Chronic pain is a significant problem and it has been estimated to affect about 50 million adult Americans. It accounts for more than 600 billion dollars in health care expenditures, disability and loss of productivity and remains one of the most common reasons that patients seek healthcare. Spinal cord stimulation (SCS) is a Food and Drug Administration (FDA)-approved neuromodulation treatment to relieve chronic refractory pain. While SCS can be used effectively in many patients with refractory chronic pain conditions, a significant portion of the patients receive suboptimal or inadequate pain suppression. Considering that over 30,000 individuals receive SCS implantation on an annual basis for chronic pain and an annual cost of over $24,000 per patient resulting from lack of satisfactory pain relief due to lack of consensus regarding optimal stimulation parameters, it is crucial to improve the clinical efficacy of SCS in chronic refractory pain. Beside the traditional stimulation (tonic), using novel stimulation waveforms such as burst and high frequency stimulation (HFS) is one approach. These waveforms do not induce paresthesia (sensation of tingling or numbness) and their effects are often delayed 24- 48 hours unlike tonic stimulation, where the effects are immediate. However, the supraspinal effects of these waveforms are still not very clear. It is also unknown why some patients respond well to one waveform over another. Another limitation is that assessment of the pain relief by SCS depends almost exclusively on patient self-reports and lack of objective measurements of SCS implants results might lead to increased number of failed permanent placements. In this regard, investigating neural patterns of SCS waveforms and assess SCS-induced pain relief by using electroencephalography (EEG) in awake and anesthetized chronic pain patients appears essential. Our preliminary data suggests that changes in alpha peak frequency and ratio of alpha and theta band power might be correlated to SCS-induced pain relief. The spatial distribution of these patterns is closely related to which waveform is used. We hypothesize that intra-operative EEG demonstrates similar spatio-spectral patterns to post-operative EEG. We predict that pain relief will correlate best with increased alpha band power in frontal and somatosensory regions in burst stimulation and somatosensory cortical regions in HFS. In this proposal, our objectives are to determine the relationship between alpha band features and SCS-induced pain relief in awake patients (Aim 1), determine the spatio-spectral differences between “sleep” and awake states EEG and characterize the intra-operative neural correlates of pain relief (Aim 2), and examine the changes in alpha band features when patients with minimal pain relief are reprogrammed to experience pain relief (Aim 3). Specifically, in Aim 3, we will develop a mathematical model based on these neural features and patients will be temporarily programmed to this EEG-guided setting. We will investigate the predictive power of the assessed neural patterns on selection of the optimal waveform. The immediate goal of this project is to develop quantified, neural signatures of pain relief. These objective markers could form an objective metric for device selection, which might reduce the healthcare expenditures associated with failed implants and help in guiding SCS parameters for better pain relief, especially in patients with minimal pain relief. Overall, these objective neurophysiological measures can be used for more personalized SCS therapy with higher efficacy, and, this study can contribute to development of neurotechnologies and neuroengineering methodologies.
