techniques.
This is a general topic that can be specified into a 25EC or a 35EC thesis project.
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