Prospective Blood Transcriptomics Study in a Motor Vehicle Collision Cohort Identified a Protective Function of the SAMD15 Gene Against Chronic Pain.

Traumatic brain injuries following motor vehicle collisions (MVCs) are ubiquitous. Surprisingly, there are no correlates between concussion impact force and long-term pain outcomes. To study the molecular underpinnings of chronic pain after MVC, we assembled a prospective cohort of 36 subjects that experienced MVC and suffered documented mild traumatic brain injuries. For each participant, a first blood sample was drawn within 72 hours of the collision, then a second one at the 6-month mark. Pain was also assessed at the second blood draw to determine if pain became chronic or resolved. Blood samples enabled transcriptomics analyses for immune cells. At the transcriptome-wide level, we found that Sterile Alpha Motif Domain Containing 15 (SAMD15) mRNA was significantly upregulated with time in subjects who resolved their pain whereas unregulated in those with persistent pain. Using several large publicly available datasets, such as the UK Biobank and the GTeX portal, we then linked elevated SAMD15 gene expression, elevated neutrophils cell counts, and decreased risk for chronic pain to increased dosage of the T allele at SNP rs4903580, situated within SAMD15's gene locus. The causality between the components of our model was established and supported by Mendelian randomization. Overall, our results support the role of SAMD15 as a potential gene effector for neutrophil-dependent chronic pain development. PERSPECTIVE: This article highlights the potential protective role of the SAMD15 gene against chronic pain following a mild traumatic brain injury. The expression of the gene is associated with a SNP rs4903580, which is itself associated with neutrophils counts as well as chronic pain in large genetic studies.

"Feeling Unwanted, When Nobody Wants You Around": Perceptions of Social Pain Among People With Autism.

IMPORTANCE: A paucity of studies have focused on pain experiences among people with autism spectrum disorder, particularly those addressing social pain in daily life contexts or learning from the perspective of autistic people. OBJECTIVE: To explore the social pain experience of autistic people. DESIGN: A descriptive qualitative design followed by deductive thematic analysis. Interviews were semistructured to capture the social pain experience, coping strategies, and implications for the participation of autistic people. SETTING: Online interviews using Zoom videoconferencing software. PARTICIPANTS: Fifteen autistic people were recruited for the study using purposeful and criterion sampling. RESULTS: Four primary themes emerged from the data analysis: (1) a definition of social pain and the distinction between social pain and other types of pain; (2) the sources-internal, external, and combined-of social pain; (3) the loneliness outcome, which echoes the gap between the desire for and lack of social contacts; and (4) coping strategies pertaining to the continuum between inward and outward coping strategies to deal with social pain. CONCLUSION AND RELEVANCE: The study indicates the existence of a discrepancy between autistic people's need for social interactions and the social pain they experience. It calls for intervention programs for autistic people to improve their coping strategies and promote their self-acceptance and better inclusion in the community. What This Article Adds: Promoting social functioning is a prime role of occupational therapists, and this article adds a novel theoretical model that contributes to that role. The model represents the social pain experiences of autistic people and their strategies to overcome this phenomenon. Firsthand accounts of autistic people regarding social pain enable a better understanding of their desire to be involved in the social context. This study suggests directions for further intervention programs to assist autistic people in fulfilling their wish for social relationships and enabling their enhanced integration into society. Positionality Statement: We recognize that use of person-first versus identity-first language is a source of debate and controversy. We have chosen to use identity-first language for two reasons. First, studies indicate person with autism is the term least preferred by autistic people (Botha et al., 2021). Second, autistic is the term used by the majority of our participants during interviews.

Indifference or hypersensitivity? Solving the riddle of the pain profile in individuals with autism.

ABSTRACT: Excitatory-inhibitory (E/I) imbalance is a mechanism that underlies autism spectrum disorder, but it is not systematically tested for pain processing. We hypothesized that the pain modulation profile (PMP) in autistic individuals is characterized by less efficient inhibitory processes together with a facilitative state, indicative of a pronociceptive PMP. Fifty-two adults diagnosed with autism and 52 healthy subjects, age matched and sex matched, underwent quantitative sensory testing to assess the function of the (1) pain facilitatory responses to phasic, repetitive, and tonic heat pain stimuli and (2) pain inhibitory processes of habituation and conditioned pain modulation. Anxiety, pain catastrophizing, sensory, and pain sensitivity were self-reported. The autistic group reported significantly higher pain ratings of suprathreshold single ( P = 0.001), repetitive (46°C- P = 0.018; 49°C- P = 0.003; 52°C- P < 0.001), and tonic ( P = 0.013) heat stimuli that were cross correlated ( r = 0.48-0.83; P < 0.001) and associated with sensitivity to daily life pain situations ( r = 0.39-0.45; P < 0.005) but not with psychological distress levels. Hypersensitivity to experimental pain was attributed to greater autism severity and sensory hypersensitivity to daily stimuli. Subjects with autism efficiently inhibited phasic but not tonic heat stimuli during conditioned pain modulation. In conclusion, in line with the E/I imbalance mechanism, autism is associated with a pronociceptive PMP expressed by hypersensitivity to daily stimuli and experimental pain and less-efficient inhibition of tonic pain. The latter is an experimental pain model resembling clinical pain. These results challenge the widely held belief that individuals with autism are indifferent to pain and should raise caregivers' awareness of pain sensitivity in autism.

Structural brain connectivity predicts early acute pain after mild traumatic brain injury.

ABSTRACT: Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site-namely, conditioned pain modulation and magnitude of suprathreshold pain-and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

Electroencephalography functional connectivity-A biomarker for painful polyneuropathy.

BACKGROUND AND PURPOSE: Advanced analysis of electroencephalography (EEG) data has become an essential tool in brain research. Based solely on resting state EEG signals, a data-driven, predictive and explanatory approach is presented to discriminate painful from non-painful diabetic polyneuropathy (DPN) patients. METHODS: Three minutes long, 64 electrode resting-state recordings were obtained from 180 DPN patients. The analysis consisted of a mixture of traditional, explanatory and machine learning analyses. First, the 10 functional bivariate connections best differentiating between painful and non-painful patients in each EEG band were identified and the relevant receiver operating characteristic was calculated. Later, those connections were correlated with selected clinical parameters. RESULTS: Predictive analysis indicated that theta and beta bands contain most of the information required for discrimination between painful and non-painful polyneuropathy patients, with area under the receiver operating characteristic curve values of 0.93 for theta and 0.89 for beta bands. Assessing statistical differences between the average magnitude of functional connectivity values and clinical pain parameters revealed that painful DPN patients had significantly higher cortical functional connectivity than non-painful ones (p = 0.008 for theta and p = 0.001 for alpha bands). Moreover, intra-band analysis of individual significant functional connections revealed a positive correlation with average reported pain in the previous 3 months in all frequency bands. CONCLUSIONS: Resting state EEG functional connectivity can serve as a highly accurate biomarker for the presence or absence of pain in DPN patients. This highlights the importance of the brain, in addition to the peripheral lesions, in generating the clinical pain picture. This tool can probably be extended to other pain syndromes.

Resting-state functional connectivity predicts motor cortex stimulation-dependent pain relief in fibromyalgia syndrome patients.

MRI-based resting-state functional connectivity (rsFC) has been shown to predict response to pharmacological and non-pharmacological treatments for chronic pain, but not yet for motor cortex transcranial magnetic stimulation (M1-rTMS). Twenty-seven fibromyalgia syndrome (FMS) patients participated in this double-blind, crossover, and sham-controlled study. Ten daily treatments of 10 Hz M1-rTMS were given over 2 weeks. Before treatment series, patients underwent resting-state fMRI and clinical pain evaluation. Significant pain reduction occurred following active, but not sham, M1-rTMS. The following rsFC patterns predicted reductions in clinical pain intensity after the active treatment: weaker rsFC of the default-mode network with the middle frontal gyrus (r = 0.76, p < 0.001), the executive control network with the rostro-medial prefrontal cortex (r = 0.80, p < 0.001), the thalamus with the middle frontal gyrus (r = 0.82, p < 0.001), and the pregenual anterior cingulate cortex with the inferior parietal lobule (r = 0.79, p < 0.001); and stronger rsFC of the anterior insula with the angular gyrus (r = - 0.81, p < 0.001). The above regions process the attentional and emotional aspects of pain intensity; serve as components of the resting-state networks; are modulated by rTMS; and are altered in FMS. Therefore, we suggest that in FMS, the weaker pre-existing interplay between pain-related brain regions and networks, the larger the pain relief resulting from M1-rTMS.

Brain Connectivity Predicts Chronic Pain in Acute Mild Traumatic Brain Injury.

OBJECTIVES: Previous studies have established the role of the cortico-mesolimbic and descending pain modulation systems in chronic pain prediction. Mild traumatic brain injury (mTBI) is an acute pain model where chronic pain is prevalent and complicated for prediction. In this study, we set out to study whether functional connectivity (FC) of the nucleus accumbens (NAc) and the periaqueductal gray matter (PAG) is predictive of pain chronification in early-acute mTBI. METHODS: To estimate FC, resting-state functional magnetic resonance imaging (fMRI) of 105 participants with mTBI following a motor vehicle collision was acquired within 72 hours post-accident. Participants were classified according to pain ratings provided at 12-months post-collision into chronic pain (head/neck pain ≥30/100, n = 44) and recovery (n = 61) groups, and their FC maps were compared. RESULTS: The chronic pain group exhibited reduced negative FC between NAc and a region within the primary motor cortex corresponding with the expected representation of the area of injury. A complementary pattern was also demonstrated between PAG and the primary somatosensory cortex. PAG and NAc also shared increased FC to the rostral anterior cingulate cortex (rACC) within the recovery group. Brain connectivity further shows high classification accuracy (area under the curve [AUC] = .86) for future chronic pain, when combined with an acute pain intensity report. INTERPRETATION: FC features obtained shortly after mTBI predict its transition to long-term chronic pain, and may reflect an underlying interaction of injury-related primary sensorimotor cortical areas with the mesolimbic and pain modulation systems. Our findings indicate a potential predictive biomarker and highlight targets for future early preventive interventions. ANN NEUROL 2022;92:819-833.

"When I'm in Pain, Everything Is Overwhelming": Implications of Pain in Adults With Autism on Their Daily Living and Participation.

Pain sensation in autism spectrum disorder (ASD) has been a growing research field in the last two decades. Existing pain research has focused on pain sensitivity, suggesting either hyposensitivity or hypersensitivity to pain in individuals with ASD. However, research about other aspects of pain experience is scarce. Moreover, most pain-related research in ASD focused on quantitative measures, such as neuroimaging or parental reports. Instead, this paper aimed to illuminate the various aspects of pain experience as perceived by adults with ASD. Its descriptive qualitative research design incorporated semi-structured interviews and deductive thematic analysis. This phenomenological approach captured the subjective pain experience through the lens of people with ASD. Four primary themes emerged from the data: (a) physical pain experience, including the sequence of pain sensitivity, pain awareness, pain-related emotional aspects, and pain communication; (b) direct and indirect coping strategies; (c) function and participation outcomes; and (d) suggestions for Healthcare Providers. The findings echo the crucial role of pain awareness and communication in the pain experience of people with ASD. These two factors have been reported as profoundly influencing coping strategies, function, and participation. The results emphasize the need to expand the exploration of pain in this population, calling for greater understanding, and listening to this population's unique pain profiles and experiences to promote better-suited evaluation, diagnosis, and intervention in pain conditions.

Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts.

BACKGROUND: To improve the treatment of painful Diabetic Peripheral Neuropathy (DPN) and associated co-morbidities, a better understanding of the pathophysiology and risk factors for painful DPN is required. Using harmonised cohorts (N = 1230) we have built models that classify painful versus painless DPN using quality of life (EQ5D), lifestyle (smoking, alcohol consumption), demographics (age, gender), personality and psychology traits (anxiety, depression, personality traits), biochemical (HbA1c) and clinical variables (BMI, hospital stay and trauma at young age) as predictors. METHODS: The Random Forest, Adaptive Regression Splines and Naive Bayes machine learning models were trained for classifying painful/painless DPN. Their performance was estimated using cross-validation in large cross-sectional cohorts (N = 935) and externally validated in a large population-based cohort (N = 295). Variables were ranked for importance using model specific metrics and marginal effects of predictors were aggregated and assessed at the global level. Model selection was carried out using the Mathews Correlation Coefficient (MCC) and model performance was quantified in the validation set using MCC, the area under the precision/recall curve (AUPRC) and accuracy. RESULTS: Random Forest (MCC = 0.28, AUPRC = 0.76) and Adaptive Regression Splines (MCC = 0.29, AUPRC = 0.77) were the best performing models and showed the smallest reduction in performance between the training and validation dataset. EQ5D index, the 10-item personality dimensions, HbA1c, Depression and Anxiety t-scores, age and Body Mass Index were consistently amongst the most powerful predictors in classifying painful vs painless DPN. CONCLUSIONS: Machine learning models trained on large cross-sectional cohorts were able to accurately classify painful or painless DPN on an independent population-based dataset. Painful DPN is associated with more depression, anxiety and certain personality traits. It is also associated with poorer self-reported quality of life, younger age, poor glucose control and high Body Mass Index (BMI). The models showed good performance in realistic conditions in the presence of missing values and noisy datasets. These models can be used either in the clinical context to assist patient stratification based on the risk of painful DPN or return broad risk categories based on user input. Model's performance and calibration suggest that in both cases they could potentially improve diagnosis and outcomes by changing modifiable factors like BMI and HbA1c control and institute earlier preventive or supportive measures like psychological interventions.

Neurofeedback Therapy for Sensory Over-Responsiveness-A Feasibility Study.

Background: Difficulty in modulating multisensory input, specifically the sensory over-responsive (SOR) type, is linked to pain hypersensitivity and anxiety, impacting daily function and quality of life in children and adults. Reduced cortical activity recorded under resting state has been reported, suggestive of neuromodulation as a potential therapeutic modality. This feasibility study aimed to explore neurofeedback intervention in SOR. Methods: Healthy women with SOR (n = 10) underwent an experimental feasibility study comprising four measurement time points (T1­baseline; T2­preintervention; T3­postintervention; T4­follow-up). Outcome measures included resting-state EEG recording, in addition to behavioral assessments of life satisfaction, attaining functional goals, pain sensitivity, and anxiety. Intervention targeted the upregulation of alpha oscillatory power over ten sessions. Results: No changes were detected in all measures between T1 and T2. Exploring the changes in brain activity between T2 and T4 revealed power enhancement in delta, theta, beta, and gamma oscillatory bands, detected in the frontal region (p = 0.03−<0.001; Cohen's d = 0.637−1.126) but not in alpha oscillations. Furthermore, a large effect was found in enhancing life satisfaction and goal attainment (Cohen's d = 1.18; 1.04, respectively), and reduced pain sensitivity and anxiety trait (Cohen's d = 0.70). Conclusion: This is the first study demonstrating the feasibility of neurofeedback intervention in SOR.

Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity.

Pain variability can be partially attributed to psycho-cognitive features involved in its processing. However, accumulating research suggests that simple linear correlation between situational and dispositional factors may not be sufficiently explanatory, with some positing a role for mediating influences. In addition, acute pain processing studies generally focus on a post-operative model with less attention provided to post-traumatic injury. As such, this study aimed to investigate a more comprehensive pain processing model that included direct and indirect associations between acute pain intensity in the head and neck, pain catastrophizing (using pain catastrophizing scale (PCS)), and pain sensitivity (using the pain sensitivity questionnaire (PSQ)), among 239 patients with post-motor vehicle collision pain. The effect of personality traits (using Ten Items Personality Inventory (TIPI)) and emotional status (using Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS)) on that model was examined as well. To this end, three Structural Equation Modeling (SEM) analyses were conducted. Overall, the data had good fit to all the models, with only PSQ found to have a direct correlation with acute pain intensity. The SEM analyses conversely revealed several mediations. Specifically, that: first, PSQ fully mediated the relationship between PCS and pain intensity; second, PCS and PSQ together fully mediated the relationship between conscientiousness (personality trait) and pain intensity; and finally, emotional status had direct and indirect links with PSQ and pain intensity. In conclusion, these models suggest that during the acute post-collision phase, pain sensitivity intermediates between emotional states and personality traits, partially via elevated pain catastrophizing thoughts.

Conditioned pain modulation is more efficient in patients with painful diabetic polyneuropathy than those with nonpainful diabetic polyneuropathy.

ABSTRACT: Endogenous pain modulation, as tested by the conditioned pain modulation (CPM) protocol, is typically less efficient in patients with chronic pain compared with healthy controls. We aimed to assess whether CPM is less efficient in patients with painful diabetic polyneuropathy (DPN) compared with those with nonpainful DPN. Characterization of the differences in central pain processing between these 2 groups might provide a central nervous system explanation to the presence or absence of pain in diabetic neuropathy in addition to the peripheral one. Two hundred seventy-one patients with DPN underwent CPM testing and clinical assessment, including quantitative sensory testing. Two modalities of the test stimuli (heat and pressure) conditioned to cold noxious water were assessed and compared between patients with painful and nonpainful DPN. No significant difference was found between the groups for pressure pain CPM; however, patients with painful DPN demonstrated unexpectedly more efficient CPMHEAT (-7.4 ± 1.0 vs -2.3 ± 1.6; P = 0.008). Efficient CPMHEAT was associated with higher clinical pain experienced in the 24 hours before testing (r = -0.15; P = 0.029) and greater loss of mechanical sensation (r = -0.135; P = 0.042). Moreover, patients who had mechanical hypoesthesia demonstrated more efficient CPMHEAT (P = 0.005). More efficient CPM among patients with painful DPN might result from not only central changes in pain modulation but also from altered sensory messages coming from tested affected body sites. This calls for the use of intact sites for proper assessment of pain modulation in patients with neuropathy.

Clinical Effects of Repetitive Transcranial Magnetic Stimulation of the Motor Cortex Are Associated With Changes in Resting-State Functional Connectivity in Patients With Fibromyalgia Syndrome.

In this double-blinded, sham-controlled, counterbalanced, and crossover study, we investigated the potential neuroplasticity underlying pain relief and daily function improvements following repetitive transcranial magnetic stimulation of the motor cortex (M1-rTMS) in fibromyalgia syndrome (FMS) patients. Specifically, we used magnetic resonance imaging (MRI) to examine changes in brain structural and resting-state functional connectivity (rsFC) that correlated with improvements in FMS symptomology following M1-rTMS. Twenty-seven women with FMS underwent real and sham treatment series, each consisting of 10 daily treatments of 10Hz M1-rTMS over 2 weeks, with a washout period in between. Before and after each series, participants underwent anatomical and resting-state functional MRI scans and questionnaire assessments of FMS-related clinical pain and functional and psychological burdens. The expected reductions in FMS-related symptomology following M1-rTMS occurred with the real treatment only and correlated with rsFC changes in brain areas associated with pain processing and modulation. Specifically, between the ventromedial prefrontal cortex and the M1 (t = -5.54, corrected P = .002), the amygdala and the posterior insula (t = 5.81, corrected P = .044), and the anterior and posterior insula (t = 6.01, corrected P = .029). Neither treatment significantly changed brain structure. Therefore, we provide the first evidence of an association between the acute clinical effects of M1-rTMS in FMS and functional alterations of brain areas that have a significant role in the experience of chronic pain. Structural changes could potentially occur over a more extended treatment period. PERSPECTIVE: We show that the neurophysiological mechanism of the improvement in fibromyalgia symptoms following active, but not sham, rTMS applied to M1 involves changes in resting-state functional connectivity in sensory, affective and cognitive pain processing brain areas, thus substantiating the essence of fibromyalgia syndrome as a treatable brain-based disorder.

Head- and neck-related symptoms post-motor vehicle collision (MVC): Separate entities or two-sides of the same coin?

BACKGROUND AND AIM: Although post-motor vehicle collision (MVC) pain and symptoms are largely convergent among those with mild traumatic brain injury (mTBI) and whiplash associated disorder (WAD), and patients oftentimes report initial neck and head complaints, the clinical picture of mTBI and WAD has been primarily studied as separate conditions which may result in an incomplete clinical picture. As such, this study was conducted to explore the role of pain and post-traumatic psychological features in explaining both head and neck-related symptom variability in a cohort of post-collision patients. This is with the goal of disentangling if contributory factors are uniquely related to each diagnosis, or are shared between the two. METHODS: Patients recruited in the very early acute phase (<72 h) returned for clinical and psychological assessment at 6 months post-accident. In order to determine which factors were unique and which ones were overlapping the same potential contributors: mean head pain, mean neck pain, female gender, number of post-collision painful body areas, PTSD, and depression were included in the regression models for both neck disability index (NDI) and Rivermead post-concussion symptoms questionnaire (RPQ). RESULTS: Of 223 recruited participants, 70 returned for a follow-up visit (age range 18-64, mean(SD) 37.6 (11.9), 29F). This cohort primarily met the criteria for mTBI, but also fulfilled the criteria for whiplash, reinforcing the duality of injury presentation. Correlations existed between the NDI and RPQ scores (Spearman's ρ=0.66, p<0.001), however overlap was only partial. Regression analysis showed that after the removal of area-of-injury pain neck related disability (r = 0.80, p <0.001) was explained solely by number of painful body areas (ß=0.52, p <0.001). In contrast, post-concussion syndrome symptoms (r = 0.86, p<0.001) are influenced by clinical pain, painful body areas (ß=0.31, p = 0.0026), female gender (ß=0.19, p = 0.0053), and psychological factors of depression (ß=0.31, p = 0.0028) and PTSD symptoms (ß=0.36, p = 0.0013). CONCLUSIONS: It seems that while mechanisms of neck- and head-related symptoms in post-collision patients do share a common explanatory feature, of residual body pain, they are not entirely overlapping. In that psychological factors influence post-concussion syndrome symptoms, but not post-whiplash neck disability.

Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity.

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person's experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

An Exploratory Study Testing Autonomic Reactivity to Pain in Women with Sensory Over-Responsiveness.

BACKGROUND: Difficulty modulating sensory input related to multi-sensory integration dysfunction, specifically the sensory over-responsive (SOR) type, is associated with psychological distress and hyperalgesia in children and adults. Scares reports suggest atypical autonomic nervous system (ANS) reactivity to innocuous sensory stimuli in children with SOR. Thus, the ANS may contribute to sensory stimuli responses and psychological distress. This exploratory study aimed to characterize the ANS reactivity to single and dual pain stimulation, and in relation to psychological distress in adults with SOR. METHODS: Healthy women with SOR (n = 9) vs. without SOR (n = 9) underwent two runs of single pain stimulation and a third run comprised of dual pain stimulation. Pain was self-rated, while heart rate variability was measured and analyzed in the time and frequency domains. In addition, questionnaires assessing anxiety and somatization were utilized. RESULTS: While controls demonstrated a vagal tone withdrawal (root mean square of successive differences in R-R-intervals; (RMSSD)) p = 0.029 from base-line to the third run, this was absent in the SOR group. However, no group differences were found in pain ratings. Furthermore, groups differed in the correlations between R-R mean and the level of both anxiety (p = 0.006) and somatization (p < 0.001); while in the SOR group, higher levels of anxiety and somatization correlated with shorter R-R intervals, the opposite was found in the control group. CONCLUSIONS: This is the first study to demonstrate in women with SOR atypical vagal tone reactivity to challenging pain load. Vagal tone reactivity is related to both pain ratings and psychological distress.

Explaining very early acute mild traumatic brain injury after motor vehicle collision pain variability: additive value of pain sensitivity questionnaire.

INTRODUCTION AND OBJECTIVES: Chronic pain is a common postcollision consequence. Wherein, a clearer understanding of acute pain can help stem the acute-to-chronic pain transition. However, the variability of acute pain is only partially explained by psychophysical pain characteristics as measured by quantitative sensory testing. The Pain Sensitivity Questionnaire (PSQ) may reflect inherent psychocognitive representations of patient's sensitivity and thus may reveal less-explored pain dimensions. In the vein of the biopsychosocial approach, this study aimed to explore whether PSQ holds additive value in explaining head and neck pain reports in very early acute-stage mild traumatic brain injury (mTBI) after collision, above the use of psychophysical assessment. METHODS: Study cohort (n = 130) consisted of mTBI patients (age range 19-66, 57 F) after accident with area-of-injury pain of at least 20 on the day of testing (mean pain 58.4 ± 21.6, range 20-100 Numerical Pain Scale) who underwent clinical, psychophysical, and pain-related psychological assessment within 72-hour after injury. RESULTS: Pain Sensitivity Questionnaire scores were significantly correlated with acute clinical, psychophysical, and pain-related psychological measures. Regression model (R 2 = 0.241, P < 0.001) showed that, together, age, sex, high PSQ, enhanced temporal summation, and less-efficient conditioned pain modulation explained head and neck pain variance. This model demonstrated that the strongest contribution to degree of postinjury pain was independently explained by PSQ (ß = 0.32) and then pressure pain threshold-conditioned pain modulation (ß = -0.25). CONCLUSION: Appraisal of cognitive daily-pain representations, by way of memory and imagination, provides an additional important dispositional facet to explain the variability in the acute mTBI postcollision clinical pain experience, above assessing nociceptive responsiveness to experimentally induced pain.

The Endogenous Analgesia Signature in the Resting Brain of Healthy Adults and Migraineurs.

Altered pain modulation and resting state functional connectivity (rsFC) were found to be related to migraine pathology and clinical manifestation. We examined how pain modulation psychophysical measures are related to resting-state networks and rsFC between bottom-up and top-down pain modulation areas. Thirty-two episodic migraineurs and 23 age-matched healthy individuals underwent temporal summation of pain (TSOP) and conditioned pain modulation (CPM) tests, followed by a resting-state imaging scan. No differences in temporal summation of pain and CPM were found between groups. However, in healthy individuals, more efficient CPM was correlated with 1) stronger rsFCs of the posterior cingulate cortex, with the ventromedial prefrontal cortex and with the pregenual anterior cingulate cortex; 2) weaker rsFC of the anterior insula with the angular gyrus. Conversely, in migraineurs, the association between CPM and rsFC was altered. Our results suggest that the functional connectivity within the default mode network (DMN) components and the functional coupling between the DMN and pain inhibitory brain areas is linked with pain inhibition efficiency. In migraineurs, this interplay is changed, yet enables normal pain inhibition. Our findings shed light on potential functional adaptation of the DMN and its role in pain inhibition in health and migraine. PERSPECTIVE: This article establishes evidence for the relationship between the resting-state brain and individual responses in psychophysical pain modulation tests, in both migraine and healthy individuals. The results emphasize the significant role of the default mode network in maintaining pain inhibition efficiency in health and in the presence of chronic pain.

A Biomarker for Discriminating Between Migraine With and Without Aura: Machine Learning on Functional Connectivity on Resting-State EEGs.

Advanced analyses of electroencephalography (EEG) are rapidly becoming an important tool in understanding the brain's processing of pain. To date, it appears that none have been explored as a way of distinguishing between migraine patients with aura (MWA) vs. those without aura (MWoA). In this work, we apply a mixture of predictive, e.g., classification methods and attribute-selection techniques, and traditional explanatory, e.g., statistical, analyses on functional connectivity measures extracted from EEG signal acquired from at-rest participants (N = 52) during their interictal period and tested them against the distinction between MWA and MWoA. We show that a functional connectivity metric of EEG data obtained during resting state can serve as a sole biomarker to differentiate between MWA and MWoA. Using the proposed analysis, we not only have been able to present high classification results (average classification of 84.62%) but also to discuss the underlying neurophysiological mechanisms upon which our technique is based. Additionally, a more traditional statistical analysis on the selected features reveals that MWoA patients show higher than average connectivity in the Theta band (p = 0.03) at rest than MWAs. We propose that our data-driven analysis pipeline can be used for resting-EEG analysis in any clinical context.

The "virtual lesion" approach to transcranial magnetic stimulation: studying the brain-behavioral relationships in experimental pain.

Transcranial magnetic stimulation (TMS) can be used to create a temporary "virtual lesion" (VL) of a target cortical area, disrupting its function and associated behavior. Transcranial magnetic stimulation can therefore test the functional role of specific brain areas. This scoping review aims at investigating the current literature of the "online" TMS-evoked VL approach to studying brain-behavioral relationships during experimental pain in healthy subjects. Ovid-Medline, Embase, and Web of Science electronic databases were searched. Included studies tested different TMS-based VLs of various pain brain areas during continuous experimental pain or when time-locked to a noxious stimulus. Outcome measures assessed different pain measurements. Initial screening resulted in a total of 403 studies, of which 17 studies were included in the review. The VLs were directed to the prefrontal, primary and secondary somatosensory, primary motor, and parietal cortices through single/double/triple/sequence of five-TMS pulses or through repeated TMS during mechanical, electrical contact, radiant heat, or capsaicin-evoked noxious stimulation. Despite a wide variability among the VL protocols, outcome measures, and study designs, a behavioral VL effect (decrease or increase in pain responses) was achieved in the majority of the studies. However, such findings on the relationships between the modified brain activity and the manifested pain characteristics were often mixed. To conclude, TMS-elicited VLs during experimental pain empower our understanding of brain-behavior relationships at specific time points during pain processing. The mixed findings of these relationships call for an obligatory standard of all pain-related TMS protocols for clearly determining the magnitude and direction of TMS-induced behavioral effects.