AMPAkines have site-specific analgesic effects in the cortex.

Different brain areas have distinct roles in the processing and regulation of pain and thus may form specific pharmacological targets. Prior research has shown that AMPAkines, a class of drugs that increase glutamate signaling, can enhance descending inhibition from the prefrontal cortex (PFC) and nucleus accumbens. On the other hand, activation of neurons in the anterior cingulate cortex (ACC) is known to produce the aversive component of pain. The impact of AMPAkines on ACC, however, is not known. We found that direct delivery of CX516, a well-known AMPAkine, into the ACC had no effect on the aversive response to pain in rats. Furthermore, AMPAkines did not modulate the nociceptive response of ACC neurons. In contrast, AMPAkine delivery into the prelimbic region of the prefrontal cortex (PL) reduced pain aversion. These results indicate that the analgesic effects of AMPAkines in the cortex are likely mediated by the PFC but not the ACC.

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients.

Introduction: Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known. Methods: We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data. Results: As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia. Discussion: These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.

Anterior cingulate cortex regulates pain catastrophizing-like behaviors in rats.

Negative pain expectation including pain catastrophizing is a well-known clinical phenomenon whereby patients amplify the aversive value of a painful or oftentimes even a similar, non-painful stimulus. Mechanisms of pain catastrophizing, however, remain elusive. Here, we modeled pain catastrophizing behavior in rats, and found that rats subjected to repeated noxious pin pricks on one paw demonstrated an aversive response to similar but non-noxious mechanical stimuli delivered to the contralateral paw. Optogenetic inhibition of pyramidal neuron activity in the anterior cingulate cortex (ACC) during the application of repetitive noxious pin pricks eliminated this catastrophizing behavior. Time-lapse calcium (Ca2+) imaging in the ACC further revealed an increase in spontaneous neural activity after the delivery of noxious stimuli. Together these results suggest that the experience of repeated noxious stimuli may drive hyperactivity in the ACC, causing increased avoidance of subthreshold stimuli, and that reducing this hyperactivity may play a role in treating pain catastrophizing.

Oxytocin promotes prefrontal population activity via the PVN-PFC pathway to regulate pain.

Neurons in the prefrontal cortex (PFC) can provide top-down regulation of sensory-affective experiences such as pain. Bottom-up modulation of sensory coding in the PFC, however, remains poorly understood. Here, we examined how oxytocin (OT) signaling from the hypothalamus regulates nociceptive coding in the PFC. In vivo time-lapse endoscopic calcium imaging in freely behaving rats showed that OT selectively enhanced population activity in the prelimbic PFC in response to nociceptive inputs. This population response resulted from the reduction of evoked GABAergic inhibition and manifested as elevated functional connectivity involving pain-responsive neurons. Direct inputs from OT-releasing neurons in the paraventricular nucleus (PVN) of the hypothalamus are crucial to maintaining this prefrontal nociceptive response. Activation of the prelimbic PFC by OT or direct optogenetic stimulation of oxytocinergic PVN projections reduced acute and chronic pain. These results suggest that oxytocinergic signaling in the PVN-PFC circuit constitutes a key mechanism to regulate cortical sensory processing.

Temporal pain processing in the primary somatosensory cortex and anterior cingulate cortex.

Pain is known to have sensory and affective components. The sensory pain component is encoded by neurons in the primary somatosensory cortex (S1), whereas the emotional or affective pain experience is in large part processed by neural activities in the anterior cingulate cortex (ACC). The timing of how a mechanical or thermal noxious stimulus triggers activation of peripheral pain fibers is well-known. However, the temporal processing of nociceptive inputs in the cortex remains little studied. Here, we took two approaches to examine how nociceptive inputs are processed by the S1 and ACC. We simultaneously recorded local field potentials in both regions, during the application of a brain-computer interface (BCI). First, we compared event related potentials in the S1 and ACC. Next, we used an algorithmic pain decoder enabled by machine-learning to detect the onset of pain which was used during the implementation of the BCI to automatically treat pain. We found that whereas mechanical pain triggered neural activity changes first in the S1, the S1 and ACC processed thermal pain with a reasonably similar time course. These results indicate that the temporal processing of nociceptive information in different regions of the cortex is likely important for the overall pain experience.

A prototype closed-loop brain-machine interface for the study and treatment of pain.

Chronic pain is characterized by discrete pain episodes of unpredictable frequency and duration. This hinders the study of pain mechanisms and contributes to the use of pharmacological treatments associated with side effects, addiction and drug tolerance. Here, we show that a closed-loop brain-machine interface (BMI) can modulate sensory-affective experiences in real time in freely behaving rats by coupling neural codes for nociception directly with therapeutic cortical stimulation. The BMI decodes the onset of nociception via a state-space model on the basis of the analysis of online-sorted spikes recorded from the anterior cingulate cortex (which is critical for pain processing) and couples real-time pain detection with optogenetic activation of the prelimbic prefrontal cortex (which exerts top-down nociceptive regulation). In rats, the BMI effectively inhibited sensory and affective behaviours caused by acute mechanical or thermal pain, and by chronic inflammatory or neuropathic pain. The approach provides a blueprint for demand-based neuromodulation to treat sensory-affective disorders, and could be further leveraged for nociceptive control and to study pain mechanisms.

Closed-loop stimulation using a multiregion brain-machine interface has analgesic effects in rodents.

Effective treatments for chronic pain remain limited. Conceptually, a closed-loop neural interface combining sensory signal detection with therapeutic delivery could produce timely and effective pain relief. Such systems are challenging to develop because of difficulties in accurate pain detection and ultrafast analgesic delivery. Pain has sensory and affective components, encoded in large part by neural activities in the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC), respectively. Meanwhile, studies show that stimulation of the prefrontal cortex (PFC) produces descending pain control. Here, we designed and tested a brain-machine interface (BMI) combining an automated pain detection arm, based on simultaneously recorded local field potential (LFP) signals from the S1 and ACC, with a treatment arm, based on optogenetic activation or electrical deep brain stimulation (DBS) of the PFC in freely behaving rats. Our multiregion neural interface accurately detected and treated acute evoked pain and chronic pain. This neural interface is activated rapidly, and its efficacy remained stable over time. Given the clinical feasibility of LFP recordings and DBS, our findings suggest that BMI is a promising approach for pain treatment.

Distance correlation application to gene co-expression network analysis.

BACKGROUND: To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear (such as Pearson's correlation) and monotonic (such as Spearman's correlation) dependence metrics, are not enough to observe the nature of real biological systems. Hence, introducing a more informative correlation metric when constructing gene co-expression networks is still an interesting topic. RESULTS: In this paper, we test distance correlation, a correlation metric integrating both linear and non-linear dependence, with other three typical metrics (Pearson's correlation, Spearman's correlation, and maximal information coefficient) on four different arrays (macrophage and liver) and RNA-seq (cervical cancer and pancreatic cancer) datasets. Among all the metrics, distance correlation is distribution free and can provide better performance on complex relationships and anti-outlier. Furthermore, distance correlation is applied to Weighted Gene Co-expression Network Analysis (WGCNA) for constructing a gene co-expression network analysis method which we named Distance Correlation-based Weighted Gene Co-expression Network Analysis (DC-WGCNA). Compared with traditional WGCNA, DC-WGCNA can enhance the result of enrichment analysis and improve the module stability. CONCLUSIONS: Distance correlation is better at revealing complex biological relationships between gene profiles compared with other correlation metrics, which contribute to more meaningful modules when analyzing gene co-expression networks. However, due to the high time complexity of distance correlation, the implementation requires more computer memory.

Disrupted population coding in the prefrontal cortex underlies pain aversion.

The prefrontal cortex (PFC) regulates a wide range of sensory experiences. Chronic pain is known to impair normal neural response, leading to enhanced aversion. However, it remains unknown how nociceptive responses in the cortex are processed at the population level and whether such processes are disrupted by chronic pain. Using in vivo endoscopic calcium imaging, we identify increased population activity in response to noxious stimuli and stable patterns of functional connectivity among neurons in the prelimbic (PL) PFC from freely behaving rats. Inflammatory pain disrupts functional connectivity of PFC neurons and reduces the overall nociceptive response. Interestingly, ketamine, a well-known neuromodulator, restores the functional connectivity among PL-PFC neurons in the inflammatory pain model to produce anti-aversive effects. These results suggest a dynamic resource allocation mechanism in the prefrontal representations of pain and indicate that population activity in the PFC critically regulates pain and serves as an important therapeutic target.

AMPAkines potentiate the corticostriatal pathway to reduce acute and chronic pain.

The corticostriatal circuit plays an important role in the regulation of reward- and aversion-types of behaviors. Specifically, the projection from the prelimbic cortex (PL) to the nucleus accumbens (NAc) has been shown to regulate sensory and affective aspects of pain in a number of rodent models. Previous studies have shown that enhancement of glutamate signaling through the NAc by AMPAkines, a class of agents that specifically potentiate the function of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, reduces acute and persistent pain. However, it is not known whether postsynaptic potentiation of the NAc with these agents can achieve the full anti-nociceptive effects of PL activation. Here we compared the impact of AMPAkine treatment in the NAc with optogenetic activation of the PL on pain behaviors in rats. We found that not only does AMPAkine treatment partially reconstitute the PL inhibition of sensory withdrawals, it fully occludes the effect of the PL on reducing the aversive component of pain. These results indicate that the NAc is likely one of the key targets for the PL, especially in the regulation of pain aversion. Furthermore, our results lend support for neuromodulation or pharmacological activation of the corticostriatal circuit as an important analgesic approach.

Pharmacological restoration of anti-nociceptive functions in the prefrontal cortex relieves chronic pain.

Chronic pain affects one in four adults, and effective non-sedating and non-addictive treatments are urgently needed. Chronic pain causes maladaptive changes in the cerebral cortex, which can lead to impaired endogenous nociceptive processing. However, it is not yet clear if drugs that restore endogenous cortical regulation could provide an effective therapeutic strategy for chronic pain. Here, we studied the nociceptive response of neurons in the prelimbic region of the prefrontal cortex (PL-PFC) in freely behaving rats using a spared nerve injury (SNI) model of chronic pain, and the impact of AMPAkines, a class of drugs that increase central glutamate signaling, on such response. We found that neurons in the PL-PFC increase their firing rates in response to noxious stimulations; chronic neuropathic pain, however, suppressed this important cortical pain response. Meanwhile, CX546, a well-known AMPAkine, restored the anti-nociceptive response of PL-PFC neurons in the chronic pain condition. In addition, both systemic administration and direct delivery of CX546 into the PL-PFC inhibited symptoms of chronic pain, whereas optogenetic inactivation of the PFC neurons or administration of AMPA receptor antagonists in the PL-PFC blocked the anti-nociceptive effects of CX546. These results indicate that restoration of the endogenous anti-nociceptive functions in the PL-PFC by pharmacological agents such as AMPAkines constitutes a successful strategy to treat chronic neuropathic pain.

Predictive coding models for pain perception.

Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats-two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out-thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.

Frequency Dependent Electrical Stimulation of PFC and ACC for Acute Pain Treatment in Rats.

As pain consists of both sensory and affective components, its management by pharmaceutical agents remains difficult. Alternative forms of neuromodulation, such as electrical stimulation, have been studied in recent years as potential pain treatment options. Although electrical stimulation of the brain has shown promise, more research into stimulation frequency and targets is required to support its clinical applications. Here, we studied the effect that stimulation frequency has on pain modulation in the prefrontal cortex (PFC) and the anterior cingulate cortex (ACC) in acute pain models in rats. We found that low-frequency stimulation in the prelimbic region of the PFC (PL-PFC) provides reduction of sensory and affective pain components. Meanwhile, high-frequency stimulation of the ACC, a region involved in processing pain affect, reduces pain aversive behaviors. Our results demonstrate that frequency-dependent neuromodulation of the PFC or ACC has the potential for pain modulation.

Effect of the Inclination Angle on Premixed Flame Dynamics in Half-Open Ducts.

The propagation of premix methane/air flames in long half-open ducts with different inclination angles θ between the sidewall and the horizon was numerically investigated using the laminar model. The numerical result was compared with the experimental and theoretical ones to validate the numerical model. The results show that the numerical results are in good agreement with them. The investigation provides the basic understanding of the effects on changing the shape of the ducts to promote the premixed flame combustion. For methane/air, the position where the flame front begins to concave is pushed back with the increase in angle θ. The so-called "tulip" flame even disappeared, if the angle θ is bigger than one certain value. Moreover, the flame propagation speed and pressure are enhanced as the angle θ increases. In addition, the numerical simulation indicates that the burning gas creates an eddy near the tip of the flame, altering the flow field and causing the tulip flame to appear. However, with the angle θ increased, the flame propagation is restrained by the change in sidewalls, resulting in the different flow patterns to suppress the formation of tulip flames and promote flame combustion.

Ketamine normalizes high-gamma power in the anterior cingulate cortex in a rat chronic pain model.

Chronic pain alters cortical and subcortical plasticity, causing enhanced sensory and affective responses to peripheral nociceptive inputs. Previous studies have shown that ketamine had the potential to inhibit abnormally amplified affective responses of single neurons by suppressing hyperactivity in the anterior cingulate cortex (ACC). However, the mechanism of this enduring effect has yet to be understood at the network level. In this study, we recorded local field potentials from the ACC of freely moving rats. Animals were injected with complete Freund's adjuvant (CFA) to induce persistent inflammatory pain. Mechanical stimulations were administered to the hind paw before and after CFA administration. We found a significant increase in the high-gamma band (60-100 Hz) power in response to evoked pain after CFA treatment. Ketamine, however, reduced the high-gamma band power in response to evoked pain in CFA-treated rats. In addition, ketamine had a sustained effect on the high-gamma band power lasting up to five days after a single dose administration. These results demonstrate that ketamine has the potential to alter maladaptive neural responses in the ACC induced by chronic pain.

Mapping Cortical Integration of Sensory and Affective Pain Pathways.

Pain is an integrated sensory and affective experience. Cortical mechanisms of sensory and affective integration, however, remain poorly defined. Here, we investigate the projection from the primary somatosensory cortex (S1), which encodes the sensory pain information, to the anterior cingulate cortex (ACC), a key area for processing pain affect, in freely behaving rats. By using a combination of optogenetics, in vivo electrophysiology, and machine learning analysis, we find that a subset of neurons in the ACC receives S1 inputs, and activation of the S1 axon terminals increases the response to noxious stimuli in ACC neurons. Chronic pain enhances this cortico-cortical connection, as manifested by an increased number of ACC neurons that respond to S1 inputs and the magnified contribution of these neurons to the nociceptive response in the ACC. Furthermore, modulation of this S1→ACC projection regulates aversive responses to pain. Our results thus define a cortical circuit that plays a potentially important role in integrating sensory and affective pain signals.

Granger causality analysis of rat cortical functional connectivity in pain.

OBJECTIVE: The primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) are two of the most important cortical brain regions encoding the sensory-discriminative and affective-emotional aspects of pain, respectively. However, the functional connectivity of these two areas during pain processing remains unclear. Developing methods to dissect the functional connectivity and directed information flow between cortical pain circuits can reveal insight into neural mechanisms of pain perception. APPROACH: We recorded multichannel local field potentials (LFPs) from the S1 and ACC in freely behaving rats under various conditions of pain stimulus (thermal versus mechanical) and pain state (naive versus chronic pain). We applied Granger causality (GC) analysis to the LFP recordings and inferred frequency-dependent GC statistics between the S1 and ACC. MAIN RESULTS: We found an increased information flow during noxious pain stimulus presentation in both S1[Formula: see text]ACC and ACC[Formula: see text]S1 directions, especially at theta and gamma frequency bands. Similar results were found for thermal and mechanical pain stimuli. The chronic pain state shares common observations, except for further elevated GC measures especially in the gamma band. Furthermore, time-varying GC analysis revealed a negative correlation between the direction-specific and frequency-dependent GC and animal's paw withdrawal latency. In addition, we used computer simulations to investigate the impact of model mismatch, noise, missing variables, and common input on the conditional GC estimate. We also compared the GC results with the transfer entropy (TE) estimates. SIGNIFICANCE: Our results reveal functional connectivity and directed information flow between the S1 and ACC during various pain conditions. The dynamic GC analysis support the hypothesis of cortico-cortical information loop in pain perception, consistent with the computational predictive coding paradigm.

A network-based pathway-extending approach using DNA methylation and gene expression data to identify altered pathways.

Pathway analysis allows us to gain insights into a comprehensive understanding of the molecular mechanisms underlying cancers. Currently, high-throughput multi-omics data and various types of large-scale biological networks enable us to identify cancer-related pathways by comprehensively analyzing these data. Combining information from multidimensional data, pathway databases and interaction networks is a promising strategy to identify cancer-related pathways. Here we present a novel network-based approach for integrative analysis of DNA methylation and gene expression data to extend original pathways. The results show that the extension of original pathways can provide a basis for discovering new components of the original pathway and understanding the crosstalk between pathways in a large-scale biological network. By inputting the gene lists of the extended pathways into the classical gene set analysis (ORA and FCS), we effectively identified the altered pathways which are correlated well with the corresponding cancer. The method is evaluated on three datasets retrieved from TCGA (BRCA, LUAD and COAD). The results show that the integration of DNA methylation and gene expression data through a network of known gene interactions is effective in identifying altered pathways.