An Interventional Response Phenotyping Study in Chronic Low Back Pain: Protocol for a Mechanistic Randomized Controlled Trial.

Evidence-based treatments for chronic low back pain (cLBP) typically work well in only a fraction of patients, and at present there is little guidance regarding what treatment should be used in which patients. Our central hypothesis is that an interventional response phenotyping study can identify individuals with different underlying mechanisms for their pain who thus respond differentially to evidence-based treatments for cLBP. Thus, we will conduct a randomized controlled Sequential, Multiple Assessment, Randomized Trial (SMART) design study in cLBP with the following three aims. Aim 1: Perform an interventional response phenotyping study in a cohort of cLBP patients (n = 400), who will receive a sequence of interventions known to be effective in cLBP. For 4 weeks, all cLBP participants will receive a web-based pain self-management program as part of a run-in period, then individuals who report no or minimal improvement will be randomized to: a) mindfulness-based stress reduction, b) physical therapy and exercise, c) acupressure self-management, and d) duloxetine. After 8 weeks, individuals who remain symptomatic will be re-randomized to a different treatment for an additional 8 weeks. Using those data, we will identify the subsets of participants that respond to each treatment. In Aim 2, we will show that currently available, clinically derived measures, can predict differential responsiveness to the treatments. In Aim 3, a subset of participants will receive deeper phenotyping (n = 160), to identify new experimental measures that predict differential responsiveness to the treatments, as well as to infer mechanisms of action. Deep phenotyping will include functional neuroimaging, quantitative sensory testing, measures of inflammation, and measures of autonomic tone.

Differential classification of states of consciousness using envelope- and phase-based functional connectivity.

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.

Distinct and Dissociable EEG Networks Are Associated With Recovery of Cognitive Function Following Anesthesia-Induced Unconsciousness.

The temporal trajectories and neural mechanisms of recovery of cognitive function after a major perturbation of consciousness is of both clinical and neuroscientific interest. The purpose of the present study was to investigate network-level changes in functional brain connectivity associated with the recovery and return of six cognitive functions after general anesthesia. High-density electroencephalograms (EEG) were recorded from healthy volunteers undergoing a clinically relevant anesthesia protocol (propofol induction and isoflurane maintenance), and age-matched healthy controls. A battery of cognitive tests (motor praxis, visual object learning test, fractal-2-back, abstract matching, psychomotor vigilance test, digital symbol substitution test) was administered at baseline, upon recovery of consciousness (ROC), and at half-hour intervals up to 3 h following ROC. EEG networks were derived using the strength of functional connectivity measured through the weighted phase lag index (wPLI). A partial least squares (PLS) analysis was conducted to assess changes in these networks: (1) between anesthesia and control groups; (2) during the 3-h recovery from anesthesia; and (3) for each cognitive test during recovery from anesthesia. Networks were maximally perturbed upon ROC but returned to baseline 30-60 min following ROC, despite deficits in cognitive performance that persisted up to 3 h following ROC. Additionally, during recovery from anesthesia, cognitive tests conducted at the same time-point activated distinct and dissociable functional connectivity networks across all frequency bands. The results highlight that the return of cognitive function after anesthetic-induced unconsciousness is task-specific, with unique behavioral and brain network trajectories of recovery.

Brain network motifs are markers of loss and recovery of consciousness.

Motifs are patterns of inter-connections between nodes of a network, and have been investigated as building blocks of directed networks. This study explored the re-organization of 3-node motifs during loss and recovery of consciousness. Nine healthy subjects underwent a 3-h anesthetic protocol while 128-channel electroencephalography (EEG) was recorded. In the alpha (8-13 Hz) band, 5-min epochs of EEG were extracted for: Baseline; Induction; Unconscious; 30-, 10- and 5-min pre-recovery of responsiveness; 30- and 180-min post-recovery of responsiveness. We constructed a functional brain network using the weighted and directed phase lag index, on which we calculated the frequency and topology of 3-node motifs. Three motifs (motifs 1, 2 and 5) were significantly present across participants and epochs, when compared to random networks (p < 0.05). The topology of motifs 1 and 5 changed significantly between responsive and unresponsive epochs (p-values < 0.01; Kendall's W = 0.664 (motif 1) and 0.529 (motif 5)). Motif 1 was constituted of long-range chain-like connections, while motif 5 was constituted of short-range, loop-like connections. Our results suggest that anesthetic-induced unconsciousness is associated with a topological re-organization of network motifs. As motif topological re-organization may precede (motif 5) or accompany (motif 1) the return of responsiveness, motifs could contribute to the understanding of the neural correlates of consciousness.

Recovery of consciousness and cognition after general anesthesia in humans.

Understanding how the brain recovers from unconsciousness can inform neurobiological theories of consciousness and guide clinical investigation. To address this question, we conducted a multicenter study of 60 healthy humans, half of whom received general anesthesia for 3 hr and half of whom served as awake controls. We administered a battery of neurocognitive tests and recorded electroencephalography to assess cortical dynamics. We hypothesized that recovery of consciousness and cognition is an extended process, with differential recovery of cognitive functions that would commence with return of responsiveness and end with return of executive function, mediated by prefrontal cortex. We found that, just prior to the recovery of consciousness, frontal-parietal dynamics returned to baseline. Consistent with our hypothesis, cognitive reconstitution after anesthesia evolved over time. Contrary to our hypothesis, executive function returned first. Early engagement of prefrontal cortex in recovery of consciousness and cognition is consistent with global neuronal workspace theory.

Anesthesia is a state of reversable, controlled unconsciousness. It has enabled countless medical procedures. But it also serves as a tool for scientists to study how the brain regains consciousness after disruptions such as sleep, coma or medical procedures requiring general anesthesia. It is still unclear how exactly the brain regains consciousness, and less so, why some patients do not recover normally after general anesthesia or fail to recover from brain injury. To find out more, Mashour et al. studied the patterns of reemerging consciousness and cognitive function in 30 healthy adults who underwent general anesthesia for three hours. While the volunteers were under anesthesia, their brain activity was measured with an EEG; and their sleep-wake activity was measured before and after the experiment. Each participant took part in a series of cognitive tests designed to measure the reaction speed, memory and other functions before receiving anesthesia, right after the return of consciousness, and then every 30 minutes thereafter. Thirty healthy volunteers who did not have anesthesia also completed the scans and tests as a comparison group. The experiments showed that certain normal EEG patterns resumed just before a person wakes up from anesthesia. The return of thinking abilities was an extended, multistep process, but volunteers recovered their cognitive abilities to nearly the same level as the volunteers within three hours of being deeply anesthetized. Mashour et al. also unexpectedly found that abstract problem-solving resumes early in the process, while other functions such as reaction time and attention took longer to recover. This makes sense from an evolutionary perspective. Sleep leaves individuals vulnerable. Quick evaluation and decision-making skills would be key to respond to a threat upon waking. The experiments confirm that the front of the brain, which handles thinking and decision-making, was especially active around the time of recovery. This suggests that therapies targeting this part of the brain may help people who experience loss of consciousness after a brain injury or have difficulties waking up after anesthesia. Moreover, disorders of cognition, such as delirium, in the days following surgery may be caused by factors other than the lingering effects of anesthetic drugs on the brain.

Phenotypic features of patients with complex regional pain syndrome compared with those with neuropathic pain.

INTRODUCTION: We hypothesized that patients with complex regional pain syndrome (CRPS) would describe a more negative pain phenotype including higher pain severity, more neuropathic pain descriptors, more centralized pain symptoms, poorer physical function, and more affective distress when compared with patients with neuropathic pain of the extremities not meeting CRPS criteria. MATERIALS AND METHODS: This was a retrospective cross-sectional study conducted at a tertiary pain center. The sample included 212 patients who met Budapest Criteria for CRPS and 175 patients with neuropathic pain of the extremities who did not meet criteria. All patients completed a packet of questionnaires before their initial visit containing validated outcome measures assessing pain severity, pain interference, physical functioning, depression, anxiety, and catastrophizing. RESULTS: Patients with CRPS reported higher physical disability (p=0.022) and more neuropathic pain symptoms (p=0.002) than patients not meeting CRPS criteria, but the groups did not otherwise differ significantly. There were no significant differences in pain severity or affective distress, despite power analyses suggesting the ability to detect small to medium effect sizes (d=0.29; w=0.14). Subanalyses of differences in neuropathic pain symptoms revealed that patients with CRPS, compared with patients not meeting CRPS criteria, were more likely to report pain with light touch (p=0.003), sudden pain attacks (p=0.003), pain with cold or heat (p=0.002), sensation of numbness (p=0.042), and pain with slight pressure (p=0.018). DISCUSSION: Counter to our hypothesis, the present study suggests that patients with CRPS do not have a worse clinical phenotype compared with patients not meeting CRPS criteria, with the exception of higher physical disability and more neuropathic pain symptoms. This corresponds to recent evidence that patients with CRPS are similar to other patient populations with chronic pain.

Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers.

Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time-neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG) was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.

Time Since Inciting Event Is Associated With Higher Centralized Pain Symptoms in Patients Diagnosed With Complex Regional Pain Syndrome.

BACKGROUND AND OBJECTIVES: We hypothesized that patients with complex regional pain syndrome (CRPS) with a longer time since their inciting event would demonstrate more symptoms of centralized pain. METHODS: We conducted a cross-sectional analysis of 160 patients with CRPS using validated measures of pain, negative mood, and functioning at the time of their new patient evaluation. The 2011 Fibromyalgia Survey Criteria is a validated self-report measure of widespread body pain and comorbid symptoms (eg, trouble thinking, headaches). The measure was used as a surrogate for centralized pain symptoms. Univariate analyses and multivariate linear regression models were used to assess the associations between patient characteristics and the duration of CRPS. RESULTS: The cohort was divided into tertiles based on the time since the inciting event (<12 months; 1-3 years; >3 years) for univariate comparisons. Unlike the other measures of pain, mood, and function, the fibromyalgia survey score was significantly associated with a longer duration of symptoms. In a multivariate model adjusting for age and sex, each year since the inciting event was associated with an increase of 0.28 in fibromyalgia survey score (Est 0.28; 95% confidence interval, 0.11-0.46; P = 0.002). The finding was distinct from self-reported spread of CRPS symptoms, which was not different based on time since the inciting event. CONCLUSIONS: Our findings suggest that the longer the patients have CRPS the more likely they are to report symptoms suggestive of centralized pain. These data may explain why some patients with a longer duration of CRPS do not respond to peripherally directed therapies.