An fMRI-based neurologic signature of physical pain

Multi-voxel pattern analysis for developmental cognitive neuroscientists

The current prevailing approaches to analyzing task fMRI data in developmental cognitive neuroscience are brain connectivity and mass univariate task-based analyses, used either in isolation or as part of a broader analytic framework (e.g., BWAS). While these are powerful tools, it is somewhat surprising that multi-voxel pattern analysis (MVPA) is not more common in developmental cognitive neuroscience given its enhanced ability to both probe neural population codes and greater sensitivity relative to the mass univariate approach. Omitting MVPA methods might represent a missed opportunity to leverage a suite of tools that are uniquely poised to reveal mechanisms underlying brain development. The goal of this review is to spur awareness and adoption of MVPA in developmental cognitive neuroscience by providing a practical introduction to foundational MVPA concepts. We begin by defining MVPA and explain why examining multi-voxel patterns of brain activity can aid in understanding the developing human brain. We then survey four different types of MVPA: Decoding, representational similarity analysis (RSA), pattern expression, and voxel-wise encoding models. Each variant of MVPA is presented with a conceptual overview of the method followed by practical considerations and subvariants thereof. We go on to highlight the types of developmental questions that can be answered by MPVA, discuss practical matters in MVPA implementation germane to developmental cognitive neuroscientists, and make recommendations for integrating MVPA with the existing analytic ecosystem in the field.

Examining the role of physical activity in older adults with epilepsy

Epilepsy disproportionately affects older adults due to acquired conditions including stroke, neurodegeneration and head trauma secondary to falls. Current literature lacks adequate representation of specific therapies and considerations for this cohort. Furthermore, older adults are more susceptible to the adverse effects of anti-seizure medications necessitating increased caution when treating. Non-pharmacological interventions, including physical activity (PA), are underrecognized, particularly in older adults where they may be of greatest benefit. The following narrative review describes how older adults are uniquely impacted by epilepsy and associated comorbidities. It examines the current literature with respect to PA in epilepsy and, where available, evidence for PA in older adults. This includes how PA can affect pathogenesis and reduce the incidence of epilepsy onset through the reduction of neuroinflammation. PA may also be utilized by older adults with epilepsy to improve cardiovascular function, seizure control, prevent falls and secondary head injury, as an adjunct treatment for mood disorders and cognitive decline, and to promote general well-being. PA has a large and underappreciated role to play in older adults with epilepsy and is increasingly being recognized by healthcare providers and incorporated into practice guidelines.

Distinct functional cerebral hypersensitivity networks during incisional and inflammatory pain in rats

Although the pathophysiology of pain has been investigated tremendously, there are still many open questions with regard to specific pain entities and their pain-related symptoms. To increase the translational impact of (preclinical) animal neuroimaging pain studies, the use of disease-specific pain models, as well as relevant stimulus modalities, are critical. We developed a comprehensive framework for brain network analysis combining functional magnetic resonance imaging (MRI) with graph-theory (GT) and data classification by linear discriminant analysis. This enabled us to expand our knowledge of stimulus modalities processing under incisional (INC) and pathogen-induced inflammatory (CFA) pain entities compared to acute pain conditions. GT-analysis has uncovered specific features in pain modality processing that align well with those previously identified in humans. These include areas such as S1, M1, CPu, HC, piriform, and cingulate cortex. Additionally, we have identified unique Network Signatures of Pain Hypersensitivity (NSPH) for INC and CFA. This leads to a diminished ability to differentiate between stimulus modalities in both pain models compared to control conditions, while also enhancing aversion processing and descending pain modulation. Our findings further show that different pain entities modulate sensory input through distinct NSPHs. These neuroimaging signatures are an important step toward identifying novel cerebral pain biomarkers for certain diseases and relevant outcomes to evaluate target engagement of novel therapeutic and diagnostic options, which ultimately can be translated to the clinic.

Expectation generation and its effect on subsequent pain and visual perception

Bayesian accounts of perception, such as predictive processing, suggest that perceptions integrate expectations and sensory experience, and thus assimilate to expected values. Furthermore, more precise expectations should have stronger influences on perception. We tested these hypotheses using a within-subject paradigm that independently manipulated the mean, variance (precision), and skewness of cues presented as ratings from 10 prior participants. Forty-five participants reported their expectations regarding the painfulness of thermal stimuli or the visual contrast of flickering checkerboards. In a second session, similar (sham) cues were each followed by either a noxious thermal or a visual stimulus. Perceptions assimilated to cue-based expectations in both modalities, but precision effects were modality-specific: more precise cues enhanced assimilation in visual perception only, while higher uncertainty slightly increased reported pain. fMRI analysis revealed that the cues affected higher-level affective and cognitive systems-including assimilation to the cue mean in a neuromarker of endogenous pain processing and in the nucleus accumbens, and activity consistent with aversive prediction-error-like encoding in the periaqueductal gray during pain perception-but not early perceptual processing systems. Furthermore, behavioral and computational models of the expectation session revealed that expectations were biased towards extreme values in both modalities, and towards low-pain cues specifically. These findings suggest that predictive processing theories should be extended with mechanisms such as selective attention to outliers, and that expectation generation and its perceptual effects are mostly modality-specific and primarily influence higher-level processes rather than early perception, at least when cues are not reinforced.

Multimodal Correspondence between Optogenetic fMRI, Electrophysiology, and Anatomical Maps of the Secondary Somatosensory Cortex in Nonhuman Primates

Optogenetic neuromodulation combined with functional MRI (opto-fMRI) enables noninvasive monitoring of brain-wide activity and probes causal connections. In this study, we focused on the secondary somatosensory (S2) cortex, a hub for integrating tactile and nociceptive information. By selectively stimulating excitatory neurons in the S2 cortex of monkeys using optogenetics, we observed widespread opto-fMRI activity in regions beyond the somatosensory system, as well as a strong spatial correspondence between opto-fMRI activity map and anatomical connections of the S2 cortex. Locally, optogenetically evoked fMRI BOLD signals from putative excitatory neurons exhibited standard hemodynamic response function. At low laser power, graded opto-fMRI signal changes are closely correlated with increases in local field potential (LFP) signals, but not with spiking activity. This indicates that LFP changes in excitatory neurons more accurately reflect the opto-fMRI signals than spikes. In summary, our optogenetic fMRI and anatomical findings provide causal functional and anatomical evidence supporting the role of the S2 cortex as a critical hub connecting sensory regions to higher-order cortical and subcortical regions involved in cognition and emotion. The electrophysiological basis of the opto-fMRI signals uncovered in this study offers novel insights into interpreting opto-fMRI results. Nonhuman primates are an invaluable intermediate model for translating optogenetic preclinical findings to humans.

Naturalistic acute pain states decoded from neural and facial dynamics

Pain remains poorly understood in task-free contexts, limiting our understanding of its neurobehavioral basis in naturalistic settings. Here, we use a multimodal, data-driven approach with intracranial electroencephalography, pain self-reports, and facial expression analysis to study acute pain in twelve epilepsy patients under continuous neural and audiovisual monitoring. Using machine learning, we successfully decode individual participants' high versus low pain states from distributed neural activity, involving mesolimbic regions, striatum, and temporoparietal cortex. Neural representation of pain remains stable for hours and is modulated by pain onset and relief. Objective facial expressions also classify pain states, concordant with neural findings. Importantly, we identify transient periods of momentary pain as a distinct naturalistic acute pain measure, which can be reliably discriminated from affect-neutral periods using neural and facial features. These findings reveal reliable neurobehavioral markers of acute pain across naturalistic contexts, underscoring the potential for monitoring and personalizing pain interventions in real-world settings.

A plank across the explanatory gap: The case of pain

According to a widely shared belief, an explanation of phenomenal experience in terms of neural mechanisms is impossible in principle. The reason for this "Explanatory Gap" is supposed to be a basic incompatibility between phenomenal and neuroscientific knowledge: while the latter is framed in terms of functional relationships, it is impossible to capture phenomenal experience in functional terms. Here, we will take three steps to avert this conclusion and show what an explanation of the qualitative character of phenomenal experience might look like. In Step I, we show that two pivotal assumptions underlying the "Explanatory Gap" argument are unfounded. This means that the problem of phenomenal experience can be solved with the familiar methods of hypothesis development and testing. In Step II, we hypothesize that paradigmatic sorts of phenomenal experience like affective pain can be captured in functional terms, provided the function is framed in cognitive rather than behavioral terms: feeling affective pain is feeling an urge to avoid. In Step III, we will present empirical evidence corroborating this claim. We will also indicate how this functional description can help to identify the neural mechanisms underlying affective pain experience. We take this as a proof of principle showing that the qualitative character of phenomenal experience can be explained in objective neuroscientific terms. We will conclude with some remarks on how our approach might contribute to future progress in our understanding of consciousness in general.

An association study of multimodal neuroimage features and gene expression in adolescents with centrally mediated abdominal pain syndrome

Centrally mediated abdominal pain syndrome (CAPS) is a complex condition characterised by persistent abdominal discomfort in the absence of clear physiological abnormalities. Its aetiology remains poorly understood, but recent research has suggested that neurobiological and genetic factors may play an important role in the pathophysiology of the syndrome. We applied partial least squares regression (PLSR) to investigate the association between multimodal neuroimaging features of 313 participants and postmortem gene expression data from AIBS. Compared to HCs, we found that (1) cortical thickness of the left inferior parietal and temporal lobes, left cingulate cortex and left caudate, sulcal depth of the right lateral occipital gyrus and volume of the right parahippocampal and right insula showed significant differences, the GO biological processes associated with these differences are mainly in "cell-substrate junction"; (2) the correlation between the default mode network and the ventral attention network, the retrosplenial temporal network and the salience network, the fronto-parietal network and the right caudate are significantly increased, the GO biological processes associated with these increases are mainly in "cell junction organization"; and (3) the mean diffusivity of sub-adjacent white matter associated with cortical ROIs of frontal cortex, cingulate cortex, temporal cortex, precuneus and insula are significantly different, the associated GO biological processes are primarily in "chromatin organization". The changed characteristics of brain neuroimaging are closely related to the biological process of down-regulation or up-regulation of gene expression. Integrating the neurobiological and genetic underpinnings is crucial to provide a theoretical framework for the mechanism of CAPS in adolescents.

Alterations in static and dynamic functional network connectivity in chronic low back pain: a resting-state network functional connectivity and machine learning study

Low back pain (LBP) is a prevalent pain condition whose persistence can lead to changes in the brain regions responsible for sensory, cognitive, attentional, and emotional processing. Previous neuroimaging studies have identified various structural and functional abnormalities in patients with LBP; however, how the static and dynamic large-scale functional network connectivity (FNC) of the brain is affected in these patients remains unclear. Forty-one patients with chronic low back pain (cLBP) and 42 healthy controls underwent resting-state functional MRI scanning. The independent component analysis method was employed to extract the resting-state networks. Subsequently, we calculate and compare between groups for static intra- and inter-network functional connectivity. In addition, we investigated the differences between dynamic functional network connectivity and dynamic temporal metrics between cLBP patients and healthy controls. Finally, we tried to distinguish cLBP patients from healthy controls by support vector machine method. The results showed that significant reductions in functional connectivity within the network were found within the DMN,DAN, and ECN in cLBP patients. Significant between-group differences were also found in static FNC and in each state of dynamic FNC. In addition, in terms of dynamic temporal metrics, fraction time and mean dwell time were significantly altered in cLBP patients. In conclusion, our study suggests the existence of static and dynamic large-scale brain network alterations in patients with cLBP. The findings provide insights into the neural mechanisms underlying various brain function abnormalities and altered pain experiences in patients with cLBP.

Modified Feature Selection for Improved Classification of Resting-State Raw EEG Signals in Chronic Knee Pain

OBJECTIVE

Diagnosing pain in research and clinical practices still relies on self-report. This study aims to develop an automatic approach that works on resting-state raw EEG data for chronic knee pain prediction.

METHOD

A new feature selection algorithm called "modified Sequential Floating Forward Selection" (mSFFS) is proposed. The improved feature selection scheme can better avoid local minima andexplore alternative search routes.

RESULTS

The feature selection obtained by mSFFS displays better class separability as indicated by the Bhattacharyya distance measures and better visualization results. It also outperforms selections generated by other benchmark methods, boosting the test accuracy to 97.5%.

CONCLUSION

The improved feature selection searches out a compact, effective subset of connectivity features that produces competitive performance on chronic knee pain prediction.

SIGNIFICANCE

We have shown that an automatic approach can be employed to find a compact connectivity feature set that effectively predicts chronic knee pain from EEG. It may shed light on the research of chronic pains and lead to future clinical solutions for diagnosis and treatment.

Neural Patterns of Social Pain in the Brain-Wide Representations Across Social Contexts

Empathy can be elicited by physiological pain, as well as in social contexts. Although physiological and different social contexts induce a strong subjective experience of empathy, the general and context-specific neural representations remain elusive. Here, it is combined fMRI with multivariate pattern analysis (MVPA) to establish neurofunctional models for social pain triggered by observing social exclusion and separation naturistic stimuli. The findings revealed that both social contexts engaged the empathy and social function networks. Notably, the intensity of pain empathy elicited by these two social stimuli does not significantly differentiate the neural representations of social exclusion and separation, suggesting context-specific neural representations underlying these experiences. Furthermore, this study established a model that traces the progression from physiological pain to social pain empathy. In conclusion, this study revealed the neural pathological foundations and interconnectedness of empathy induced by social and physiological stimuli and provide robust neuromarkers to precisely evaluate empathy across physiological and social domains.

Comparing neural responses to cutaneous heat and pressure pain in healthy participants

Even though acute pain comes in many different shapes and forms, a lot of experimental pain studies predominantly employ cutaneous heat pain. This makes a comparison between different pain types and the link between findings from these experimental studies to clinical pain difficult. To bridge this gap, we investigated both cuff pressure pain and cutaneous heat pain using a within-subject design in combination with functional magnetic resonance imaging (fMRI). Noxious stimuli were applied with a 17-s duration at three different intensities above the pain threshold using a thermode and a computer-controlled cuff pressure device. Both pain modalities led to contralateral activation in the anterior insula and parietal operculum. Heat pain showed greater activation in the precentral gyrus, pontine reticular nucleus, and dorsal posterior insula, whilst pressure pain showed greater activation in the primary somatosensory cortex and bilateral superior parietal lobules. Most importantly, the time course of the fMRI signal changes differed between modalities, with pressure pain peaking in the first stimulus half, whereas heat pain led to a prolonged and increasing response across the stimulus duration with a peak in the second stimulus half. Our findings suggest that pressure and heat pain lead to common as well as different (temporal) activation patterns in key pain processing regions.

Periaqueductal gray functional connectivity abnormalities associated with acute post-traumatic headache

BACKGROUND

The purpose of this study was to investigate pain network and periaqueductal gray matter (PAG) functional connectivity (FC) in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI) compared to healthy controls (HC).

METHODS

Ninety-eight participants with acute PTH and 85 HC underwent 3 T magnetic resonance imaging. Static FC among regions of the pain matrix and between PAG to the rest of the brain were examined. Correlations between FC and clinical parameters were investigated using linear regression. PTH outcomes (improved or not improved) were determined at 3 months post-enrollment.

RESULTS

Stronger FC between the PAG and right somatosensory and left lingual areas, and weaker FC between left thalamus and left caudate were found in the PTH group compared to HC. Whole-brain analysis showed increased PAG FC, primarily with somatosensory, motor, and occipital areas of participants with PTH relative to HC. These differences had associations with headache frequency, state anxiety, and time since mTBI. A PAG FC model for PTH improvement at 3 months had a sensitivity of 82% and a specificity of 100%. Participants with PTH who did not improve at 3 months had stronger baseline FC from the PAG to the right temporal region and the left insula relative to the improved group or to HC.

CONCLUSION

PAG FC could serve as an early biomarker identifying participants with acute PTH at risk of developing persistent PTH.

The heart of social pain: examining resting blood pressure and neural sensitivity to exclusion

Previous work suggests blood pressure (BP) relates to social algesia, where those with higher BP are more tolerant of social pain. The neural correlates of this association, however, are unknown. Based on findings suggesting neural regions involved in physical pain are activated during social pain, the current study explores whether BP relates to subjective and neural responses to social pain, apart from emotional responding. BP was measured, after which participants completed emotional processing and social exclusion functional magnetic resonance imaging (fMRI) paradigms. Results replicated previous findings, with higher systolic BP related to lower trait sensitivity to social pain. However, there were no associations between BP and reported sensitivity to social pain during social exclusion. Moreover, after accounting for adiposity, we found no association between BP and anterior insula (AI) or dorsal anterior cingulate cortex (dACC) activity to exclusion. Finally, there were no reliable associations between BP and reported valence or arousal, or AI and dACC activity to emotional images. Findings partly replicate and extend prior findings on BP and emotional responding to social pain; however, they appear inconsistent with predictions at the neural level. Future experimental manipulation of BP may allow for causal inferences and adjudication of conceptual perspectives on cardiovascular contributions to social algesia.

Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine

Osteoarthritis (OA) is a highly prevalent chronic joint disorder affecting ~600 million individuals worldwide and is characterized by complex pain mechanisms that significantly impair patient quality of life. Challenges exist in accurately assessing and measuring pain in OA due to variations in pain perception among individuals and the heterogeneous nature of the disease. Conventional pain assessment methods, such as patient-reported outcome measures and clinical evaluations, often fail to fully capture the heterogeneity of pain experiences among individuals with OA. This review will summarize and evaluate current methods of pain assessment in OA and highlight future directions for standardized pain assessment. We discuss the role of animal models in enhancing our understanding of OA pain pathophysiology and highlight the necessity of translational research to advance pain assessment strategies. Key challenges explored include identifying phenotypes of pain susceptibility, integrating biomarkers into clinical practice, and adopting personalized pain management approaches through the incorporation of multi-modal data and multilevel analysis. We underscore the imperative for continued innovation in pain assessment and management to improve outcomes for patients with OA.

Evaluation of pressure-induced pain in patients with disorders of consciousness based on functional near infrared spectroscopy

Objective

This study aimed to investigate the brain's hemodynamic responses (HRO) and functional connectivity in patients with disorders of consciousness (DoC) in response to acute pressure pain stimulation using near-infrared spectroscopy (NIRS).

Methods

Patients diagnosed with DoC underwent pressure stimulation while brain activity was measured using NIRS. Changes in oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) concentrations were monitored across several regions of interest (ROIs), including the primary somatosensory cortex (PSC), primary motor cortex (PMC), dorsolateral prefrontal cortex (dPFC), somatosensory association cortex (SAC), temporal gyrus (TG), and frontopolar area (FPA). Functional connectivity was assessed during pre-stimulation, stimulation, and post-stimulation phases.

Results

No significant changes in HbO or HbR concentrations were observed during the stimulation vs. baseline or stimulation vs. post-stimulation comparisons, indicating minimal activation of the targeted brain regions in response to the pressure stimulus. However, functional connectivity between key regions, particularly the PSC, PMC, and dPFC, showed significant enhancement during the stimulation phase (r > 0.9, p < 0.001), suggesting greater coordination among sensory, motor, and cognitive regions. These changes in connectivity were not accompanied by significant activation in pain-related brain areas.

Conclusion

Although pain-induced brain activation was minimal in patients with DoC, enhanced functional connectivity during pain stimulation suggests that the brain continues to process pain information through coordinated activity between regions. The findings highlight the importance of assessing functional connectivity as a potential method for evaluating pain processing in patients with DoC.

Neuroplasticity in chronic pain: insights into diagnosis and treatment

Chronic pain is a universal problem that directly evolves the central nervous system, altering both its structure and function. This review discusses neuroplastic alterations in critical areas in the brain like the anterior cingulate cortex, insula, prefrontal cortex, primary (S1) and secondary (S2) somatosensory cortices, and thalamus. These regions exhibit gray matter decrease and changes in connectivity during chronic pain. Several cortical networks, mainly the central executive network, the default mode network, and the salience network exhibit neuroplasticity which reallocates cognitive and emotional resources to pain processing. Thus, it was reported that sensitivity to pain enhances emotional suffering, indicating that altered connectivity and functional reorganization of these networks support maladaptive pain processing and underpin chronic pain persistence. Neuroplasticity-focused treatments such as brain stimulation, neuro-feedback, and exercise-based therapies constitute potential interventions for preventing such negative changes. Further, innovative neuroimaging biomarkers are effective in demonstrating precise neural changes and in providing information about the diagnosis of chronic pain syndromes. This review highlights neuro-plastic changes in chronically painful patients and acknowledges the brain's plasticity as a target for chronic pain treatment. It, also, points to the diagnostic strategies and practical interventions that address these alterations.

A pilot investigation on inflammatory markers and theta burst stimulation protocol interaction along a three-month recovery course following an isolated upper limb fracture

This study investigates the effects of theta burst stimulation (TBS) on inflammatory markers in patients with isolated upper limb fractures (IULF). Participants underwent a 10-day TBS intervention following a randomized matched pair design. Blood samples collected at three time points were analyzed for inflammatory biomarkers, mainly including interleukin-1 receptor antagonist (IL-1Ra), IL-1β, and IL-6. Results revealed a significant interaction between TBS and time for IL-1Ra, indicating a more pronounced decrease in IL-1Ra expression over time in the active TBS group. However, IL-6 levels decreased over time regardless of TBS intervention, suggesting a natural decline in response to injury. No significant interaction was found for IL-1β. While IL-1Ra levels were associated with higher functional disability prior to treatment initiation, active TBS intervention led to a decrease of IL-1Ra levels at both follow-up time points. These changes were not associated with alterations in pain or disability, suggesting that TBS may primarily influence recovery processes independent of pain modulation. Notably, IL-1β levels were negatively correlated with disability in the active TBS group at the 3-month follow-up. This study sheds light on the potential of TBS to modulate inflammatory responses in orthopedic trauma, emphasizing the need for further research to elucidate its therapeutic implications. Clinical Significance: TBS may offer a promising adjunctive therapy for promoting functional recovery in patients with upper limb fractures.

Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning

BACKGROUND

Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain-gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diagnostic criteria and biomarkers. This study aims to investigate brain network alterations in IBS patients using the functional connectivity strength (FCS) method and to develop a support vector machine (SVM) classifier for distinguishing IBS patients from healthy controls (HCs).

METHODS

Thirty-one patients with IBS and thirty age and sex-matched HCs were enrolled in this study and underwent resting-state functional magnetic resonance imaging (fMRI) scans. We applied FCS to assess global brain functional connectivity changes in IBS patients. An SVM-based machine - learning approach was then used to evaluate whether the altered FCS regions could serve as fMRI-based markers for classifying IBS patients and HCs.

RESULTS

Compared to the HCs, patients with IBS showed significantly increased FCS in the left medial orbitofrontal cortex (mOFC) and decreased FCS in the bilateral cingulate cortex/precuneus (PCC/Pcu) and middle cingulate cortex (MCC). The machine-learning model achieved a classification accuracy of 91.9% in differentiating IBS patients from HCs.

CONCLUSION

These findings reveal a unique pattern of FCS alterations in brain areas governing pain regulation and emotional processing in IBS patients. The identified abnormal FCS features have the potential to serve as effective biomarkers for IBS classification. This study may contribute to a deeper understanding of the neural mechanisms of IBS and aid in its diagnosis in clinical practice.

The projection from the rostral anterior cingulate cortex to the ventral tegmental area regulates 5-HT-induced itch aversion and scratching in rats

Many studies in humans and rodents have shown that the anterior cingulate cortex (ACC) plays a critical role in the regulation of pain-related aversion and that the projection from the rostral ACC (rACC) to the ventral tegmental area (VTA) is implicated in this modulation process. The ACC is also reported to be involved in the regulation of itch-scratch behavior. However, it remains unclear whether the ACC is involved in the modulation of the negative emotions induced by acute itch sensation. In this study, we investigated the pruritogen-induced conditioned place aversion (CPA) and itch-scratching behavior in rats after pharmacogenetic inhibition of the activities of rACC-VTA pathway or the rACC neurons, respectively. Pharmacogenetic inhibition of glutamatergic neurons of rACC projecting to the VTA alleviated the CPA responses and itch-scratching behavior induced by the subcutaneous injection of 5-HT, a nonhistamine-dependent pruritogen. However, pharmacogenetic inhibition of rACC neurons did not change the CPA behavior associated with itch and, conversely, increased itch-scratching behavior. These results reveal that a specific subpopulation of rACC neurons projecting to the VTA positively regulates itch sensation and the negative emotion accompanying itch, whereas the global rACC negatively modulates acute non-histaminergic itch in rats. Postsynaptic GABAergic neurons in the VTA may mediate emotion modulation of the rACC-VTA pathway. The current findings contribute to a better understanding of the circuit mechanisms underlying the processing of different components of itch, such as sensation and emotion.

Decoding Mindfulness With Multivariate Predictive Models

Identifying the brain mechanisms that underlie the salutary effects of mindfulness meditation and related practices is a critical goal of contemplative neuroscience. Here, we suggest that the use of multivariate predictive models represents a promising and powerful methodology that could be better leveraged to pursue this goal. This approach incorporates key principles of multivariate decoding, predictive classification, and model-based analyses, all of which represent a strong departure from conventional brain mapping approaches. We highlight 2 such research strategies-state induction and neuromarker identification-and provide illustrative examples of how these approaches have been used to examine central questions in mindfulness, such as the distinction between internally directed focused attention and mind wandering and the effects of mindfulness interventions on somatic pain and drug-related cravings. We conclude by discussing important issues to be addressed with future research, including key tradeoffs between using a personalized versus population-based approach to predictive modeling.

Defining the need for analgesia in the emergency department: protocol for an international Delphi process

INTRODUCTION

The high prevalence of pain in the emergency department (ED) highlights the importance of accurate assessments to provide effective interventions. However, common pain scales such as the Numerical Pain Rating Scale have shown limitations in assessing analgesic requirements and adequacy. The ideal outcome for evaluating a pain scale predicting analgesic requirements would be the 'need for analgesia', for which there is no universally accepted definition. Accordingly, the primary aim of this study is to define the 'need for analgesia' using an interdisciplinary approach. The secondary aim is to define the 'adequacy of analgesia'.

METHODS AND ANALYSIS

A two-stage modified Delphi process will be conducted by a core study group chosen for its expertise in ED pain management. A larger expert panel, identified through a comprehensive search in Scopus and CINAHL databases, will be invited to participate in the study and will be supplemented by patients recruited via international patient organisations or snowballing. In stage 1, the expert panel will complete a written survey to collect potential clinical variables for defining the 'need for analgesia' and 'adequacy of analgesia'. The core study group will elaborate on these variables. In stage 2, the same participants will use a five-point Likert scale to achieve consensus defined as ≥80% of combined agreement on the proposed variables, over a maximum of three rounds. The same process will be used to define the 'adequacy of analgesia'.

ETHICS AND DISSEMINATION

The Ethics Committee of Northwestern and Central Switzerland exempted the project from committee approval under the Human Research Act. Written consent will be obtained from all participants. Results will be disseminated through publication in peer-reviewed journals and conferences.

Biological research on mental pain, social pain and other pains not primarily felt in the body: methodological systematic review

BACKGROUND

Researchers explore the biology of painful experiences not primarily felt in the body ('non-physical pain'), sometimes referred to as mental, social or emotional pain. A critical challenge lies in how to operationalise this subjective experience for biological research, a crucial process for translating findings into clinical practice.

AIMS

To map studies investigating biological features of non-physical pain, focusing on their conceptual features (i.e. terms and definitions of non-physical pain) and methodological characteristics (e.g. experimental paradigms and measures).

METHOD

This methodological systematic review searched reports of primary research on the biological features of non-physical pain across Embase, MEDLINE and Web of Science. Using a meta-research approach, we synthetised results on terms, definitions, populations, experimental paradigms, confounders, measures of non-physical pain and investigation methods (e.g. functional magnetic resonance imaging).

RESULTS

We identified 92 human studies, involving 7778 participants. Overall, 59.1% of the studies did not report any definition of non-physical pain, and 82% of studies did not use a specific measure. Regarding the possibility of translating results to clinical settings, most of the human studies involved only healthy participants (71.7%) and the seven different experimental paradigms used to induce non-physical pain had unknown external validity. Confounders were not considered by 32.4% of the experimental studies. Animal studies were rare, with only four rodent studies.

CONCLUSIONS

Biomedical studies of non-physical pain use heterogeneous concepts with unclear overlaps and methods with unknown external validity. As has been done for physical pain, priority actions include establishing an agreed definition and measurement of non-physical pain and developing experimental paradigms with good external validity.

Nature exposure induces analgesic effects by acting on nociception-related neural processing

Nature exposure has numerous health benefits and might reduce self-reported acute pain. Given the multi-faceted and subjective quality of pain and methodological limitations of prior research, it is unclear whether the evidence indicates genuine analgesic effects or results from domain-general effects and subjective reporting biases. This preregistered neuroimaging study investigates how nature modulates nociception-related and domain-general brain responses to acute pain. Healthy participants (N = 49) receiving electrical shocks report lower pain when exposed to virtual nature compared to matched urban or indoor control settings. Multi-voxel signatures of pain-related brain activation patterns demonstrate that this subjective analgesic effect is associated with reductions in nociception-related rather than domain-general cognitive-emotional neural pain processing. Preregistered region-of-interest analyses corroborate these results, highlighting reduced activation of areas connected to somatosensory aspects of pain processing (thalamus, secondary somatosensory cortex, and posterior insula). These findings demonstrate that virtual nature exposure enables genuine analgesic effects through changes in nociceptive and somatosensory processing, advancing our understanding of how nature may be used to complement non-pharmacological pain treatment. That this analgesic effect can be achieved with easy-to-administer virtual nature exposure has important practical implications and opens novel avenues for research on the precise mechanisms by which nature impacts our mind and brain.

Could the perception of effort help us unravel the potential of "living low-training high"? A perspective article

Living low-training high may promote favourable physiological adaptations and improvement of exercise performance in normoxia following training at altitudes above 1500 m. Whether and how physiological adaptations to training high interact with the perception of effort remains unknown. This perspective article aims to carve out potential contributory effects of the perception of effort on performance changes following living low-training high interventions. It is based on two unique case reports, findings on known physiological adaptations to living low-training high, and integration of current knowledge on the neurophysiology of effort perception. Considering the current state of knowledge on the effect of exercising in hypoxia on perceived effort, we propose that the hypoxia exposure associated with living low-training high protocols interact with the perception of effort and its rating, by inducing adaptations that i) slow the development of neuromuscular fatigue and associated compensatory increase in motor command, ii) alter the functioning of the anterior cingulate cortex and/or the motor areas, and iii) alter the interaction with other psychological responses to the exercise. In the proposed framework using a psychophysiological approach, changes in the participants' report of their perceived effort would reflect underlying neurophysiological and psychological adaptations to hypoxia exposure.

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples

Human social interactions rely on the ability to reflect on one's own and others' internal states and traits-a psychological process known as mentalizing. Impaired or altered self- and other-related mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total N=281) to train and validate fMRI brain signatures that predict 1) mentalizing about the self, 2) mentalizing about another person, and 3) both types of mentalizing. We test their generalizability across healthy adults, adolescents, and adults diagnosed with schizophrenia and bipolar disorder. The classifier trained across both types of mentalizing showed 98% predictive accuracy in independent validation datasets. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. Classifier patterns across cohorts revealed better self/other separation in 1) healthy adults compared to individuals with schizophrenia and 2) with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving mentalizing about self and others-present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as mechanistic neuromarkers to measure social-cognitive processes in different contexts and clinical conditions.

Predicting Individual Pain Sensitivity Using a Novel Cortical Biomarker Signature

Importance

Biomarkers would greatly assist decision-making in the diagnosis, prevention, and treatment of chronic pain.

Objective

To undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of 2 measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).

Design, Setting, and Participants

This cohort study at a single center (Neuroscience Research Australia) recruited participants from November 2020 to October 2022 through notices placed online and at universities across Australia. Participants were healthy adults aged 18 to 44 years with no history of chronic pain or a neurological or psychiatric condition. Participants experienced a model of prolonged temporomandibular pain with outcomes collected over 30 days. Electroencephalography to assess PAF and transcranial magnetic stimulation (TMS) to assess CME were recorded on days 0, 2, and 5. Pain was assessed twice daily from days 1 through 30.

Exposure

Participants received an injection of nerve growth factor (NGF) to the right masseter muscle on days 0 and 2 to induce prolonged temporomandibular pain lasting up to 4 weeks.

Main Outcomes and Measures

The predictive accuracy of the PAF/CME biomarker signature was determined using a nested control-test scheme: machine learning models were run on a training set (n = 100), where PAF and CME were predictors and pain sensitivity was the outcome. The winning classifier was assessed on a test set (n = 50) comparing the predicted pain labels against the true labels.

Results

Among the final sample of 150 participants, 66 were female and 84 were male; the mean (SD) age was 25.1 (6.2) years. The winning classifier was logistic regression, with an outstanding area under the curve (AUC = 1.00). The locked model assessed on the test set had excellent performance (AUC = 0.88; 95% CI, 0.78-0.99). Results were reproduced across a range of methodological parameters. Moreover, inclusion of sex and pain catastrophizing as covariates did not improve model performance, suggesting the model including biomarkers only was more robust. PAF and CME biomarkers showed good to excellent test-retest reliability.

Conclusions and Relevance

This study provides evidence for a sensorimotor cortical biomarker signature for pain sensitivity. The combination of accuracy, reproducibility, and reliability suggests the PAF/CME biomarker signature has substantial potential for clinical translation, including predicting the transition from acute to chronic pain.

The brain's action-mode network

The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function. In the action-mode, arousal is heightened, attention is focused externally and action plans are created, converted to goal-directed movements and continuously updated on the basis of relevant feedback, such as pain. Here, we synthesize classical and recent human and animal evidence that the action-mode of the brain is created and maintained by an action-mode network (AMN), which we had previously identified and named the cingulo-opercular network on the basis of its anatomy. We discuss how rather than continuing to name this network anatomically, annotating it functionally as controlling the action-mode of the brain increases its distinctiveness from spatially adjacent networks and accounts for the large variety of the associated functions of an AMN, such as increasing arousal, processing of instructional cues, task general initiation transients, sustained goal maintenance, action planning, sympathetic drive for controlling physiology and internal organs (connectivity to adrenal medulla), and action-relevant bottom-up signals such as physical pain, errors and viscerosensation. In the functional mode continuum of the awake brain, the AMN-generated action-mode sits opposite the default-mode for self-referential, emotional and memory processing, with the default-mode network and AMN counterbalancing each other as yin and yang.

Assessing the Modulatory Effects of tDCS and Acupuncture on Cerebral Blood Flow in Chronic Low Back Pain Using Arterial Spin Labeling Perfusion Imaging

BACKGROUND

Both transcranial direct current stimulation (tDCS) and acupuncture are promising methods for managing chronic low back pain (cLBP), however, their underlying mechanisms remain unclear.

METHODS

To explore the neural mechanisms of tDCS and acupuncture on cLBP, we examined how real and sham tDCS applied to the bilateral motor cortex (M1), combined with real or sham acupuncture, influenced cerebral blood flow (CBF) using pulsed continuous arterial spin labeling (pCASL) imaging. tDCS was administered over six sessions, combined with real or sham acupuncture, over one month.

RESULTS

Following real tDCS, we observed increased CBF in the bilateral occipital cortex, precuneus, left hippocampus, and parahippocampal gyrus/posterior cingulate cortex. After sham tDCS, CBF decreased in regions including the bilateral superior parietal lobule, precuneus, bilateral precentral and postcentral gyri, and left angular gyrus. Real acupuncture led to reduced CBF in the bilateral occipital cortex and hippocampus, and left posterior cingulate gyrus, and increased CBF in the right postcentral gyrus, superior parietal lobule, and frontal areas. Sham acupuncture was associated with decreased CBF in the bilateral hippocampus and anterior cingulate gyrus.

CONCLUSIONS

These results suggest both shared and distinct patterns of CBF changes between real and sham tDCS, as well as between real and sham acupuncture, reflecting mode-dependent effects on brain networks involved in pain processing and modulation. Our findings highlight the different neural circuits implicated in the therapeutic mechanisms of tDCS and acupuncture in the management of cLBP.

Omissions of threat trigger subjective relief and prediction error-like signaling in the human reward and salience systems

The unexpected absence of danger constitutes a pleasurable event that is critical for the learning of safety. Accumulating evidence points to similarities between the processing of absent threat and the well-established reward prediction error (PE). However, clear-cut evidence for this analogy in humans is scarce. In line with recent animal data, we showed that the unexpected omission of (painful) electrical stimulation triggers activations within key regions of the reward and salience pathways and that these activations correlate with the pleasantness of the reported relief. Furthermore, by parametrically violating participants' probability and intensity related expectations of the upcoming stimulation, we showed for the first time in humans that omission-related activations in the VTA/SN were stronger following omissions of more probable and intense stimulations, like a positive reward PE signal. Together, our findings provide additional support for an overlap in the neural processing of absent danger and rewards in humans.

Survey on Pain Detection Using Machine Learning Models: Narrative Review

BACKGROUND

Pain, a leading reason people seek medical care, has become a social issue. Automated pain assessment has seen notable advancements over recent decades, addressing a critical need in both clinical and everyday settings.

OBJECTIVE

The objective of this survey was to provide a comprehensive overview of pain and its mechanisms, to explore existing research on automated pain recognition modalities, and to identify key challenges and future directions in this field.

METHODS

A literature review was conducted, analyzing studies focused on various modalities for automated pain recognition. The modalities reviewed include facial expressions, physiological signals, audio cues, and pupil dilation, with a focus on their efficacy and application in pain assessment.

RESULTS

The survey found that each modality offers unique contributions to automated pain recognition, with facial expressions and physiological signals showing particular promise. However, the reliability and accuracy of these modalities vary, often depending on factors such as individual variability and environmental conditions.

CONCLUSIONS

While automated pain recognition has progressed considerably, challenges remain in achieving consistent accuracy across diverse populations and contexts. Future research directions are suggested to address these challenges, enhancing the reliability and applicability of automated pain assessment in clinical practice.

Individual variability in cortical representations of tonic pain

When people experience pain in everyday situations, the experience is often long-lasting and fluctuating. However, pain research predominantly focuses on artificial brief and repeated singular painful events. Here, we aimed to approximate clinically relevant pain in 152 sessions from 38 participants who underwent four sessions each. We applied variable levels of contact heat pain to the forearm using a thermode. Participants were asked to continuously rate their pain experience through a potentiometer device. In a whole-brain approach, we related the dynamic fluctuations of cortical activity and connectivity to the time courses of pain. We also explored the variability of cortical processing across participants. In an individual approach, we compared the cortical processing pattern of each individual with the overall group findings. The results revealed a large discrepancy between the group results that are usually reported in publications and the 4-session individual processing patterns: the group findings corroborated previous work localising tonic pain encoding to the secondary somatosensory cortex. By contrast, this region was shadowed by a variety of activity patterns across individuals, represented by a low spatial correlation between group statistics and individual results. The current findings challenge the usefulness and applicability of group results. They do not inform us how pain is processed in the brain as none of the participants exhibited the processing pattern of the group statistics. Therapies to relieve pain that rely on the modulation of brain regions will fail unless they are adapted to an individual's unique pain processing characteristics.

Innovations in acute and chronic pain biomarkers: enhancing diagnosis and personalized therapy

Pain affects millions worldwide, posing significant challenges in diagnosis and treatment. Despite advances in understanding pain mechanisms, there remains a critical need for validated biomarkers to enhance diagnosis, prognostication, and personalized therapy. This review synthesizes recent advancements in identifying and validating acute and chronic pain biomarkers, including imaging, molecular, sensory, and neurophysiological approaches. We emphasize the emergence of composite, multimodal strategies that integrate psychosocial factors to improve the precision and applicability of biomarkers in chronic pain management. Neuroimaging techniques like MRI and positron emission tomography provide insights into structural and functional abnormalities related to pain, while electrophysiological methods like electroencepholography and magnetoencepholography assess dysfunctional processing in the pain neuroaxis. Molecular biomarkers, including cytokines, proteomics, and metabolites, offer diagnostic and prognostic potential, though extensive validation is needed. Integrating these biomarkers with psychosocial factors into clinical practice can revolutionize pain management by enabling personalized treatment strategies, improving patient outcomes, and potentially reducing healthcare costs. Future directions include the development of composite biomarker signatures, advances in artificial intelligence, and biomarker signature integration into clinical decision support systems. Rigorous validation and standardization efforts are also necessary to ensure these biomarkers are clinically useful. Large-scale collaborative research will be vital to driving progress in this field and implementing these biomarkers in clinical practice. This comprehensive review highlights the potential of biomarkers to transform acute and chronic pain management, offering hope for improved diagnosis, treatment personalization, and patient outcomes.

Magnetoencephalography studies in migraine and headache disorders: A systematic review

BACKGROUND

Understanding the neural mechanisms underlying migraine and other primary headache disorders is critical for the development of long-term cures. Magnetoencephalography (MEG), an imaging modality that measures neuronal currents and cortical excitability with high temporal and superior spatial resolution, has been increasingly used in neurological research. Initial MEG studies showed promise in directly recording cortical spreading depression-a cortical correlate of migraine with aura. However, lately MEG technology has highly evolved with greater potential to reveal underlying pathophysiology of migraine and primary headache disorders, and aid in the identification of biomarkers.

OBJECTIVE

To systematically review the use of MEG in migraine and other primary headache disorders and summarize findings.

METHODS

We conducted a systematic search and selection of MEG studies in migraine and primary headache disorders from inception until June 8, 2023, in Medline, Embase, Cochrane, and Scopus databases. Peer-reviewed English articles reporting the use of MEG for clinical or research purposes in migraine and primary headache disorders were selected.

RESULTS

We found 560 articles and included 38 in this review after screening. Twelve studies investigated resting-state, while others investigated a sensory modality using an evoked or event-related paradigm with a total of 35 cohort and 3 case studies. Thirty-two studies focused exclusively on migraine, while the rest reported other primary headache disorders.

CONCLUSION

The findings show an evolution of MEG from a 7- to a 306-channel system and analysis evolving from sensor-level evoked responses to more advanced source-level connectivity measures. A relatively few MEG studies portrayed migraine and primary headache disorders as a sensory abnormality, especially of the visual system. We found heterogeneity in the datasets, data reporting standards (due to constantly evolving MEG technology and analysis methods), and patient characteristics. Studies were inadequately powered and there was no evidence of blinding procedures to avoid selection bias in case-control studies, which could have led to false-positive findings. More studies are needed to investigate the affective-cognitive aspects that exacerbate pain and disability in migraine and primary headache disorders.

Decoding pain: uncovering the factors that affect the performance of neuroimaging-based pain models

ABSTRACT

Neuroimaging-based pain biomarkers, when combined with machine learning techniques, have demonstrated potential in decoding pain intensity and diagnosing clinical pain conditions. However, a systematic evaluation of how different modeling options affect model performance remains unexplored. This study presents the results from a comprehensive literature survey and benchmark analysis. We conducted a survey of 57 previously published articles that included neuroimaging-based predictive modeling of pain, comparing classification and prediction performance based on the following modeling variables-the levels of data, spatial scales, idiographic vs population models, and sample sizes. The findings revealed a preference for population-level modeling with brain-wide features, aligning with the goal of clinical translation of neuroimaging biomarkers. However, a systematic evaluation of the influence of different modeling options was hindered by a limited number of independent test results. This prompted us to conduct benchmark analyses using a locally collected functional magnetic resonance imaging dataset (N = 124) involving an experimental thermal pain task. The results demonstrated that data levels, spatial scales, and sample sizes significantly impact model performance. Specifically, incorporating more pain-related brain regions, increasing sample sizes, and averaging less data during training and more data during testing improved performance. These findings offer useful guidance for developing neuroimaging-based biomarkers, underscoring the importance of strategic selection of modeling approaches to build better-performing neuroimaging pain biomarkers. However, the generalizability of these findings to clinical pain requires further investigation.

Enhancing task fMRI individual difference research with neural signatures

Task-based functional magnetic resonance imaging (tb-fMRI) has advanced our understanding of brain-behavior relationships. Standard tb-fMRI analyses suffer from limited reliability and low effect sizes, and machine learning (ML) approaches often require thousands of subjects, restricting their ability to inform how brain function may arise from and contribute to individual differences. Using data from 9,024 early adolescents, we derived a classifier ('neural signature') distinguishing between high and low working memory loads in an emotional n-back fMRI task, which captures individual differences in the separability of activation to the two task conditions. Signature predictions were more reliable and had stronger associations with task performance, cognition, and psychopathology than standard estimates of regional brain activation. Further, the signature was more sensitive to psychopathology associations and required a smaller training sample (N=320) than standard ML approaches. Neural signatures hold tremendous promise for enhancing the informativeness of tb-fMRI individual differences research and revitalizing its use.

Management of Fibromyalgia: Novel Nutraceutical Therapies Beyond Traditional Pharmaceuticals

The pathophysiology of fibromyalgia, a condition that causes chronic pain throughout the body, involves abnormal pain signaling, genetic predispositions, and abnormal neuroendocrine function, significantly impairing quality of life. Fibromyalgia is commonly characterized by musculoskeletal pain, chronic fatigue, and severe sleep alterations. Changes in the central processing of sensory input and defects in endogenous pain inhibition could be the basis of enhanced and persistent pain sensitivity in individuals with fibromyalgia. The term central sensitivity syndrome was chosen as an umbrella term for fibromyalgia and related illnesses, including myalgic encephalomyelitis/chronic fatigue syndrome, migraine, and irritable bowel syndrome. Given the substantial impact of fibromyalgia on health, there is a need for new prevention and treatment strategies, particularly those involving bioavailable nutraceuticals and/or phytochemicals. This approach is particularly important considering the adverse effects of current fibromyalgia pharmaceutical treatments, such as antidepressants and anticonvulsants, which can lead to physical dependence and tolerance. Natural products have recently been considered for the design of innovative analgesics and antinociceptive agents to manage fibromyalgia pain. Polyphenols show promise in the management of neuropathic pain and fibromyalgia, especially considering how anti-inflammatory treatments, including corticosteroids and nonsteroidal medical drugs, are effective only when inflammatory processes coexist and are not recommended as the primary treatment for fibromyalgia.

Pain sensitivity mediates the relationship between empathy for pain and psychopathic traits

Psychopathic traits and antisocial behavior show a well-documented relationship with decreased empathic processing. It has been proposed that a reduced own experience of pain leads to perceiving others' pain as less severe, which potentially facilitates exploitative, aggressive behavior towards others. We evaluated the link between psychopathic traits, experimental pain sensitivity and empathy for pain in a community sample (n = 74). Participants rated images depicting painful situations through either a self-centered or other-oriented perspective. Psychopathic traits (Interpersonal, Affective, Lifestyle and Antisocial) were assessed with the Self-Report Psychopathy Scale, and pain threshold (cold, electrical, pressure) and tolerance (cold, electrical) were measured. A Bayesian Structural Equation Modelling approach indicated that self-centered pain estimates and sensitivity to electrical pain predicted judgments of others' pain ('pain empathy'). The superordinate psychopathy factor, encompassing the overlap in underlying features of the construct, was shown to indirectly affect pain empathy through the mediating role of electrical pain sensitivity. These results provide support for the notion that a reduced sensitivity to own pain underlies diminished pain empathy, and may hold important implications for understanding the mechanisms of antisocial behavior in psychopathy.

Music and hypnosis for well-being in retirement homes: A pilot study

Anxiety, pain and poor well-being are major issues in elderly individuals. Complementary interventions, such as music and hypnosis, are increasingly used to address these issues. The objectives of this study were to assess immediate changes in anxiety, pain and well-being during personalized prerecorded music and hypnosis interventions compared to control sessions, and to explore participants' subjective experiences. We employed a multiple time series model with daily measurements with older people living in retirement homes in rural areas (n = 8). The Edmonton Symptom Assessment Scale (ESAS) evaluated these three dimensions before and after each session, while participants' subjective experience was collected using an unstructured interview. The primary results showed a significant improvement in the composite score of anxiety, pain, and well-being for the music (p < .001), hypnosis (p = .0158), and music/hypnosis (p = .013) intervention sessions compared to the control sessions. The secondary results indicated a reduction in anxiety for both the music and music/hypnosis interventions (p < .05), along with a significant improvement in well-being. These effects may be attributed to mechanisms such as absorption, episodic memory, cognitive agency, positive emotion, rhythmic entrainment, and rapport, which could have modulated the interventions' impact. In conclusion, personalized prerecorded music and hypnosis interventions appear to be effective in enhancing the well-being of older individuals residing in retirement homes. Further studies are needed to assess the generalizability of these results to a larger population from diverse sociodemographic backgrounds, and better understand the subjective experiences that mediate these effects.

Alterations in orbitofrontal cortex communication relate to suicidal attempts in patients with major depressive disorder

BACKGROUND

Investigating how the interaction between the orbitofrontal cortex (OFC) and various brain regions/functional networks in major depressive disorder (MDD) patients with a history of suicide attempt (SA) holds importance for understanding the neurobiology of this population.

METHODS

We employed resting-state functional magnetic resonance imaging (rs-fMRI) to analyze the OFC's functional segregation in 586 healthy individuals. A network analysis framework was then applied to rs-fMRI data from 86 MDD-SA patients and 85 MDD-Control patients, utilizing seed mappings of OFC subregions and a multi-connectivity-indicator strategy involving cross-correlation, total interdependencies, Granger causality, and machine learning.

RESULTS

Four functional subregions of left and right OFC, were designated as seed regions of interest. Relative to the MDD-Control group, the MDD-SA group exhibited enhanced functional connectivity (FC) and attenuated interaction between the OFC and the sensorimotor network, imbalanced communication between the OFC and the default mode network, enhanced FC and interaction between the OFC and the ventral attention network, enhanced interaction between the OFC and the salience network, and attenuated FC between the OFC and the frontoparietal network.

LIMITATIONS

The medication and treatment condition of patients with MDD was not controlled, so the medication effect on the alteration model cannot be affirmed.

CONCLUSION

The findings suggest an imbalanced interaction pattern between the OFC subregions and a set of cognition- and emotion-related functional networks/regions in the MDD-SA group.

Introspective psychophysics for the study of subjective experience

Studying subjective experience is hard. We believe that pain is not identical to nociception, nor pleasure a computational reward signal, nor fear the activation of "threat circuitry". Unfortunately, introspective self-reports offer our best bet for accessing subjective experience, but many still believe that introspection is "unreliable" and "unverifiable". But which of introspection's faults do we find most damning? Is it that introspection provides imperfect access to brain processes (e.g. perception, memory)? That subjective experience is not objectively verifiable? That it is hard to isolate from non-subjective processing capacity? Here, I argue none of these prevents us from building a meaningful, impactful psychophysical research program that treats subjective experience as a valid empirical target through precisely characterizing relationships among environmental variables, brain processes and behavior, and self-reported phenomenology. Following recent similar calls by Peters (Towards characterizing the canonical computations generating phenomenal experience. 2022. Neurosci Biobehav Rev: 142, 104903), Kammerer and Frankish (What forms could introspective systems take? A research programme. 2023. J Conscious Stud 30:13-48), and Fleming (Metacognitive psychophysics in humans, animals, and AI. 2023. J Conscious Stud 30:113-128), "introspective psychophysics" thus treats introspection's apparent faults as features, not bugs-just as the noise and distortions linking environment to behavior inspired Fechner's psychophysics over 150 years ago. This next generation of psychophysics will establish a powerful tool for building and testing precise explanatory models of phenomenology across many dimensions-urgency, emotion, clarity, vividness, confidence, and more.

Mindfulness Meditation and Placebo Modulate Distinct Multivariate Neural Signatures to Reduce Pain

BACKGROUND

Rather than a passive reflection of nociception, pain is shaped by the interplay between one's experiences, current cognitive-affective states, and expectations. The placebo response, a paradoxical yet reliable phenomenon, is postulated to reduce pain by engaging mechanisms shared with active therapies. It has been assumed that mindfulness meditation, practiced by sustaining nonjudgmental awareness of arising sensory events, merely reflects mechanisms evoked by placebo. Recently, brain-based multivariate pattern analysis has been validated to successfully disentangle nociceptive-specific, negative affective, and placebo-based dimensions of the subjective pain experience.

METHODS

To determine whether mindfulness meditation engages distinct brain mechanisms from placebo and sham mindfulness to reduce pain, multivariate pattern analysis pain signatures were applied across 2 randomized clinical trials that employed overlapping psychophysical pain testing procedures (49 °C noxious heat; visual analog pain scales) and distinct functional magnetic resonance imaging techniques (blood oxygen level-dependent; perfusion based). After baseline pain testing, 115 healthy participants were randomized into a 4-session mindfulness meditation (n = 37), placebo-cream conditioning (n = 19), sham mindfulness meditation (n = 20), or book-listening control (n = 39) intervention. After each intervention, noxious heat was administered during functional magnetic resonance imaging and each manipulation.

RESULTS

A double dissociation in the multivariate pattern analysis signatures supporting pain regulation was revealed by mindfulness meditation compared with placebo cream. Mindfulness meditation produced significantly greater reductions in pain intensity and pain unpleasantness ratings and nociceptive-specific and negative affective pain signatures than placebo cream, sham mindfulness meditation, and control interventions. The placebo-cream group significantly lowered the placebo-based signature.

CONCLUSIONS

Mindfulness meditation and placebo engaged distinct and granular neural pain signatures to reduce pain.

A multisite validation of brain white matter pathways of resilience to chronic back pain

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have pointed to brain characteristics as predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over 6- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.

Functional Brain Changes in Younger Population of Cervical Spondylosis Patients with Chronic Neck Pain

Purpose

The aim of the research was to observe the variations in brain activity between young cervical spondylosis patients with chronic neck pain (CNP) and healthy volunteers in the resting state and to investigate the central remodeling mechanisms in the patients.

Patients and methods

Our study recruited 31 patients with chronic neck pain from cervical spondylosis and 30 healthy volunteers. Eventually, 29 patients (CNP group) and 29 healthy volunteers (HC group) completed the acquisition of clinical data and resting-state functional magnetic resonance (rs BOLD-fMRI) amplitude of low-frequency fluctuations (ALFF) data; in addition, we assessed the relationship between differentially active brain regions and clinical indicators.

Results

The CNP group found greater ALFF values in the insula, cingulate gyrus, prefrontal lobe, and other brain regions. The occipital, parietal, and other brain regions had lower ALFF values. In addition, there was a negative connection between the duration of the sickness in the CNP group and the ALFF value of the right superior parietal gyrus (SPG.R). The level of tenderness threshold exhibited a negative correlation with the ALFF value of the left insula (INS.L). In addition, the NPQ score showed a negative association with the ALFF value of the ORBinf.R and a positive correlation with the ALFF value of the CC1.L. Finally, the HADS-A score exhibited a positive correlation with the ALFF value of the right anterior cingulate and paracingulate gyrus (ACG.R).

Conclusion

Young patients with chronic neck pain show extensive central remodeling, with altered functional activity in pain-emotion brain areas (such as the cingulate gyrus and insula), pain-cognition brain areas (such as the prefrontal lobe), and other special sensory brain areas (such as the parietal and occipital lobes). These changes are linked to clinical tenderness, functional disability, and negative emotion indicators.

Distinguishing deception from its confounds by improving the validity of fMRI-based neural prediction

Deception is a universal human behavior. Yet longstanding skepticism about the validity of measures used to characterize the biological mechanisms underlying deceptive behavior has relegated such studies to the scientific periphery. Here, we address these fundamental questions by applying machine learning methods and functional magnetic resonance imaging (fMRI) to signaling games capturing motivated deception in human participants. First, we develop an approach to test for the presence of confounding processes and validate past skepticism by showing that much of the predictive power of neural predictors trained on deception data comes from processes other than deception. Specifically, we demonstrate that discriminant validity is compromised by the predictor's ability to predict behavior in a control task that does not involve deception. Second, we show that the presence of confounding signals need not be fatal and that the validity of the neural predictor can be improved by removing confounding signals while retaining those associated with the task of interest. To this end, we develop a "dual-goal tuning" approach in which, beyond the typical goal of predicting the behavior of interest, the predictor also incorporates a second compulsory goal that enforces chance performance in the control task. Together, these findings provide a firmer scientific foundation for understanding the neural basis of a neglected class of behavior, and they suggest an approach for improving validity of neural predictors.

Modulating subjective pain perception with decoded Montreal Neurological Institute-space neurofeedback: a proof-of-concept study

Pain is a complex emotional experience that still remains challenging to manage. Previous functional magnetic resonance imaging (fMRI) studies have associated pain with distributed patterns of brain activity (i.e. brain decoders), but it is still unclear whether these observations reflect causal mechanisms. To address this question, we devised a new neurofeedback approach using real-time decoding of fMRI data to test if modulating pain-related multivoxel fMRI patterns could lead to changes in subjective pain experience. We first showed that subjective pain ratings can indeed be accurately predicted using a real-time decoding approach based on the stimulus intensity independent pain signature (SIIPS) and the neurologic pain signature (NPS). Next, we trained participants (n = 16) in a double-blinded decoded fMRI neurofeedback experiment to up- or downregulate the SIIPS. Our results indicate that participants can learn to downregulate the expression of SIIPS independently from NPS expression. Importantly, the success of this neurofeedback training was associated with the perceived intensity of painful stimulation following the intervention. Taken together, these results indicate that closed-loop brain imaging can be efficiently conducted using a priori fMRI decoders of pain, potentially opening up a new range of applications for decoded neurofeedback, both for clinical and basic science purposes. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Neural responses to stress and alcohol cues in individuals with pain with and without alcohol use disorder

Pain and alcohol use disorder (AUD) frequently co-occur, but the underlying neurobiology is not well-understood. Although many studies have reported disruptions in stress and reward cue-elicited neural reactivity and heightened alcohol craving in individuals with AUD, little is known about these constructs among patients who experience pain. Here, individuals with pain (Pain+, n = 31) and without pain (Pain-, n = 37) completed a well-validated functional magnetic resonance imaging (fMRI) paradigm involving stress (S), alcohol (A) and neutral (N) cue exposure with repeated alcohol craving assessments. Using whole-brain, voxel-based analyses (p < 0.001, whole-brain cluster correction at α < .05), the Pain+ versus Pain- group evidenced greater dorsal anterior cingulate cortex and left amygdala hyperactivation during N, but hypoactivation during the S-N contrast. Additionally, Pain+ exhibited blunted right anterior insular cortex (AIC) during S-N and blunted anteromedial thalamus and left AIC with hyperactive orbitofrontal cortex (OFC) during A-N. Exploratory analyses further revealed that individuals with pain and AUD (n = 17) relative to pain alone (n = 14) showed hyperactive bilateral AIC and hypoactive right dorsal caudate during A-N. Alcohol cue-induced craving, significantly higher in Pain+ (p = 0.03), correlated with blunted right AIC and OFC responses during A-N. In sum, these results provide first evidence of heightened alcohol cue-elicited craving and disrupted stress- and alcohol cue-reactivity within corticostriatal-limbic regions implicated in negative affect and preoccupation/anticipation stages of AUD in those with pain and with comorbid pain and AUD. Future investigations of pain-AUD interaction are needed that include systematic pain assessment and longitudinal designs with larger sample sizes.

Multisensory sensitivity in relation to pain: a scoping review of terminology and assessment

Chronic pain is a debilitating health problem affecting 20 million Americans annually. Most patients with chronic pain report negative impacts on daily function and quality of life, which can result in devastating emotional and financial stress. Although the causes of chronic pain remain elusive, there is increasing interest in sensitivity to everyday sensory stimuli as it relates to chronic pain, potentially serving as an indirect marker of altered central nervous system sensory processing. However, sensitivity to multiple sensory inputs, eg, bright lights, certain fabrics, loud noises, etc, is described using multiple terminologies. The lack of a common vocabulary makes it difficult to find and summarize related discoveries, potentially inhibiting scientific progress. Thus, the purpose of this scoping review was to identify and characterize the terminology used in publications assessing some form of multisensory sensitivity as it relates to pain (eg, a pain cohort or pain sensitivity). Our review of 6 databases (PubMed, Scopus, Embase, CINAHL, PsycINFO+, and Cochrane) comprehensively cataloged peer-reviewed studies published through March 2023 in this domain. Of 12,841 possible studies identified, 92 met all inclusion criteria, with over 80% being published in the last decade. A wide range of terminology has been used for this construct, likely in part a result of the many different professional disciplines represented. These results provide valuable insights for future development of a standardized vocabulary and serve as a resource to aid future investigators of multisensory sensitivity and pain in their study design.

A distributed brain response predicting the facial expression of acute nociceptive pain

Pain is a private experience observable through various verbal and non-verbal behavioural manifestations, each of which may relate to different pain-related functions. Despite the importance of understanding the cerebral mechanisms underlying those manifestations, there is currently limited knowledge of the neural correlates of the facial expression of pain. In this functional magnetic resonance imaging (fMRI) study, noxious heat stimulation was applied in healthy volunteers and we tested if previously published brain signatures of pain were sensitive to pain expression. We then applied a multivariate pattern analysis to the fMRI data to predict the facial expression of pain. Results revealed the inability of previously developed pain neurosignatures to predict the facial expression of pain. We thus propose a facial expression of pain signature (FEPS) conveying distinctive information about the brain response to nociceptive stimulations with minimal or no overlap with other pain-relevant brain signatures associated with nociception, pain ratings, thermal pain aversiveness, or pain valuation. The FEPS may provide a distinctive functional characterization of the distributed cerebral response to nociceptive pain associated with the socio-communicative role of non-verbal pain expression. This underscores the complexity of pain phenomenology by reinforcing the view that neurosignatures conceived as biomarkers must be interpreted in relation to the specific pain manifestation(s) predicted and their underlying function(s). Future studies should explore other pain-relevant manifestations and assess the specificity of the FEPS against simulated pain expressions and other types of aversive or emotional states.