Research Program

The objective of our research program is to formulate and validate mechanistic explanations of cognitive phenomena, that is explanations in terms of their underlying neurophysiological mechanisms. Our research program consists of three components: basic science, methodology and application.

Basic Science

The basic science component of our research program is about cognitive phenomena such as attention, expectation, and sensory evidence accumulation. These phenomena explain the variable response of an organism to a stimulus. In fact, this response does not passively reflect the physical properties of a stimulus, but also depends on the current state of the organism. In other words, the organism has an active role in the way a stimulus (1) is transformed into a pattern of neuronal activity and (2) elicits a particular behavioral response. We want to explain the organism's role in terms of its underlying neurophysiological mechanisms.


The methodological component of our research program is the characterization of interactions in spatially distributed neural activity. To explain cognitive phenomena in neurophysiological terms, we need methods to identify these interactions. We contribute to this in two ways. First, we do quantitative work on the identification of the interacting components in the distributed activity. At this moment, this work is strongly driven by the working hypothesis that neuronal oscillations play an important role in establishing these interactions, which we assume to be reflected in the phase consistency across interacting sites. Second, we have developed a setup in which we can record epidural local field potentials (LFPs) over a large part of the rat somatosensory and part of the auditory system, allowing us to investigate neuronal interactions across these areas. We are now extending this setup such that we can combine these epidural LFP recordings with CMOS-technology-based recordings in the neuropil directly under the epidural electrode grid.


We are continuously seeking to apply our expertise to issues with societal and clinical relevance. For example, we were involved in brain-computer interfacing (BCI), which is about extracting a signal from measured brain activity that reflects the intentions of the subject.