If you are interested in writing a thesis or doing a research internship within the field of one of our projects, just contact us! Please do not hesitate to contact Dr.  Ima Trempler, if you need guidance choosing a topic. You are also very welcome to approach us with your own ideas. We look forward to hearing from you!

team AE Schubotz
© AE Schubotz

'Alternative facts' - How the brain warrants stable and flexible predictions from faithful and modified memories of a person's true past

contact: Sophie Siestrup

contact: Benjamin Jainta

In this project we aim to distinguish sequential expectations from non-sequential expectations that are driven by a cued episodic retrieval.
The basis for prediction is memory. From this perspective, memory is not autotelic, but should be optimized to serve the anticipation of upcoming events and the planning of action. This optimization entails updating when the world has truly changed. In the current project, we will trigger the recall of episodic memories either with regard to sequential expectations (based on the episodic memory trace) or with regard to non-sequential expectations (based on semantic information). In a first step, participants will be videotaped while performing and observing everyday actions. Subsequently, three experiments will be conducted using BOLD-sensitive functional Magnetic Resonance Imaging to assess the cerebral basis of episodic expectation, surprise (information-theoretical: surprisal), and re-consolidation during presentation of these action videos. We employ a set of novel experimental factors concerning the episodes’ mnemonic solidity (retrieval times and consolidation) and experiential quality (self-perspective and self-performance) to test their impact on sequential and object-semantic surprise. This approach is motivated by the question as to which conditions render the memory of a truly experienced episode more or less susceptible to later modification of its spatiotemporal structure or its object-semantic content. Moreover, we systematically compare the conditions for the presence of memory updating effects due to reconsolidation separately for sequential structure and object-semantic content. Behavioral analyses will be combined with BOLD fMRI contrast, representational similarity, and graph theoretical analyses to specifically determine the role of hippocampal and selected cortical areas in stable and flexible episodic memory.

This project gets funded by the German Research Foundation (SCHU1439-10-1)


Rich club “chronoarchitecture” forms the neural basis for the processing of hierarchical stimuli

contact: Falko Mecklenbrauck

Not only the world around us consist of a multitude of nested and non-nested hierarchical structures, but also our brain can be described in the ways of structural and functional hierarchies. Thus, it has been theorized that the neural processing of hierarchical stimuli also behaves in a hierarchical manner. Evidence from cytoarchitectural and frequency analysis studies as well as various theories of frontal lobe functions proposed an anterior-posterior hierarchy of processing steps (e.g. Badre & Nee, 2018). However, the question remains, which organizational principle structures the stimuli hierarchically. A promising approach we want to focus on in project is the temporal persistence of stimuli. Areas near the top of the hierarchy are able to integrate and maintain information over a longer span of time (Koechlin & Summerfield, 2007). The structural backbone of this temporal hierarchy might be constructed by the rich club organization of the cerebral network. Following this idea, hierarchically higher thus more stable processing near a rich club hub and hierarchically lower, more transient processing closer to more peripheral nodes, could build an axis of “chronoarchitecture” (Gollo et al., 2015) which possibly offers a very general theory of information processing. Therefore, we will combine function magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI) and graph theoretical analyses to connect the functional processes to the network architecture. In the first experiment, the participants will be presented sequences of numbers, that contain hierarchical structures of different level and length. This paradigm will be applied to determine “temporal receptive windows” (Hasson et al., 2008) of different cortical areas which will then be mapped onto the furthermore identified structural network to address relation of hierarchical stimuli, their temporal persistence, and the underlying neural organization.

Badre, D., & Nee, D. E. (2018). Frontal Cortex and the Hierarchical Control of Behavior. In Trends in Cognitive Sciences (Vol. 22, Issue 2, pp. 170–188). Elsevier Ltd.

Gollo, L. L., Zalesky, A., Matthew Hutchison, R., Van Den Heuvel, M., & Breakspear, M. (2015). Dwelling quietly in the rich club: Brain network determinants of slow cortical fluctuations. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1668).

Hasson, U., Yang, E., Vallines, I., Heeger, D. J., & Rubin, N. (2008). A hierarchy of temporal receptive windows in human cortex. Journal of Neuroscience, 28(10), 2539–2550.

Koechlin, E., & Summerfield, C. (2007). An information theoretical approach to prefrontal executive function. Trends in Cognitive Sciences, 11(6), 229–235.


TUJOTA - Turn Taking at the Joint Action Table

contact: Rosari Naveena

In this collaborative project between Prof. Florentin Wörgötter (head of Computational Neuroscience department at the University of Göttingen) and our lab, we aim to investigate the cognitive architecture of action perception. Our particular focus of interest is the neurocognitive basis of a behavior or function called ‘turn taking’ that has been first described in conversations. Here, taking turns means that while the listener still decodes what s/he hears, s/he already prepares the own upcoming utterance so that the average transition time between the two conversational partners is no more than 200 msec. Since the planning of an utterance itself takes considerably longer, it becomes obvious that turn taking entails several coincident anticipatory processes: predicting the approximate content of the so far unspoken, predicting the timing of the other’s current utterance and hence the most probable point in time where a reply is suitable, and preparing the own utterance. Turn taking is also evident in joint action but has been rarely investigated. In the current project, we measure brain responses, hand movements, and eye movements of an action observer getting reading for turn taking. Using computer vision at the Göttingen lab, we will assess cues that an observer derives from an observed object manipulation performed by an actor/actress and measure the observer’s eye movements as well as the point in time where s/he starts turn taking. Using these data points to model entropy and surprisal in an fMRI study in Münster, we will examine the brain activity in action observers presented with videos from the same actions. Our findings may contribute to the development of robots that can engage in joint action with human beings.


Interoception and emotion recognition

contact: Amelie Hübner

Interoception, defined as the sense of the internal physiological condition of the body, has gained growing interest in recent years because of its impact on physical and mental health, as well as processing of emotion. Classical appraisal theories on emotion processing postulate emotional experiences to arise from the contextualised perception and interpretation of bodily responses to external stimuli. Interoceptive precision may be a key to the striking differences individuals show in their interoceptive abilities. Emotional sensations and inferring another’s emotional states have been suggested to both depend on predictive models of the causes of bodily sensations, so-called interoceptive inferences. There are three different areas of predictive functioning, i.e., the exteroceptive, interoceptive, and proprioceptive dimension, underlying perception, emotion, and action, respectively. These can operate both amodal and multimodal, depending on the level of the predictive hierarchy at which predictions are violated. According to the interoceptive predictive coding model, high sensitivity to interoceptive changes and, correspondingly, in emotional experience, is suggested to correspond with the ability to raise the precision of interoceptive prediction errors by focused attention. According to this assumption, in our project we investigate whether individuals’ interoceptive abilities effect their ability in inferring others’ emotional states. The present study investigated these assumptions using an emotion classification task as well as different psychophysiological measures (Skin conductance response, fMRI). In order to present the development of emotions as naturally as possible and to map the prediction process as part of the development or initiation of the emotion, we created videos where neutral facial expressions dynamically turn to emotional ones.


Should I stay or should I go? Dopaminergic modulation of cognitive stability and flexibility

Contact: Ima Trempler

In daily life, it is of crucial importance to adjust our behavior to environmental changes without losing track of our action goals. On the one hand, we have to stabilize our predictions in the face of potential distracters. On the other hand, we need to adapt these stable predictions to altered circumstances. Recent physiological as well as neurocomputational models suggest that this balance between cognitive stability and flexibility is mediated by dopamine. Dopamine in the prefrontal cortex binding on so-called D1-receptors might be essential for stabilization of working memory (Durstewitz & Seamans, 2008). In contrast, dopamine acting on D2-receptors in the striatum possibly plays a considerable role for cognitive flexibility (Friston et al., 2012). Motor as well as cognitive dysfunctions resulting from dopaminergic decline in idiopathic Parkinson’s disease (IPD) may thus be described as specific impairments of cognitive stability and/or flexibility. In order to test this hypothesis, we investigate the explicit and implicit stabilization and flexibilization of prediction in patients with IPD (dopaminergic medication “on” and “off”) and healthy controls. Using a modified serial prediction task (sequence switch detection), we collect behavioral data (reaction times and error rates) as well as physiological measures (skin conductance responses (SCR), and BOLD functional Magnetic Resonance Imaging (fMRI)). In a further study, we examine the genotype dopamine catabolism’s (COMT-polymorphism) influence and that of dopamine receptor density (DRD2-polymorphism) on cognitive stability and flexibility in healthy subjects and patients.

Durstewitz, D. & Seamans, J. (2008). The dual-state theory of prefrontal cortex dopamine function with relevance to catechol-o-methyltransferase genotypes and schizophrenia. Biol Psychiatry, 64, 739-749.

Friston, K. J., Shiner, T., FitzGerald, T., Galea, J. M., Adams, R., Brown, H., ... Bestmann, S. (2012). Dopamine, affordance and active inference. PLoS Comput Biol 8(1, e1002327.

Schubotz, R. I. & von Cramon D.Y. (2004). Anterior-posterior functional gradient within premotor fields: fMRI on memory-driven versus stimulus-driven sequencing. Neuroimage, 22 (1), 33.


Human Validation of Computer-Driven Action Segmentation

Contact: Jennifer Pomp

Human action is composed of chunks that are smoothly joined to form a continuous signal. Correspondingly, human observers as well as computers can decompose (segment) actions into characteristic phases. However, it remains unclear whether or not these phases are representative and relevant for action processing in the brain. To address this problem, we seek to quantify action phases asking whether purely data-driven action segmentation by computers is convergent with signatures of natural action segmentation as measured by human brain responses (fMRI) and behavior.
Thus, the common aim of this work is to arrive at an objective description of actions, and to biologically validate this approach to the characterization of human object manipulations.

This project gets funded by the German Research Foundation (SCHU1439-8-1)

Schubotz, R. I., Korb, F. M., Schiffer, A.-M., Stadler, W. & von Cramon, D. Y. (2012). The fraction of an action is more than a movement: Neural signatures of event segmentation in fMRI. NeuroImage, 61(4), 1195-1205.

Wörgötter, F., Aksoy, E. E.., Krüger, N., Piater, J., Ude, A. & Tamosiunaite, M. (2013). A simple ontology of manipulation actions based on hand-object relations. IEEE Transactions on Autonomous Mental Development, 5(2), 117-134.


Measures of Content and Dynamics of Anticipation in the Brain

contact: Marlen Roehe

The environment we live in is highly dynamic and yet it presents us with continuous sensory regularities. This allows us to implicitly and explicitly extract regularities and associations from our environment and establish internal representations of the external world (Clark, 2013). Once these representations are built to form a hierarchical generative model, temporal regularities can be anticipated through top-down predictions. Meaning, less time and attention is required to process these sensory stimuli. Neurophysiological accounts postulate that these top-down predictions are represented by beta/alpha oscillation dominance, whilst feedforward projection of novel information is represented by dominating gamma oscillations (Cao et al., 2017). Furthermore, to optimise the bidirectional information transfer, this interplay of oscillations does not occur simultaneously but is instead segregated into periods of either dominating beta/alpha or dominating gamma oscillations (Fontolan et al., 2014). Yet, what remains speculative is the generation process of implicit predictions, i.e. we know little about the electrophysiological nature outlining the build-up of predictions and how these predictions are influenced by the constant stream of competing interoceptive and exteroceptive input. With this study we therefore intend to investigate the electrophysiological insights into the nature of predictions underlying visual statistical learning.

Cao, L., Thut, G., & Gross, J. (2017). The role of brain oscillations in predicting self-generated sounds. NeuroImage, 147, 895-903.

Clark A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brains Sci, 36, 181-204.

Fontolan, L., Morillon, B., Liegeois-Chauvel, C., & Giraud, A.-L. (2014). The contribution of frequency-specific activity to hierarchical information processing in the human auditory cortex. Nature Communications, 5, 1-10.


The interplay of positive and negative prediction error signals during expectation violations of visual stimuli

contact: Lena Schliephake

Surprising scenarios can have different behavioural and neuronal consequences depending on the violation of the expectation. On the one hand, previous research has shown that the omission of a visual stimulus results in a robust cortical response representing that missing stimulus, a so-called negative prediction error. On the other hand, a large amount of studies revealed positive prediction error signals, entailing an increased neural response that can be attributed to the experience of a surprising, unexpected stimulus. However, it still remains unclear how and when these prediction error signals co-occur. In this project, we investigate whether positive and negative prediction error signals evoked by unpredicted cross-category stimulus transitions can temporally coincide. Moreover, we seek to clarify the relationship between the effects of positive and negative predictions errors and stimulus transition effects caused by equal or unequal stimulus category presentations. We use event-related fMRI and forced-choice decision tasks in which participants have to respond to individual visual images presented in a continuous stream with sequential contingencies.