Systems of Learning and Memory
Research group
Systems of Learning and Memory
Research group
Systems of Learning and Memory
Research group


Our group investigates brain systems that are involved in the transformation of experience into enduring memories. Classically, human learning and memory was mainly divided into explicit (with awareness) and implicit (without awareness) memory, but this behavioural characterization cannot simply be mapped to distinct brain areas. For example, we have shown that implicit learning can recruit structures of the medial temporal lobe (MTL) system, which was previously regarded as exclusive to explicit memory. We are using functional magnetic resonance imaging (fMRI) and time-frequency based EEG analysis techniques to examine the systems that contribute to the different aspects of learning and memory. Combined fMRI- EEG experiments are used to describe locations and network dynamics involved in learning and memory. We further incorporate EEG- based Neurofeedback to modulate ongoing activity and examine the consequences for stimulus processing and memory formation.

Michael Rose
Priv.-Doz. Dr.
Michael Rose
Signe-Luisa Winterling

Signe is a doctoral student who joined the group in April 2014. In her PhD project, she investigates the functional role of pre-stimulus brain activity in memory formation. She examines the nature of oscillatory states that seem to be beneficial for the encoding of new information, how such states can be modulated and whether these modulations can be used to influence encoding success. Methodologically, she is interested in EEG time-frequency analyses, brain-computer-interfaces and combined EEG-fMRI measurements.

Philipp Taesler

Philipp has joined the group at the start of 2013. He's been investigating the relationship between ongoing neuronal activity and the variability of perceptual classifications (e.g. pain) using BCI-based neurofeedback. Currently, he is focusing on the crossmodal transfer of information in implicit learning, also employing BCI-based methods in EEG and EEG-fMRI. Further interests of his include the limitations of perception, psychophysics and machine learning.

Julia is a doctoral student who joined the group in April 2016. In her PhD project, she investigates how crossmodal predictions can be achieved implicitly and the underlying transition from implicit to verbally reportable (explicit) knowledge. Based on fMRI and EEG measurements, she investigates the neurological mechanisms associated with implicit learning of crossmodal predictions in order to detect the underlying different indicators of crossmodal integration and prediction of implicit knowledge. Furthermore, she is interested in brain-computer-interfaces, the study of consciousness and affective neuroscience.

  • Staff
    • The neuronal basis of learning and memory

    • Involvement of MTL structures in implicit learning

    • The development of explicit access to implicitly learned information

    • The effect of pre-stimulus activity on memory formation

    • Neurofeedback

  • Taesler, P. and Rose, M. (2016). Pre-stimulus theta oscillations and connectivity modulate pain perception. Journal of Neuroscience 36(18); 5026-5033.

    Schneider, S. and Rose, M. (2015). Intention to encode boosts memory-related pre-stimulus EEG beta power. NeuroImage 14;125:978-987. doi: 10.1016

    Salari, N. and Rose, M. (2015). Dissociation of the functional relevance of different pre- stimulus oscillatory activity for memory formation. NeuroImage 2015; pii: S1053-8119(15)00948-9. doi: 10.1016/.

    Haider, H., Eberhardt, K. Esser, S. & Rose, M. (2014). Implicit visual learning: How the task set modulates learning by determining the stimulus-response binding. Consciousness and Cognition. Consciousness and Cognition; 26:145-61

    Rose M, Haider H, Salari N, Büchel C (2011). Functional Dissociation of Hippocampal Mechanism during Implicit Learning Based on the Domain of Associations. Journal of Neuroscience, 2011 Sep 28;31(39):13739-45.

    Rose M, Haider H, Büchel C. (2010). The Emergence of Explicit Memory during Learning. Cerebral Cortex. 2010 Mar 1.

    Rose, M., Büchel, C. (2005). Neural coupling binds visual tokens to moving stimuli. Journal of Neuroscience, 25(44).

    Michael Rose, Hilde Haider, Cornelius Weiller & Christian Büchel (2002).The role of medial temporal lobe structures in implicit learning: an event-related fMRI study. Neuron, 36 (6), 1221-31.

  • SFB TRR 169: “Crossmodal Learning: Adaptivity, Prediction and Interaction”. Starting in 2016 the project within the Transregional Collaborative Research Center TRR169 funded by the DFG examines neurocognitive mechanisms for implicit learning of crossmodal predictions. The TRR is established as a Collaboration between Hamburg University and Beijing University. Project coordinator in Hamburg: Michael Rose

    DFG Project RO 2653/6-1: „Funktion und Relevanz oszillatorischer prästimulus Aktivität für die Gedächtnisbildung“. Coordinator: Michael Rose

  • Prof. Dr. Hilde Haider
    University of Cologne, Germany

    Prof. Dr. Rolf Verleger
    University of Lübeck, Germany

    Prof. Dr. Qiufang Fu
    Chinese Academy of Sciences, Beijing, China

    Prof. Dr. Xiaorong Gao
    Biomedical Engineering, Tsinghua University, Beijing, China

    Dr. Karsten Rauss
    University of Tübingen, Germany