Gray Matter Changes Following Cognitive Behavioral Therapy for Patients With Comorbid Fibromyalgia and Insomnia: A Pilot Study.

STUDY OBJECTIVES: Insomnia frequently co-occurs with fibromyalgia, which is associated with gray matter atrophy. We examined the effect of cognitive behavioral therapy for insomnia (CBT-I) and pain (CBT-P) on cortical thickness. METHODS: Patients with fibromyalgia and insomnia underwent MRI before and after random assignment to CBT-I (n = 14), CBT-P (n = 16), or waitlist control (WLC; n = 7). RESULTS: Repeated-measures analyses of variance revealed significant interactions for two regions (left lateral orbitofrontal cortex, left rostral middle frontal, Ps < .05) and trends for four regions (right medial orbitofrontal cortex, right posterior cingulate, left caudal middle frontal, left transverse temporal; Ps < .10). Cortical thickness increased in all regions for CBT-I and decreased in five regions for CBT-P and WLC. Hierarchical regressions revealed that for the CBT-I group, reductions in wake after sleep onset were associated with an increase in cortical thickness. CONCLUSIONS: Our pilot study presents novel evidence suggesting that CBT-I may slow or reverse cortical gray matter atrophy in patients with fibromyalgia and insomnia. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov, Identifier: NCT02001077, Title: Sleep and Pain Interventions in Fibromyalgia (SPIN), URL: https://clinicaltrials.gov/ct2/show/NCT02001077.

Frontal Structural Neural Correlates of Working Memory Performance in Older Adults.

Working memory is an executive memory process that allows transitional information to be held and manipulated temporarily in memory stores before being forgotten or encoded into long-term memory. Working memory is necessary for everyday decision-making and problem solving, making it a fundamental process in the daily lives of older adults. Working memory relies heavily on frontal lobe structures and is known to decline with age. The current study aimed to determine the neural correlates of decreased working memory performance in the frontal lobes by comparing cortical thickness and cortical surface area from two demographically matched groups of healthy older adults, free from cognitive impairment, with high versus low N-Back working memory performance (N = 56; average age = 70.29 ± 10.64). High-resolution structural T1-weighted images (1 mm isotropic voxels) were obtained on a 3T Philips MRI scanner. When compared to high performers, low performers exhibited significantly decreased cortical surface area in three frontal lobe regions lateralized to the right hemisphere: medial orbital frontal gyrus, inferior frontal gyrus, and superior frontal gyrus (FDR p < 0.05). There were no significant differences in cortical thickness between groups, a proxy for neurodegenerative tissue loss. Our results suggest that decreases in cortical surface area (a proxy for brain structural integrity) in right frontal regions may underlie age-related decline of working memory function.

Effective connectivity predicts future placebo analgesic response: A dynamic causal modeling study of pain processing in healthy controls.

A better understanding of the neural mechanisms underlying pain processing and analgesia may aid in the development and personalization of effective treatments for chronic pain. Clarification of the neural predictors of individual variability in placebo analgesia (PA) could aid in this process. The present study examined whether the strength of effective connectivity (EC) among pain-related brain regions could predict future placebo analgesic response in healthy individuals. In Visit 1, fMRI data were collected from 24 healthy subjects (13 females, mean age=22.56, SD=2.94) while experiencing painful thermal stimuli. During Visit 2, subjects were conditioned to expect less pain via a surreptitiously lowered temperature applied at two of the four sites on their feet. They were subsequently scanned again using the Visit 1 (painful) temperature. Subjects used an electronic VAS to rate their pain following each stimulus. Differences in ratings at conditioned and unconditioned sites were used to measure placebo response (PA scores). Dynamic causal modeling was used to estimate the EC among a set of brain regions related to pain processing at Visit 1 (periaqueductal gray, thalamus, rostral anterior cingulate cortex, dorsolateral prefrontal cortex). Individual PA scores from Visit 2 were regressed on salient EC parameter estimates from Visit 1. Results indicate that both greater left hemisphere modulatory DLPFC➔PAG connectivity and right hemisphere, endogenous thalamus➔DLPFC connectivity were significantly predictive of future placebo response (R(2)=0.82). To our knowledge, this is the first study to identify the value of EC in understanding individual differences in PA, and may suggest the potential modifiability of endogenous pain modulation.

Fibromyalgia patients have reduced hippocampal volume compared with healthy controls.

OBJECTIVE: Fibromyalgia patients frequently report cognitive abnormalities. As the hippocampus plays an important role in learning and memory, we determined whether individuals with fibromyalgia had smaller hippocampal volume compared with healthy control participants. METHODS: T1-weighted structural magnetic resonance imaging (MRI) scans were acquired from 40 female participants with fibromyalgia and 22 female healthy controls. The volume of the hippocampus was estimated using the software FreeSurfer. An analysis of covariance model controlling for potentially confounding factors of age, whole brain size, MRI signal quality, and Beck Depression Inventory scores were used to determine significant group differences. RESULTS: Fibromyalgia participants had significantly smaller hippocampi in both left (F[1,56]=4.55, P=0.037, η (2) p=0.08) and right hemispheres (F[1,56]=5.89, P=0.019, η (2) p=0.10). No significant effect of depression was observed in either left or right hemisphere hippocampal volume (P=0.813 and P=0.811, respectively). DISCUSSION: Potential mechanisms for reduced hippocampal volume in fibromyalgia include abnormal glutamate excitatory neurotransmission and glucocorticoid dysfunction; these factors can lead to neuronal atrophy, through excitotoxicity, and disrupt neurogenesis in the hippocampus. Hippocampal atrophy may play a role in memory and cognitive complaints among fibromyalgia patients.

Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.

UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging classification methods imperative. However, the relative performance of ML on neuroimaging and self-report data have not been compared. This study used commonly reported ML algorithms to measure differences between "objective" neuroimaging data and "subjective" self-report (ie, mood and pain intensity) in their ability to discriminate between individuals with and without chronic pain. Structural magnetic resonance imaging data from 26 individuals (14 individuals with fibromyalgia and 12 healthy controls) were processed to derive volumes from 56 brain regions per person. Self-report data included visual analog scale ratings for pain intensity and mood (ie, anger, anxiety, depression, frustration, and fear). Separate models representing brain volumes, mood ratings, and pain intensity ratings were estimated across several ML algorithms. Classification accuracy of brain volumes ranged from 53 to 76%, whereas mood and pain intensity ratings ranged from 79 to 96% and 83 to 96%, respectively. Overall, models derived from self-report data outperformed neuroimaging models by an average of 22%. Although neuroimaging clearly provides useful insights for understanding neural mechanisms underlying pain processing, self-report is reliable and accurate and continues to be clinically vital. PERSPECTIVE: The present study compares neuroimaging, self-reported mood, and self-reported pain intensity data in their ability to classify individuals with and without fibromyalgia using ML algorithms. Overall, models derived from self-reported mood and pain intensity data outperformed structural neuroimaging models.

Test-retest reliability of pain-related brain activity in healthy controls undergoing experimental thermal pain.

UNLABELLED: Although functional magnetic resonance imaging (fMRI) has been proposed as a method to elucidate pain-related biomarkers, little information exists related to psychometric properties of fMRI findings. This knowledge is essential for potential translation of this technology to clinical settings. The purpose of this study was to assess the test-retest reliability of pain-related brain activity and how it compares to the reliability of self-report. Twenty-two healthy controls (mean age = 22.6 years, standard deviation = 2.9) underwent 3 runs of an fMRI paradigm that used thermal stimuli to elicit experimental pain. Functional MRI summary statistics related to brain activity during thermal stimulation periods were extracted from bilateral anterior cingulate cortices and anterior insula. Intraclass correlations (ICCs) were conducted on these summary statistics and generally showed "good" test-retest reliability in all regions of interest (ICC range = .32-.88; mean = .71); however, these results did not surpass ICC values from pain ratings, which fell within the "excellent" range (ICC range = .93-.96; mean = .94). Findings suggest that fMRI is a valuable tool for measuring pain mechanisms but did not show an adequate level of test-retest reliability for fMRI to potentially act as a surrogate for individuals' self-report of pain. PERSPECTIVE: This study is one of the first reports to demonstrate the test-retest reliability of fMRI findings related to pain processing and provides a comparison to the reliability of subjective reports of pain. This information is essential for determining whether fMRI technology should be potentially translated for clinical use.