Characteristics of local field potentials correlate with pain relief by deep brain stimulation

Rates and Predictors of Pain Reduction With Intracranial Stimulation for Intractable Pain Disorders

BACKGROUND AND OBJECTIVES

Intracranial modulation paradigms, namely deep brain stimulation (DBS) and motor cortex stimulation (MCS), have been used to treat intractable pain disorders. However, treatment efficacy remains heterogeneous, and factors associated with pain reduction are not completely understood.

METHODS

We performed an individual patient review of pain outcomes (visual analog scale, quality-of-life measures, complications, pulse generator implant rate, cessation of stimulation) after implantation of DBS or MCS devices. We evaluated 663 patients from 36 study groups and stratified outcomes by pain etiology and implantation targets.

RESULTS

Included studies comprised primarily retrospective cohort studies. MCS patients had a similar externalized trial success rate compared with DBS patients (86% vs 81%; P = .16), whereas patients with peripheral pain had a higher trial success rate compared with patients with central pain (88% vs 79%; P = .004). Complication rates were similar for MCS and DBS patients (12% vs 15%; P = .79). Patients with peripheral pain had lower likelihood of device cessation compared with those with central pain (5.7% vs 10%; P = .03). Of all implanted patients, mean pain reduction at last follow-up was 45.8% (95% CI: 40.3-51.2) with a 31.2% (95% CI: 12.4-50.1) improvement in quality of life. No difference was seen between MCS patients (43.8%; 95% CI: 36.7-58.2) and DBS patients (48.6%; 95% CI: 39.2-58) or central (41.5%; 95% CI: 34.8-48.2) and peripheral (46.7%; 95% CI: 38.9-54.5) etiologies. Multivariate analysis identified the anterior cingulate cortex target to be associated with worse pain reduction, while postherpetic neuralgia was a positive prognostic factor.

CONCLUSION

Both DBS and MCS have similar efficacy and complication rates in the treatment of intractable pain. Patients with central pain disorders tended to have lower trial success and higher rates of device cessation. Additional prognostic factors include anterior cingulate cortex targeting and postherpetic neuralgia diagnosis. These findings underscore intracranial neurostimulation as an important modality for treatment of intractable pain disorders.

The Influence of Etiology and Stimulation Target on the Outcome of Deep Brain Stimulation for Chronic Neuropathic Pain: A Systematic Review and Meta-Analysis

OBJECTIVES

Deep brain stimulation (DBS) to treat chronic neuropathic pain has shown variable outcomes. Variations in pain etiologies and DBS targets are considered the main contributing factors, which are, however, underexplored owing to a paucity of patient data in individual studies. An updated meta-analysis to quantitatively assess the influence of these factors on the outcome of DBS for chronic neuropathic pain is warranted, especially considering that the anterior cingulate cortex (ACC) has emerged recently as a new DBS target.

MATERIALS AND METHODS

A comprehensive literature review was performed in PubMed, Embase, and Cochrane data bases to identify studies reporting quantitative outcomes of DBS for chronic neuropathic pain. Pain and quality of life (QoL) outcomes, grouped by etiology and DBS target, were extracted and analyzed (α = 0.05).

RESULTS

Twenty-five studies were included for analysis. Patients with peripheral neuropathic pain (PNP) had a significantly greater initial stimulation success rate than did patients with central neuropathic pain (CNP). Both patients with CNP and patients with PNP with definitive implant, regardless of targets, gained significant follow-up pain reduction. Patients with PNP had greater long-term pain relief than did patients with CNP. Patients with CNP with ACC DBS gained less long-term pain relief than did those with conventional targets. Significant short-term QoL improvement was reported in selected patients with CNP after ACC DBS. However, selective reporting bias was expected, and the improvement decreased in the long term.

CONCLUSIONS

Although DBS to treat chronic neuropathic pain is generally effective, patients with PNP are the preferred population over patients with CNP. Current data suggest that ACC DBS deserves further investigation as a potential way to treat the affective component of chronic neuropathic pain.

Neural mechanisms of priming effects of spicy food pictures induced analgesia

In this study, the effects of the priming of spicy food pictures on pain perception were evaluated in female participants using standardized methods of pain. Results from behavior tests revealed that the priming of spicy food pictures significantly reduced pain perception, particularly at high-pain intensities. Electrophysiological analysis showed that the analgesic effects of spicy food pictures were linked to decreased pain-related event-related potentials, such as N2 and P2 amplitudes, and suppressed θ-oscillations in the sensorimotor cortex. Both N2 amplitudes and θ-oscillations activities were found to be correlated with participants' pain perception. These results suggest that spicy-arousal stimuli may act as an "antagonist" to the increase in N2 amplitudes and θ-oscillations power induced by pain and influence the neuronal networks involved in integrating spontaneous nociceptive resources, which supports the dissociation theory of pain sensation and affection. These findings highlight the potential use of spicy-arousal stimuli as an analgesic and emphasize the importance of considering both the intensity of the stimuli and the individual's emotional state in the assessment and treatment of pain.

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

Real-time removal of stimulation artifacts in closed-loop deep brain stimulation

Objective.Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters.Approach.We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals andin vivoclosed-loop DBS applications in Parkinsonian animal models.Main results. The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2-150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS applicationsin vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations.Significance.The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.

Decoding pain from brain activity

Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.

A Controlled Thermoalgesic Stimulation Device for Exploring Novel Pain Perception Biomarkers

OBJECTIVE

To develop a new device for identifying physiological markers of pain perception by reading the brain's electrical activity and hemodynamic interactions while applying thermoalgesic stimulation.

METHODS

We designed a compact prototype that generates well-controlled thermal stimuli using a computer-driven Peltier cell while simultaneously capturing electroencephalography (EEG) and photoplethysmography (PPG) signals. The study was performed on 35 healthy subjects (mean age 30.46 years, SD 4.93 years; 20 males, 15 females). We first determined the heat pain threshold (HPT) for each subject, defined as the maximum temperature that the subject can withstand when the Peltier cell gradually increased the temperature. Next, we defined the painful condition as the one occurring at temperature equal to 90% of the HPT, comparing this to the no-pain state (control) in the absence of thermoalgesic stimulation.

RESULTS

Both the one-dimensional and the two-dimensional spectral entropy (SE) obtained from both the EEG and PPG signals differentiated the condition of pain. In particular, the SE for PPG was significantly reduced in association with pain, while the SE for EEG increased slightly. Moreover, significant discrimination occurred within a specific range of frequencies, 26-30 Hz for EEG and about 5-10 Hz for PPG.

CONCLUSION

Hemodynamics, brain dynamics and their interactions can discriminate thermal pain perception.

SIGNIFICANCE

The possibility of monitoring on-line variations in thermal pain perception using a similar device and algorithms may be of interest to study different pathologies that affect the peripheral nervous system, such as small fiber neuropathies, fibromyalgia or painful diabetic neuropathy.

Supraspinal Effects of Dorsal Root Ganglion Stimulation in Chronic Pain Patients

OBJECTIVES

Dorsal root ganglion stimulation (DRGS) has become a popular neuromodulatory treatment for neuropathic pain. We used magnetoencephalography (MEG) to investigate potential biomarkers of pain and pain relief, based on the differences in power spectral density (PSD) during varying degrees of pain and how these oscillations change during DRGS-mediated pain relief.

MATERIALS AND METHODS

Thirteen chronic pain patients with implanted dorsal root ganglion stimulators were included in the MEG analysis. MEG Recordings were performed at rest while the stimulator was turned ON or OFF. Numerical rating scale (NRS) scores were also recorded before and after DRGS was turned OFF and ON. Power spectral and source localization analyses were then performed on preprocessed MEG recordings.

RESULTS

With DRGS-OFF, patients in severe pain had significantly increased cortical theta (4-7 Hz) power and decreased cortical alpha (7-13 Hz) power compared to patients reporting less pain. This shift in power toward lower frequencies was contrasted by a shift toward the higher frequency power spectrum (low beta 13-20 Hz activity) during DRGS-mediated pain relief. A significant correlation was found between the increase in low beta activity and the degree of reported pain relief.

CONCLUSION

Our results demonstrate increased low-frequency power spectral activity in chronic pain patients in the absence of stimulation which shifts toward higher frequency power spectrum activity in response to therapeutic DRGS. These cortical changes in response to DRGS provide support for the use of neuroimaging in the search for potential biomarkers of pain.

Functional dynamics of thalamic local field potentials correlate with modulation of neuropathic pain

Understanding the functional dynamics of neural oscillations in the sensory thalamus is essential for elucidating the perception and modulation of neuropathic pain. Local field potentials were recorded from the sensory thalamus of twelve neuropathic pain patients. Single and combinational neural states were defined by the activity state of a single or paired oscillations. Relationships between the duration or occurrence rate of neural state and pre-operative pain level or pain relief induced by deep brain stimulation were evaluated. Results showed that the occurrence rate of the single neural state of low-beta oscillation was significantly correlated with pain relief. The duration and occurrence rate of combinational neural states of the paired low-beta with delta, theta, alpha, high-beta or low-gamma oscillations were more significantly correlated with pain relief than the single neural states. Moreover, these significant combinational neural states formed a local oscillatory network with low-beta oscillation as a key node. The results also showed correlations between measures of combinational neural states and subjective pain level as well. The duration of combinational neural states of paired alpha with delta or theta oscillations and the occurrence rate of neural states of the paired delta with low-beta or low-gamma oscillations were significantly correlated with pre-operative pain level. In conclusion, this study revealed that the integration of oscillations and the functional dynamics of neural states were differentially involved in modulation and perception of neuropathic pain. The functional dynamics could be biomarkers for developing neural state-dependent deep brain stimulation for neuropathic pain.

Electroacupuncture Treatment Alleviates the Remifentanil-Induced Hyperalgesia by Regulating the Activities of the Ventral Posterior Lateral Nucleus of the Thalamus Neurons in Rats

Mechanisms underlying remifentanil- (RF-) induced hyperalgesia, a phenomenon that is generally named as opioid-induced hyperalgesia (OIH), still remain elusive. The ventral posterior lateral nucleus (VPL) of the thalamus, a key relay station for the transmission of nociceptive information to the cerebral cortex, is activated by RF infusion. Electroacupuncture (EA) is an effective method for the treatment of pain. This study aimed to explore the role of VPL in the development of OIH and the effect of EA treatment on OIH in rats. RF was administered to rats via the tail vein for OIH induction. Paw withdrawal threshold (PWT) in response to mechanical stimuli and paw withdrawal latency (PWL) to thermal stimulation were tested in rats for the assessment of mechanical allodynia and thermal hyperalgesia, respectively. Spontaneous neuronal activity and local field potential (LFP) in VPL were recorded in freely moving rats using the in vivo multichannel recording technique. EA at 2 Hz frequency (pulse width 0.6 ms, 1-3 mA) was applied to the bilateral acupoints "Zusanli" (ST.36) and "Sanyinjiao" (SP.6) in rats. The results showed that both the PWT and PWL were significantly decreased after RF infusion to rats. Meanwhile, both the spontaneous neuronal firing rate and the theta band oscillation in VPL LFP were increased on day 3 post-RF infusion, indicating that the VPL may promote the development of RF-induced hyperalgesia by regulating the pain-related cortical activity. Moreover, 2 Hz-EA reversed the RF-induced decrease both in PWT and PWL of rats and also abrogated the RF-induced augmentation of the spontaneous neuronal activity and the power spectral density (PSD) of the theta band oscillation in VPL LFP. These results suggested that 2 Hz-EA attenuates the remifentanil-induced hyperalgesia via reducing the excitability of VPL neurons and the low-frequency (theta band) oscillation in VPL LFP.

Gi protein functions in thalamic neurons to decrease orofacial nociceptive response

Orofacial pain includes neuronal pathways that project from the trigeminal nucleus to and through the thalamus. What role the ventroposterior thalamic complex (VP) has on orofacial pain transmission is not understood. To begin to address this question an inhibitory G protein (Gi) designer receptor exclusively activated by a designer drug (DREADD) was transfected in cells of the VP using adeno-associated virus isotype 8. Virus infected cells were identified by a fluorescent tag and immunostaining. Cells were silenced after injecting the designer drug clozapine-n-oxide, which binds the designer receptor activating Gi. Facial rubbing and local field potentials (LFP) in the VP were then recorded in awake, free moving Sprague Dawley rats after formalin injection of the masseter muscle to induce nociception. Formalin injection significantly increased LFP and the nociceptive behavioral response. Activation of DREADD Gi with clozapine-n-oxide significantly reduced LFP in the VP and reduced the orofacial nociceptive response. Because DREADD silencing can result from Gi-coupled inwardly-rectifying potassium channels (GIRK), the GIRK channel blocker tertiapin-Q was injected. Injection of GIRK blocker resulted in an increase in the nociceptive response and increased LFP activity. Immunostaining of the VP for glutamate vesicular transporter (VGLUT2) and gamma-aminobutyric acid vesicular transporter (VGAT) indicated a majority of the virally transfected cells were excitatory (VGLUT2 positive) and a minority were inhibitory (VGAT positive). We conclude first, that inhibition of the excitatory neurons within the VP reduced electrical activity and the orofacial nociceptive response and that the effect on excitatory neurons overwhelmed any change resulting from inhibitor neurons. Second, inhibition of LFP and nociception was due, in part, to GIRK activation.

Local field potential decoding of the onset and intensity of acute pain in rats

Pain is a complex sensory and affective experience. The current definition for pain relies on verbal reports in clinical settings and behavioral assays in animal models. These definitions can be subjective and do not take into consideration signals in the neural system. Local field potentials (LFPs) represent summed electrical currents from multiple neurons in a defined brain area. Although single neuronal spike activity has been shown to modulate the acute pain, it is not yet clear how ensemble activities in the form of LFPs can be used to decode the precise timing and intensity of pain. The anterior cingulate cortex (ACC) is known to play a role in the affective-aversive component of pain in human and animal studies. Few studies, however, have examined how neural activities in the ACC can be used to interpret or predict acute noxious inputs. Here, we recorded in vivo extracellular activity in the ACC from freely behaving rats after stimulus with non-noxious, low-intensity noxious, and high-intensity noxious stimuli, both in the absence and chronic pain. Using a supervised machine learning classifier with selected LFP features, we predicted the intensity and the onset of acute nociceptive signals with high degree of precision. These results suggest the potential to use LFPs to decode acute pain.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation

OBJECTIVE

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations.

APPROACH

Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model.

MAIN RESULTS

This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief.

SIGNIFICANCE

The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations.

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.