Identifying resting state differences salient for resilience to chronic pain based on machine learning multivariate pattern analysis

You, Beibei; Wen, Hongwei; Jackson, Todd

doi:10.1111/psyp.13921

Cited by 15 publications

(11 citation statements)

References 103 publications

(114 reference statements)

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“…This is consistent with previous studies focused on cognitive-affective processes of pain ( Gentili et al, 2019 ; Gonzalez et al, 2019 ; You et al, 2021 ). You et al (2021) demonstrated the existence of pain-specific resilience, referring to the ability to maintain relatively stable and healthy levels of psychological functioning in face of ongoing and persistent pain ( You et al, 2021 ).…”

Section: Discussionsupporting

confidence: 93%

“… You et al (2021) demonstrated the existence of pain-specific resilience, referring to the ability to maintain relatively stable and healthy levels of psychological functioning in face of ongoing and persistent pain ( You et al, 2021 ). Sociodemographic ( Tanner et al, 2021 ), structural and functional MRI ( Tanner et al, 2021 ; You et al, 2021 ), clinical pain symptoms, negative pain-related emotions, and PC ( Sturgeon and Zautra, 2013 ; Gonzalez et al, 2019 ) have been related to resilience and better outcomes in the presence of recurrent pain, while to our knowledge, this is the first study to explore the interaction between all these variables.…”

Section: Discussionmentioning

confidence: 99%

“…Also, the neural correlates of these phenomena have been explored in multiple studies. Altered brain connectivity in pain disorders in task-oriented and resting-state functional magnetic resonance imaging (rs-fMRI) has been shown altered in the presence of acute and CP ( Baliki et al, 2014 ; Kucyi et al, 2014 ; Yu et al, 2014 ; Hemington et al, 2016 ; Pfannmöller and Lotze, 2019 ; Spisak et al, 2019 ; You et al, 2021 ; De Ridder et al, 2022 ; Solé-Padullés et al, 2022 ). Crucially it has been suggested that two specific main large-scale brain networks are related to altered pain processing and pain chronification: the dorsoattentional network (DAN), and the default mode network (DMN) ( Spreng et al, 2013 ; Baliki et al, 2014 ; Becerra et al, 2014 ; Kucyi et al, 2014 ; Kilpatrick et al, 2015 ; Seidler et al, 2015 ; Franzmeier et al, 2017 ; Kim et al, 2019 ; van Ettinger-Veenstra et al, 2019 ; Jones et al, 2020 ; De Ridder et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Brain system segregation and pain catastrophizing in chronic pain progression

et al. 2023

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Pain processing involves emotional and cognitive factors that can modify pain perception. Increasing evidence suggests that pain catastrophizing (PC) is implicated, through pain-related self-thoughts, in the maladaptive plastic changes related to the maintenance of chronic pain (CP). Functional magnetic resonance imaging (fMRI) studies have shown an association between CP and two main networks: default mode (DMN) and dorsoattentional (DAN). Brain system segregation degree (SyS), an fMRI framework used to quantify the extent to which functional networks are segregated from each other, is associated with cognitive abilities in both healthy individuals and neurological patients. We hypothesized that individuals suffering from CP would show worst health-related status compared to healthy individuals and that, within CP individuals, longitudinal changes in pain experience (pain intensity and affective interference), could be predicted by SyS and PC subdomains (rumination, magnification, and helplessness). To assess the longitudinal progression of CP, two pain surveys were taken before and after an in-person assessment (physical evaluation and fMRI). We first compared the sociodemographic, health-related, and SyS data in the whole sample (no pain and pain groups). Secondly, we ran linear regression and a moderation model only in the pain group, to see the predictive and moderator values of PC and SyS in pain progression. From our sample of 347 individuals (mean age = 53.84, 55.2% women), 133 responded to having CP, and 214 denied having CP. When comparing groups, results showed significant differences in health-related questionnaires, but no differences in SyS. Within the pain group, helplessness (β = 0.325; p = 0.003), higher DMN (β = 0.193; p = 0.037), and lower DAN segregation (β = 0.215; p = 0.014) were strongly associated with a worsening in pain experience over time. Moreover, helplessness moderated the association between DMN segregation and pain experience progression (p = 0.003). Our findings indicate that the efficient functioning of these networks and catastrophizing could be used as predictors of pain progression, bringing new light to the influence of the interplay between psychological aspects and brain networks. Consequently, approaches focusing on these factors could minimize the impact on daily life activities.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Brain system segregation and pain catastrophizing in chronic pain progression

et al. 2023

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“…ALFF maps were used to classify chronic low back pain patients and controls with a moderate discriminate performance (accuracy rate >70%) ( 29 ). In addition, ReHo maps showed poor performance in classifying the more resilient chronic pain patients from the less resilient chronic pain patients (accuracy rate = 55%); however, the accuracy rate of combined ReHo and fractional ALFF achieved 79% ( 30 ). In the present study, the combined ALFF and ReHo showed satisfactory classification performance (accuracy rate = 93.7%) between BMP patients and HCs, which is comparable with the classification performance of FC maps.…”

Section: Discussionmentioning

confidence: 94%

Altered brain functional activity and connectivity in bone metastasis pain of lung cancer patients: A preliminary resting-state fMRI study

et al. 2022

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Bone metastasis pain (BMP) is one of the most prevalent symptoms among cancer survivors. The present study aims to explore the brain functional activity and connectivity patterns in BMP of lung cancer patients preliminarily. Thirty BMP patients and 33 healthy controls (HCs) matched for age and sex were recruited from inpatients and communities, respectively. All participants underwent fMRI data acquisition and pain assessment. Low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) were applied to evaluate brain functional activity. Then, functional connectivity (FC) was calculated for the ALFF- and ReHo-identified seed brain regions. A two-sample t-test or Manny–Whitney U-test was applied to compare demographic and neuropsychological data as well as the neuroimaging indices according to the data distribution. A correlation analysis was conducted to explore the potential relationships between neuroimaging indices and pain intensity. Receiver operating characteristic curve analysis was applied to assess the classification performance of neuroimaging indices in discriminating individual subjects between the BMP patients and HCs. No significant intergroup differences in demographic and neuropsychological data were noted. BMP patients showed reduced ALFF and ReHo largely in the prefrontal cortex and increased ReHo in the bilateral thalamus and left fusiform gyrus. The lower FC was found within the prefrontal cortex. No significant correlation between the neuroimaging indices and pain intensity was observed. The neuroimaging indices showed satisfactory classification performance between the BMP patients and HCs, and the combined ALFF and ReHo showed a better accuracy rate (93.7%) than individual indices. In conclusion, altered brain functional activity and connectivity in the prefrontal cortex, fusiform gyrus, and thalamus may be associated with the neuropathology of BMP and may represent a potential biomarker for classifying BMP patients and healthy controls.

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“…Resilience and 'mental toughness' are similar concepts and the two terms are used interchangeably in our review. Resilience and mental toughness convey benefits across the lifespan, from childhood (11) to older adulthood (12), and it is implicated as a positive influence in outcomes as diverse as infectious disease (13), cardiometabolic health (14), cancer (15), pain (16), and mental and cognitive health (17). As mentioned above, many of these processes are also, in some way, related to sleep.…”

Section: Introductionmentioning

confidence: 99%