# Electroencephalography, magnetoencephalography and pain: where do we stand, and where are we going

Luis Garcia-Larrea, Nathalie André-Obadia

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Luis Garcia-Larrea, Nathalie André-Obadia. Electroencephalography, magnetoencephalography and pain: where do we stand, and where are we going. Pain, 2025, 166 (11S), pp.S65-S70. 10.1097/j.pain.0000000000003689. hal-05139668

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# Electroencephalography, magnetoencephalography and pain: where do we stand, and where are we going

Luis Garcia-Larreaª,*, Nathalie André-Obadiaª,ᵇ

## Abstract

Considerable progress has been made over the past decade in the use, practicality, and clinical relevance of electroencephalography (EEG) and magnetoencephalography (MEG)-derived data, improving our understanding of cortical nociceptive processing, the transition from nociception to conscious pain, and its cognitive-emotional modulations. Multimodal responses to heat, cold, and tactile/electrical stimuli, combined with autonomic reactions, provide objective sensory tests that bypass the limitations of verbal responses, while emerging approaches to spontaneous EEG/MEG analysis are changing the game in the still elusive area of ongoing pain. We can expect that all departments involved in the assessment of chronic pain will gradually be able to access these powerful and flexible techniques.

**Keywords:** EEG, MEG, Electroencephalography, Magnetoencephalography, Event-related, Evoked potentials, Laser, LEP, CHEP, CEP, Neuropathic pain, Chronic pain, Thalamocortical dysrhythmia, Alpha peak frequency, PAF

## 1. Introduction

Among the noninvasive techniques exploring brain activity, electroencephalography (EEG) and magnetoencephalography (MEG) provide the best temporal resolution with a reasonable spatial selectivity. Electroencephalography and magnetoencephalography reveal millisecond activity patterns of local brain networks, and their inter-regional correlation reflects functional connectivity. Electroencephalography and magnetoencephalography are safe, noninvasive, and the low cost of EEG-derived methods is attractive for daily clinical use. This article does not attempt any direct comparison of EEG vs MEG, which would be out of scope. It reviews the joint contribution of these techniques to characterize cortical pain processing and pathological pain states, but also the insufficiencies and oversimplifications which hamper their practical use, together with possible avenues which should enlarge their applicability in the next decade.

## 2. Event-related electroencephalography/ magnetoencephalography

In contrast to responses linked to the activation of large peripheral fibres available since the mid-20th century, brain responses to pain and temperature were inaccessible until the 1980s¹³ when laser technology allowed activating selectively and synchronously

A-delta/C fibres conveying thermo-nociceptive input. Since then, laser-evoked potentials (LEPs) have provided enormous advances in our understanding of pain physiology: Combined scalp and intracranial recordings uncovered the differential organization of sensory cortex to tactile vs painful stimuli,²⁹,¹⁰⁶ highlighted the role of postero-dorsal insula and adjacent operculum as a functional unit receiving thermo-noxious input,³⁵,⁸⁷ and described the timing of nociceptive modulation by attention and distraction.²⁶,⁸⁰,¹⁰³ The temporal resolution of EEG/MEG allowed demonstrating that nociceptive input reached sensorimotor, cingulate-attentional, and amygdala-affective areas simultaneously,⁶,²⁹,¹⁰⁹ before the orderly involvement of multiple networks ensuring the transition to conscious pain.³⁰,³³

The clinical use of Laser-EPs has been, by contrast, relatively restricted. Significant results have been reported regarding the characterization of painful neuropathies,²³,³⁸,⁵⁷,⁹⁹,¹²⁴ the differential diagnosis of neuropathic vs non-neuropathic pain,⁷⁴,⁸³ and the mechanistic dissection of neuropathic syndromes,³⁶,¹²⁶,¹²⁷ including the pathophysiological distinction of constant vs paroxysmal pain.¹²⁵,¹²⁷ In addition, LEPs allowed for diagnosis of previously unrecognized central pain syndromes¹⁷,³⁷ and demonstrated nociceptive disinhibition in migraine and nociceptive widespread pain.²⁰,¹³¹,¹³² However, due to expensive equipment and technical and safety constraints, the routine clinical use of LEPs has remained limited to groups acting in large hospitals. Less expensive and handier alternatives for selective stimulation of thin fibres have been developed using intra-epidermal electrodes,⁵²,¹³⁶ and especially with the use of contact thermodes capable to deliver heat and cold pulses to the skin.

Contact heat-evoked responses (CHEPs) had been reported in the 1990s,⁴⁵,⁵³ but slow temperature ramps (50-70°C/second) with insufficient synchronisation of afferent fibres limited their clinical use.⁴ Newly developed contact thermodes generating much steeper temperature ramps (up to 300°C/second) can trigger cortical responses of comparable quality to laser EPs⁷⁰

<footnote>Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.</footnote>

<footnote>ª Neuropain Lab, Lyon Centre for Neuroscience (CNRL), INSERM U1028 & University Claude Bernard Lyon 1, Lyon, France, ᵇ Department of Functional Neurology & Epileptology, Neurological University Hospital, Lyon, France</footnote>

<footnote>*Corresponding author. Address: Neuropain Lab, Lyon Centre for Neuroscience (CNRL), INSERM U1028 & University Claude Bernard Lyon 1, 69677 Lyon, France. E-mail address: larrea@univ-lyon1.fr (L. Garcia-Larrea).</footnote>

<footnote>© 2025 International Association for the Study of Pain http://dx.doi.org/10.1097/j.pain.0000000000003689</footnote>
and permit the recording of both heat and cold-evoked potentials (CEPs) of sufficient quality for single-patient clinical use. Notably, cooling pulses activate A-delta fibres at non-noxious ranges, which is important in clinical settings, and CEPs were recently applied successfully with diagnostic purposes in central and peripheral neuropathic cohorts by different groups.⁵⁸,¹⁰⁵ In a head-to-head study, CEPs and LEPs were found to be highly correlated, but selective CEP abnormalities were observed in patients with symptoms limited to cold perception.¹⁰⁵

Although event-related EEG/MEG responses accurately reflect “negative” symptoms (axonal loss or desynchronisation), they have notorious difficulties to reflect “positive” manifestations of neuropathic pain (hyperalgesia and allodynia), whose assessment commonly relies on verbal reports. Autonomic markers such as pupillary dilation, heart rate, or sympathetic skin responses are able to capture arousal reactions triggered by pain and can objectify hyperalgesic reactions in both healthy subjects¹¹¹,¹¹⁶ and patients, including infants.⁵¹,⁸⁴ The coexistence of attenuated cortical responses (reflecting somatosensory damage) with exaggerated vegetative reactions (reflecting pain-related hyperarousal) is a signature of neuropathic allodynia or hyperalgesia. Combining cortical responses to different stimulus modes (thermal, prick, and electrical) with autonomic reactions and psychophysical measurements is enabling to develop a comprehensive phenotypic assessment of patients suffering chronic pain, through objective quantitative sensory testing.²⁴,³⁴ Being able to correlate subjective and objective pain responses in a cost-effective way and within a timeframe compatible with clinical requirements is an achievable goal for the next decade.

### 3. Resting-state electroencephalography/ magnetoencephalography measures

Unlike epilepsy, metabolic failure, or impaired vigilance, chronic pain states do not produce changes directly visible on the spontaneous EEG/MEG, so their interpretation requires more sophisticated processing methods, principally frequency or time-frequency analysis. These techniques decompose the complex EEG signal into a sum of sinusoids at different frequencies and analyse the relative importance of frequency bands reflecting different aspects of brain function. This approach has been applied to assess pain-related brain activity in healthy volunteers and chronic pain patients.

The discovery that neurons within the thalamus of neuropathic pain patients exhibited abnormal low-frequency bursting gave rise to the “thalamocortical dysrhythmia” (TCD) concept.⁴⁸,⁵⁵,⁷³ Thalamocortical dysrhythmia postulates that thalamic bursts induce abnormal cortical oscillatory patterns that are potentially detectable by EEG/MEG and underlie abnormal pain states.⁷³,⁸¹ Similar thalamic bursting can be recorded during physiological sleep⁴⁸,¹²⁸ and also in patients with “productive” symptoms different from pain, such as tremor, dystonia, or tinnitus.⁵⁶,¹⁰⁷ It is therefore considered that the precise thalamic location of the dysrhythmia may determine the occurrence of pain or other positive symptoms.⁸⁵,¹³⁵

Thalamocortical dysrhythmia is considered to produce EEG/MEG abnormal oscillations at theta frequencies (4-7 Hz), replacing alpha activity (8-12 Hz).¹⁴,⁷³,¹²⁰ Indeed, power increase in the theta band has been often reported in NP patients⁹,¹¹²,¹¹⁸ and viewed as a characteristic of neuropathic pain (reviews in Refs. 100, 138). The specificity of these findings remains doubtful, however, because identical abnormalities have been reported in non-neuropathic pain syndromes such as fibromyalgia or migraine,²¹,²⁵,⁷⁹ as well as in major depression or

pathological fatigue.⁴⁷,¹¹⁸ A common feature in these studies is that most patients were treated with psychotropic drugs, which also entail characteristic increases in theta power.²,⁸,⁸⁶ Although the effects of medication have been sometimes dismissed,¹³⁹ their relevance is supported by clinical EEG data spanning 30 years (review in Ref. 2) and by the lack of theta power changes observed in patient's groups with no or little exposure to psychotropic medication.⁶⁶,¹¹⁷,¹³⁴

A related abnormality reported in both experimental and chronic pain states is the slowing of peak alpha frequency (PAF), which entails a shift of the spectrum toward lower frequencies, and tends to also enhance theta power. This effect has been often reported in chronic pain conditions²²,²⁷,⁴⁹,⁵⁹,⁷⁹,¹¹³,¹¹⁴ and used to tentatively distinguish phenotypic clusters¹²¹ or predict postsurgical pain.⁴⁴,⁹⁷ Low PAF values were suggested as a potential marker of individual pain susceptibility in healthy volunteers.¹⁶,³¹,³²,¹⁰⁸

As with TCD, some inconsistent results and confounders hamper the use of peak alpha frequency to detect pain states. Psychotropic medication, attention deficits, low arousal, and physical fatigue can by themselves decrease PAF independently of pain,²,⁸,⁶⁴,¹⁰¹ and conversely PAF can remain unchanged under both neuropathic⁶⁶,¹²² and non-neuropathic¹⁸,⁸²,⁹⁴ pain conditions, and was found inconsistently related to improvement after multimodal analgesia⁴⁶ or general analgesic procedures (compare the following references).⁴⁶,⁹²,⁹⁸,¹¹⁵ The predictive value of PAF on postoperative pain is also subject to confounders because executive and memory deficits, which also predict postsurgical pain,⁵,⁶²,⁸⁹ are themselves associated with lower PAF values.⁷,⁶⁴,⁶⁵

In healthy volunteers, pain sensitivity was inconstantly associated to PAF: experimental pain could entail either PAF decrease,³¹,³² increase,¹⁰² or no change,⁹¹ and PAF behaved quite similarly in response to painful stimuli or unpleasant sounds.¹²⁹,¹³⁰ This has led several authors to suggest that PAF changes reflect nonspecific adjustments in cortical activity such as changes in attention, arousal, or active blocking of sensory inputs which, although can be associated to pain, are causally independent from pain sensitivity.¹⁹,⁵⁰,⁷⁸,⁹¹,⁹³,¹²⁹,¹³⁰ Accordingly, PAF analyses guided by positron-emission tomography or functional MRI showed strong correlation with attentional networks including the thalamus, insula, and anterior cingulate, supporting a robust relationship between PAF and attention/salience network function.⁵⁴,⁹³

### 3.1. Avenues for the near future

The complexity of painful experiences cannot possibly be captured by simple metrics such as frequency shifts or power changes, and new EEG/MEG processing methods are needed to expand our understanding of physiological and pathological pain mechanisms. Some of them extend existing methods, eg, using Bayesian hypothesis testing, applying multiverse analysis¹¹⁹ or focusing in aperiodic spectral components,⁴⁴,⁴⁶,⁷² while others such as network connectivity combined with source analysis represent real changes in paradigm.⁶⁷,¹²²

Network connectivity models analyse brain activity for functionally interconnected networks detected by source reconstruction algorithms¹,¹⁰,⁹⁵ and amenable to dynamic graph analysis.²⁸,¹³³ When based on robust anatomo-physiological hypotheses and a sufficient density of sensors, mathematical source reconstructions have closely matched intracranial recordings of pain responses.¹¹ Combining source and network analyses with functional connectivity measures has led to
concepts such as the "dynamic pain connectome" (DPC⁶⁷), encompassing networks that are highly correlated during both spontaneous and pain-related activity, and whose alteration may underlie abnormal pain states. Dynamic pain connectome studies have shown abnormal coupling between spontaneous and evoked network activity in neuropathic vs non-neuropathic patients,⁶⁰,⁶³ with notable sex differences.²⁷

Electroencephalography/magnetoencephalography "micro-states" are short-time periods of stable configuration of potential fields, suggesting quasi-simultaneous activity among the nodes of large-scale networks, and defining distinct functional moments of the resting brain.⁹⁶ Initially developed more than 30 years ago,⁶⁹ their application to pain research is however very recent and takes advantage of new computing procedures such as source analysis. Microstate abnormalities have been recently reported in different chronic pain conditions, including fibromyalgia, migraine, and complex regional pain syndrome,³⁹,⁷⁶,¹⁰⁴,¹⁴⁰ and the technique has been used to separate chronic pain phenotypes⁹⁰ to predict postoperative pain after cancer surgery⁷⁷ and procedural pain responses in neonates.¹² Although these studies are still preliminary and their potential confounders rarely assessed, microstate/source analysis appears as a robust technique resistant to artefacts and able to capture rapidly changing brain states, which should develop and automatize in coming years.

Despite advances in automatized data processing, extracting meaningful activity patterns with the methods above is highly time-consuming. To improve clinical applicability, artificial intelligence machine learning (ML) procedures are being explored, whereby algorithms are trained to detect patterns in initial data sets, and then identify them in new data. Their reliability and potential clinical implementation remain a matter of debate, but recent results have shown promise in detecting the emergence of subjective pain perception,¹⁵,⁴³,¹¹⁰ classifying EEG patterns in chronic pain patients,⁶¹,⁷⁵,¹²²,¹³⁵ predicting pain after neural injury,³,⁴³,⁷¹,¹²³ or predicting success of therapeutic procedures.⁴⁰⁻⁴²,¹³⁷ Although in general machine learning discriminated groups better than chance, it offered only moderate levels of sensitivity/specificity. Accordingly, while recognising that ML may eventually be useful to assist clinical care, a recent review found poor reporting, methodological heterogeneity, and limited validation across 44 studies, thereby hindering clinical translation.⁸⁸ Notwithstanding such difficulties, the field is evolving rapidly, and an interesting avenue where ML could rapidly outclass previous approaches is the segregation of potential "pain markers" across different conditions (neuropathic, nociceptive, and Parkinson-related) through huge data banks that are increasingly available.⁶⁸,¹³⁵ This approach may disentangle nonspecific alterations due to medication or other confounders, from disease-specific changes serving as potential markers of disease progression or intensity.

## 4. Conclusions

Electroencephalography and magnetoencephalography have led to a better understanding of cortical nociceptive processing, its cognitive-emotional modulations, and the subsecond transition from nociception to conscious pain. Evoked EEG/MEG responses already provide objective markers of somatosensory lesions or diseases associated with neuropathic pain. While simple spectral changes proposed as pain biomarkers are challenged by lack of specificity, emerging approaches exploring nonperiodic EEG/MEG features, microstates, and network models of the "dynamic pain connectome" are

changing the landscape. Combined with evoked brain activity, psychophysical, and autonomic data, they are refining both clinical phenotyping and diagnostic power for the benefit of our patients.

## Conflict of interest statement

The authors declare that they have no conflicts of interest relevant to this paper.

## Acknowledgements

This work received support from the Network of European Funding for Neuroscience Research (ERA-NET Neuron Transnational Networking Groups on Chronic Pain 2022.ANR-23-NEUG-0001-01).

## Article history:

Received 16 April 2025

Received in revised form 15 May 2025

Accepted 16 May 2025

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