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

Migraine Subclassification via a Data-Driven Automated Approach Using Multimodality Factor Mixture Modeling of Brain Structure Measurements

BACKGROUND

The current subclassification of migraine is according to headache frequency and aura status. The variability in migraine symptoms, disease course, and response to treatment suggest the presence of additional heterogeneity or subclasses within migraine.

OBJECTIVE

The study objective was to subclassify migraine via a data-driven approach, identifying latent factors by jointly exploiting multiple sets of brain structural features obtained via magnetic resonance imaging (MRI).

METHODS

Migraineurs (n = 66) and healthy controls (n = 54) had brain MRI measurements of cortical thickness, cortical surface area, and volumes for 68 regions. A multimodality factor mixture model was used to subclassify MRIs and to determine the brain structural factors that most contributed to the subclassification. Clinical characteristics of subjects in each subgroup were compared.

RESULTS

Automated MRI classification divided the subjects into two subgroups. Migraineurs in subgroup #1 had more severe allodynia symptoms during migraines (6.1 ± 5.3 vs. 3.6 ± 3.2, P = .03), more years with migraine (19.2 ± 11.3 years vs 13 ± 8.3 years, P = .01), and higher Migraine Disability Assessment (MIDAS) scores (25 ± 22.9 vs 15.7 ± 12.2, P = .04). There were not differences in headache frequency or migraine aura status between the two subgroups.

CONCLUSIONS

Data-driven subclassification of brain MRIs based upon structural measurements identified two subgroups. Amongst migraineurs, the subgroups differed in allodynia symptom severity, years with migraine, and migraine-related disability. Since allodynia is associated with this imaging-based subclassification of migraine and prior publications suggest that allodynia impacts migraine treatment response and disease prognosis, future migraine diagnostic criteria could consider allodynia when defining migraine subgroups.

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.

Lower Functional Connectivity of the Periaqueductal Gray Is Related to Negative Affect and Clinical Manifestations of Fibromyalgia

Fibromyalgia (FM) syndrome is characterized by chronic widespread pain, muscle tenderness and emotional distress. Previous studies found reduced endogenous pain modulation in FM. This deficiency of pain modulation may be related to the attributes of chronic pain and other clinical symptoms experienced in patients with FM. Thus, we tested whether there is a link between the clinical symptoms of FM and functional connectivity (FC) of the periaqueductal gray (PAG), a key node of pain modulation. We acquired resting state 3T functional MRI (rsfMRI) data from 23 female patients with FM and 16 age- and sex- matched healthy controls (HC) and assessed FM symptoms with the Brief Pain Inventory (BPI), Fibromyalgia Impact Questionnaire (FIQ), Hospital Anxiety and Depression Scale (HADS) and Pain Catastrophizing Scale (PCS). We found that patients with FM exhibit statistically significant disruptions in PAG FC, particularly with brain regions implicated in negative affect, self-awareness and saliency. Specifically, we found that, compared to HCs, the FM patients had stronger PAG FC with the lingual gyrus and hippocampus but weaker PAG FC with regions associated with motor/executive functions, the salience (SN) and default mode networks (DMN). The attenuated PAG FC was also negatively correlated with FIQ scores, and positively correlated with the magnification subscale of the PCS. These alterations were correlated with emotional and behavioral symptoms of FM. Our study implicates the PAG as a site of dysfunction contributing to the clinical manifestations and pain in FM.

Brain Rhythms of Pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain.

Legal and ethical issues of using brain imaging to diagnose pain

Pain, by definition, is a subjective experience, and as such its presence has usually been based on a self-report. However, limitations of self-reports for pain diagnostics, particularly for legal and insurance purposes, has led some to consider a brain-imaging-based objective measure of pain. This review will provide an overview of (1) differences between pain and nociception, (2) intersubject variability in pain perception and the associated brain structures and functional circuits, and (3) capabilities and limitations of current brain-imaging technologies. I then discuss how these factors impact objective proxies of pain. Finally, the ethical, privacy, and legal implications of a brain-imaging-based objective measure of pain are considered as potential future technological developments necessary to create a so-called "painometer test."

The Neural Code for Pain: From Single-Cell Electrophysiology to the Dynamic Pain Connectome

Pain occurs in time. In naturalistic settings, pain perception is sometimes stable but often varies in intensity and quality over the course of seconds, minutes, and days. A principal aim in classic electrophysiology studies of pain was to uncover a neural code based on the temporal patterns of single neuron firing. In contrast, modern neuroimaging studies have placed emphasis on uncovering the spatial pattern of brain activity (or “map”) that may reflect the pain experience. However, in the emerging field of connectomics, communication within and among brain networks is characterized as intrinsically dynamic on multiple time scales. In this review, we revisit the single-cell electrophysiological evidence for a nociceptive neural code and consider how those findings relate to recent advances in understanding systems-level dynamic processes that suggest the existence of a “dynamic pain connectome” as a spatiotemporal physiological signature of pain. We explore how spontaneous activity fluctuations in this dynamic system shape, and are shaped by, acute and chronic pain experiences and individual differences in those experiences. Highlighting the temporal dimension of pain, we aim to move pain theory beyond the concept of a static neurosignature and toward an ethologically relevant account of naturalistic dynamics.