Kasey S. Hemington

Abnormal cross-network functional connectivity in chronic pain and its association with clinical symptoms.

Cortical functioning within the default mode network (DMN) and salience network (SN) is altered in chronic pain patients. The mechanisms underlying these alterations are unknown, but a novel unexamined source is cross-network communication. Aberrant functional connectivity (FC) between the DMN and SN, whose activity is normally anticorrelated, reflects disease severity in many brain disorders. Further, stronger FC between the posterior cingulate cortex (PCC) and anterior insula has been reported in chronic pain, pointing to abnormal DMN–SN interactions. Here, we tested the hypothesis that cross-network FC between the DMN and SN is abnormal in chronic pain, and is related to pain and associated symptoms. We used resting state fMRI to examine FC within and between the DMN and SN in 20 patients with chronic pain due to ankylosing spondylitis and 20 healthy controls. A whole-network analysis revealed that compared to healthy controls, patients exhibited less anticorrelated FC between the SN and DMN, and the degree of cross-network abnormality tracked pain and disease-related symptoms. This suggests that cross-network FC is a metric of functional brain abnormality in chronic pain. In a complementary seed-based analysis, the PCC was strongly connected with the SN and weakly connected with the DMN in chronic pain compared to healthy controls, suggesting that the PCC acts as a hub for altered network interaction. Sensorimotor cortex cross-network FC correlated with measures of physical function, suggesting that physical functioning also impacts brain network interaction in chronic pain. Our study implicates altered communication between brain networks as a key factor underlying chronic pain.

Regional brain signal variability: a novel indicator of pain sensitivity and coping.

Abstract Variability in blood oxygen level–dependent (BOLD) functional magnetic resonance imaging (fMRI) signals reflects the moment-by-moment fluctuations in resting-state fMRI (rs-fMRI) activity within specific areas of the brain. Regional BOLD signal variability was recently proposed to serve an important functional role in the efficacy of neural systems because of its relationship to behavioural performance in aging and cognition studies. We previously showed that individuals who better cope with pain have greater fluctuations in interregional functional connectivity, but it is not known whether regional brain signal variability is a mechanism underlying pain coping. We tested the hypothesis that individual pain sensitivity and coping is reflected by regional fMRI BOLD signal variability within dynamic pain connectome–brain systems implicated in the pain experience. We acquired resting-state fMRI and assessed pain threshold, suprathreshold temporal summation of pain, and the impact of pain on cognition in 80 healthy right-handed individuals. We found that regional BOLD signal variability: (1) inversely correlated with an individuals temporal summation of pain within the ascending nociceptive pathway (primary and secondary somatosensory cortex), default mode network, and salience network; (2) was correlated with an individuals ability to cope with pain during a cognitive interference task within the periaqueductal gray, a key opiate-rich brainstem structure for descending pain modulation; and (3) provided information not captured from interregional functional connectivity. Therefore, regional BOLD variability represents a pain metric with potential implications for prediction of chronic pain resilience vs vulnerability.

The periaqueductal gray and descending pain modulation: why should we study them and what role do they play in chronic pain?

In this Neuro Forum we discuss the significance of a recent study by Yu et al. (Neuroimage Clin 6: 100-108, 2014). The authors examined functional connectivity of a key node of the descending pain modulation pathway, the periaqueductal gray (PAG), in chronic back pain patients. Altered PAG connectivity to pain-related regions was found; we place results within the context of recent literature and emphasize the importance of understanding the descending component of pain in pain research.

Slow-5 dynamic functional connectivity reflects the capacity to sustain cognitive performance during pain.

&NA; Some individuals are more distracted by pain during a cognitive task than others, representing poor pain coping. We have characterized individuals as A‐type (attention dominates) or P‐type (pain dominates) based on how pain interferes with task speed. The ability to optimize behavior during pain may relate to the flexibility in communication at rest between the dorsolateral prefrontal cortex (DLPFC) of the executive control network, and the anterior mid‐cingulate cortex (aMCC) of the salience network (SN) – regions involved in cognitive‐interference. The aMCC and aIns (SN hub) also signify pain salience; flexible communication at rest between them possibly allowing prioritizing task performance during pain. We tested the hypotheses that pain‐induced changes in task performance are related to resting‐state dynamic functional connectivity (dFC) between these region pairs (DLPFC‐aMCC; aMCC‐aIns). We found that 1) pain reduces task consistency/speed in P‐type individuals, but enhances performance in A‐type individuals, 2) task consistency is related to the FC dynamics within DLPFC‐aMCC and aMCC‐aIns pairs, 3) brain‐behavior relationships are driven by dFC within the slow‐5 (0.01–0.027 Hz) frequency band, and 4) dFC across the brain decreases at higher frequencies. Our findings point to neural communication dynamics at rest as being associated with prioritizing task performance over pain. HighlightsPain reduces task consistency and speed in P‐type individuals.Pain improves task performance in A‐type individuals.Individuals who prioritize task over pain have more flexible brain connectivity.DLPFC‐aMCC and salience network dynamic connectivity underlie task‐pain flexibility.Dynamic FC is stronger in the slow‐5 (0.01–0.027 Hz) than in higher frequency bands.

Pain in ankylosing spondylitis: a neuro-immune collaboration

Clinicians have commonly differentiated chronic back pain into two broad subsets: namely, non-inflammatory (or mechanical) back pain and inflammatory back pain. As the terminology suggests, the latter category, in which ankylosing spondylitis (AS) is prominent, presupposes a close link between pain and inflammation. Advances in research into the genetics and immunology of AS have improved our understanding of the inflammatory processes involved in this disease, and have led to the development of potent anti-inflammatory biologic therapeutic agents. However, evidence from clinical trials and from biomarker and imaging studies in patients with AS indicate that pain and inflammation are not always correlated. Thus, the assumption that pain in AS is a reliable surrogate marker for inflammation might be an over-simplification. This Review provides an overview of current concepts relating to neuro-immune interactions in AS and summarizes research that reveals an increasingly complex interplay between the activation of the immune system and pain pathways in the nervous system. The different types of pain experienced by patients with AS, insights from brain imaging studies, neurological mechanisms of pain, sex bias in pain and how the immune system can modify pain in patients with AS are also discussed.

Using magnetic resonance imaging to visualize the brain in chronic pain

The development of neuroimaging has revolutionized our understanding of the brain’s instrumental role in pain perception. Magnetic resonance imaging–based methods have provided noninvasive access to visualize the brain in awake, feeling humans. Common techniques include functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging to assess white matter (diffusion tensor imaging and tractography) and grey matter (volumetric, cortical thickness analyses) (Fig. 1). Each of these techniques capitalizes on biological properties of the tissues to generate contrast in the image. In fMRI, detection of brain function is derived from neurovascular coupling mechanisms in which neural activity drives changes in local blood fl ow that can be detected because of the difference in magnetic properties between oxygenated (oxy Hb) and deoxygenated hemoglobin (deoxy Hb).1 In diffusion imaging, restricted (white matter) vs unrestricted (eg, cerebral spinal fl uid) diffusion of water has different magnetic properties that provide contrast in the image and provide details about the tissue architecture.8 These techniques do not provide a direct measure of neural functioning or anatomical structure unlike neurophysiological recordings or tracer methodologies.1,8 Neuroimaging can evaluate the engagement of brain regions during pain,5,9 the impact of context (eg, attentional state),2 and how these regions interact and organize into static and dynamic networks.9,10 fMRI can be used to study responses to stimulus-evoked acute pain, while analysis of activity during taskfree “resting state” can identify aberrant intrinsic functioning and spontaneous activity in chronic pain patients. For example, studies have shown that brain connectivity in regions of the salience and default mode brain networks is abnormal in chronic back pain patients,3,7 with partial restoration after treatment.3 Peripheral nerve and central nervous system white matter can be assessed using diffusion-weighted imaging and diffusion tensor imaging. Tractography can be used to delineate pathways and quantify abnormalities in chronic pain patients and with group-based analyses such as tract-based spatial statistics with diffusion metrics (fractional anisotropy, axial, radial, and mean diffusivity) indicative of white matter integrity, demyelination, neuroinfl ammation, and edema.6 Diffusion abnormalities correspond to pain outcomes and pain severity.5 Grey matter assessment, such as cortical thickness analysis or voxel-based morphometry, can elucidate the relationship between pain severity and treatment outcomes and grey matter abnormalities (eg, due to changes in neuronal size or number, synaptogenesis, dendritic branching, axon sprouting, synaptic pruning, neuronal cell death, alterations in vasculature, and the size/number of glial cells).5 For example, gray matter volumes of the amygdala and hippocampal brain in sub-acute back pain patients predict risk for chronic pain.11 Some imaging fi ndings are commonly seen across diverse chronic pain conditions and others do not generalize as they are related to specifi c disease states. Recent advances in neuroimaging are applying machine learning to predict treatment outcomes in chronic pain patients to inform prognostics for personalized pain management. Paralleling this work, it is imperative to consider the ethical and legal implications of using brain imaging for diagnostics.4

Patients with chronic pain exhibit a complex relationship triad between pain, resilience, and within- and cross-network functional connectivity of the default mode network

Abstract Resilience is a psychological trait that strongly predicts chronic pain–related health outcomes. The neural correlates of both pain and trait resilience are critical to understand the brain–behaviour relationship in chronic pain; yet, neural correlates of resilience in chronic pain states are unknown. However, measures of pain perception and a wide range of psychological health measures have been linked to function of the default mode network (DMN). Thus, we aimed to determine the relationships between resilience, pain perception, and functional connectivity (FC) within the DMN and between the DMN and other brain networks. Resting-state functional magnetic resonance imaging data were acquired from 51 chronic pain patients with a form of spondylarthritis (ankylosing spondylitis) and 51 healthy control participants. Participants completed a questionnaire on their individual trait resilience (the Resilience Scale), and patients reported their clinical pain. In healthy controls, we found within-DMN FC to be stronger in less resilient individuals. In patients with chronic pain, individual resilience was negatively correlated with pain and disease activity. Cross-network FC between the DMN and the sensorimotor network was abnormally high in patients with high clinical pain scores on the day of the study. Finally, there was an interaction between within-DMN FC and clinical pain report in patients: In patients reporting greater pain, the relationship between within-DMN connectivity and resilience was atypical. Thus, our findings reveal different neural representations of resilience and pain. The way in which these behavioural measures interact provides insight into understanding the neural correlates of chronic pain.

Dynamic pain connectome functional connectivity and oscillations reflect multiple sclerosis pain

Abstract Pain is a prevalent and debilitating symptom of multiple sclerosis (MS); yet, the mechanisms underlying this pain are unknown. Previous studies have found that the functional relationships between the salience network (SN), specifically the right temporoparietal junction a SN node, and other components of the dynamic pain connectome (default mode network [DMN], ascending and descending pathways) are abnormal in many chronic pain conditions. Here, we use resting-state functional magnetic resonance imaging and measures of static and dynamic functional connectivity (sFC and dFC), and regional BOLD variability to test the hypothesis that patients with MS have abnormal DMN-SN cross-network sFC, dFC abnormalities in SN-ascending and SN-descending pathways, and disrupted BOLD variability in the dynamic pain connectome that relates to pain inference and neuropathic pain (NP). Thirty-one patients with MS and 31 controls completed questionnaires to characterize pain and pain interference, and underwent a resting-state functional magnetic resonance imaging scan from which measures of sFC, dFC, and BOLD variability were compared. We found that (1) ∼50% of our patients had NP features, (2) abnormalities in SN-DMN sFC were driven by the mixed-neuropathic subgroup, (3) in patients with mixed NP, dFC measures showed that there was a striking change in how the SN was engaged with the ascending nociceptive pathway and descending modulation pathway, (4) BOLD variability was increased in the DMN, and (5) the degrees of sFC and BOLD variability abnormalities were related to pain interference. We propose that abnormal SN-DMN cross-network FC and temporal dynamics within and between regions of the dynamic pain connectome reflect MS pain features.

Neuropathic pain and pain interference are linked to alpha-band slowing and reduced beta-band magnetoencephalography activity within the dynamic pain connectome in patients with multiple sclerosis

Abstract Chronic pain is a common occurrence in multiple sclerosis (MS) that severely affects quality of life, but the underlying brain mechanisms related to these symptoms are unknown. Previous electroencephalography studies have demonstrated a role of alpha-band and beta-band power in pain processing. However, how and where these brain signals change in MS-related chronic pain is unknown. Here, we used resting state magnetoencephalography to examine regional spectral power in the dynamic pain connectome—including areas of the ascending nociceptive pathway, default mode network (DMN), and the salience network (SN)—in patients with chronic MS pain and in healthy controls. Each patient was assessed for pain, neuropathic pain (NP), and pain interference with activities of daily living. We found that patients with MS exhibited an increase of alpha-band power and a decrease of beta-band power, most prominently in the thalamus and the posterior insula of the ascending nociceptive pathway and in the right temporoparietal junction of the SN. In addition, patients with mixed-NP exhibited slowing of alpha peak power within the thalamus and the posterior insula, and in the posterior cingulate cortex of the DMN. Finally, pain interference scores in patients with mixed-NP were strongly correlated with alpha and beta peak power in the thalamus and posterior insula. These novel findings reveal brain mechanisms of MS-related pain in the ascending nociceptive pathway, SN, and DMN, and that these spectral abnormalities reflect the impact of pain on quality of life measures.

Brain Dynamics and Temporal Summation of Pain Predicts Neuropathic Pain Relief from Ketamine Infusion.

What We Already Know about This Topic Ketamine is an N-methyl-D-aspartate antagonist with growing use in the management of chronic pain Descending pain modulatory circuits are key modulators of chronic pain What This Article Tells Us That Is New The infusion of ketamine resulted in meaningful pain relief in about 50% of patients with chronic neuropathic pain The magnitude of temporal summation of pain and the dynamic engagement of the descending pain modulatory circuit predicted treatment efficacy and point to mechanisms by which ketamine can relieve pain Background: Ketamine is an N-methyl-D-aspartate receptor antagonist that reduces temporal summation of pain and modulates antinociception. Ketamine infusions can produce significant relief of neuropathic pain, but the treatment is resource intensive and can be associated with adverse effects. Thus, it is crucial to select patients who might benefit from this treatment. The authors tested the hypothesis that patients with enhanced temporal summation of pain and the capacity to modulate pain via the descending antinociceptive brain pathway are predisposed to obtain pain relief from ketamine. Methods: Patients with refractory neuropathic pain (n = 30) and healthy controls underwent quantitative sensory testing and resting-state functional magnetic resonance imaging and then completed validated questionnaires. Patients then received outpatient intravenous ketamine (0.5 to 2 mg · kg−1 · h−1; mean dose 1.1 mg · kg−1 · h−1) for 6 h/day for 5 consecutive days. Pain was assessed 1 month later. Treatment response was defined as greater than or equal to 30% pain relief (i.e., reduction in pain scores). We determined the relationship between our primary outcome measure of pain relief with pretreatment temporal summation of pain and with brain imaging measures of dynamic functional connectivity between the default mode network and the descending antinociceptive brain pathway. Results: Approximately 50% of patients achieved pain relief (mean ± SD; Responders, 61 ± 35%; Nonresponders, 7 ± 14%). Pretreatment temporal summation was associated with the effect of ketamine (&rgr; = −0.52, P = 0.003) and was significantly higher in Responders (median [25th, 75th] = 200 [100, 345]) compared with Nonresponders (44 [9, 92]; P = 0.001). Pretreatment dynamic connectivity was also associated with the clinical effect of ketamine (&rgr; = 0.51, P = 0.004) and was significantly higher in Responders (mean ± SD, 0.55 ± 0.05) compared with Nonresponders (0.51 ± 0.03; P = 0.006). Finally, the dynamic engagement of the descending antinociceptive system significantly mediated the relationship between pretreatment pain facilitation and pain relief (95% CI, 0.005 to 0.065). Conclusions: These findings suggest that brain and behavioral measures have the potential to prognosticate and develop ketamine-based personalized pain therapy.