The ability to monitor performance and adapt behavior in response to a constantly changing environment is a crucial cognitive skill shared by humans and other animals. One way we achieve such adaptation is by detecting and learning the statistical structure of our surroundings. The performance monitoring system—critical for flexible adaptation—resides primarily in the posterior medial frontal cortex (pMFC) [1]. In addition, other frontal regions, such as the dorsolateral prefrontal cortex (dlPFC), have been implicated in error detection and outcome evaluation [2].

While prefrontal structures monitor performance and evaluate behavioral outcomes, the hippocampus encodes knowledge about the structure and regularities of the environment [3]. Furthermore, distinct hippocampal subfields have been shown to produce activity patterns that predict whether associations have been successfully encoded or not [4].

The process of continued belief updating and behavioral adaptation has been described using reinforcement learning [5]. Novelty detection and behavioral adaptation signatures can be found in the brain and are known to be modulated by acetylcholine [6]. Furthermore, uncertainty—an inherent aspect of reinforcement learning—has been shown to differentially engage neuronal populations across the brain in ways that can be decoded using multivariate techniques [7]. These insights raise a central question: how do prefrontal signals influence hippocampal activity patterns when established associations must be updated and behavior adapted?

Building on the findings above, this project aims to investigate how performance monitoring structures (e.g., pMFC and dlPFC) and the hippocampus interact during belief updating and behavioral adaptation. To do so, we will use reinforcement learning and associative learning tasks.
By characterizing this mechanism, we aim to generate testable predictions about the consequences of cholinergic suppression. In later stages of the project, we will probe these predictions using pharmacological interventions that reduce cholinergic neurotransmission, thereby providing causal evidence for the relationship between cholinergic modulation, prefrontal monitoring, and hippocampal encoding.

Given the critical role of cholinergic neurotransmission in human learning, memory, attention, and executive function—as well as its involvement in Alzheimer’s disease and age-related cognitive decline—our work has direct relevance for clinical and aging populations. Using ultra-high-field functional magnetic resonance imaging and computational modeling, this project will establish a mechanistic and testable model of belief updating and advance our understanding of cortical–subcortical communication during adaptive behavior.

References:

[1] Kirschner, H., Fischer, A. G., & Ullsperger, M. (2022). Feedback-related EEG dynamics separately reflect decision parameters, biases, and future choices. NeuroImage, 259, 119437. https://doi.org/10.1016/j.neuroimage.2022.119437


[2] Weuthen, A., Kirschner, H., & Ullsperger, M. (2025). Error-driven upregulation of memory representations. Communications Psychology, 3(1), 1–13. https://doi.org/10.1038/s44271-025-00199-5


[3] Schapiro, A. C., Turk-Browne, N. B., Botvinick, M. M., & Norman, K. A. (2017). Complementary learning systems within the hippocampus: A neural network modelling approach to reconciling episodic memory with statistical learning. Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1711), 20160049. https://doi.org/10.1098/rstb.2016.0049


[4] Wanjia, G., Favila, S. E., Kim, G., Molitor, R. J., & Kuhl, B. A. (2021). Abrupt hippocampal remapping signals resolution of memory interference. Nature Communications, 12(1), 4816. https://doi.org/10.1038/s41467-021-25126-0


[5] Behrens, T. E. J., Woolrich, M. W., Walton, M. E., & Rushworth, M. F. S. (2007). Learning the value of information in an uncertain world. Nature Neuroscience, 10(9), 1214–1221. https://doi.org/10.1038/nn1954


[6] Caldenhove, S., Borghans, L. G. J. M., Blokland, A., & Sambeth, A. (2017). Role of acetylcholine and serotonin in novelty processing using an oddball paradigm. Behavioural Brain Research, 331, 199–204. https://doi.org/10.1016/j.bbr.2017.05.031


[7] Nassar, M. R., McGuire, J. T., Ritz, H., & Kable, J. W. (2019). Dissociable Forms of Uncertainty-Driven Representational Change Across the Human Brain. Journal of Neuroscience, 39(9), 1688–1698. https://doi.org/10.1523/JNEUROSCI.1713-18.2018