Model based analysis of latent neurocognitive processes of selective stopping strategies

• Applicant: Privatdozentin Dr. Alexandra Sebastian
• Subject Area: General, Cognitive and Mathematical Psychology
• Term: from 2017 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 347736680

In our complex human environment the ability to selectively control urges and impulses is essential for targeted behavioral control. Disturbance specifically of selective response inhibition is assumed to be a central pathomechanism of different neuropsychiatric diseases. Selective response inhibition can be assessed with a selective stopping task. When performing such a selective stopping task in which participants have to inhibit a response upon occurrence of one critical signal (stop-signal) but not of another signal (attentional capture-signal), different strategies can be applied: Individuals may inhibit their response truly selectively only upon viewing a stop-signal (Independent Discriminate then Stop strategy, ID), whenever viewing a stop- or ac-signal (Stop then Discriminate Strategy, SD), or the discrimination- and go-process may interact (Dependent Discriminate then Stop strategy, DD). These strategies are associated with differences in reaction times and brain activation patterns. Yet, strategic differences could be driven by differences in latent cognitive functions such as speed of data processing (i.e. drift rate), speed-accuracy trade-off/ response caution (i.e. boundary separation), or a priori bias for a response alternative (i.e. bias in cognitive information processing). Latent cognitive functions and their neural underpinnings can only be assessed using a model-based cognitive neuroscientific approach combining experimental psychology, mathematical psychology and traditional neuroscience. Variation in such latent cognitive functions has the potential to best explain distinct brain activation patterns associated with distinct selective stopping strategies rather than a simple comparison of the strategies using traditional neuroscientific approaches. In order to bridge the gap between neural processes and overt behavior, state-of-the-art methods of model-based cognitive neuroscience will be applied on a data set of a study with 80 participants performing a selective stopping task during functional magnetic resonance imaging.

• DFG Programme: Research Fellowships
• International Connection: Netherlands
• Host: Professorin Dr. Birte U. Forstmann