Nadine Diersch
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Research Scientist / Principal Investigator
Aging & Cognition Research Group German Center for Neurodegenerative Diseases (DZNE) E-Mail: nadine.diersch@dzne.de Phone: +49 391 / 67 245 86 Twitter: @nadine_diersch Linkedin: nadine-diersch Supervision: Tuğçe Belge (PhD Candidate, Aging & Cognition Research Group, DZNE Magdeburg) Jonas Marquardt (PhD Candidate, Multimodal Neuroimaging Research Group, DZNE Magdeburg) Aniruddh Shukla (MSc Student, Data and Knowledge Engineering, OvGU Magdeburg) |
Research Interests
The potential of real-world movement trajectories to serve as a digital biomarker for neurodegeneration
Research on Alzheimer’s disease (AD) is still facing the challenge of detecting changes in cognitive and sensorimotor function that precede clinical manifestations of the disease. Assessing the ability to navigate in our surroundings might be able to overcome this challenge because older adults and patients at preclinical stages of AD often show difficulties in laboratory-based spatial navigation tasks using virtual reality setups. However, how this translates to their behavior in real-world settings remains unclear. To overcome this gap, I conceptualized and designed the smartphone-based application “Explore”, that collects GPS and sensor data, while the user performs a navigation task in the real world (supported by a DZNE Innovation to Application Award and realized by Intenta GmbH). Currently, a first proof-of-concept study is performed in a sample of healthy younger and older adults as well as patients with subjective cognitive decline (SCD). In our analyses, group differences in the GPS trajectories and certain aggregated measures (e.g. wayfinding distance) will be determined, while applying pattern classification and clustering algorithms to characterize movement patterns that are indicative of age and, in contrast to standard neuropsychological assessments of cognitive health, may be suitable to differentiate normal aging from early signs of AD.
Impairments in the encoding & retrieval of spatial information in healthy aging and Alzheimer’s Disease
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Older adults often have problems to find their way in novel environments, even after repeatedly visiting them, and studies in aged rodents and non-human primates suggest that this might be related to changes in hippocampal place cell firing patterns. In my research at the DZNE, I characterized age-related problems in learning a novel virtual environment, by measuring how well healthy older and younger adults are able to retrieve its spatial layout across several learning blocks, and investigated the underlying neural mechanisms using fMRI and effective connectivity analysis (DCM PEB). To estimate subject-specific learning states per block, we developed a Bayesian implementation of a state-space model. I found that although some older adults learned just as well as younger adults, the majority of them showed substantial deficits in retrieving information about the initially unfamiliar environment. While I could replicate findings from earlier studies in younger adults (i.e. learning-related activity changes in the retrosplenial cortex and the hippocampus), I found that activity in these regions does not change systematically in older adults across repeated episodes in the environment. Importantly, I further show that their learning deficits are linked to impaired spatial information processing in the hippocampus, as evidenced by an age-related reduction in the inhibitory self-connection of this region.
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Building-up on recent findings from the lab, I will investigate next the functional mechanisms that underlie the reduced stability of grid-cell-like representations in the entorhinal cortex and remapping changes in the hippocampus in individuals, who are at-risk for developing AD [Link]. In addition, I am leading the implementation of a clinical task paradigm to study grid-cell-like representations in the entorhinal cortex during the progression from healthy aging to neurodegenerative disease within the context of a large-scale cohort study of the DZNE [Link].
References:
Diersch, N., Valdes-Herrera, J.P., Tempelmann, C., Wolbers T. (2021). Increased hippocampal excitability and altered learning dynamics mediate
cognitive mapping deficits in human aging. Journal of Neuroscience, 41, 3204-3221. [Link]
Diersch, N., & Wolbers, T. (2019). The potential of virtual reality in spatial navigation research across the adult lifespan. Journal of Experimental
Biology, 222, doi: 10.1242/jeb.187252. [Link]
Stangl, M., Achtzehn, J., Huber, K., Dietrich, C., Tempelmann, C., & Wolbers, T. (2018). Compromised grid-cell-like representations in old age as a key
mechanism to explain age-related navigational deficits. Current Biology, 28, 1108-1115. [Link]
References:
Diersch, N., Valdes-Herrera, J.P., Tempelmann, C., Wolbers T. (2021). Increased hippocampal excitability and altered learning dynamics mediate
cognitive mapping deficits in human aging. Journal of Neuroscience, 41, 3204-3221. [Link]
Diersch, N., & Wolbers, T. (2019). The potential of virtual reality in spatial navigation research across the adult lifespan. Journal of Experimental
Biology, 222, doi: 10.1242/jeb.187252. [Link]
Stangl, M., Achtzehn, J., Huber, K., Dietrich, C., Tempelmann, C., & Wolbers, T. (2018). Compromised grid-cell-like representations in old age as a key
mechanism to explain age-related navigational deficits. Current Biology, 28, 1108-1115. [Link]
Action prediction in the aging mind
Non-verbal social interactions depend on our ability to infer and anticipate other people's actions. Theoretical accounts of motor activity during action observation suggest that the observer employs their motor system to make a prediction of the sensory consequences of observed actions. Consistent with this, many studies have shown that differences in motor expertise result in differences in performance and neural activation patterns, when experts and non-experts observe the same actions. But what happens when the observer’s brain and motor system are aging? My research in this domain shows that older compared to younger adults are less precise in anticipating the time-course of actions that are partly occluded from view. I further provided evidence that the neural implementation of predicting observed actions gets less distinctive with age and entails a shift from automatic, sensorimotor processing to a more controlled, visual processing. However, the internal representation of observed actions is sensitive to physical training and is modulated by the amount of sensorimotor experience with the observed actions, even in older age groups.
References:
Kuehn, E., Perez-Lopez, M. B., Diersch, N., Döhler, J., Wolbers, T., & Riemer, M. (2018). Embodiment in the aging mind. Neuroscience and Biobehavioral
Reviews, 86, 207-225, doi: 10.1016/j.neubiorev.2017.11.016. [Link]
Kirsch, L. P., Diersch, N., Sumanapla, D. K., & Cross, E. S. (2018). Dance training shapes action perception and its neural implementation within the young and
older adult brain. Neural Plasticity, 5459106, 1-20, doi: 10.1155/2018/5459106. [Link]
Diersch, N., Jones, A. L., & Cross, E. S. (2016). The timing and precision of action prediction in the aging brain. Human Brain Mapping, 37, 54–66.
doi: 10.1002/hbm.23012. [Link]
Diersch, N., Mueller, K., Cross, E. S., Stadler, W., Rieger, M., & Schütz-Bosbach, S. (2013). Action prediction in younger versus older adults: Neural correlates
of motor familiarity. PLOS ONE, 8, e64195. doi: 10.1371/journal.pone.0064195. [Link]
Diersch, N., Cross, E. S., Stadler, W., Schütz-Bosbach, S., & Rieger, M. (2012). Representing others' actions: The role of expertise in the aging mind.
Psychological Research, 76, 525-541. doi: 10.1007/s00426-011-0404-x. [Link]
Kuehn, E., Perez-Lopez, M. B., Diersch, N., Döhler, J., Wolbers, T., & Riemer, M. (2018). Embodiment in the aging mind. Neuroscience and Biobehavioral
Reviews, 86, 207-225, doi: 10.1016/j.neubiorev.2017.11.016. [Link]
Kirsch, L. P., Diersch, N., Sumanapla, D. K., & Cross, E. S. (2018). Dance training shapes action perception and its neural implementation within the young and
older adult brain. Neural Plasticity, 5459106, 1-20, doi: 10.1155/2018/5459106. [Link]
Diersch, N., Jones, A. L., & Cross, E. S. (2016). The timing and precision of action prediction in the aging brain. Human Brain Mapping, 37, 54–66.
doi: 10.1002/hbm.23012. [Link]
Diersch, N., Mueller, K., Cross, E. S., Stadler, W., Rieger, M., & Schütz-Bosbach, S. (2013). Action prediction in younger versus older adults: Neural correlates
of motor familiarity. PLOS ONE, 8, e64195. doi: 10.1371/journal.pone.0064195. [Link]
Diersch, N., Cross, E. S., Stadler, W., Schütz-Bosbach, S., & Rieger, M. (2012). Representing others' actions: The role of expertise in the aging mind.
Psychological Research, 76, 525-541. doi: 10.1007/s00426-011-0404-x. [Link]