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Frahm KS, Andersen OK, Arendt-Nielsen L, Gervasio S, Mørch CD. Topical capsaicin modulates the two-point discrimination threshold-Modulation depends on stimulation modality and intensity. Eur J Pain 2024. [PMID: 39116004 DOI: 10.1002/ejp.4701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 06/07/2024] [Accepted: 07/04/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Spatial acuity concerns the ability to localize and discriminate sensory input and is often tested using the two-point discrimination threshold (2PDT). Sensitization of the pain system can affect the spatial acuity, but it is unclear how 2PDTs of different testing modalities are affected. The aim was to investigate if the 2PDTs for mechanical and heat stimulation at different intensities were modulated by topical capsaicin sensitization. METHODS 30 healthy subjects were divided into either a capsaicin or a placebo group. The 2PDT was tested using two different modalities, mechanical and thermal (laser) delivered at innocuous and noxious intensities. The 2PDT were determined at baseline and re-assessed 48 h later. In the follow-up session, the subjects either had a capsaicin patch (8%) or placebo patch placed in the testing area for 30 min before re-testing the 2PDT. RESULTS The 2PDT was highly dependent on stimulation modality and intensity. The lowest 2PDT was found for innocuous mechanical stimuli (40.0 mm, 95% CI 38.1-41.9 mm), and the highest 2PDT was found for innocuous thermal stimuli (81.7 mm, 95% CI 73.9-89.5 mm). Topical capsaicin generally increased the 2PDT, but this was only significant for innocuous mechanical stimuli. The perceived intensity of the stimuli was increased following capsaicin and was generally higher for noxious stimuli than for innocuous stimuli (ANOVA, p < 0.001). CONCLUSIONS This study showed that capsaicin provoked pain sensitization increased the 2PDT. The 2PDT tested using innocuous mechanical stimuli showed less variable results indicating that this test is most suitable to detect this aspect of spatial acuity. SIGNIFICANCE STATEMENT This study investigated how the two-point discrimination threshold (2PDT) can be modulated by topical capsaicin. The 2PDT was assessed for two different modalities (thermal and mechanical) and for two different intensities (innocuous and noxious) before and after capsaicin. The results showed that the 2PDT was generally impaired following capsaicin, but this was only significant for mechanical innocuous stimuli. Furthermore, it was shown that mechanical innocuous stimuli assessed the 2PDT with lower variability than other combinations.
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Affiliation(s)
- Ken Steffen Frahm
- Integrative Neuroscience Group, CNAP-Center for Neuroplasticity and Pain, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Ole Kæseler Andersen
- Integrative Neuroscience Group, CNAP-Center for Neuroplasticity and Pain, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Lars Arendt-Nielsen
- Translational Pain Biomarkers, CNAP-Center for Neuroplasticity and Pain, SMI®, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
- Department of Gastroenterology & Hepatology, Mech-Sense, Department of Clinical Medicine, Aalborg University Hospital, Aalborg, Denmark
- Steno Diabetes Center North Denmark, Aalborg University Hospital, Aalborg, Denmark
| | - Sabata Gervasio
- Neural Engineering and Neurophysiology Group, SMI®, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Carsten Dahl Mørch
- Integrative Neuroscience Group, CNAP-Center for Neuroplasticity and Pain, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
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2
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Izadi M, Franklin S, Bellafiore M, Franklin DW. Motor Learning in Response to Different Experimental Pain Models Among Healthy Individuals: A Systematic Review. Front Hum Neurosci 2022; 16:863741. [PMID: 35399361 PMCID: PMC8987932 DOI: 10.3389/fnhum.2022.863741] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 02/28/2022] [Indexed: 12/30/2022] Open
Abstract
Learning new movement patterns is a normal part of daily life, but of critical importance in both sport and rehabilitation. A major question is how different sensory signals are integrated together to give rise to motor adaptation and learning. More specifically, there is growing evidence that pain can give rise to alterations in the learning process. Despite a number of studies investigating the role of pain on the learning process, there is still no systematic review to summarize and critically assess investigations regarding this topic in the literature. Here in this systematic review, we summarize and critically evaluate studies that examined the influence of experimental pain on motor learning. Seventeen studies that exclusively assessed the effect of experimental pain models on motor learning among healthy human individuals were included for this systematic review, carried out based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. The results of the review revealed there is no consensus regarding the effect of pain on the skill learning acquisition and retention. However, several studies demonstrated that participants who experienced pain continued to express a changed motor strategy to perform a motor task even 1 week after training under the pain condition. The results highlight a need for further studies in this area of research, and specifically to investigate whether pain has different effects on motor learning depending on the type of motor task.
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Affiliation(s)
- Mohammad Izadi
- Sport and Exercise Research Unit, Department of Psychology, Educational Sciences and Human Movement, University of Palermo, Palermo, Italy
| | - Sae Franklin
- Institute for Cognitive Systems, Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany
| | - Marianna Bellafiore
- Sport and Exercise Research Unit, Department of Psychology, Educational Sciences and Human Movement, University of Palermo, Palermo, Italy
| | - David W. Franklin
- Neuromuscular Diagnostics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
- Munich School of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
- Munich Data Science Institute, Technical University of Munich, Munich, Germany
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3
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Ball F, Spuerck I, Noesselt T. Minimal interplay between explicit knowledge, dynamics of learning and temporal expectations in different, complex uni- and multisensory contexts. Atten Percept Psychophys 2021; 83:2551-2573. [PMID: 33977407 PMCID: PMC8302534 DOI: 10.3758/s13414-021-02313-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2021] [Indexed: 01/23/2023]
Abstract
While temporal expectations (TE) generally improve reactions to temporally predictable events, it remains unknown how the learning of temporal regularities (one time point more likely than another time point) and explicit knowledge about temporal regularities contribute to performance improvements; and whether any contributions generalise across modalities. Here, participants discriminated the frequency of diverging auditory, visual or audio-visual targets embedded in auditory, visual or audio-visual distractor sequences. Temporal regularities were manipulated run-wise (early vs. late target within sequence). Behavioural performance (accuracy, RT) plus measures from a computational learning model all suggest that learning of temporal regularities occurred but did not generalise across modalities, and that dynamics of learning (size of TE effect across runs) and explicit knowledge have little to no effect on the strength of TE. Remarkably, explicit knowledge affects performance-if at all-in a context-dependent manner: Only under complex task regimes (here, unknown target modality) might it partially help to resolve response conflict while it is lowering performance in less complex environments.
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Affiliation(s)
- Felix Ball
- Department of Biological Psychology, Faculty of Natural Science, Otto-von-Guericke-University Magdeburg, PO Box 4120, 39106, Magdeburg, Germany.
- Center for Behavioral Brain Sciences, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
| | - Inga Spuerck
- Department of Biological Psychology, Faculty of Natural Science, Otto-von-Guericke-University Magdeburg, PO Box 4120, 39106, Magdeburg, Germany
| | - Toemme Noesselt
- Department of Biological Psychology, Faculty of Natural Science, Otto-von-Guericke-University Magdeburg, PO Box 4120, 39106, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
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4
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Seymour B, Mancini F. Hierarchical models of pain: Inference, information-seeking, and adaptive control. Neuroimage 2020; 222:117212. [PMID: 32739554 DOI: 10.1016/j.neuroimage.2020.117212] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 07/21/2020] [Accepted: 07/25/2020] [Indexed: 11/26/2022] Open
Abstract
Computational models of pain consider how the brain processes nociceptive information and allow mapping neural circuits and networks to cognition and behaviour. To date, they have generally have assumed two largely independent processes: perceptual inference, typically modelled as an approximate Bayesian process, and action control, typically modelled as a reinforcement learning process. However, inference and control are intertwined in complex ways, challenging the clarity of this distinction. Here, we consider how they may comprise a parallel hierarchical architecture that combines inference, information-seeking, and adaptive value-based control. This sheds light on the complex neural architecture of the pain system, and takes us closer to understanding from where pain 'arises' in the brain.
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Affiliation(s)
- Ben Seymour
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, United Kingdom; Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan.
| | - Flavia Mancini
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, United Kingdom.
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5
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Torta DME, Ninghetto M, Ricci R, Legrain V. Rating the Intensity of a Laser Stimulus, but Not Attending to Changes in Its Location or Intensity Modulates the Laser-Evoked Cortical Activity. Front Hum Neurosci 2020; 14:120. [PMID: 32296320 PMCID: PMC7136469 DOI: 10.3389/fnhum.2020.00120] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 03/16/2020] [Indexed: 11/13/2022] Open
Abstract
Top-down attention towards nociceptive stimuli can be modulated by asking participants to pay attention to specific features of a stimulus, or to provide a rating about its intensity/unpleasantness. Whether and how these different top-down processes may lead to different modulations of the cortical response to nociceptive stimuli remains an open question. We recorded electroencephalographic (EEG) responses to brief nociceptive laser stimuli in 24 healthy participants while they performed a task in which they had to compare two subsequent stimuli on their Spatial location (Location task) or Intensity (Intensity Task). In two additional blocks (Location + Ratings, and Intensity + Ratings) participants had to further provide a rating of the perceived intensity of the stimulus. Such a design allowed us to investigate whether focusing on spatial or intensity features of a nociceptive stimulus and rating its intensity would exert different effects on the EEG responses. We did not find statistical evidence for an effect on the signal while participants were focusing on different features of the signal. We only observed a significant cluster difference in frontoparietal leads at approximately 300-500 ms post-stimulus between the magnitude of the signal in the Intensity and Intensity + Rating conditions, with a less negative response in the Intensity + Rating condition in frontal electrodes, and a less positive amplitude in parietal leads. We speculatively propose that activity in those electrodes and time window reflects magnitude estimation processes. Moreover, the smaller frontal amplitude in the Intensity + Rating condition can be explained by greater working memory engagement known to reduce the magnitude of the EEG signal. We conclude that different top-down attentional processes modulate responses to nociceptive laser stimuli at different electrodes and time windows depending on the underlying processes that are engaged.
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Affiliation(s)
- Diana M E Torta
- Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium.,Health Psychology Research Group, University of Leuven, Leuven, Belgium
| | - Marco Ninghetto
- Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium.,Department of Psychology, University of Turin, Turin, Italy.,Neuroplasticity Laboratory, Nencki Institute for Experimental Biology, Polish Academy of Science, Warsaw, Poland
| | | | - Valéry Legrain
- Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium.,Psychological Sciences Research Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
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6
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Beck B, Gnanasampanthan S, Iannetti GD, Haggard P. No temporal contrast enhancement of simple decreases in noxious heat. J Neurophysiol 2019; 121:1778-1786. [PMID: 30840535 PMCID: PMC6589718 DOI: 10.1152/jn.00335.2018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Offset analgesia (OA) studies have found that small decreases in the intensity of a tonic noxious heat stimulus yield a disproportionately large amount of pain relief. In the classic OA paradigm, the decrease in stimulus intensity is preceded by an increase of equal size from an initial noxious level. Although the majority of researchers believe this temporal sequence of two changes is important for eliciting OA, it has also been suggested that the temporal contrast mechanism underlying OA may enhance detection of simple, isolated decreases in noxious heat. To test whether decreases in noxious heat intensity, by themselves, are perceived better than increases of comparable sizes, we used an adaptive two-interval alternative forced choice task to find perceptual thresholds for increases and decreases in radiant and contact heat. Decreases in noxious heat were more difficult to perceive than increases of comparable sizes from the same initial temperature of 45°C. In contrast, decreases and increases were perceived equally well within a common range of noxious temperatures (i.e., when increases started from 45°C and decreases started from 47°C). In another task, participants rated the pain intensity of heat stimuli that randomly and unpredictably increased, decreased, or remained constant. Ratings of unpredictable stimulus decreases also showed no evidence of perceptual enhancement. Our results demonstrate that there is no temporal contrast enhancement of simple, isolated decreases in noxious heat intensity. Combined with previous OA findings, they suggest that long-lasting noxious stimuli that follow an increase-decrease pattern may be important for eliciting the OA effect. NEW & NOTEWORTHY Previous research suggested that a small decrease in noxious heat intensity feels surprisingly large because of sensory enhancement of noxious stimulus offsets (a simplified form of “offset analgesia”). Using a two-alternative forced choice task where participants detected simple increases or decreases in noxious heat, we showed that decreases in noxious heat, by themselves, are no better perceived than increases of comparable sizes. This suggests that a decrease alone is not sufficient to elicit offset analgesia.
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Affiliation(s)
- Brianna Beck
- Institute of Cognitive Neuroscience, University College London , London , United Kingdom
| | | | - Gian Domenico Iannetti
- Department of Neuroscience, Physiology and Pharmacology, University College London , London , United Kingdom
| | - Patrick Haggard
- Institute of Cognitive Neuroscience, University College London , London , United Kingdom
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7
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Mano H, Kotecha G, Leibnitz K, Matsubara T, Sprenger C, Nakae A, Shenker N, Shibata M, Voon V, Yoshida W, Lee M, Yanagida T, Kawato M, Rosa MJ, Seymour B. Classification and characterisation of brain network changes in chronic back pain: A multicenter study. Wellcome Open Res 2018; 3:19. [PMID: 29774244 PMCID: PMC5930551 DOI: 10.12688/wellcomeopenres.14069.2] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2018] [Indexed: 01/03/2023] Open
Abstract
Background. Chronic pain is a common, often disabling condition thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. Methods. We investigated brain network architecture using resting-state fMRI data in chronic back pain patients in the UK and Japan (41 patients, 56 controls), as well as open data from USA. We applied machine learning and deep learning (conditional variational autoencoder architecture) methods to explore classification of patients/controls based on network connectivity. We then studied the network topology of the data, and developed a multislice modularity method to look for consensus evidence of modular reorganisation in chronic back pain. Results. Machine learning and deep learning allowed reliable classification of patients in a third, independent open data set with an accuracy of 63%, with 68% in cross validation of all data. We identified robust evidence of network hub disruption in chronic pain, most consistently with respect to clustering coefficient and betweenness centrality. We found a consensus pattern of modular reorganisation involving extensive, bilateral regions of sensorimotor cortex, and characterised primarily by negative reorganisation - a tendency for sensorimotor cortex nodes to be less inclined to form pairwise modular links with other brain nodes. Furthermore, these regions were found to display increased connectivity with the pregenual anterior cingulate cortex, a region known to be involved in endogenous pain control. In contrast, intraparietal sulcus displayed a propensity towards positive modular reorganisation, suggesting that it might have a role in forming modules associated with the chronic pain state. Conclusion. The results provide evidence of consistent and characteristic brain network changes in chronic pain, characterised primarily by extensive reorganisation of the network architecture of the sensorimotor cortex.
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Affiliation(s)
- Hiroaki Mano
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
| | - Gopal Kotecha
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kenji Leibnitz
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
| | | | - Christian Sprenger
- Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, UK
| | - Aya Nakae
- Osaka University School of Medicine, Osaka, Japan.,Immunology Frontiers Research Center, Osaka University, Osaka, Japan
| | - Nicholas Shenker
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Valerie Voon
- School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Wako Yoshida
- Advanced Telecommunications Research Center International, Kyoto, Japan
| | - Michael Lee
- School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Toshio Yanagida
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
| | - Mitsuo Kawato
- Advanced Telecommunications Research Center International, Kyoto, Japan
| | - Maria Joao Rosa
- Max-Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Department of Computer Science, University College London, London, UK
| | - Ben Seymour
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan.,Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, UK.,Immunology Frontiers Research Center, Osaka University, Osaka, Japan.,Advanced Telecommunications Research Center International, Kyoto, Japan
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8
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Impact of transcranial direct current stimulation on somatosensory transfer learning: When the secondary somatosensory cortex comes into play. Brain Res 2018; 1689:98-108. [DOI: 10.1016/j.brainres.2018.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2017] [Revised: 03/11/2018] [Accepted: 03/26/2018] [Indexed: 11/22/2022]
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9
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Mano H, Kotecha G, Leibnitz K, Matsubara T, Nakae A, Shenker N, Shibata M, Voon V, Yoshida W, Lee M, Yanagida T, Kawato M, Rosa MJ, Seymour B. Classification and characterisation of brain network changes in chronic back pain: A multicenter study. Wellcome Open Res 2018; 3:19. [DOI: 10.12688/wellcomeopenres.14069.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2018] [Indexed: 11/20/2022] Open
Abstract
Background. Chronic pain is a common, often disabling condition thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. Methods. We investigated brain network architecture using resting-state fMRI data in chronic back pain patients in the UK and Japan (41 patients, 56 controls), as well as open data from USA. We applied machine learning and deep learning (conditional variational autoencoder architecture) methods to explore classification of patients/controls based on network connectivity. We then studied the network topology of the data, and developed a multislice modularity method to look for consensus evidence of modular reorganisation in chronic back pain. Results. Machine learning and deep learning allowed reliable classification of patients in a third, independent open data set with an accuracy of 63%, with 68% in cross validation of all data. We identified robust evidence of network hub disruption in chronic pain, most consistently with respect to clustering coefficient and betweenness centrality. We found a consensus pattern of modular reorganisation involving extensive, bilateral regions of sensorimotor cortex, and characterised primarily by negative reorganisation - a tendency for sensorimotor cortex nodes to be less inclined to form pairwise modular links with other brain nodes. In contrast, intraparietal sulcus displayed a propensity towards positive modular reorganisation, suggesting that it might have a role in forming modules associated with the chronic pain state. Conclusion. The results provide evidence of consistent and characteristic brain network changes in chronic pain, characterised primarily by extensive reorganisation of the network architecture of the sensorimotor cortex.
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10
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Thermosensory Perceptual Learning Is Associated with Structural Brain Changes in Parietal-Opercular (SII) Cortex. J Neurosci 2017; 37:9380-9388. [PMID: 28847806 PMCID: PMC5618259 DOI: 10.1523/jneurosci.1316-17.2017] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Revised: 06/30/2017] [Accepted: 07/31/2017] [Indexed: 01/07/2023] Open
Abstract
The location of a sensory cortex for temperature perception remains a topic of substantial debate. Both the parietal–opercular (SII) and posterior insula have been consistently implicated in thermosensory processing, but neither region has yet been identified as the locus of fine temperature discrimination. Using a perceptual learning paradigm in male and female humans, we show improvement in discrimination accuracy for subdegree changes in both warmth and cool detection over 5 d of repetitive training. We found that increases in discriminative accuracy were specific to the temperature (cold or warm) being trained. Using structural imaging to look for plastic changes associated with perceptual learning, we identified symmetrical increases in gray matter volume in the SII cortex. Furthermore, we observed distinct, adjacent regions for cold and warm discrimination, with cold discrimination having a more anterior locus than warm. The results suggest that thermosensory discrimination is supported by functionally and anatomically distinct temperature-specific modules in the SII cortex. SIGNIFICANCE STATEMENT We provide behavioral and neuroanatomical evidence that perceptual learning is possible within the temperature system. We show that structural plasticity localizes to parietal–opercular (SII), and not posterior insula, providing the best evidence to date resolving a longstanding debate about the location of putative “temperature cortex.” Furthermore, we show that cold and warm pathways are behaviorally and anatomically dissociable, suggesting that the temperature system has distinct temperature-dependent processing modules.
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