Complex regional pain syndrome (CRPS) is a chronic neuropathic pain disorder characterized by hyperexcitability of the central nervous system and hypersensitivity to pain [1, 2]. Sustained pain-related rumination, feeling of helplessness, and magnification of pain intensity are commonly observed symptoms of CRPS [1]. Considering the debilitating effects of CRPS on life quality, CRPS is a critical health problem, necessitating the development of strategies for prevention and intervention [3, 4]. As the central hyper-sensitization underlies the mechanisms of CRPS [2], the pathophysiological mechanisms in the nervous system should be investigated in relation to CRPS symptoms [4-6].

Previous studies have suggested that the chronic pain conditions may be closely related to the functional balance among somatosensory perception, sensory gating, and cognitive control [6-8]. As such, intrinsic functional alterations within and between the somatosensory, salience, attention, and default mode networks have been increasingly reported in chronic pain conditions such as CRPS [6-8]. However, the functional alterations at the whole brain level, as opposed to predefined regions-of-interests (ROIs) or selected large-scale functional networks, remain largely unknown in CRPS.

Pain catastrophizing, conceptualized as a detrimental cognitive process involving pain, is frequently observed in centralized pain conditions [1, 9]. Patients with pain catastrophizing experience symptoms characterized by rumination (sustained focus on pain sensations), helplessness (perceived inability to manage pain), and magnification (exaggerated threat of pain sensations) [1, 9]. Pain catastrophizing is known to be closely related to physical and mental distress, perceived pain intensity, and clinical outcomes of centralized pain conditions such as chronicity and prognosis [9, 10]. Given the clinical significance of pain catastrophizing in CRPS, the functional alterations at the whole brain network level underlying pain catastrophizing may provide additional insights into the pathophysiology of CRPS.

In the current study, we aimed to investigate and compare the differential resting-state functional connectivity patterns between CRPS patients and healthy controls using Network-based Statistics (NBS) analysis. Moreover, the relationships between these functional alterations and the severity of pain catastrophizing were investigated within CRPS patients.

Participants and clinical assessments

The current study included participants reported in our previously published studies [6, 11] consisting of 21 patients diagnosed with CRPS according to the International Association for the Study of Pain criteria (16 men, 5 women; mean age±standard deviation [SD]=37.7±10.9 years) and 49 healthy individuals matched for age and sex (39 men, 10 women; mean age±SD=36.8±9.4 years) [12, 13]. Exclusion criteria were any of the following: having a major medical or neurological disorder; a current diagnosis of Axis 1 psychiatric disorders other than major depressive disorder; contraindication to brain magnetic resonance imaging; a history of traumatic brain injury with loss of consciousness.

The pain-related catastrophic thinking including rumination, helplessness, and magnification was measured using the Pain Catastrophizing Scale (PCS) in all patients diagnosed with CRPS. The PCS is a 13-item questionnaire filled by the patients with a 5-point Likert scale, where higher scores indicate more severe pain catastrophizing, with a total score ranging from 0 to 52 [1].

Patients with CRPS also completed the short-form of the McGill Pain Questionnaire (MPQ), a 15-item report assessing the severity of CRPS-related pain. The MPQ measures the affective (4 items) and sensory (11 items) aspects of CRPS-related pain. The total score ranges from 0 to 45, with higher scores indicating greater pain severity [13].

Written informed consent was provided by all participants. The study protocol was approved by the Institutional Review Board of the Catholic University of Korea College of Medicine.

Brain magnetic resonance imaging acquisition

High-resolution T1-weighted and resting-state functional magnetic resonance imaging (rsfMRI) data were collected using a 3.0 Tesla Magnetic Resonance scanner (Skyra, Siemens, Erlangen, Germany). The acquisition parameters of the T1-weighted images were as follows: repetition time (TR)/echo time (TE), 1900/2.49 ms; flip angle (FA), 9°; field of view (FOV), 230×230 mm²; slice thickness, 0.9 mm; slices, 208. The rsfMRI data were acquired with a T2*-weighted echo planar imaging sequence using the following parameters: TR/TE, 3000/20 ms; FA, 90°; FOV, 192×192 mm²; slice thickness, 3 mm; volumes, 120; slices, 48. The participants were instructed to keep their eyes closed, not to fall asleep, and let mind wander freely during the rsfMRI scan.

Functional connectivity analysis

The CONN toolbox (https://web.conn-toolbox.org) and Statistical Parametric Mapping 12 (SPM12; https://www.fil.ion.ucl.ac.uk/spm) were used for the preprocessing of the rsfMRI data [14].

The T1-weighted images were processed in the following steps: segmentation into grey matter, white matter, and cerebrospinal fluid; normalization into the Montreal Neurological Institute (MNI) space; and resampling into 1-mm isotropic voxels. The rsfMRI images were processed in the following steps: realignment and unwarping; correction for slice timing; scrubbing of outlier volumes; spatial normalization into the MNI space; resampling into 2-mm isotropic voxels. Outlier volumes with a deviation from the mean intensity of the session greater than 5×SD of the average intensity or a framewise displacement larger than 0.9 mm were identified and regressed out using the Artifact Detection Tools (ART; http://www.nitrc.org/projects/artifact_detect).

The processed rsfMRI images were denoised with the linear regression of the potential confounding effects (noise from the white matter and cerebrospinal fluid, estimated subject-level motion parameters, and head motion outlier volumes) using the anatomical component-based noise correction method (aCompCor) [15]. Then, temporal band pass filtering (0.008~0.09 Hz) was applied.

Automated Anatomical Labeling (AAL) atlas (Table 1) was used to define 45 cortical and subcortical regions per hemisphere [16, 17]. The time courses of all voxels within each ROI were extracted and averaged. The bivariate Pearson's correlation coefficients between each pair of the ROIs were computed and converted to z scores using Fisher's r-to-z transformation, generating a 90×90 connectivity matrix for each participant.

Network-based statistics analysis

The generated connectivity matrix was analyzed to identify the network components exhibiting significant differences in functional connectivity between patients with CRPS and healthy controls, using the two-sample t-test adjusting for age and sex with the NBS toolbox (https://www.nitrc.org/projects/nbs) [18]. The NBS is cluster-level statistical test based on graph theory, which controls for multiple comparisons while performing univariate testing [18]. The NBS identifies the network components composed of supra-threshold connections. A permutation testing is then conducted to determine a p value controlled for family-wise error (FWE) for each network based on its size. The initial test statistic threshold was set at a t value of 4.0, and 5,000 permutations were performed to identify a network component with p<0.05 corrected for FWE.

Statistical analysis

Differences in age and sex were assessed between the groups using an independent t-test or chi-squared test, respectively.

Linear regression was used to examine the associations between the mean functional connectivity of the network components with significant group differences and the total scores of the PCS or MPQ in individuals with CRPS. Inter-network connections were investigated using Pearson's correlation coefficients in each group as an auxiliary analysis.

A two-tailed p value of less than 0.05 was considered to indicate statistical significance. All statistical analyses were conducted using the software Stata version 16 (StataCorp., College Station, USA).

Demographic and clinical characteristics

The CRPS patients and healthy controls showed non-significant differences in age (t=-0.33, p=0.74) and sex (χ²=0.10, p=0.75). The mean disease duration was 27.5±25.3 months; PCS score, 34.8±14.4; and MPQ score, 31.1±9.3 (mean±SD). The affected side in CRPS patients was mostly the right side (61.9%), and the most common inciting event was fracture (33.3%). The demographic and clinical characteristics of the study participants are indicated in Table 2.

Network components showing altered functional connectivity

The NBS analysis revealed a total of six network components with significant between-group differences in functional connectivity (Table 3). Compared with healthy controls, CRPS patients showed higher functional connectivity in two subnetworks mainly involving the bilateral somatosensory regions (network components 1 and 2; Fig. 1A). However, CRPS patients showed lower functional connectivity within the prefronto-posterior cingulate cortex (PCC) subnetwork (component 3), the prefrontal cortex subnetwork (component 4), the prefronto-parietal cortex subnetwork (component 5), and the thalamo-anterior cingulate cortex (ACC) subnetwork (component 6), relative to healthy controls (Fig. 1B).

Relationships between functional connectivity and pain-related characteristics

For the post-hoc correlation analysis, the mean connectivity values across the network components with higher functional connectivity (components 1~2) and those with lower functional connectivity (components 3~6) were extracted. We assessed the potential relationships between the altered functional connectivity and the levels of pain catastrophizing in CRPS patients. Higher functional connectivity of the somatosensory subnetworks (components 1~2) were associated with higher PCS scores in CRPS patients (β=0.45, p=0.04) (Fig. 2A). Furthermore, lower levels of functional connectivity across the prefronto-parieto-cingulo-thalamic subnetworks (component 3~6) were associated with higher PCS scores in the CRPS group (β=-0.49, p=0.047; Fig. 2B).

The total MPQ scores did not significantly correlate with the levels of functional connectivity of the network components that were higher (components 1~2, β=0.14, p=0.55) or lower (components 3~6, β=-0.05, p=0.83) in CRPS patients.

Inter-network connections in CRPS patients and healthy controls

As an auxiliary analysis, inter-network connections between the network components that showed significant group differences were estimated in CRPS and control groups. Mean functional connectivity levels of the somatosensory subnetworks (components 1~2) were significantly associated with functional connectivity levels across the prefronto-parieto-cingulo-thalamic subnetworks (component 3~6) in CRPS patients (r=-0.61, p=0.003). However, this relationship was not observed in healthy controls (r=-0.14, p=0.34; Fig. 3).

The current study provides additional insights suggesting that abnormal functional connectivity at subnetwork levels may underlie dysfunctional perception and interpretation of pain in CRPS. We found that CRPS patients showed higher functional connectivity in the somatosensory and lower functional connectivity in the prefronto-parieto-cingulo-thalamic subnetworks, and these functional alterations were related to the level of pain catastrophizing.

We observed a relation between higher levels of functional connectivity within the bilateral somatosensory networks (components 1~2) and more severe pain catastrophizing in CRPS patients. Due to hypervigilant somatosensory perception, neutral sensory stimuli could be exaggerated and interpreted as a pain-related signal, leading to pain catastrophizing in CRPS. In line with the current findings, alterations and hyperactivation within the somatosensory functional network have been reported in chronic pain conditions, including CRPS [5, 19-21]. The postcentral gyrus, as the primary somatosensory cortex involved in localization and discrimination of pain, showed co-activations with other somatosensory regions during motor performance of an affected limb in CRPS and during cognitive processing of neuropathic pain [22, 23]. As in our study, higher functional connectivity in the postcentral, median cingulate, and parieto-occipital cortices may indicate dysfunctional sensory-discriminatory processing over encoded location and the degree of exteroceptive pain signals [24-26]. The heightened connectivity between the somatosensory and precuneus/cingulate cortices involved in interoceptive processing may explain rumination and fixation associated with CRPS-related pain [27].

In contrast, CRPS patients, compared to healthy controls, showed lower functional connectivity within the prefronto-PCC (component 3) subnetwork. The prefronto-PCC regions are key node regions of the default mode network involved in interoceptive processing [27, 28]. The PCC as a hub related to self-referential cognition engages in regulating arousal and internal or external focus of attention [5, 7, 27]. Lower functional connectivity in the default mode network may implicate dysfunctional interoceptive processing of the pain-related signals, potentially leading to rumination, helplessness, and magnification seen in CRPS [5, 7, 27]. This is further supported by previously reported associations between default mode dysfunction and rumination in chronic pain conditions [27, 29] and other studies on patients with depression and healthy individuals [30, 31]. In line with the current findings, the structural and functional alterations within the default mode network have been reported in chronic pain conditions [7, 27, 32, 33].

Lower functional connectivity within the prefrontal (component 4) regions including the medial frontal and dorsolateral frontal cortices was reported to underlie pain catastrophizing in CRPS patients. The prefrontal regions involved in cognitive and affective processing of pain are anatomically connected to the descending pain modulatory system [27, 34]. Accordingly, functional alterations in the medial frontal regions related to pain anticipation, dorsolateral prefrontal regions involved in pain attention, and frontal regions engaged in emotional pain processing were reported in relation to pain catastrophizing [34, 35]. Manifested as lower functional connectivity within the prefrontal cortex, dysfunctional top-down cognitive control of somatosensory perception may potentially lead to pain catastrophizing characterized by rumination, helplessness, and magnification in CRPS [5, 7, 27]. The current findings are in alignment with the structural and functional alterations within the prefrontal regions reported in chronic pain conditions [22, 36].

Moreover, CRPS patients, compared with healthy controls, showed lower functional connectivity within the bilateral prefronto-parietal (component 5) subnetwork. The left-lateralized and right-lateralized frontoparietal networks, which showed functional hypoconnectivity in CRPS, engage in cognitive attention and perception-somesthesis-pain processing, respectively [28]. In accordance with the present findings, an altered functional connectivity within the frontoparietal networks was reported in chronic pain conditions including CRPS [6, 33, 37]. The previously reported association between functional hypoconnectivity in the right frontoparietal network and more severe pain catastrophizing in CRPS further supports the current findings [6]. Lower functional connectivity in the left and right prefronto-parietal subnetworks may suggest dysfunctional attentional control and pain processing, respectively, leading to pain catastrophizing in CRPS [6, 33, 37].

Furthermore, the lower thalamo-ACC functional connectivity reported in CRPS patients (component 6) is in line with the previous literature reporting thalamo-cingulate hypoconnectivity in chronic pain [5]. The thalamus as a hub in sensory gating relays nociceptive information from the subcortical structures to the ACC through the afferent pain pathways; then, the ACC engages in motivational-affective processing of pain perception, particularly in subjective processing of pain [38-40]. The ACC related to cognitive and emotional attention to pain may exaggerate exteroceptive signals from the olfactory cortex and putamen, leading to magnification of pain signals in CRPS [5, 38-40]. Due to a hypoconnectivity and miscommunication within the thalamo-cingulate network, the ACC may subjectively misinterpret exteroceptive somatosensory signals received from the thalamus, leading to catastrophizing of CRPS-related pain [5, 38-40].

Alterations in functional connectivity observed in CRPS patients were correlated with the levels of pain catastrophizing. Moreover, the levels of functional connectivity within specific subnetworks that showed increases or decreases in CRPS patients were inter-correlated. The heightened somatosensory and lower functional connectivity within the prefronto-parieto-cingulo-thalamic networks observed in relation to higher pain catastrophizing may imply dysfunctions in exteroceptive and interoceptive processing of the pain stimuli underlying CRPS, respectively [5-7, 40, 41]. As such, externally somatosensory perception and internally motivational-affective-cognitive processing may closely interact for adaptive regulation of the pain [5-7, 40, 41]. In contrast, the functional mismatch and imbalance within and between externally somatosensory perception and internally motivational-affective-cognitive processing may potentially lead to magnification, rumination, and helplessness in CRPS [5-7, 40, 41]. This interpretation is supported by heighted inter-network correlations between the salience and attention networks in relation to higher levels of pain catastrophizing in CRPS [6]. Moreover, the functional alterations within and between the sensorimotor, salience, and attention networks are suggested to underlie cognitive dysfunctions including pain catastrophizing [42-44].

The following limitations of this study should be considered. Due to the cross-sectional nature and small number of CRPS patients, generalizability and causality of the CRPS-related brain functional alterations reported at subnetwork levels may be limited in the current study. The causal relationship between the CRPS-related functional alterations in the somatosensory and prefronto-parieto-cingulo-thalamic subnetworks and pain catastrophizing should be investigated further in larger longitudinal studies of CRPS. In addition, the assessment of the severity of CRPS based on a questionnaire filled by the participants may be subjective with potential bias, necessitating future studies relying on objective measures of CRPS symptoms. Lastly, further studies comparing functional brain changes of CRPS with those of other centralized chronic pain conditions are warranted to evaluate the specificity of the current findings.

In conclusion, increased functional connectivity in the somatosensory subnetworks and decreased functional connectivity within the prefronto-parieto-cingulo-thalamic subnetworks were observed in CRPS patients and associated with higher levels of pain catastrophizing. Our findings indicate that the functional balance within and between externally somatosensory perception and internally cognitive-affective-motivational processing of pain may be of significance in future research on the pathophysiology of CRPS. The above-mentioned brain networks could be potential targets for CRPS treatment such as non-invasive brain stimulation, by modulating altered functional connectivity and abnormal pain processing.

This research was supported by the National Research Foundation of Korea funded by the Korean government (NRF-2020M3E5D9080555 and NRF-2020R1A6A1A03043528 to I.K.L. and NRF-2020R1A2C2005901 to S.Y.).

Regions defined in the Automated Anatomical Labeling (AAL) atlas

Demographic and clinical characteristics of study participants

Brain network components with significant differences in functional connectivity between CRPS patients and healthy controls