Pre-stimulus alpha power affects vertex N2-P2 potentials evoked by noxious stimuli

Event-related modulation of alpha rhythm explains the auditory P300-evoked response in EEG

Evoked responses and oscillations represent two major electrophysiological phenomena in the human brain yet the link between them remains rather obscure. Here we show how most frequently studied EEG signals: the P300-evoked response and alpha oscillations (8-12 Hz) can be linked with the baseline-shift mechanism. This mechanism states that oscillations generate evoked responses if oscillations have a non-zero mean and their amplitude is modulated by the stimulus. Therefore, the following predictions should hold: (1) the temporal evolution of P300 and alpha amplitude is similar, (2) spatial localisations of the P300 and alpha amplitude modulation overlap, (3) oscillations are non-zero mean, (4) P300 and alpha amplitude correlate with cognitive scores in a similar fashion. To validate these predictions, we analysed the data set of elderly participants (N=2230, 60-82 years old), using (a) resting-state EEG recordings to quantify the mean of oscillations, (b) the event-related data, to extract parameters of P300 and alpha rhythm amplitude envelope. We showed that P300 is indeed linked to alpha rhythm, according to all four predictions. Our results provide an unifying view on the interdependency of evoked responses and neuronal oscillations and suggest that P300, at least partly, is generated by the modulation of alpha oscillations.

Intensity-dependent modulation of cortical somatosensory processing during external, low-frequency peripheral nerve stimulation in humans

External low-frequency peripheral nerve stimulation (LFS) has been proposed as a novel method for neuropathic pain relief. Previous studies have reported that LFS elicits long-term depression-like effects on human pain perception when delivered at noxious intensities, whereas lower intensities are ineffective. To shed light on cortical regions mediating the effects of LFS, we investigated changes in somatosensory-evoked potentials (SEPs) during four LFS intensities. LFS was applied to the radial nerve (600 pulses, 1 Hz) of 24 healthy participants at perception (1 times), low (5 times), medium (10 times), and high intensities (15 times detection threshold). SEPs were recorded during LFS, and averaged SEPs in 10 consecutive 1-min epochs of LFS were analyzed using source dipole modeling. Changes in resting electroencephalography (EEG) were investigated after each LFS block. Source activity in the midcingulate cortex (MCC) decreased linearly during LFS, with greater attenuation at stronger LFS intensities, and in the ipsilateral operculo-insular cortex during the two lowest LFS stimulus intensities. Increased LFS intensities resulted in greater augmentation of contralateral primary sensorimotor cortex (SI/MI) activity. Stronger LFS intensities were followed by increased α (alpha, 9-11 Hz) band power in SI/MI and decreased θ (theta, 3-5 Hz) band power in MCC. Intensity-dependent attenuation of MCC activity with LFS is consistent with a state of long-term depression. Sustained increases in contralateral SI/MI activity suggests that effects of LFS on somatosensory processing may also be dependent on satiation of SI/MI. Further research could clarify if the activation of SI/MI during LFS competes with nociceptive processing in neuropathic pain.NEW & NOTEWORTHY Somatosensory-evoked potentials during low-frequency stimulation of peripheral nerves were examined at graded stimulus intensities. Low-frequency stimulation was associated with decreased responsiveness in the midcingulate cortex and increased responsiveness in primary sensorimotor cortex. Greater intensities were associated with increased midcingulate cortex θ band power and decreased sensorimotor cortex α band power. Results further previous evidence of an inhibition of somatosensory processing during and after low-frequency stimulation and point toward a potential augmentation of activity in somatosensory processing regions.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Predictability modulates the anticipation and perception of pain in both self and others

Predictability has been suggested to modulate both the anticipation and perception of self-pain. Considering the overlapping neural circuits between self-pain and other-pain perceptions, the present study investigated how the predictability of forthcoming pain modulates the anticipation and perception of self-pain and other-pain. We used a balanced, within-participant experimental design in which a visual cue indicating the recipient, intensity and predictability of an upcoming painful electrical stimulation was presented before its delivery. Subjective ratings and electroencephalography activities to the anticipation and perception of self-pain and other-pain were recorded and compared between certain and uncertain conditions. Results showed that predictability affected the perception of self-pain and other-pain in a similar manner such that the differences in behavioral ratings and event-related potentials to high-intensity and low-intensity pain were significantly reduced when the intensity was uncertain. The strengths of predictability-induced modulation of self-pain and other-pain perceptions were positively correlated with each other. Furthermore, predictability also modulated the anticipation of both self-pain and other-pain such that pre-stimulus high-frequency α-oscillation power at sensorimotor electrodes contralateral to the stimulation side was maximally suppressed when anticipating certain high-intensity pain. These findings demonstrate that predictability-induced modulation on pain anticipation and perception was similarly applied to both self-pain and other-pain.

Magnitude and Temporal Variability of Inter-stimulus EEG Modulate the Linear Relationship Between Laser-Evoked Potentials and Fast-Pain Perception

The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice.

Pain Related Cortical Oscillations: Methodological Advances and Potential Applications

Alongside the time-locked event-related potentials (ERPs), nociceptive somatosensory inputs can induce modulations of ongoing oscillations, appeared as event-related synchronization or desynchronization (ERS/ERD) in different frequency bands. These ERD/ERS activities are suggested to reflect various aspects of pain perception, including the representation, encoding, assessment, and integration of the nociceptive sensory inputs, as well as behavioral responses to pain, even the precise details of their roles remain unclear. Previous studies investigating the functional relevance of ERD/ERS activities in pain perception were normally done by assessing their latencies, frequencies, magnitudes, and scalp distributions, which would be then correlated with subjective pain perception or stimulus intensity. Nevertheless, these temporal, spectral, and spatial profiles of stimulus induced ERD/ERS could only partly reveal the dynamics of brain oscillatory activities. Indeed, additional parameters, including but not limited to, phase, neural generator, and cross frequency couplings, should be paid attention to comprehensively and systemically evaluate the dynamics of oscillatory activities associated with pain perception and behavior. This would be crucial in exploring the psychophysiological mechanisms of neural oscillation, and in understanding the neural functions of cortical oscillations involved in pain perception and behavior. Notably, some chronic pain (e.g., neurogenic pain and complex regional pain syndrome) patients are often associated with the occurrence of abnormal synchronized oscillatory brain activities, and selectively modulating cortical oscillatory activities has been showed to be a potential therapy strategy to relieve pain with the application of neurostimulation techniques, e.g., repeated transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS). Thus, the investigation of the oscillatory activities proceeding from phenomenology to function, opens new perspectives to address questions in human pain psychophysiology and pathophysiology, thereby promoting the establishment of rational therapeutic strategy.

Pre-stimulus alpha and post-stimulus N2 foreshadow imminent errors in a single task

Performance errors have been attributed to distinct neural mechanisms in different tasks. Two temporally and physiologically dissociable neural patterns prior to errors, i.e., pre-stimulus alpha (8-13 Hz) power indicative of sustained attention and post-stimulus N2 amplitude indicative of cognitive control, have been widely (but independently) reported in many studies. However, it is still largely unknown whether these two neural mechanisms for error commission exist in a single task at the same time and, if so, whether they can be probed simultaneously and how they lead to response accuracy (collectively or separately). To this end, we measured high-density electroencephalography (EEG) signals in a color-word matching Stroop task. We quantified both patterns on EEG data from individual stimulus condition (congruent or incongruent), as well as on pooled data from both conditions. Enhanced pre-stimulus alpha power for errors was identified over the parieto-occipital area in the congruent condition and the pooled data. Reduced post-stimulus N2 amplitude was only revealed in the incongruent condition. More importantly, for the first time, a balanced interaction between these two EEG patterns was revealed in correct trials, but not in error trials. These findings suggest that errors in one task could occur due to distinct neural mechanisms, e.g., poor sustained attention, poor cognitive control, or missed balance between these two. The present results further suggest that the detection of neural patterns related to different neural mechanisms could be complicated by other modulation factors, such as stimulus condition. Therefore, more than one neural marker should be simultaneously monitored to effectively predict imminent errors.

Machine learning on encephalographic activity may predict opioid analgesia

BACKGROUND

Opioids are used for the treatment of pain. However, 30-50% of patients have insufficient effect to the opioid initially selected by the physician, and there is an urgent need for biomarkers to select responders to the most appropriate drug. Since opioids mediate their effect in the central nervous system, this study aimed to investigate if electroencephalography (EEG) during rest or pain before treatment could predict the analgesic response.

METHODS

EEG from 62 channels was recorded in volunteers during rest and tonic pain (cold pressor test). Morphine (30 mg) or placebo was then administered, and the pain test repeated 60 min after. Washout period between drugs was 7 days. Based on pain ratings, subjects were stratified into responders and non-responders. Spectral analysis was performed on the EEG. Conventional statistics on group basis were used and, furthermore, the most discriminative EEG features were subjected to support vector machine classification to predict the response for the individual subjects.

RESULTS

Conventional statistics on the frequency bands revealed no differences between responders and non-responders. On the individual basis, no differences between groups were found using resting EEG. However, EEG during cold pain was able to classify responders with an accuracy of 72% (p = 0.01) and the result was reproducible using baseline data from both study days.

CONCLUSIONS

Machine learning based on EEG before treatment enabled separation between responders and non-responders. This study represents the first step towards the prediction of opioid analgesia based on EEG features prior to drug administration, and advocates for the use of machine learning in future studies.

Subjective pain perception mediated by alpha rhythms

Suppression of spontaneous alpha oscillatory activities, interpreted as cortical excitability, was observed in response to both transient and tonic painful stimuli. The changes of alpha rhythms induced by pain could be modulated by painful sensory inputs, experimental tasks, and top-down cognitive regulations such as attention. The temporal and spatial characteristics, as well as neural functions of pain induced alpha responses, depend much on how these factors contribute to the observed alpha event-related desynchronization/synchronization (ERD/ERS). How sensory-, task-, and cognitive-related changes of alpha oscillatory activities interact in pain perception process is reviewed in the current study, and the following conclusions are made: (1) the functional inhibition hypothesis that has been proposed in auditory and visual modalities could be applied also in pain modality; (2) the neural functions of pain induced alpha ERD/ERS were highly dependent on the cortical regions where it is observed, e.g., somatosensory cortex alpha ERD/ERS in pain perception for painful stimulus processing; (3) the attention modulation of pain perception, i.e., influences on the sensory and affective dimensions of pain experience, could be mediated by changes of alpha rhythms. Finally, we propose a model regarding the determinants of pain related alpha oscillatory activity, i.e., sensory-discriminative, affective-motivational, and cognitive-modulative aspects of pain experience, would affect and determine pain related alpha oscillatory activities in an integrated way within the distributed alpha system.

Characterizing the cortical activity through which pain emerges from nociception

Nociception begins when Adelta- and C-nociceptors are activated. However, the processing of nociceptive input by the cortex is required before pain can be consciously experienced from nociception. To characterize the cortical activity related to the emergence of this experience, we recorded, in humans, laser-evoked potentials elicited by physically identical nociceptive stimuli that were either perceived or unperceived. Infrared laser pulses, which selectively activate skin nociceptors, were delivered to the hand dorsum either as a pair of rapidly succeeding and spatially displaced stimuli (two-thirds of trials) or as a single stimulus (one-third of trials). After each trial, subjects reported whether one or two distinct painful pinprick sensations, associated with Adelta-nociceptor activation, had been perceived. The psychophysical feedback after each pair of stimuli was used to adjust the interstimulus interval (ISI) of the subsequent pair: when a single percept was reported, ISI was increased by 40 ms; when two distinct percepts were reported, ISI was decreased by 40 ms. This adaptive algorithm ensured that the probability of perceiving the second stimulus of the pair tended toward 0.5. We found that the magnitude of the early-latency N1 wave was similar between perceived and unperceived stimuli, whereas the magnitudes of the later N2 and P2 waves were reduced when stimuli were unperceived. These findings suggest that the N1 wave represents an early stage of sensory processing related to the ascending nociceptive input, whereas the N2 and P2 waves represent a later stage of processing related, directly or indirectly, to the perceptual outcome of this nociceptive input.

Fundamentals of electroencefalography, magnetoencefalography, and functional magnetic resonance imaging

This review introduces readers to fundamentals of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI). EEG and MEG signals are mainly produced by postsynaptic ionic currents of synchronically active pyramidal cortical neurons. These signals reflect the integrative information processing of neurons representing the output of cortical neural modules. EEG and MEG signals have a high temporal resolution (<1ms) ideal to investigate an emerging propriety of brain physiology, namely the brain rhythms. A background spontaneous oscillatory activity of brain neurons at about 10Hz generates dominant alpha rhythms of resting-state EEG and MEG activity. This background activity is blocked during sensory and cognitive-motor events. Standard EEG shows a low spatial resolution (5-9cm), which partially improves by high-resolution EEG including 64-128 channels and source estimation techniques (1-3cm); source estimation of MEG data shows a better spatial resolution (0.5-2cm). fMRI is an indirect measurement of regional brain activity based on the ratio between deoxyhemoglobin and oxyhemoglobin blood (BOLD) during events referenced to baseline conditions. Event-related BOLD response has low temporal resolution (>1s) and quite high spatial resolution (<1cm), and is especially suitable to investigate spatial details of both cortical and subcortical activation.