Exploration of the Pathophysiology of Chronic Pain Using Quantitative EEG Source Localization.

Chronic pain affects more than 35% of the US adult population representing a major public health imperative. Currently, there are no objective means for identifying the presence of pain, nor for quantifying pain severity. Through a better understanding of the pathophysiology of pain, objective indicators of pain might be forthcoming. Brain mechanisms mediating the painful state were imaged in this study, using source localization of the EEG. In a population of 77 chronic pain patients, significant overactivation of the "Pain Matrix" or pain network, was found in brain regions including, the anterior cingulate, anterior and posterior insula, parietal lobule, thalamus, S1, and dorsolateral prefrontal cortex (DLPFC), consistent with those reported with conventional functional imaging, and extended to include the mid and posterior cingulate, suggesting that the increased temporal resolution of electrophysiological measures may allow a more precise identification of the pain network. Significant differences between those who self-report high and low pain were reported for some of the regions of interest (ROIs), maximally on left hemisphere in the DLPFC, suggesting encoding of pain intensity occurs in a subset of pain network ROIs. Furthermore, a preliminary multivariate logistic regression analysis was used to select quantitative-EEG features which demonstrated a highly significant predictive relationship of self-reported pain scores. Findings support the potential to derive a quantitative measure of the severity of pain using information extracted from a multivariate descriptor of the abnormal overactivation. Furthermore, the frequency specific (theta/low alpha band) overactivation in the regions reported, while not providing direct evidence, are consistent with a model of thalamocortical dysrhythmia as the potential mechanism of the neuropathic painful condition.

Evaluation of the pain matrix using EEG source localization: a feasibility study.

OBJECTIVES: An extensive neuroimaging literature on chronic pain demonstrates increased cerebral blood flow and metabolism consistent with increased neuronal activity in the structures comprising the "pain matrix"; furthermore, some of these regions have been shown to encode pain intensity. It is the objective of this study to demonstrate the feasibility of using quantitative electroencephalography (EEG) source localization to reflect and to quantify activity in the pain matrix. METHODS: Eyes closed resting EEG was recorded from 19 standardized scalp locations, in a pilot sample of five patients with chronic neuropathic pain, before and after pain reduction. Quantitative electro encephalography (QEEG) source localization was computed estimating the mathematically most probable source generators of EEG surface potentials in each state. Sources identified in this way have been demonstrated to coregister with those identified by neuroimaging methods. RESULTS: QEEG sources demonstrated frequency specific increased neuronal activity in the baseline high pain state in structures including the thalamus, somatosensory cortex, anterior and posterior insula, medial and lateral prefrontal cortex and cingulate. Significant reduction of activation in these regions was seen when pain was reduced (≥50% on subjective ratings). CONCLUSION: The areas that were activated in the high pain state localized to the same regions reported by other neuroimaging methods and with frequency specificity. The frequency and regionally specific activation may indicate distinctive patterns of pathophysiology underlying the pain matrix. Although in a small number of patients, this work suggests that QEEG may be a useful tool in the exploration and quantification of the pain matrix in a clinical setting.

Source imaging of QEEG as a method to detect awareness in a person in vegetative state.

BACKGROUND: Assessment of awareness in patients with severe brain injury remains subjective, although patients with even limited awareness (e.g. minimal conscious state, MCS) have different prognoses and treatment than those in vegetative state (VS). Recently, task appropriate differential regional activation in VS has been reported using fMRI during mental imagery. PRIMARY OBJECTIVE: Demonstration of conscious awareness in reproducible differential EEG source localization images in a VS patient reflecting requested mental imagery was performed. METHODS: A VS patient (with re-test) and a normal control were requested to imagine singing and to mentally perform serial subtraction, while EEG was recorded. QEEG source localization was performed to identify regions of brain activation in response to tasks. RESULTS: Replicable distinctive activation of brain areas appropriate for each task was seen in the VS patient and control. Frequency spectra shifted to beta, with significant source activation in regions including the bilateral anterior cingulate, insula, left caudate and dorsolateral pre-frontal cortex to singing and the putamen, insula, left pre-frontal cortex and right temporal gyrus to subtraction by 7's. CONCLUSIONS: Results from this single case suggests the potential utility of QEEG source localization images to detect awareness in patients clinically diagnosed as being in VS. This indicates the possibility that EEG may serve as an important adjunct to the assessment of awareness in patients with disorders of consciousness in the clinical setting.

Outcome related electrophysiological subtypes of cocaine dependence.

We previously described the existence of two quantitative EEG (QEEG) subtypes of cocaine dependent males, identified at baseline, displaying differential proneness to relapse. The current study expands the population to include females and enhances the measure set to include both QEEG and somatosensory EP (SEP) features. Fifty-seven cocaine dependent adults (16 F, 41 M) were evaluated 5-14 days after last cocaine use, while in residence at a drug-free therapeutic community. The median length of stay in treatment (continued abstinence) was 25 weeks. Using a small subset of QEEG and SEP baseline features, three subtypes (CLUS) were identified. CLUS 2 (n = 25) and CLUS 3 (n = 23) replicated the published subtypes, while CLUS 1 (n = 9) was previously undescribed. Cluster membership was significantly associated with length of stay in treatment (chi 2 = 13.789, P < 0.001), but not with length of exposure to crack cocaine or to any demographic or clinical features. Seventy-eight percent of CLUS 1 and 65% of CLUS 3 left treatment < or = 25 weeks, whereas 80% of CLUS 2 remained in treatment > 25 weeks. The existence of outcome related subtypes may reflect: [1] differential neurophysiological vulnerability, "traits," predisposing individuals to cocaine addiction; or [2] differential neurosensitivity, "states," due to the effects of chronic cocaine exposure, and associated differences in treatment outcome. Using Variable Resolution Electrical Tomographic Analysis (VARETA), the mathematically most probable neuroanatomical source of the scalp recorded EEG data was localized. Computation of VARETA on the baseline Cluster profiles suggest significant differences in the underlying pathophysiology of these subtypes.