Max Planck Research Group Pain Perception

In its acute form, pain is a beneficial signal that is warning us about impending or actual tissue damage. In its chronic form however, pain is a source of immense suffering for millions of people. At the same time, the perception of pain does not exhibit a one-to-one relationship with tissue damage, i.e. there are situations where we might not perceive much pain despite having sustained a strong injury (and vice versa). This flexibility suggests a strong involvement of the central nervous system in the perception of pain and our group's focus is to investigate the neural ‘building blocks’ of this multi-faceted pain experience. For this endeavour, we use behavioural recordings in combination with advanced neuroimaging techniques at all level of the central nervous system, focussing especially on the human spinal cord, which is the first station of central nervous system pain processing and also critically involved in pathological forms of pain. Our main research areas currently are:

(1) Constructing pain via prediction and prediction error signals

Our group’s main approach to pain stems from a perspective that characterises perception not as a passively arising response to sensory stimuli, but as an active inferential process, in which the central nervous system constantly generates predictions about the sensory inputs it receives and adjusts these predictions in light of new sensory input. In other words, our perception arises from the central nervous system trying to optimise its predictions of sensory input and minimising its prediction errors (i.e. the difference between the predicted and received sensory input). We aim to first characterise and then manipulate these prediction and prediction error signals in order to investigate how they relate to the perception of pain in various experimental contexts. Questions we aim to answer with this approach include for example: How does our past experience shape our current pain perception? Is it possible to boost prediction signals in order to enhance pain relief and can we apply this successfully in chronic pain? 


Key publications:


Nickel, M. M.; Tiemann, L.; Hohn, V. D.; May, E. S.; Gil Ávila, C.; Eippert, F.; Ploner, M.: Temporal-spectral signaling of sensory information and expectations in the cerebral processing of pain. Proceedings of the National Academy of Sciences of the United States of America 119 (1), e2116616119 (2022)
Geuter, S.; Boll, S.; Eippert, F.; Büchel, C.: Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula. eLife 6, e24770 (2017)
Büchel, C.; Geuter, S.; Sprenger, C.; Eippert, F.: Placebo analgesia: A predictive coding perspective. Neuron 81 (6), pp. 1223 - 1239 (2014)
Eippert, F.; Finsterbusch, J.; Bingel, U.; Büchel, C.: Direct evidence for spinal cord involvement in placebo analgesia. Science 326 (5951), p. 404 - 404 (2009)

 

(2) Functional neuroanatomy of the human spinal cord

Despite the spinal cord being the main sensorimotor interface between the brain and the body, our knowledge of the precise spatial layout and temporal organization of spinal cord responses as well as the interaction between different parts of the spinal cord remains sparse. To provide such knowledge (which is also crucial for a proper interpretation of results arising from the above-mentioned projects), we will use task-based investigations that probe the spinal cord’s response in various experimental paradigms, as well as task-free investigations that allow an assessment of the spinal cord’s intrinsic (resting-state) activity. Questions our group aims at answering include for example: How does the human spinal cord encode the intensity, the location or the duration of noxious stimuli? How do different regions of the spinal cord interact with each other and how does a painful experience change this pattern of information flow?


Key publications:


Eippert, F.; Kong, Y.; Winkler, A. M.; Andersson, J. L.; Finsterbusch, J.; Büchel, C.; Brooks, J. C. W.; Tracey, I.: Investigating resting-state functional connectivity in the cervical spinal cord at 3 T. NeuroImage 147, pp. 589 - 601 (2017)
Kong, Y.; Eippert, F.; Beckmann, C. F.; Andersson, J.; Finsterbusch, J.; Büchel, C.; Tracey, I.; Brooks, J. C. W.: Intrinsically organized resting state networks in the human spinal cord. Proceedings of the National Academy of Sciences of the United States of America 111 (50), pp. 18067 - 18072 (2014)

 

(3) Methods development for spinal cord fmri

Both of the above research areas depend on obtaining high-quality data from the spinal cord. Yet, fMRI of the spinal cord is still at an early stage of development and faces several unique challenges, such as i) the small size of the spinal cord, ii) spatially varying magnetic fields, and iii) the degrading influence of physiological noise originating from our breathing and heart-beat. A further aim of our group is thus to develop strategies that address these challenges - both from an acquisition and an analysis perspective - in order to obtain high-quality spinal cord fMRI data that allow for novel insights.


Key publications:


Kaptan, M.; Vannesjo, S. J.; Mildner, T.; Horn, U.; Hartley-Davies, R.; Oliva, V.; Brooks, J. C. W.; Weiskopf, N.; Finsterbusch, J.; Eippert, F.: Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord. Human Brain Mapping 43 (18), pp. 5389 - 5407 (2022)
Eippert, F.; Kong, Y.; Jenkinson, M.; Tracey, I.; Brooks, J. C. W.: Denoising spinal cord fMRI data: Approaches to acquisition and analysis. NeuroImage 154, pp. 255 - 266 (2017)
Finsterbusch, J.; Eippert, F.; Büchel, C.: Single, slice-specific z-shim gradient pulses improve T2*-weighted imaging of the spinal cord. NeuroImage 59 (3), pp. 2307 - 2315 (2012)

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