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Recently, Hu Li's research group of the Key Laboratory of Mental Health of the Chinese Academy of Sciences used EEG and functional magnetic resonance imaging technology to reveal stable and specific neural indicators
of pain resolution 。 The results have been published online in Cell Reports Medicine under the title Selective and Replicable Neuroimaging-based Indicators of Pain Discriminability
.
that humans cannot ignore.
For individuals, the endless pain caused by pain can lead to depression and even suicide; For the whole society, the prevalence of chronic pain is as high as 20%~50%, causing economic losses
of more than hundreds of billions of yuan to China every year.
In order to more effectively promote the development of analgesic methods to eliminate pain, it is necessary to deeply understand the neural processing mechanisms of pain and develop objective neurological indicators
of pain.
However, most pain-stimulus-induced brain responses are not pain-specific [1,2] and therefore cannot be used as pain-specific neuromarkers
in clinical applications.
To solve this problem, Hu Li's research group creatively distinguishes pain sensitivity into two separate concepts
: absolute sensitivity and differential sensitivity.
Absolute pain sensitivity describes differences in individual perception of the same painful stimulus, while differential pain sensitivity (or pain resolution) represents an individual's ability to
distinguish between different painful stimuli 。 Studies have often explored only the relationship between pain-induced brain responses and absolute pain sensitivity, ignoring which neural responses reflect differential pain sensitivity, even though there has been a strong association between differential pain sensitivity and chronic pain [3,4].
To compensate for this shortcoming, Hu's research group conducted an EEG study and a functional magnetic resonance imaging study, using signal detection theory to quantify sensory resolution, examine which neural indicators reflect pain resolution, and examine the reproducibility and pain specificity
of these neural indicators in five large data sets.
The EEG study included three large datasets (dataset 1~3, total N = 366).
Each dataset uses the same experimental task: the participants are stimulated by four sensory modalities: pain, touch, hearing and vision, each of which has two intensities, high and low, and finally requires the participants to make a subjective intensity score
of 0~10 for the stimulus.
The results show that in Dataset 1, the difference in N1, N2, and P2 amplitudes (high-low) induced by high- and low-intensity pain stimuli is significantly correlated with pain resolution index (AUC) based on signal detection theory (Figure 1).
This finding is well replicated
in datasets 2 and 3.
On the other hand, the difference in amplitude (high-low) between high and low intensity is not strongly correlated with the corresponding tactile, auditory, and visual resolution (Figure 2).
In-depth analysis ruled out possible confounding factors: switching to different resolution indicators (AUC, d′, score differences at high and low stimulus intensities), matching subjective score differences between different modalities, and matching AUC indicators with different modalities did not change the main results, and only EEG responses in pain modalities had a stable correlation
with resolution.
Figure 1.
Pain-induced EEG responses are associated with stable resolution
Figure 2.
Non-painful stimuli induce EEG response and are not stable in resolution
with EEG studies.
The study contained two large datasets (datasets 4 and 5, total N = 399), and the experimental task also required participants to subjectively score
sensory stimuli of different modalities and intensities.
The analysis results of dataset 4 showed that the activation differences (high-low) of a series of brain regions at high and low intensity, such as the primary somatosensory cortex, the secondary somatosensory cortex, the insula, the anterior cingulate gyrus, and the thalamus, were significantly correlated with pain resolution (Figure 3).
This result is also replicated
in dataset 5.
However, unlike pain modalities, few voxels in tactile, auditory, and visual modalities correlate with corresponding resolution (Figure 4).
Switching to different resolution indicators and matching subjective scores between different modalities still yielded consistent results
.
It can be seen that the activation of brain regions induced by painful stimuli can specifically reflect pain resolution
.
Figure 3.
Pain-induced activation of brain regions is associated with stable resolution
Figure 4.
Non-painful stimulation induces brain activation and is not stable in resolution
of pain perception and its internal mechanism.
Previous studies have demonstrated abnormalities in pain resolution in patients with chronic pain, and pain resolution prior to treatment can predict the prognosis of chronic pain [3,4].
Therefore, the neural indicators of pain resolution found in this study also provide important enlightenment
for the diagnosis and treatment of chronic pain and individualized pain assessment in clinical practice.
The research was supported by the National Natural Science Foundation of China (32071061, 31822025, 32171077), the Natural Science Foundation of Beijing Municipality (JQ22018), the Science and Technology Innovation 2030-"Brain Science and Brain-like Research" Young Scientist Program of the Ministry of Science and Technology (2022ZD0206400), and the Science Foundation of the Institute of Psychology, Chinese Academy of Sciences (E2CX4015
).
The first author of the paper is Zhang Libo, a doctoral student in the Institute of Psychology, and the corresponding author is researcher
Hu Li.
Information on papers: Zhang LB, Lu XJ, Huang G, Zhang HJ, Tu YH, Kong YZ, & Hu L.
(2022).
Selective and replicable neuroimaging-based indicators of pain discriminability, Cell Reports Medicine, https://doi.
org/10.
1016/j.
xcrm.
2022.
100846 references: 1.
Mouraux, A.
, & Iannetti, G.
D.
(2009).
Nociceptive laser-evoked brain potentials do not reflect nociceptive-specific neural activity.
Journal of Neurophysiology, 101(6), 3258–3269.
2.
Mouraux, A.
, Diukova, A.
, Lee, M.
C.
, Wise, R.
G.
, & Iannetti, G.
D.
(2011).
A multisensory investigation of the functional significance of the “pain matrix.
” NeuroImage, 54(3), 2237–2249.
3.
Naliboff, B.
D.
, Cohen, M.
J.
, Schandler, S.
L.
, & Heinrich, R.
L.
(1981).
Signal detection and threshold measures for chronic back pain patients, chronic illness patients, and cohort controls to radiant heat stimuli.
Journal of Abnormal Psychology, 90(3), 271–274.
4.
Malow, R.
M.
, & Olson, R.
E.
(1981).
Changes in pain perception after treatment for chronic pain.
Pain, 11(1), 65–72.
Source:
Key Laboratory of Mental Health, Chinese Academy of Sciences
Hu Li Research Group
