My research centres on the behavioural and neurobiological mechanisms underlying the processing of pain.
On a very basic level, I am interested in how nociceptive information is represented in the human central nervous system (CNS). I am especially interested in the spinal cord, as this is the first station of the CNS where nociceptive information from the body periphery is processed. The experience of pain is however not perfectly correlated with the amount of peripheral noxious input, and can even be strongly decoupled from it, depending on our cognitive and emotional states. It is these modulatory processes that I am mainly investigating, whereby my focus lies on paradigms that shape the expectancy of pain relief (and worsening).
Another line of research concerns the processing of pain-predictive cues, as evident
Falk Eippert
Post-Doctoral Researcher
for example in associative learning paradigms, where pain serves as a teaching signal and endows neutral stimuli with negative value. I am using various paradigms from the classical conditioning literature to study the development by which cues become pain predictive (or non-predictive) and the subsequent interactions between these cues and pain itself, which is also of high relevance when considering the development of chronic pain. Of the various neurotransmitters involved in the underlying neuronal computations, I am specifically interested in endogenous opioids, the role of which can be established by pharmacological challenge studies e.g. using the opioid antagonist naloxone.
I use both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) in combination with various peripheral physiological and subjective measures to study the above topics. One of my main methodological interests is the development and application of novel fMRI acquisition and analysis techniques to investigate the human spinal cord.
Apart from my research, I enjoy teaching in the field of Scientific Computing at the FMRIB Graduate Programme in Oxford and the neurodapt Graduate School in Hamburg, with a focus on data analysis and programming in Matlab, R, and UNIX.
Publications: PubMed, Google Scholar, ORCID
Key publications
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Intrinsically organized resting state networks in the human spinal cord
Journal article
Kong Y. et al, (2014), Proceedings of the National Academy of Sciences, 111, 18067 - 18072
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Placebo Analgesia: A Predictive Coding Perspective
Journal article
Büchel C. et al, (2014), Neuron, 81, 1223 - 1239
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Neurobiological Mechanisms Underlying the Blocking Effect in Aversive Learning
Journal article
Eippert F. et al, (2012), Journal of Neuroscience, 32, 13164 - 13176
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Direct Evidence for Spinal Cord Involvement in Placebo Analgesia
Journal article
Eippert F. et al, (2009), Science, 326, 404 - 404
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Activation of the Opioidergic Descending Pain Control System Underlies Placebo Analgesia
Journal article
Eippert F. et al, (2009), Neuron, 63, 533 - 543
Recent publications
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Placebo Effects on the Neurologic Pain Signature
Journal article
Zunhammer M. et al, (2018), JAMA Neurology, 75, 1321 - 1321
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Determining the Neural Substrate for Encoding a Memory of Human Pain and the Influence of Anxiety
Journal article
Tseng M-T. et al, (2017), The Journal of Neuroscience, 37, 11806 - 11817
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Denoising spinal cord fMRI data: Approaches to acquisition and analysis
Journal article
Eippert F. et al, (2017), NeuroImage, 154, 255 - 266
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Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula
Journal article
Geuter S. et al, (2017), eLife, 6
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Investigating resting-state functional connectivity in the cervical spinal cord at 3 T
Journal article
Eippert F. et al, (2017), NeuroImage, 147, 589 - 601